Prison Labor: The Price of Prisons and the Lasting
Effects of Incarceration∗
Belinda Archibong
Barnard College

†

Nonso Obikili ‡
ERSA and Stellenbosch University
January 29, 2021
Abstract

Institutions of justice, like prisons, can be used to serve economic and other extrajudicial interests, with lasting deleterious effects. We study the effects on incarceration
when prisoners are used primarily as a source of labor using evidence from British
colonial Nigeria. We digitized sixty-five years of archival records on prisons from 1920
to 1995 and provide new estimates on the value of prison labor and the effects of labor
demand shocks on incarceration. We find that prison labor was economically valuable
to the colonial regime, making up a significant share of colonial public works expenditure. Positive economic shocks increased incarceration rates over the colonial period.
This result is reversed in the postcolonial period, where prison labor is not a notable
feature of state public finance. We document a significant reduction in contemporary
trust in legal institutions, like police, in areas with high historic exposure to colonial
imprisonment. The resulting reduction in trust is specific to legal institutions today.

JEL classification: H5, J47, O10, O43, N37
Keywords: Prison, Taxation, Convict Labor, Public Works, Economic Shocks, Trust
∗ Thanks

to Stelios Michalopoulos, Nathan Nunn, James Fenske, James Robinson, Liz Ananat, Ebonya
Washington, Eduardo Montero, Nancy Qian, David Weiman, Alan Dye, Marlous van Waijenburg, Suresh
Naidu, Warren Whatley, Lee Alston, Leonard Wantchekon, Michiel de Haas, Denis Cogneau, Rajiv Sethi,
Ewout Frankema, Florence Bernault, Naomi Lamoreaux, Gerald Jaynes, Tim Guinnane, Anja BenshaulTolonen, Robynn Cox, Francesc Ortega, Marcellus Andrews, Sandy Black, Owen Ozier, Bryce Steinberg,
Ellora Derenoncourt and participants at the NBER and BREAD meetings, the Harvard, Yale, Duke, Brown,
UC Berkeley, Columbia University, Queens College, Tennessee, Williams College, University of Michigan,
and Stanford Economics seminars, the SSHA, LACEHA, AEHN, ASA, AEA and other conferences for useful
comments and suggestions. Thanks to Yuusuf Caruso, Monique Harmon, Anamaria Lopez, Robrenisha
Williams, Chloe Dennison, and Serena Lewis for excellent research assistance. All errors are our own.
† Corresponding author. Barnard College, Columbia University. 3009 Broadway, New York, NY 10027,
USA. ba2207@columbia.edu.
‡ Economic Research Southern Africa (ERSA) and Stellenbosch University. me@nonsoobikili.com.

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1

Introduction
“The Prison at Port Harcourt has been considerably developed and at the close
of the year there were 829 prisoners in custody and these are employed by the
Eastern Railway. The Engineer in charge at Port Harcourt is highly pleased with
the way the prisoners are worked; they have given no trouble and have been of
great assistance in developing that station. It was my intention to have 1,000
prisoners stationed there before the close of the year, but this was impossible as
two prisons...which should have supplied the drafts to make up the number, had
an outbreak of chicken-pox...”
- E. Jackson, Acting Inspector of Prisons, Lagos, 23rd April, 1915
There are more people incarcerated today than at any other point in human history1 .

The current prison population is estimated at around 11 million people globally, and with
trends of rising incarceration around the world, the policy discussion has turned to what
to do with the large reserve of incarcerated people (Jacobson, Heard, and Fair, 2017). One
suggestion that has risen to prominence in recent years in countries like the United States and
China, is to use prisoners for labor- for work on everything from manufacturing and public
works projects to fighting fires and making hand sanitizer to combat pandemics (Campbell,
2020; Chapman, 2019; Doston and Vanfleet, 2014). Despite the fact that in the US alone2 ,
prison labor contributes to a lower bound estimate of $2 billion a year in industrial output3 ,
there is almost no economics research examining the incentive issues that might arise when
1 Sources:

World Prison Brief and Prison Policy Initiative
United States has been a particularly heated center of the debate around prison labor since it holds
the title of the country with the highest incarceration rate globally; around 0.7% of the US population was
incarcerated as of 2019, and the US has over 20% of the world’s prison population with just 5% of the global
overall population. Source: World Prison Brief.
3 Estimates as of 2004. Sources: Prison Policy Initiative and Bair (2007). There are almost no quantitative
estimates on the value of goods produced by prison labor in the Untied States.
2 The

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prisoners are viewed primarily as a reserve of labor by governments. What are the effects
on incarceration when prisoners are viewed and used as a source of labor to serve economic
interests? And what are the potential implications for citizens’ views of state legitimacy,
when an institution of state justice, like prisons, is used to serve economic interests?
We answer these questions using evidence from colonial Nigeria over 1920 to 19594 ,
where prison labor was a feature of state public finance and the labor market; and from
post-colonial Nigeria over 1971 to 1995, when prison labor was not a major feature of state
finance. We construct a novel dataset from 65 years of archival records on prisons from
1920 to 1995. We assembled data on prisons, wages, prices and colonial public finance
from colonial and postcolonial archives, along with geocoded climate information from high
resolution NASA data to test our hypotheses.
The aim of this paper is to examine how incarceration responds to economic shocks
when prison labor is a major feature of state policy and public finance. To investigate
this topic, we conduct our analysis in 3 steps. First, we assess the importance of prison
labor by first calculating the value of unpaid prison labor and then estimating the share of
prison labor in colonial public finance. A key insight from the historical archives is that, as
part of explicit colonial policy, prison labor on government public works was a mandated
part of incarceration5 . Unpaid prison labor was an essential input in the construction and
maintenance of key revenue-generating public works like the railroad, used to transport
agricultural commodities for export. We provide the first, to our knowledge, set of estimates
of the value of unpaid prison labor in British colonial Africa. We measure the overall value
of prison labor as the amount of unpaid wages to prison laborers.
We find that prison labor was economically valuable to the colonial regime. The overall,
4 Nigeria

as an amalgamated entity was a British colony from 1914 to 1960, so our dataset covers almost
40 of the 47 years of the colonial period. The country was under military rule for most of 1960 to 1999,
before transitioning to democracy in 1999.
5 The 1916 Prison Ordinance outlined the use of convict labor explicitly (Kingdon, 1923).

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gross value of prison labor is strictly positive over the entire colonial period. Even after
accounting for the most expansive set of prisoner maintenance costs, the net value of prison
labor is nonnegative and strictly positive in 60% and 57% respectively of the years from
1920 to 1959 in Nigeria. Prison labor made up a significant share of colonial public works
expenditure. The share of overall prison labor in public works expenditure ranged between
40% and 249%, with an average of 101% over 1920 to 1959. After adjusting for extensive
measures of prisoner maintenance costs, the share of overall prison labor in colonial public
works expenditure remains economically significant with a mean of 5% and a maximum of
up to 42% during this period.
Having established the value of convict labor for the colonial regime, next, we assess the
effects of shocks to economic productivity on incarceration and the use of prison labor using a
panel regression framework. We construct two measures of shocks to economic productivity.
The first measure exploits district level rainfall deviations in a primarily agricultural setting.
The second measure uses agricultural commodity prices and district level crop suitability. We
show that incarceration rates are procyclical during the colonial period. Positive economic
shocks increase colonial incarceration rates and the use of prison labor. The positive effect
is specific to short-term incarceration rates only, with temporary shocks increasing the share
of prisoners with sentences less than 6 months. There is no effect of positive shocks on
long-term imprisonment or the share of prisoners with sentences greater than 2 years. In one
specification, moderate positive rainfall shocks that raise agricultural productivity increase
short-term incarceration rates by 16.7 prisoners per 100,000 population, a 12% increase
relative to a mean of 134.7 prisoners per 100,000 population. This effect is reversed in the
postcolonial period where prison labor is not a main feature of state policy and negative
productivity shocks like droughts increase incarceration rates. Using an index of export crop
prices, we also show that a 1% increase in export prices for a major cash crop in producing
regions is associated with a 2% increase in short-term incarceration relative to the sample
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mean.
We provide evidence from the historical literature and show that a primary reason
for the procyclical behavior of incarceration rates during the colonial period was increased
labor demand for construction and maintenance of public works like railroads, needed to
intensify exports of agricultural commodities during periods of positive productivity shocks.
Labor shortages and tight labor markets, worsened by wage ceilings in the government public
works sector, increased the demand for unpaid prison labor, in line with predictions from
theoretical models of labor coercion (Acemoglu and Wolitzky, 2011). One way colonial
authorities addressed these labor shortages was to increase the share of incarcerated people
by, for example, switching the punishment of certain crimes from fines to imprisonment
(Killingray, 1999). We test the tight labor market hypothesis by examining the effects of
rising wages on incarceration rates by distance to the colonial railroad. The results show
that while prisons closer to the railroad have higher short-term incarceration rates, higher
wages increase the share of short-term prisoners from prisons farther away from the railroad.
The quantitative estimates support historical accounts of prisoners being transported from
prisons throughout districts to work on railroad and other colonial public works projects
during periods of labor shortages (Killingray, 1999).
Finally, to explore the implications of colonial use of prison labor for present day views
of state judicial legitimacy, we present a brief discussion and suggestive evidence of the longrun effects of colonial incarceration on contemporary trust in legal institutions. Given that
the origins of the modern prison and accompanying legal system in Nigeria and other former
British colonies are rooted in the use of state policy around labor coercion, what are the
long-term effects, if any, of exposure to these systems on citizens’ trust in these institutions
today? We use Afrobarometer data from Nigeria on trust in historical legal institutions
(e.g. police, courts, tax administration) and trust in individuals (e.g. neighbors, relatives,

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president) to test whether past exposure to coercive, ostensibly economically influenced
colonial prison structures is associated with trust in legal institutions today. We document
a significant reduction in contemporary trust in legal institutions, and police in particular,
in areas with high historic exposure to colonial imprisonment. The resulting reduction in
trust is specific to legal institutions, with no effect of colonial imprisonment on interpersonal,
trust in individuals.
Colonial Nigeria is an informative region to study these issues, with generalizable
lessons for many jurisdictions today, for a number of reasons. First, colonial Nigeria had
relatively high incarceration rates. As of 1940, the British colonial government in Nigeria
was incarcerating more people (.3-.4% in 1940) than countries in Europe over a similar period (.06% in 1950)6 . In fact, colonial Nigeria was incarcerating about the same fraction of
people as the US prison system was incarcerating of its Black population under the notoriously racially unequal Jim Crow laws over the same time period, and at a higher rate than
the overall US incarceration average of less than .2%7 . To put these figures in context with
contemporary data, Figure 1 shows the top 40 of 222 countries/jurisdictions by incarceration
rate in the world as of 2018. If we place colonial Nigeria’s incarceration rates in 1940 on the
chart, it would have ranked at number 15 of 222 in the world today right between Seychelles
and Panama, as shown in the figure. Nigeria incarcerates a much lower share of people today,
ranking at around 211 of 222 by World Prison Brief estimates.
We add to several distinct literatures. First, we add to the literature on the economics
of forced labor and coercive labor contracts (Acemoglu and Wolitzky, 2011; Bobonis and
Morrow, 2014; Dell, 2010; Gregory and Lazarev, 2013; Juif and Frankema, 2018; Lowes and
Montero, 2020a; Naidu and Yuchtman, 2013; van Waijenburg, 2018; Saleh, 2019; Dippel,
6 Source:

Author estimates from archival data and World Prison Brief.
Nigeria at a rate of between .2-.4% on average compared to the US Black incarceration rate of
around .4% over the same period. Source: (Muller, 2012).
7 Colonial

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Greif, and Trefler, 2020; Sokoloff and Engerman, 2000). Previous work has examined the
impacts of economic shocks on coercive contract enforcement (Naidu and Yuchtman, 2013),
and estimated the share of forced labor in colonial public finance (van Waijenburg, 2018),
but there is very little evidence on the economics of prison labor, with most of the research
on prison labor concentrated on the United States (Poyker, 2019; Travis, Western, and
Redburn, 2014; Cox, 2010) and the Soviet Union (Gregory and Lazarev, 2013). We also add
to the literature on the economics of incarceration (Becker, 1968; Avio, 1998; Katz, Levitt,
and Shustorovich, 2003). While previous work has focused on the effects of crime and prison
conditions on incarceration rates and recidivism (Becker, 1968; Freeman, 1999; Bhuller et al.,
2020; Katz, Levitt, and Shustorovich, 2003), here we highlight the role of economic shocks
in increasing incarceration under coercive state institutions.
There is almost no social science research providing quantitative estimates on the economics of prison labor. Of the 95,916 articles on prison labor in the scholarly archive Jstor,
just 4% are classified in ‘economics’ journals. And of those, only 2 papers provide quantitative estimates on the value and economic drivers of prison labor, with research focused on
estimating the value of British convict labor in 18th century America (Grubb, 2000, 2001).
Although there is a robust qualitative literature in history, political science and sociology on
convict labor, previous efforts at providing quantitative estimates of the economic drivers of
prison labor have been stymied by the paucity of detailed, micro-level data on incarceration
and the value of prison labor. Our paper is the first, to our knowledge, to provide quantitative estimates on both the value of prison labor and the effects of economic shocks on
the use of prison labor, particularly when convict labor is a major part of state policy and
public finance, using evidence from extensive archival data.
While previous work has examined the long-run impacts of institutions like the slave
trade (Nunn, 2008), colonial labor concessions (Dell, 2010; Lowes and Montero, 2020a; Dell

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and Olken, 2020) and health (Lowes and Montero, 2020b; Alsan and Wanamaker, 2018)
on development outcomes, interpersonal trust (Nunn and Wantchekon, 2011; Okoye, 2021)
and trust in modern medicine (Lowes and Montero, 2020b; Alsan and Wanamaker, 2018),
our paper is the first, to our knowledge, to explore the long-term effects of prison labor
systems on trust in legal institutions, like police, and views of state legitimacy. Given the
discussion in the United States and around the world on the effects of incarceration on views
of state legitimacy, for example around the relationship between the high historic racial gap
in incarceration in the US and the Black-white racial gap in trust in legal institutions like
the police (Sherman, 2015), it is important to understand how systems of prison labor may
affect trust in legal institutions. This is needed, particularly in light of research linking
environments of low trust in legal institutions and low views of state legitimacy with conflict
(Rohner, Thoenig, and Zilibotti, 2013), low domestic investment and higher transaction costs
from weak contract enforcement (Knack and Keefer, 1997), and issues with effective policing,
crime and law enforcement (O’Flaherty and Sethi, 2019).
The paper is organized as follows: Section 2 provides historical background on prison
labor in colonial Africa. Section 3 reports quantitative estimates of the value of prison labor
to the colonial regime. Section 4 describes the data on prison labor and economic shocks and
presents the results on the effects of economic shocks on incarceration rates and the use of
prison labor. Section 5 discusses the links between colonial imprisonment and contemporary
trust in legal institutions. Section 6 concludes.

2
2.1

Prison Labor in Colonial Africa
A History of Forced Labor

Prison labor was a small part of a larger regime of domestic forced labor in colonial Africa.
European colonial governments were tasked with pursuing strategies to maximize revenue
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extraction while minimizing costs of administration in Africa (Gardner, 2012). Attempts
to raise revenue to fund expenditures on key public works projects like roads and railroads
necessary for both revenue extraction from cash crop exports and expansion of control of
colonies, rested crucially on the colonial government’s ability to raise revenue through direct
or indirect taxation and cut costs associated with expenditures. Labor shortages were an
endemic feature of the African colonies (Okia, 2012; Ash, 2006). Shortages were driven
partly by an unattractive wage labor market for government projects, which itself was partly
spurred by artificially imposed below-market wage compensation, set both as a cost-cutting
measure and to prevent competition with the private sector, and to satisfy the economic and
political demands of white settler employers (Okia, 2012; Maul, 2007; Ofonagoro, 1982).
To address these constraints, colonial governments enacted a series of strategies to meet
labor and revenue demands. Among these strategies included the use of direct taxation like
hut and poll taxes requiring cash payment to induce Africans into the wage labor market,
the use of labor tax legislation to force Africans to donate a certain number of hours of
often unpaid labor to private and public sector work, and the use of precolonial communal
labor requirements to compel Africans, under the direction of the chiefs, to provide unpaid
labor for private and public works projects (Okia, 2012; Harris, 1914; Trevor, 1936; van
Waijenburg, 2018; Cooper, 1996).
Forced labor was recognized by the colonial regime as so essential to the functioning of
the state, that in one instance, when the colonial office in Nigeria surveyed commissioners
in 1911 on their preferences for terminating the House Rule Ordinance which bolstered the
authority of chiefs to coerce labor for the government, the minutes from the meeting report
that “Perhaps most interesting evidence of all is that of the Commissioners who with one
lament ask how is the administration to be carried out if we cannot go to the Head of a
House and demand carriers and paddlers? How is the work of sanitation, road making and

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clearing to be carried on if we cannot hold the Head of the House responsible for finishing
the necessary labour? They are all of the opinion that the necessary labour cannot be got,
even at a ruinous price, and that thus the progress and development of the country would
be retarded.” (Ofonagoro, 1982), p. 2138 . Another important source of forced labor was
convicts.
2.2

Prison Labor in British Colonial Nigeria

Two main reasons for the use of prison labor emerge in the historical literature. First,
prisoners were employed to work as punishment for crimes, as defined by regimes, and
second, mostly unpaid prison labor was viewed as a source of cheap labor particularly for
industrial projects in the colonies (Adamson, 1984). Similar crimes did not correspond to
similar punishment, a fact which was often exploited by European colonial governments to
address fiscal pressures and labor shortages9 (Branch, 2005; Anderson, 2000).
In British colonial Nigeria, which lasted formally from 1914 to 1960, and throughout
its African colonies, labor taxes and labor laws worked in concert with Masters and Servants
Ordinances, vagrancy laws, labor registration, pass laws and Native Authority Ordinances
that mandated the conscription of African laborers to work on colonial public works projects
(Hynd, 2015). Although there is limited disaggregated data on the types of crimes individuals
8 Ward-Price,

op. cit., p.213. See also CO/520/107, ‘Native House Rule Ordinance’, minutes by Sir Percy
Anderson, 18/12/1911.
9 An example of this can be found in an account from British Kenya between 1895 and 1939 where
Anderson (2000) outlines the ways in which a combination of labor demands by the colonial government
and racist views around physical punishment as a ‘necessary evil’ for ‘civilizing’ African populations, led
to differential prosecution of African convicts versus their European and Asian counterparts under alleged
violations of the 1906 Masters and Servants Ordinance. The Ordinance regulated employment contracts
between workers and employers in the region and heavily favored private employers, most of whom were
white European settlers in disputes. Among the possible punishments for violations of the ordinance, which
included ‘desertion’ from work without prior notice, “absence during work hours”, “careless or improper
work” and “using insulting language to the master”, were fines, prison time extending up to 6 months and
whipping (Anderson, 2000), p. 462. Europeans and Asians convicted for breach of the Masters and Servants
Ordinance were much more likely to get fines than prison time or whipping, with Africans more than three
times likely to get prison time than their European counterparts and the only group to be whipped as
punishment between 1931 and 1938.

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were convicted of, available data from colonial records in Nigeria show that over 50% of total
convictions in colonial courts were from “offences against revenue laws, municipal, road and
other laws relating to social economy of the colony” between 1920 and 1937 as shown in Figure
210 . The colonial regime was highly dependent on revenue from agricultural commodity
exports as shown in Figure 311 and relied on domestic labor in facilitating production and
exports.
Alongside the growth of coercive laws in the colonies, was the increased use of the
prison system and convict labor to work on government public works projects, particularly
in the early part of the 20th century (Hynd, 2015; Akurang-Parry, 2000; Abiodun, 2017;
Bernault, 2007). Individuals who refused or were unable to pay direct or labor taxes or the
fines associated with non-payment, or committed petty crimes against the colonial regime
or their Native Authorities, were arrested and placed in prison, after which their labor was
subsequently used to work on colonial public works projects. An example of this is presented
in accounts by Felix Ekechi (1989) and Stacey Hynd (2015) where a sizable number of the
inmates in the Owerri prison in South-Eastern Nigeria were young men who had resisted
mandated labor under the labor regulations, after which they were imprisoned and employed
as convict labor on the Eastern Railway. In Nigeria and the Gold Coast, Roger Thomas
(1973) notes that convict labor was often used to manage labor shortages in cash crop
production and mining through the 1920s.
In Nigeria, as of the time of its amalgamation from two separate northern and southern
provinces to a single entity under the governorship of Sir Frederick Lugard in 1914, the
need for cheap labor combined with the reticence of indigenous workers to work at below
market rate wages on often grueling industrial railroad, road construction and other public
10 Source:

British colonial Blue Books, multiple years. There is no disaggregated crime data by the
categories listed in the colonial records between 1940 and 1960.
11 This is reversed in the postcolonial regime when revenues from petroleum replace agricultural exports
as the major source of government revenue.

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infrastructure projects, motivated Lugard to pass the 1916 Prisons Ordinances act giving,
among other things, control of the use of prison labor to the Governor (Kingdon, 1923;
Abiodun, 2017). The Prisons Ordinance along with the 1914 Native Courts Ordinance also
outlined the functioning of Nigeria’s dual prison system, with the colonial prisons under the
management of the Director of Prisons and Native Authority Prisons overseen generally by
the local chiefs12 (Kingdon, 1923). Only government agencies were permitted to use prison
labor and prisoners were tasked to work within their provincial districts (Kingdon, 1923;
Abiodun, 2017; Foreign and Office, 1947).
Colonial prisons served a dual mandate, functioning as centers of control of African populations, and a source of cheap labor, allowing the regime to address chronic labor shortages
by providing government administrators with a steady supply of convict labor (Saleh-Hanna,
2017). So significant was the role of prison labor in the revenues and expenditures of the
colonies, that in 1911, the Governor of Northern Nigeria remarked that “The value (calculated at 2/3 of the market rate) of prisoners’ labor in connection with public works, which
would otherwise have had to be paid for in cash was 3,878 pounds. If calculated at the
ordinary market rates the value of the prisoners’ useful labor would have exceeded the entire
cost of the Prison Department” (Salau, 2015), p. 323.
Following Lugard’s Order in Council act on July 20, 1916, colonial prisons were classified into three types: convict prisons, with prisoners serving 2 or more years to life sentences, provincial prisons, with prisoners serving greater than 6 months and less than 2 years
sentences, and divisional prisons, with prisoners serving less than or equal to 6 months sentences (Kingdon, 1923; Abiodun, 2017). Most prisoners were unskilled laborers, with 65%
to 90% of them in provincial or divisional prisons, having short sentences of less than 2
12 There

is little historical information on the functioning of the Native Authority prisons, and we use
records on colonial prisons here. This means the number of prisoners presented here represent only a
fraction of the total number of people imprisoned during this period. We discuss this further in Section 3.

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years, mainly for defaulting on tax payments, and minor offenses like petty thefts (Hynd,
2015; Report, 1925). Popular departments for the use of prison labor were Public Works,
Railways and Harbors, Native Administration, Police, Public Health and Education, particularly for short-term prisoners (with sentences less than 2 years). A robust prison industry
system including bakeries, tailoring, shoe-making, carpentry, printing and blacksmithing,
among others, meant that longer term prisoners (with sentences greater than 2 years) were
taught and tasked with learning a trade like carpentry, basket making, and cloth weaving to
create furniture, uniforms etc which could be sold for cash returns that were remitted to the
prison department’s funds (Hynd, 2015; Report, 1925). They were also tasked, as part of the
partly punitive, partly “reformatory” motivation of prison work, with hard labor including
activities like stone breaking and stone carrying. Prison labor was reserved exclusively for
government use, and colonial officials were careful to choose sectors for convict labor to avoid
competing with private industries13 .
Short-term prisoners were tasked with activities like “road construction, street clearing,
grass-cutting, wood cutting, sanitation, conservancy and farm work”, with the labor of shortterm prisoners contributing significantly to public works projects like quarries in Abeokuta
province, coalfields in Enugu, industries in Lagos, and the Eastern Railway extending from
Port-Harcourt in Owerri province which used large gangs of prison labor (Abiodun, 2017;
Foreign and Office, 1960). The colonial government was heavily reliant on convict labor, with
many of the coal mining projects and railroad construction work in southeastern Nigeria,
for example through the early to mid 20th century, staffed by prison labor (Abiodun, 2017;
Foreign and Office, 1960). Under the colonial prison labor system, unpaid prisoners were
hired out to other government departments, who then remitted payment to the prison department for the use of their labor. To make the system more efficient, prisoners’ labor was
13 Source:

“Annual report on the Treatment of Offenders, 1947”.

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classified into three broad types: unskilled hard labor, skilled hard labor, and light labor14 .
In Nigeria’s southern provinces, between 73% and 91% of prisoners were engaged in hard or
light labor over the 1920 to 1937 period of available data15 . Prisoners engaged in hard labor
alone made up over 70% of convicts over the same period. The vast majority of prisoners
had to work, usually on public works projects like roads, railroads, building construction and
in the mines16 .
The recruitment of prisoners for labor was also stated explicitly by colonial officials, as
illustrated in Abiodun (2017)’s account of the response of colonial government officials to a
request for increased funds for the employment of wage labor by a British sanitary inspector
in 1923: “the officials asked the prison department to find ways to either increase the prison
population or recruit convicts from outstation prisons to complete the tasks.”17 . In another
example, the Inspector of Prisons, W.H. Beverley, in the 1916 Annual Report on Prisons lists
two main reasons for creating categories of prisons according to prison sentence as (a) to place
‘special prisons’ in “townships which are on good lines of communication and afford the most
suitable description of penal labour. (Abeokuta, Enugu, Lagos , and Port Harcourt, on the
eastern and western lines of the Nigerian Railway, provide quarrying, industrial work, labour
connected with shipping and transport, etc.)” and (b) “the ensuring, as far as possible, of an
automatic and constant supply of prisoners to each class of prisons. At the end of the year,
14 Source:

British Blue Books, Nigeria, multiple years. Other similar classifications included “industrial
labor, domestic labor and unskilled labor”, where ‘domestic labor’ was considered light labor and industrial
and unskilled labor were considered hard labor. Unskilled hard labor included work for which “no training
was needed”, with examples given including “coaling ship, grass-cutting, painting and refuse disposal”.
Skilled hard labor included work for which “special training was necessary” including jobs like “basketweaving, brick-making, carpentry, clerical work, cooking, laundering, mat-making, masonry and tailoring”.
Light labor consisted of “easy duties suitable to the bodily or mental infirmity of the prisoner” including
“cell-cleaning, lamp-trimming, sweeping and preparation of foodstuffs for cooking”’ (Foreign and Office,
1960).
15 Between 9% and 26% of prisoners were considered ‘unfit’ for work either due to being non-sentenced
debtors or other not yet sentenced individuals in custody awaiting trial or being too sick to work. Source:
British Blue Books, Nigeria, multiple years.
16 Source: British Blue Books, Nigeria, multiple years.
17 NAI, CSO 26/2 09591 Vol.1 ‘Lieutenant Governor Southern Province to Resident Calabar Province:
Memorandum on Prison labor’ 23rd April 1923.

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the system appeared to be working well; the long and medium sentence men were in the
prisons appointed to retain them, the prison population was evenly distributed, and nowhere
was there shortage of convict labour.” (Foreign and Office, 1960).
The practice of prison labor in Nigeria continued sporadically through the 1950s, and
ended prior to Nigeria’s independence in 1960 with increasing protest from local anti-colonial
groups and labor unions (Killingray, 1999; Abiodun, 2017). Section A.2 in the Appendix
provides more detail on the history of prison labor in British colonial Africa.

3

Estimating the Value of Prison Labor

3.1

Historical Data

To assess the significance of unpaid prison labor for colonial public works expenditures or the
value of prison labor, we digitized archival records on the prison population, wages, public
works expenditure and revenue from the British colonial Blue Books and Annual Report on
the Administration of the Prisons Department18 between 1920 and 1959. The Blue Books
were statistical returns that governors of British dependencies were required to submit on
an annual basis and report a complete record of prisons and colonial public finance between
1920 and 1938 in Nigeria19 . The Blue Books and the Annual Report also include qualitative
descriptions of the activities undertaken by prison departments, as reported by the Director
of Prisons. An example of the archival data is shown in Figure 4. These data sources and
the variables we use in our analysis are described in detail in Appendix A.1.
Figure 5 shows maps of Nigeria with its colonial provinces, regions and prison locations
18 Referred

to as the Annual Report subsequently.
is amalgamated from separate regions into a single country in 1914 and although the Blue Books
data extend back to 1914, some information is missing between 1914 and 1920, so we start our analysis in
1920 for completeness. The Blue Books data on prisons and public finance ends in 1938. For prison data
after 1938, we use records from the Annual Report on the Administration of the Prisons Department.
19 Nigeria

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labeled, including the extent of the colonial railroad. We note an important point here: the
colonial prisons data represent only a fraction of the overall prison population in Nigeria.
There is no detailed data on Native Prisons administered by local chiefs in the colonial
archives prior to 1940. Available data on Native prisons in the Annual Reports from 1940
show that the addition of Native prison estimates to the colonial estimates presented in
this paper would almost double the incarceration rate in 1940 from around 224 per 100,000
population to 399 per 100,000 population. This suggests that the data we present here from
1920 to 1959 may be an underestimate of the total level of incarceration during this period.
There are also clear differences in the distribution of colonial prisons by region. Of the
48 prisons recorded in 1938, about 90% are located in the southern provinces. The map is
reversed for Native prisons, with just 13% of Native prisons, 9 of 65 recorded in 1940, located
in the southern provinces as shown in Figure A2 in the Appendix. Historical differences in
the level of precolonial state bureaucracy drive differences in the geographical distribution
of Native vs colonial prisons (Archibong, 2019)20 . Using the available data from colonial
prisons, we present results here as lower bound estimates on the total value of convict labor
over this period.
3.2

Empirical Strategy

We measure the value of convict labor to the colonial regime by adapting the strategy from
van Waijenburg (2018) to estimate the value of unpaid prison labor and its relative share in
expenditure on new construction of colonial public works21 . In essence we ask, ‘how much
would the colonial state have had to pay if they had to hire non-remunerated prison workers
20 Appendix

A.3 presents a brief discussion of the historical drivers behind these differences. See Archibong
(2019) for a more in-depth discussion.
21 We use expenditure on new public works construction only here as a comparison as it reflects valueadding investment in productive public works rather than just upkeep or maintenance. New expenditure
represents about 40% of total, new and maintenance, public works expenditure between 1920 and 1959.
In Appendix A.4.3, we compare the value of prison labor figures to total public works spending, including
recurrent expenditure on regular maintenance of public works reported in the archives.

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for a market rate wage?’
We calculate the overall value of unpaid prison labor in each year t as:

Value of prison labort = Annual wagest ×

N
X

Prisonersnt

(1)

n=1

This gives us an overall, gross value of benefits accruing to government consumers
of prison labor. As a measure of wages, we use the average annual market wages paid to
unskilled laborers. This captures the wages for some of the types of work that prisoners
were required to perform, including felling trees and breaking rocks to clear areas for road
construction as discussed in Section 2. P risonersnt is the daily average number of people
in prisons over n days in the year from the archival records. This measure captures the
amount of convict labor that was available on any given day. To estimate the relative value
of prison labor, we divide the results from Equation 1 by public works expenditures, prison
expenditures and overall expenditure figures from the Blue Books.
The specification in Equation 1 does not factor in the costs of prisoner maintenance,
including food, clothing and prison staff salaries. The archival data reports 2 sets of costs
for prison maintenance: (i) food costs, which is reported as the main cost of prisoner upkeep
and (ii) total prisoner maintenance costs, an estimate that divides all expenses involved in
operating the prison (i.e. everything from staff salaries to equipment purchases) by the total
number of prisoners in a given year. Food costs account for an average of 35% of total
prisoner costs between 1920-1959, with food costs ranging from 27% to 51% of total costs
over the study period. Food costs and staff salaries make up over 50% of the total prisoner
costs from 1920 to 1959. The total prisoner maintenance cost category is the most expansive
measure of prison upkeep costs. We present results on the net value of prison labor using
both the food costs and the total prison maintenance costs in Section 3.3.

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Figure 6(a) shows the trends in the reported average annual wages and prisoner food
and overall maintenance costs. The total reported prisoner upkeep costs closely tracks the
wage, reflecting increases in staff salaries over time, with a steep increase after 1940. Prisoner
food costs follows a similar pattern, though the post-1940 increase in costs is less steep than
the wage and total prisoner costs. Figure 6b shows the daily average number in prison over
the study period. The wage is above prisoner food costs in all years, and above total prisoner
costs in over 51% of the years between 1920 and 1959. The daily average numbers in prison
fluctuate notably between 1920 and 1940, increasing through 1930, then decreasing between
1930 and 1940 before sharply increasing after 1943. Interestingly, the daily average numbers
in prison also appear to track the average annual wage figures in Figure 6a22 .
We estimate various versions of Equation 1 in alternate specifications, including estimates using alternate wage measures, adjusting for inflation and addressing potential bias in
prisoner estimates by computing a weighted average measure of people committed to prison
for penal imprisonment in each year. The trends in the results remain unchanged and are
detailed in Appendix A.4.
3.3

Value of Prison Labor Results

Figure 7(a) and Table A2 in Appendix A.4 report our imputed total and net value of prison
labor results. The total, gross value of prison labor starts out around 178,498 pounds in
1920 and fluctuates, first decreasing, then increasing through 1927, before mostly declining
through 1943, then increasing sharply afterwards, peaking at 1,532,634 pounds in 195923 .
The average gross value of prison labor is 313,742 pounds over the colonial period. We
observe similar trends with the net value of prison labor figures, less prisoner food costs;
22 The

correlation between the daily average numbers in prison and the average annual wage to unskilled
laborers is 0.87, p < .001.
23 Given the debates around the choice of the price index for colonial Africa, we present the figures in
nominal terms here (Frankema and Van Waijenburg, 2012). We present the real estimates in Appendix A.4.
The trends remain unchanged.

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the net value of prison labor less food costs remains strictly positive over the study period
with the average falling to 195,260 pounds. When we estimate the net value of prison labor
using the most expansive measure of prisoner maintenance costs reported, the mean falls
further to 31,674 pounds. The net value of prison labor, subtracting total reported prisoner
maintenance costs from the gross value of prison labor, is nonnegative and strictly positive
in 60% and 57% of years respectively over the colonial period in Nigeria.
To evaluate the significance of the prison labor value for colonial public finance and
spending on public works, the major category prison labor was employed on, in particular, we
estimate the ratio of our prison labor values to reported new public works expenditure. We
also compare the prison labor values to overall prison expenditure and overall expenditure
by the colonial government. Figure 7(b) and Table A2 report the estimates for the share of
prison labor in public works expenditure from 1920 to 1959. The share, using the gross value
of labor coercion, fluctuates throughout the colonial period; it starts out at 133% in 1920,
then declines through 1932, before increasing through 1936 and declining through the 1940s.
The prison labor share in public works expenditure increases sharply post 1943, peaking in
1952 and 1953 at 249% before declining through 1959. The share of overall prison labor in
colonial public works expenditure ranged between 40% and 249%, with an average of 101%
over 1920 to 1959. After adjusting for extensive measures of prisoner maintenance costs,
the share of overall prison labor in colonial public works expenditure remains economically
significant with a mean of 5% and a maximum of up to 42% during this period.
We show similar trends for the prison labor share of total prison expenditures and
overall colonial expenditures over this period in Figure 7(c) and Figure 7(d) respectively.
Given the relatively small share of new public works expenditure in overall colonial spending24 , prison labor shares in overall colonial expenditure are low; making up an average of
24 An

average of 2.2% between 1920 and 1959.

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2% and 0.1% of total expenditures, using the gross and net values of prison labor (including total prisoner maintenance costs) respectively. The results show that prison labor was
economically valuable to the colonial regime.
3.3.1

Comparing Imputed Estimates of the Value of Prison Labor to Reported
Colonial Estimates

As a specification check, we compare our estimates of the value of prison labor to the colonial
government’s own estimates of the value of prison labor, shown in Figure 7(a) and Table
A2. In some years, the colonial authorities published their own estimates of the total value
of prison labor in Nigeria. Prisoners were most often hired to the Public Works and other
government agencies for labor. Although the prisoners themselves were not paid, payment
was remitted directly from these agencies to the Prisons department for prisoners’ work.
The prison department then had to set prices for their prisoners’ work for other government
agencies. These prices are explicitly listed as their estimates of the ‘value of prison labor’ in
the Annual Reports25 .
We compiled these estimates where available, and they provide us with comparable
data from 1919 to 1925. Figure 8 shows our estimates of the difference in the daily market
wage rate versus the prison rate in the Lagos colony and southern provinces for laborers or
unskilled hard labor and for carpenters and joiners and bricklayers and masons, two classes
of skilled hard labor. Lacking data past 1921 on the per diem prison rates, we assume,
25 The Directors of Prisons, for example, W.H. Beverly, E. Jackson or W. Reeder in the southern provinces
over 1915 to 1921, recorded per diem estimates of the value of labor between 1916 and 1921 in the Lagos
colony and southern provinces for Nigeria. Using the classification of labor into skilled hard labor, unskilled
hard labor and light labor, described in Section 2.2, hard labor, both unskilled and skilled are given a value
of 5 pence per day, with light labor given a value of 3 pence per day in 1916. Starting in 1917, skilled hard
labor is given a value of 1 shilling and 6 pence or 18 pence, unskilled hard labor is assigned a value of 5
pence and light labor is assigned a value of 3 pence. The rates for unskilled hard labor stay the same from
1918 through 1921, with no reporting on the exact value assigned to skilled hard labor or light labor over
this time. After 1921, the reports stop including information on the per diem value assigned to the different
classes of labor.

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based on the past record, that the rates remain stable through 1925. As shown in Figure
8, prisoners performing unskilled hard labor, which made up the majority of the prison
population (prisoners with shorter-term sentences), were assigned a value between about
60% to 80% below the market wage rate over 1919 to 192526 . Our measures of the value of
prison labor are higher than the estimates of the colonial authorities; colonial prison officials
were consistently undervaluing prisoners’ labor to keep costs of administration for their peer
departments low while attempting to balance their budgets.

4

The Effects of Economic Shocks on Incarceration Rates and the
Use of Prison Labor

4.1

Data on Incarceration Rates and Economic Shocks

Given the economic significance of prison labor for colonial public works shown in Section
3, to understand the effects of economic conditions on the use of prison labor, we examine
the effects of economic shocks on incarceration rates over the colonial period. Our outcome,
incarceration rates, are only available in disaggregated form during the colonial period from
1920 to 1938, and we limit our analysis to these years for the colonial era. The Blue Books
reports imprisonment data at the prison level, and we aggregate up to the district level,
where district is the colonial province between 1920-1938, and calculate incarceration rates
as the number of newly admitted prisoners per 100,000 population for each province in each
year.
The imprisonment data is broken down by length of prison sentence, classified as shortterm (less than 6 months), medium-term (between 6 months and 2 years) and long-term
26 This

confirms the report written by Beverley himself in the 1915 Annual Report on Prisons where he
states that values assigned to prisoners’ labor is below “wages demanded by workmen in civil life”. He
recommends a doubling of values to balance prison expenditure amounts, illustrating the balance sheet
calculus that appeared to drive the setting of values of prison labor.

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(greater than 2 years) prisoners. We use this classification of sentences for falsification tests,
to test the hypothesis that yearly variation in economic shocks should affect short-term
prisoners whose populations are more elastic than long-term prisoners. As an additional
falsification test, and to test the hypothesis presented in Section 1 and Section 2 that the
impacts of shocks on incarceration should differ between the colonial and postcolonial period due to differences in the economic structure and state policy regarding incarceration
between the two periods, we use available data on postcolonial incarceration rates at the
current administrative state level between 1971 and 1995 from Nigeria’s Annual Abstract of
Statistics27 .
To measure economic shocks, and test the hypothesis presented in the introduction that
positive shocks will increase incarceration rates under a regime that uses prison labor to serve
economic interests, we use two sets of data. Since our setting is primarily agricultural28 , we
can measure shocks to economic productivity using data on rainfall and agricultural commodity export prices. First, we use rainfall data from 69 weather stations recorded in the
Blue Books to construct measures of rainfall deviations or z-scores, as deviations from the
province long-term mean. We use this to estimate the effects of rainfall shocks on incarceration rates29 . For our falsification test in the post-colonial period, we use precipitation data
from the National Aeronautics and Space Administration (NASA) MERRA-2 database30 .
Second, we estimate the effects of productivity shocks on colonial incarceration rates
using export crop price data on the major cash crop exports in colonial Nigeria, cocoa, palm
27 The

postcolonial data does not include breakdown by sentence.
share of agriculture in GDP has ranged between 40% and 60% between 1960 and 2012 by some
estimates (Ahungwa, Haruna, and Abdusalam, 2014).
29 In alternate specifications, we test results with interpolated data from the University of Delaware
database, and confirm that while there is a significant positive correlation between the rainfall values, the
correlation is low and does not translate to the z-scores which are the main explanatory variable used here.
Given that the Delaware values from 1920 are less fine interpolations than the weather station data, we use
the weather station data here for our main results.
30 The NASA MERRA-2 data is not available prior to 1980.
28 The

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oil and groundnuts, from the Wageningen University African Commodity Trade Database
(ACTD) (Frankema, Williamson, and Woltjer, 2018). We combine the price data with land
suitability and crop production data from the Global Agro-Ecological Zones (GAEZ) and
Blue Books databases respectively to enable us to identify which prices would theoretically
affect which districts.
4.2

Summary Statistics

Summary statistics are presented in Table 1. The average incarceration rate falls by almost
a third between the colonial and postcolonial periods from around 241 prisoners per 100,000
people to 92 respectively as shown in Table 1 and Figure 9. The spatial distribution of
incarceration between the colonial and postcolonial period also changes significantly with
prisoners being clustered in the southern provinces over the colonial period, and significantly
more spatial dispersion in the postcolonial period as shown in Figure 10. Incarceration rates
are also higher on average in the southern provinces at 216 prisoners per 100,000 population
versus 19 prisoners per 100,000 population in the northern provinces31 . Trends in overall
colonial incarceration rates track the trends in southern incarceration rates as shown in
Figure 11.
Short-term prisoners make-up the vast majority of the colonial prison population at
58% of all newly committed prisoners and 84% of penal imprisonment on average between
1920 and 1938 as shown in Table 1. The share of long-term prisoners in penal imprisonment
is comparatively much smaller at 5% over the same period. The shares of prisoners with
previous convictions are similarly low, with 11% of prisoners having 1 previous conviction
31 Although we do not have detailed data on Native prisons, data provided from the colonial archives for
2 years, 1940 and 1945, show similar north-south trends in Native incarceration rates as shown in Figure
A3 in Appendix A.3. From Figure A3, incarceration rates are higher in a southern province, Oyo, than in
the northern provinces on average. The southern Native prisons, for the available data in the 1940s, also
incarcerate more people than their northern counterparts on average, following the trends in the colonial
incarceration data. Average incarceration rates in Native prisons between 1940 and 1945 (181 per 100,000
population) are slightly higher than in colonial prisons (130 per 100,000 population) over the same period.

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and only 2% of prisoners with 2 or 3 previous convictions.
Figure 12 shows the spatial distribution of cash crop production over the colonial
period. Palm oil and cocoa are produced in the southern provinces, while groundnut is the
major cash crop export produced in the northern Provinces. The time series of export cash
crop prices are shown in Figure 11. Prices for cash crops in the southern provinces, namely
cocoa and palm oil, are 2 times and 1.5 times higher, on average, than prices for groundnut
produced in the northern provinces over 1920 to 1938. Prices remain relatively stable, after
an initial decline in 1920, through 1930, before there is a sharp Depression-era drop in export
prices through 1935. Prices start to rise again briefly before another decline towards the end
of the 1938 period.
4.3

Estimating Equations

To examine the effects of shocks to economic productivity on incarceration rates and the use
of prison labor in the colonial period, we use three estimating equations as follows: (1) a
nonlinear, quadratic specification, that allows the effect of rainfall shocks on incarceration to
vary more flexibly with the level of district level rainfall deviation and estimates the effects
of positive productivity shocks on incarceration rates; (2) a linear specification that identifies
the impacts of moderate positive rainfall shocks, in particular, on incarceration, and (3) a
linear specification that identifies the effects of productivity shocks with an interaction term
for agricultural export commodity prices. We include district (province or current state for
colonial or postcolonial data respectively) and year fixed effects in all specifications, along
with clustered standard errors at the district level. Following Cameron, Gelbach, and Miller
(2008), we apply wild bootstrap-based tests to our estimates to account for potentially low
numbers of clusters in estimating our standard errors and include wild cluster bootstrap
p-values in our results. The rationale behind each empirical strategy is discussed in further
detail in the proceeding sections. Our main specifications will be related models (1) and (2),
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though we interpret the results from all 3 models in Section 4.4.
4.3.1

Nonlinear Effects of Economic Shocks on Incarceration Rates

Following the discussion in Section 1 and Section 2, positive rainfall and agricultural commodity price shocks that boost economic productivity may increase incarceration rates by
increasing prison labor demand for construction and maintenance of public works like railroads, needed to intensify exports of agricultural commodities during periods of positive
productivity shocks
Colonial officials push forward construction and intensify maintenance on public works
like roads and the railroad, but facing severe labor shortages due to the increased relative
value of African laborer/farmer outside options during periods of heightened agricultural
productivity, switch the prosecutions/sentencing of certain crimes to short-term prison sentences to better utilize unpaid prison labor. This is partly reflected in Figure 2 showing that
the majority of crimes leading to imprisonment are “crimes against the colonial economy”
(e.g. tax default). Our hypotheses here are that: (a) the main functional form of the relationship between rainfall shocks and incarceration rates in the colonial period is an inverted-u.
The demand for prison labor peaks during periods of moderate positive rainfall shocks which
reflect increases in agricultural productivity; in contrast, extremes in rainfall deviations like
droughts and floods which lower agricultural productivity lower the demand for prison labor.
Additionally, as a falsification test, these effects should only hold for short-term incarceration, which is more elastic and should be more responsive to short-term economic shocks
than long-term imprisonment.
A testable implication of (a) is that: (b) as a falsification test, the effect of rainfall
shocks on incarceration rates be u-shaped during the colonial period if a major motive for
state incarceration was not prison labor. Under a non-convict labor motivated prison system,

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droughts and floods that lower agricultural productivity should increase incarceration rates
through a rise in economic crimes like theft in line with past theory and evidence from the
crime literature (Becker, 1968). Incidentally, “offences against property” or property theft is
also the major category of prison convictions over the postcolonial period as shown in Figure
2.
The nonlinear relationship between rainfall and agricultural output has been highlighted in previous literature as well (Lesk, Rowhani, and Ramankutty, 2016; Kaur, 2019;
Sarsons, 2015). We can then estimate the causal effect of rainfall shocks on incarceration
rates by assessing panel regressions of the following nonlinear, quadratic form:

Prisonersit = β1 RainfallDevit + β2 RainfallDev2it + µi + δt + it

(2)

where P risonersit is the incarceration rate or number of newly committed prisoners
per 100,000 population32 in district i at year t; Rainf allDev it is the rainfall deviation or
z-score for each district in each year relative to the district’s long-term expectation33 ; µi and
δt are district and year fixed effects respectively. Errors are clustered at the district level
to allow for arbitrary correlations34 . Our key parameter of interest is β2 which should be
significantly negative if hypothesis (a) above holds and positive if hypothesis (b) holds.
Given the different shares of Native to colonial prisons and prisoners in the northern
(more Native, less colonial prisons) versus southern (more colonial prisons and prisoners)
provinces, and the implications of those shares for how prisoners were used for prison labor
as discussed in Section 2, our third hypothesis is that: (c) the positive effect of agricultural
32 The

results remain unchanged if we standardize by the adult population only.
find no effects when we test the specification using lagged rainfall deviations instead following results
in previous literature (Amare et al., 2018).
34 We estimate all models with standard errors clustered at the district level and Conley standard errors
with a cut-off window of 100 km to account for spatial auto-correlation (Conley, 1999). The results are
robust to both specifications, and we present the district level clustering results here.
33 We

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productivity enhancing rainfall shocks on incarceration rates should hold more strongly in the
southern provinces than the northern provinces over the colonial period. To test hypothesis
(c), we examine heterogeneity in the effects of Equation 2 by region.
4.3.2

Identifying the Effects of Positive Rainfall Shocks on Incarceration Rates

While Equation 2 allows us to more flexibly identify the effects of rainfall shocks on incarceration rates and the use of colonial prison labor, it does not allow us to distinguish between
positive and negative rainfall and productivity shocks. Specifically, Equation 2 does not
allow us to distinguish between moderate positive rainfall shocks that signal increases in
agricultural productivity and extreme positive and negative shocks that signal floods and
droughts respectively that can reduce productivity.
A problem that arises when trying to distinguish positive and negative shocks, and
identify moderate positive rainfall shocks from droughts and floods is that the classification
is often highly dependent on the particular regional context/climate, and, as mentioned
previously, the relationship between rainfall and agricultural output is often non-linear (Lesk,
Rowhani, and Ramankutty, 2016; Sarsons, 2015; Kaur, 2019; Amare et al., 2018; Jensen,
2000). Additionally, while there is a robust literature on rainfall shocks and agricultural
productivity in South Asia, there is relatively little research on the links between rainfall
shocks and productivity in West Africa (Amare et al., 2018; Papaioannou and de Haas, 2017;
Dillon, McGee, and Oseni, 2015; Jensen, 2000).
Since we do not have data on agricultural output, we adapt definitions of rainfall
shocks in Africa from previous literature (Dillon, McGee, and Oseni, 2015; Amare et al., 2018;
Jensen, 2000) and estimate transition points in Equation 2 from non-parametric loess models
linking rainfall deviations to colonial incarceration rates. From the transition points, we
distinguish between moderate positive shocks, extreme positive shocks and extreme negative

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shocks as follows: (a) Positive shock (M), where ‘M’ is moderate, is an indicator equal to
1 if 0 < Rainf allDev it < 0.75 and a proxy for increases in agricultural productivity; (b)
Positive shock (E), where ‘E’ is extreme, is an indicator equal to 1 if Rainf allDev it > 0.75,
and signifies floods that reduce agricultural productivity and (c) Negative shock (E), is
an indicator equal to 1 if Rainf allDev it < −0.5, and signifies droughts that also reduce
agricultural productivity.
We can then directly estimate the causal effect of moderate positive rainfall shocks on
incarceration rates by estimating the following linear specification:

Prisonersit = αPositive shock (M)it + µi + δt + it

(3)

where Positive shock (M)it is the moderate positive rainfall shock and other variables
are as defined in Section 4.3.1. The main parameter of interest in Equation 3 is α, defined as
the effect of moderate positive shocks that increase agricultural productivity on the incarceration rate. In alternate specifications, we include the extreme positive and negative rainfall
shock variables to check the robustness of our results. We also examine heterogeneity by
southern and northern province and examine the effects of positive shocks on postcolonial
incarceration rates, repeating the heterogeneity and falsification exercises in Section 4.3.1.
Though we do not have disaggregated data on crime, to test the ‘sentence-switching as
a way to increase the share of short-term prisoners for prison labor in response to positive
economic shocks’ hypothesis mentioned in Section 4.3.1, we estimate Equation 3 using the
difference between custody/awaiting trial and short-term incarceration figures as an outcome.
The rationale here is that, given that only sentenced prisoners could legally be used for prison
labor, if there is more sentence switching from ‘awaiting trial’ to short-term imprisonment
in response to positive economic shocks, α will be significantly negative for the difference.

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4.3.3

Effects of Cash Crop Price Shocks on Colonial Incarceration Rates

As a robustness check, following the literature on commodity price shocks and agricultural
productivity (Dube and Vargas, 2013; Naidu and Yuchtman, 2013), we examine the effects
of plausibly exogenous agricultural export price shocks, signaling increases in agricultural
productivity, on colonial incarceration rates and use of prison labor. We estimate equations
of the following form:

Prisonersit =

3
X

γc Cash Cropci × Cash Crop Pricect + µi + δt + it

(4)

c=1

where Cash Cropci is an indicator that equals 1 if province i produces one of the
3 major export cash crops c ∈ (cocoa, palmoil, groundnut) over the colonial period, and
Cash Crop Pricect is the natural log of the export price of c in year t. The coefficient of
interest is the interaction term γc measuring the effect of increases in cash crop prices in
producing provinces on incarceration rates.
The railroad was an important capital input in colonial revenue production functions,
given its importance in the transport of cash crops for export (Okoye, Pongou, and Yokossi,
2019). A major use of prison labor was for public works and railroad construction and
maintenance as discussed in Section 2 and shown in Section 3. As an additional specification
check, we examine the effects of increases in nation-wide wages on colonial incarceration rates
by distance to the railroad. The wage time series measure interacted with distance from each
prison to the railroad, gives us a proxy for labor market tightness to test if a tighter labor
market intensifies the demand for prison labor as reflected in colonial incarceration rates
around the railroad.

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4.4
4.4.1

Results
Nonlinear Effects of Economic Shocks on Incarceration Rates Results

To examine the causal effect of economic shocks on incarceration rates, we first present the
results using the rainfall deviation measures in Equation 2 in Table 2. While the quadratic
term is negative but not significant when we examine all penal imprisonment over the colonial
period in column (1), the effect is significant and negative for short-term incarceration rates.
The negative quadratic coefficient for short-term incarceration is consistent with an invertedu relationship between rainfall deviation and short-term imprisonment or the use of prison
labor. β2 , the squared rainfall deviation term is not significant for medium or long-term
incarceration rates, in line with the predictions in Section 4.3.1.
The results of the falsification test for postcolonial imprisonment are shown in column
(5) of Table 2. β2 from Equation 2 is positive and significant for postcolonial incarceration
rates. The positive significant estimate for postcolonial incarceration is consistent with
hypothesis (b) from Section 4.3.1 that the impacts of rainfall shocks on incarceration rates
should be u-shaped when prison labor is not a major feature of state policy; imprisonment
increases instead primarily as a response to increases in economic crimes like theft, in the
aftermath of negative productivity shocks like drought or floods.
Table 3 reports the results when we examine heterogeneity by southern and northern province. β2 is negative and significant for short-term imprisonment in the southern
provinces, but positive and significant for northern provinces, following the discussion in
Section 3. Given the relatively higher share of Native Administration prisoners in the northern provinces, one explanation for the reversal is that colonial prisons in the North contained
fewer prisoners than their Native counterparts. Northerners may have been more likely to
be incarcerated in colonial prisons after committing crimes that were specifically targeted

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against Europeans or non-African natives, like theft or violations of the aforementioned
‘colonial economy’ laws (Killingray, 1999; Bernault, 2007).
So while there is prison labor in both regions, the colonial prisons in the southern
provinces, being the only arm of the prison system for most southern provinces35 are used
more intensely for prison labor in response to labor demand shocks than their northern colonial prison counterparts. Consistent with the hypothesis that there should be no effect of
yearly economic shocks on long-term prisoners, we see no effect for this category, disaggregated by region in Table 3. Consistent with the inverted u-shaped hypothesis, moderate
positive rainfall shocks increase short-term imprisonment and the use of prison labor, particularly in the southern region where colonial prisons were often the only source of prison
labor.
4.4.2

Identifying the Effects of Positive Rainfall Shocks on Incarceration Rates
Results

Table 4 reports the results from Equation 3 identifying the effects of moderate positive
rainfall shocks that raise agricultural productivity, versus extreme positive or negative rainfall
shocks, signifying floods or droughts respectively that reduce productivity on incarceration
rates. The results from our main specification in column (1) show that moderate positive
rainfall shocks have a significant positive effect on short-term imprisonment over the colonial
period. A moderate positive rainfall shock increases the short-term incarceration rate by
16.7 per 100,000 population, or around 12% relative to the sample mean of 135 per 100,000
population. The effect remains significant, increasing short-term incarceration by about 9%
when we add controls for extreme negative and positive rainfall shocks in column (3) of Table
4.
35 There

are 56 Native prisons in the Northern provinces vs only 9 in the South, and concentrated entirely
in the southwest region as of 1940 as shown in Figure A2.

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In line with the inverted u-shape prediction, column (2) and column (3) of Table
4, shows the opposite result for extreme negative rainfall shocks which reduce short-term
colonial imprisonment. Extreme negative rainfall shocks like droughts signal a decrease in
agricultural productivity and decrease demand for unpaid prison labor under the colonial
system; this is reflected in the lowered incarceration rates, with extreme negative rainfall
shocks associated with a 13% to 15% decline in short-term incarceration relative to the
sample mean. There are no effects of rainfall shocks on long-term incarceration as shown in
columns (4) to (6).
In contrast, the postcolonial results show that while moderate positive rainfall shocks
have no significant effect on postcolonial incarceration rates (column (7) and column (9)),
extreme negative (column (8)) and extreme positive (column (9)) rainfall shocks increase the
postcolonial imprisonment rates. From column (9), the magnitude of the increase in postcolonial imprisonment from droughts/extreme negative rainfall shocks and floods/extreme
positive rainfall shocks is a 21% and 19% increase in incarceration rates relative to a sample mean of 105 per 100,000 population. The linear specification results are consistent
with the results from the quadratic specification in Equation 2 showing an inverted u-shape
relationship between rainfall deviation and incarceration rates in the colonial era, with a
reversal/u-shape relationship in the postcolonial period.
Table 5 reports estimates from the heterogeneity by region analysis and confirms the
results from Section 4.4.1. The positive relationship between moderate positive rainfall
shocks and colonial incarceration rates is driven by short-term incarceration in the southern
provinces.
Table A4 in Appendix A.5 provides suggestive evidence of ‘sentence-switching’ as a
strategy to increase the share of short-term prisoners for prison labor in response to positive
productivity shocks. While the specifications in columns (1) to (4) confirm a positive, mostly

32

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significant relationship between moderate positive rainfall shocks and both ’custody/awaiting
trial’ and short-term incarceration rates, the effect of shocks on their difference, in columns
(5) and (6), is negative. Given that the coefficients on both custody and short term incarceration rates are positive, the only way for their difference to be negative is if short-term
incarceration is rising faster than custody sentences in response to moderate positive rainfall shocks. One interpretation is that people may have been transferred at a faster rate
from custody/awaiting trial to short-term sentences so that the state can take advantage of
their unpaid prison labor when moderate positive rainfall shocks increase labor demand and
worsen labor shortages. The α coefficient is not robust to the inclusion of the other rainfall
shock terms as shown in column (6) and should be interpreted with caution, but provides
suggestive evidence of the switching hypothesis.
4.4.3

Effects of Cash Crop Price Shocks on Colonial Incarceration Rates Results

Table 6 presents the results from Equation 4. The results show that the effect of plausibly exogenous positive agricultural export price shocks signaling increases in agricultural
productivity on colonial incarceration rates and the use of prison labor is concentrated in
relatively higher value cash crops, like palm oil, that are produced in the southern provinces.
We interpret the coefficients from the full specification of the model in column (1), with
short-term incarceration rates as the outcome of interest.
A 1% increase in palm oil prices in palm oil producing regions is associated with an increase in the short-term incarceration rate by around 3 per 100,000 population, a 2% increase
in short-term incarceration relative to the sample mean. Short-term incarceration rates are
elastic and responsive to increases in palm oil prices signaling increases in agricultural productivity. The effect is strongest for palm oil producing regions in the southern region where
colonial prisons are the only source of unpaid prison labor, in the absence of Native prisons.
There is no effect of the palm oil price interaction on long-term incarceration rates in column
33

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(5). Note for almost all cash crops in column (1) and column (2), colonial production of the
crop is significantly positively associated with both short-term and long-term incarceration.
There were more colonial prisoners, on average, in provinces with cash crop production. The
positive effects of cash crop production on short and long-term imprisonment are particularly
robust, based on the bootstrapped p-values, for palm oil producing areas.
4.4.4

Railroad, Wages and Incarceration Rates

As discussed in Section 2 and shown in Section 3, a major use of prison labor was for
public works and construction and maintenance of the railroad which was essential for the
transport of cash crops for export. Railroad construction began in 1898 and had expanded
to its full extent across the country by the 1950s as shown in Figure 5. As an additional
specification check, we examine the effects of wages on colonial incarceration rates by distance
to the railroad. Although we do not have data on unemployment rates, the wage time series
measure interacted with distance from each prison to the railroad gives us a proxy for labor
market tightness; we can then test if a tighter labor market intensifies the demand for prison
labor as reflected in colonial incarceration rates around the railroad. Table 7 reports the
estimates for the effects of rising wages and distance to railroad on short-term incarceration
rates at each prison. While short-term incarceration rates are higher in prisons closer to the
railroad on average, rising wages also increase short-term imprisonment in prisons farther
away from the railroad as reflected in the positive interaction in column (2).
The interpretation of the result is intuitive. While short-term prisoners near the railroad are generally used as a reserve of unpaid labor for railroad construction and maintenance, increasing wages intensify the demand for unpaid prison labor and worsen labor
shortages and labor market tightness. To increase the share of prison labor, colonial officials
would need to increase the share of prisoners in prisons further away from the railroad as well.
They could then transport them within the province to conduct work on the railroad and
34

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associated public works as needed (Foreign and Office, 1960). In Appendix A.2, we present
qualitative historical evidence from the archival material supporting this interpretation36 .

5

Discussion: Colonial Imprisonment and Contemporary Trust in
Legal Institutions

To understand the implications of the colonial use of prison labor for present day views of
state judicial legitimacy, we present a brief discussion and suggestive evidence of the long-run
effects of colonial incarceration on contemporary trust in legal institutions. Given that the
origins of the modern prison and accompanying legal system in Nigeria and other former
British colonies are rooted in the use of state policy around labor coercion, what are the
long-term effects, if any, of exposure to these systems on citizens’ trust in these institutions
today? We use Afrobarometer data from Nigeria on trust in historical legal institutions
(e.g. police, courts, tax administration) and trust in individuals (e.g. neighbors, relatives,
elected local governing council members) to test whether past exposure to coercive, ostensibly
economically influenced colonial prison structures affects trust in legal institutions today.
To test the hypothesis that historical exposure to colonial imprisonment centered
around prison labor may be associated with lowered contemporary trust in legal institutions, with no effect on interpersonal trust, we estimate equations of the following form:

Trustaigst = βPrisonersi + X0aigst θ + X0g φ + µs + δt + aigst

(5)

where Trustasit is the contemporary trust outcome of interest for individual a residing
in historical colonial province i, in current sub-district or local government area (LGA) g, in
state s for the Afrobameter survey administered in year t. We include vectors of individual
36 Table

A5 in Appendix A.5 shows similar results when we use agricultural commodity price shocks to
examine the effects of crop export price increases on incarceration rates.

35

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level covariates X0aigst and LGA level covariates X0g 37 . All regressions include state and year
fixed effects. Standard errors are clustered at the district (colonial province or current state)
level and wild cluster bootstrap p-values are included to account for potentially low numbers
of clusters as before.
We measure Prisonersi or long-term colonial imprisonment with the average of longterm colonial imprisonment over 1920 to 1938 for each province. The rationale here is that
although there is a significant, high positive correlation between short-term and long-term
colonial imprisonment (.61, p < .001), when it comes to the long-term effects of colonial
prison-labor systems, what stands out in public memory is the stock (long-term imprisonment) not the flow (short-term imprisonment) of incarceration rates. And while there is little
recorded information on the determinants of long versus short-term sentences, the historical
literature has documented that crimes against Europeans and colonial officials were often
punished and sentenced more harshly (Abiodun, 2017; Killingray, 1999; Bernault, 2007).
So one hypothesis is that a higher share of long-term imprisonment, consisting of
relatively more political prisoners, or prisoners that have committed crimes against European
colonists, when coupled with the existing economically motivated system of convict labor,
is highlighted in local memory as unjust. Exposure to long-term colonial imprisonment
then reduces residents’ trust in legal institutions with colonial origins like modern courts,
police and systems of tax administration as a result of repeated negative experiences and
long local memories as described in previous literature (Nunn and Wantchekon, 2011; Lowes
and Montero, 2020a,b). A key assumption here is that there are relatively low levels of
internal migration, with most people residing in their provincial homelands. Although there
is no available data on migration, previous research has documented significant positive
correlations (0.7, p < 0.001) between historic, c.1850, ethnic/province level residence and
37 Data

is described in detail in Appendix A.6.

36

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contemporary Afrobarometer respondent locations by ethnicity (Archibong, 2019; Nunn and
Wantchekon, 2011); this suggests that the low migration assumption is reasonable here.
As a falsification test, we examine the effects of long-term colonial imprisonment on
interpersonal trust, and hypothesize that the effects of colonial imprisonment should only
be significant for trust in legal institutions, largely created during the colonial era, but
not interpersonal trust which perhaps may be determined by factors before the advent of
colonialism like the slave trade as shown in Nunn and Wantchekon (2011). As an additional
falsification test, we examine the relationship between postcolonial imprisonment and trust
outcomes, to check that the result on the negative effect of historical imprisonment on trust in
legal institutions only holds for colonial imprisonment but not for postcolonial imprisonment,
where prison labor was not used coercively by the state. As a final falsification test, to
ensure that the associations are not being driven by differences in crime between high and
low colonial imprisonment areas, we also test the following ‘crime propensity’ outcomes from
the Afrobarometer: whether the respondent has feared being the victim of a crime in their
home, and how often an individual had to bribe a government official to obtain a document
or permit in the last year.
While Equation 5 includes a rich set of controls, β does not identify the causal effect of
long-term colonial imprisonment on trust in legal institutions. It is possible that there is an
omitted variable, like lower inherent trust among imprisoned populations, that determines
both long-term colonial imprisonment exposure and trust in legal institutions. To address
this issue, we present results using an instrumental variables approach. We construct an
instrument for our colonial imprisonment outcome that is the interaction between two variables: (1) the soil suitability for palm oil and (2) an indicator that equals one if the colonial
province produced palm oil. The instrument is based on the findings of the strong predictive
power of palm oil production and prices for colonial imprisonment in Section 4.4.3. For

37

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instrument validity and for the exclusion restriction to hold, the soil suitability for palm oil
instrument must only affect the trust outcomes through colonial imprisonment.
To address concerns that the instrument may directly affect our trust in legal institutions outcomes through a channel other than colonial imprisonment, we include a rich set of
controls alongside the qualitative evidence from the historical literature. The quantitative
results and falsification tests when coupled with historical accounts of Nigerian residents’
contentions about the injustices of the colonial penal system, are suggestive of the negative
long-term impacts of colonial imprisonment on trust in legal institutions like police. We
present further evidence from the qualitative history in Appendix A.6.
Columns (1) to (3) in Table 8 show the OLS results on the association between longterm colonial imprisonment and trust in historical legal institution outcomes, while columns
(4) to (6) show the results on the association with interpersonal trust outcomes. High levels
of historic long-term colonial imprisonment are significantly negatively correlated with trust
in legal institutions, with no significant effect for interpersonal trust. The result does not
hold for the relationship between postcolonial imprisonment and trust in legal institutions
outcomes, as shown in Table A7 in the Appendix.
Panel A of Table 9 presents the first stage estimates for the instrument- using the
“soil suitability for palm oil x colonial palm oil production indicator” to predict our colonial
imprisonment outcome. The instrument predicts long-term colonial imprisonment, with
an F-stat greater than 10 across all specifications. Panel B of Table 9 reports the second
stage estimates for our main measure of trust in legal institutions, trust in police, and
one measure of interpersonal trust, trust in relatives. The IV estimates support the OLS
results for some trust outcomes38 . Exposure to long-term colonial imprisonment significantly
decreased contemporary trust in police. There is no effect on trust in relatives.
38 Tables

for other trust outcomes are available in Appendix A.6.

38

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To check that the result on the negative association between colonial imprisonment
and trust in legal institutions is not being driven by underlying differences in crime rates
between regions of high versus low levels of colonial imprisonment, we present results on crime
in Table A8. There is no significant association between colonial imprisonment and our three
crime variables as shown in columns (1) to (3). Respondents from areas with high levels
of colonial imprisonment are not more likely to experience or commit crimes. Interestingly,
when we examine the links between postcolonial imprisonment and crime, there is a small
significant positive association with the likelihood of an individual bribing a government
official to obtain a document or permit in column (4). The results provide strong, suggestive
evidence of the detrimental long-run effects of colonial incarceration, centered around prison
labor, on contemporary trust in legal institutions like police39 .

6

Conclusion

What are the effects on incarceration when prisoners are viewed and used as a source of labor
to serve economic interests? And what are the potential implications for citizens’ views of
state legitimacy, when an institution of state justice, like prison, is used to serve economic
interests? To answer these questions, we first digitized annual data from archival sources for
British colonial Nigeria. First, we show that prison was economically valuable to the colonial
regime. We present the first quantitative estimates on the value of prison labor in British
colonial Africa and find that the value of prison labor is strictly positive over the colonial
period. Even after accounting for an extensive set of prisoner maintenance costs, the net
value of prison labor is strictly positive in the majority of years in colonial Nigeria. Prison
labor made up a significant share of public works expenditures, up to 249% and 42% using
our gross and net values of prison labor respectively.
39 A

detailed discussion of the channels through which these effects may persist is beyond the scope of this
paper, though we present some preliminary analysis in Appendix A.6.

39

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We examine the effects of shocks to economic productivity on incarceration and the use
of prison labor. We find that incarceration rates during the colonial period are procyclical.
Moderate positive rainfall shocks and positive export price shocks that proxy increased agricultural productivity increase incarceration rates and the use of prison labor in the colonial
period. We provide quantitative and qualitative evidence that to show that a primary reason
for the procyclical behavior of incarceration rates during the colonial period was increased
labor demand for construction and maintenance of public works like railroads, needed to
intensify exports of agricultural commodities during periods of positive productivity shocks.
Labor shortages and tight labor markets increased the demand for unpaid prison labor, reflected in the rise in incarceration rates. The effect is reversed in the postcolonial period
where prison labor is not a major feature of state policy and public finance and negative
shocks increase incarceration rates.
We explore the implications of exposure to prison labor systems for present day views of
state judicial legitimacy and provide suggestive evidence of the negative long-term effects of
colonial incarceration on contemporary trust in legal institutions. We document a significant
reduction in contemporary trust in legal institutions like police in areas with high historical
levels of colonial imprisonment. The reduction in contemporary trust is specific to legal
institutions, with no effect on interpersonal trust. Historic exposure to judicial systems like
prisons prioritizing economic interests over ‘justice’ may lower individuals’ views of state
legitimacy and trust in legal institutions today. Conversely, effect does not hold for exposure
to postcolonial imprisonment. Given the renewed debates on the use of prison labor and the
judicial system in countries like the US, China and globally, our paper is the first, to our
knowledge, to provide quantitative estimates on the effects on incarceration when prisoners
are used as a store of labor, and its potentially detrimental effects on citizens’ views of state
legitimacy.

40

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Top 40 countri es, pri soners per 100,000 population, 2018
United States of America
El Salvador
Turkmenistan
Virgin Islands (USA}
Thailand
Cuba
Maldives
Northern Mariana Islands (USA}
Virgin Islands (United Kingdom}

Rwanda
Bahamas
St. Vincent and the Grenadines
Grenada
Panama
Seychelles
St. Kitts and Nevis

2:- Cayman Islands (United Kingdom}

_
_g

~
c

Guam (USA}
Costa Rica
Russian Federation
Anguilla (United Kingdom}
Belize

8

American Samoa (USA}

t:
Q)

::,

Brazil

Palau
Belarus
Nicaragua
Antigua and Barbuda
Bermuda (United Kingdom}
Turkey
Puerto Rico (USA}
Barbados
Cape Verde (Cabo Verde}
Uruguay
Namibia
Iran

Trinidad and Tobago
Dominica
Guyana
St. Lucia
0

200

400

600

Prisoners per 100,000 pop.

Figure 1: Top 40 countries/territories for incarceration rates, 2018 with Nigeria incarceration
rates in red (year 1940) and blue (year 2018). Source: World Prison Brief

41

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Share of total convictions

Share of total convictions by crime, 1920−1940
0.6

crime_convictions
miscellaneous minor offences

0.4

offences against property
offences against revenue, road, social economy colony laws

0.2

offences against the person

1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940

Year

Share of prison admissions

Share of total prison admissions by crime, 1977−1993
0.6

prison_admissions
miscellaneous minor offences

0.4

offences against property
offences against revenue, social economy laws

0.2

offences against the person
0.0
1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

Year

Figure 2: Share of total convictions in colonial courts and share of total prison admissions
in postcolonial period by crime in Nigeria, 1920-1993. Source: see text

Share of Direct and Indirect Taxes in Tax Revenue in Nigeria, 1933-1980

20.15-

share_tax_type

?

/'i.

~

1-

' a.ir.tom/tax

1-

d i'ect/tax

1-

petrolelffidiract

0.50•

~

~
~0.25-

"'

==n~u~~o~•-••~=-=n~n~•~n~-~~-=nNnnunu~u~
Year
Share of Direct and Indirect Taxes in Total Govt. Reven ue in Nigeria, 1933-1980

~
~0.75•
0:

;:

share_total_type

8 050·

1-

lcustom/totel

-

d i'eclltotal

-;;;

~
0
10.25-

"'
1932

1934

1936 1933 1940 1942 1944

HM6

1948 1950 1952 1954

1956 1958 1960

1962 1964

1966 1968 1970 1972

1974

1976

1978

1980 1982

Year

Figure 3: Composition of tax revenue in Nigeria, 1930-1980

42

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---

AVDA• aAft Of' WAOU ,oa La.8DUL

ftn911D6Lanvu . . . . . . . . . . . 111Ga81.A. ..

J

.. ,,-~.......,___ _...... --.

(lit~e.,.•·

~==::~~-::~-=
:..'::.:'-~ . . . - «•--...

.

I

:::

........
...,
,

fi

Figure 4: Example of archival data on prisons and wages from the British Blue Books (1922)

Colonial Provinces by Reg ion
1500000

zone_south

1250000

1.00
Q)

u

0.75

,E 1000000
co

0.50

:::l

_J

0.25
0.00
Legend
•

Pnsons

+ + RaiWOOd

500000

C)Provlnces

0e+00

4e+05

8e+05

Longitude

Figure 5: Nigeria provinces with colonial prison locations and railroad network shown (left)
and regions (right)

43

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(a) Annual average wage and prisoner costs, 1920-1959

(b) Daily average number in prison
14000

§

12000

"'
"§..
.!:

~

E
::,

.,C 10000
Cl

~

~
.?::-

·.;
0

1920

1930

1940

1950

8000

1960

Year
categ ory

~

Prison costs

~

Prisoner costs: food

~

1920

Urban unskilled wage

1930

1940

1950

1960

Year

Figure 6: Wages, prisoner costs and daily average number in prisons in colonial Nigeria,
1920-1959
(a) Value of prison labor

(b) Prison la bor as a share of public w orks expenditure

,sooooo

1i

1000000

.8.,,

l~
0

!l
~

c a tegory -

Net value less food costs -

Net value less pmon costs -

Total value, estimate -

Total value, reported

(c) Prison labor as a share of expenditure on prisons

1920

catego ry -

""

...

,

"'"'

Net value less prison costs/prison exp -

Net value less pris on costs/public worts exp

-

T otal value/public wonr.s exp

(d ) Prison labor as a share of total expenditure

Year

Net value less food costs/prison exp. -

Net value ktu food costs/public wori<.s exp -

category -

Total value/prison exp.

...

,

1920

Year
category -

Net v l!lue len food costs/total exp

Figure 7: Relative value of prison labor, 1920-1959

44

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-

Net value less prison costsllotal exp

-

Total value/total exp

Value of wages for laborers
25

40

sector
market

20

I

0
1919

1920

1921

1922

1923

1924

prison

Value of wages (pence)

Value of wages (pence)

Value of wages for bricklayers
60

20
15
10
5
0

1925

L LLLLL
1919

1920

1921

Year

■ market
■ prison

20

0
1922

1923

1924

Fraction below market rate

Value of wages (pence)

sector

1921

1924

I

prison

1925

Percentage of prison wages below market rate

40

1920

1923

market

Year

Value of wages for carpenters

1919

1922

sector

1925

0.80
0.75

professions
bricklayer

0.70

carpenter
0.65

laborer

0.60
1919

Year

1920

1921

1922

1923

1924

1925

Year

Figure 8: Value of wages for different skill categories in prison and market sectors, 1919-1925

45

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Mean Nos. of Prisoners (per 10^5 pop.), 1920−1995, Nigeria

Prisoners ( 105)

300

200

100

1920

1930

1940

1950

1960

1970

1980

1990

Year

Figure 9: Mean number of prisoners per 100,000 population, 1920-1995
Prisoners per 100,000 pop., 1920

Prisoners per 100,000 pop., 1980
14

1500000

12

prisoners

prisoners
600

1000000

400
200

Latitude

Latitude

1250000

10

200
150
100

8

50
0

750000

6

500000
4
0e+00

4e+05

8e+05

5

Longitude

10

Longitude

Figure 10: Prison populations in colonial (1920) and postcolonial (1980) Nigeria

46

Electronic copy available at: https://ssrn.com/abstract=3635484

15

Table 1: Summary Statistics: Economic shocks and incarceration rates
Statistic

N

Mean

St. Dev.

Min

Max

Prisoners, 1920-1938
All Prisoners Total
Penal Imprisonment Total
Custody Total
Short-Term (<= 6 Months) Total
Medium-Term (6Mo-2Y) Total
Long-Term (>=2yr) Total
1 Previous Total
2 Previous Total
3 Previous Total
All Prisoners /100, 000
Penal Imprisonment /100, 000
Custody /100, 000
Short-Term /100, 000
Medium-Term /100, 000
Long-Term /100, 000
Share w/ 1 Previous
Share w/ 2 Previous
Share w/ 3 Previous

324
324
324
324
324
324
324
324
324
324
324
324
324
324
324
324
324
324

1, 811.76
1, 251.83
509.59
1, 051.05
127.15
68.93
285.26
49.51
31.80
240.73
162.03
71.73
134.66
16.56
10.18
0.11
0.02
0.02

2, 286.76
1, 626.78
635.57
1, 409.20
171.34
84.10
503.19
73.51
48.07
254.56
169.55
83.47
144.95
18.26
12.88
0.15
0.03
0.03

3.00
2.00
0.00
2.00
0.00
0.00
0.00
0.00
0.00
0.26
0.26
0.00
0.16
0.00
0.00
0.00
0.00
0.00

10, 231.00
7, 010.00
3, 039.00
6, 377.00
882.00
417.00
2, 967.00
503.00
321.00
1, 123.30
759.99
333.66
649.43
80.45
83.45
0.90
0.32
0.18

Agricultural Commodities and Rainfall Deviation, 1920-1938
Cocoa Producing
Groundnut Producing
Palm Oil Producing
Log Cocoa Price
Log Groundnut Price
Log Palm Oil Price
Rainfall Dev.
Rainfall Dev. Sq.
Positive Rainfall Shock (M)
Negative Rainfall Shock (E)
Positive Rainfall Shock (E)

393
393
393
393
393
393
393
393
393
393
393

0.15
0.18
0.19
1.04
0.35
0.72
−0.00
0.95
0.17
0.30
0.21

0.35
0.39
0.39
0.40
0.36
0.53
0.97
1.83
0.38
0.46
0.41

0.00
0.00
0.00
0.47
−0.36
−0.22
−2.21
0.00
0.00
0.00
0.00

1.00
1.00
1.00
1.96
0.88
1.69
4.08
16.67
1.00
1.00
1.00

Prisoners and Rainfall Deviation, 1971-1995
All Prisoners Total
All Prisoners /100, 000
Share w/ 1 Previous*
Share w/ 2 Previous*
Share w/ 3 Previous*
Rainfall Dev.
Rainfall Dev. Sq.
Positive Rainfall Shock (M)
Negative Rainfall Shock (E)
Positive Rainfall Shock (E)

871
871
6
6
6
560
560
560
560
560

2, 005.81
92.48
0.21
0.12
0.13
0.01
0.09
0.49
0.04
0.01

1, 210.56
60.43
0.02
0.02
0.04
0.30
0.12
0.50
0.19
0.11

104.00
9.91
0.18
0.10
0.05
−0.62
0.00
0.00
0.00
0.00

7, 092.00
361.99
0.23
0.16
0.18
1.06
1.11
1.00
1.00
1.00

Notes: See text and online appendix for details. *denotes that data is based on available time series information from
1975-1980.

47

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Mean Nos. of Prisoners (per 10'5 pop.), 1920-1938, Nigeria

Mean Nos. of Prisoners (per 10'5 pop.) by Region, 1920- 1938, Nigeria

300
400

~;:;

-

~

~

~ 300

--

prisoners
-

~

~

short_ temi

.···-..

g
~

..

prisoners

..:::. 200

£
it

long_term

100

all
oorth

200

-- · south

100

---- --- --- --------- --1925

1920

1935

1930

1920

1925

1930

Year

1935

Year

Agricultural Commodity Prices, 1920-1938

Mean Nos. of Prisoners (per 10'5 pop.), 1971-1995, Nigeria

2.0

1.5

B

ct
g- 1.0

commodity

0

.c

3

groundnut

05

--· palmoil

.3

0.0

1920

1935

1930

1925

1970

1975

1985

1980

Year

1990

Year

Figure 11: Prisoners and agricultural commodity prices, 1920-1995, Nigeria

Cocoa Producing Locations, 1920-1938

Groundnut Producing Locations, 1920-1938
1500000

1500000

cocoa
1250000

groundnut
1250000

1.00

-g
"

0.75

1.00

"
!" 1000000

0.75

~

~1000000

0.50

0.50

0.25

0.25

750000

750000
0.00

0.00

500000

500000

Oe•OO

4e•05

4e+0s
Longitude

8e+05

longitude

Palm oil Producing Locations, 1920-1938

ae-os

Colonial Provinces by Region

1500000

1500000

palmoil
1250000

1250000

1.00

~

0 .75

j

0.50

-~ 1000000

1.00

-8

0 . 75

~1 000000

0.50

j

0.25

750000

0.25

750000
0 00

500000

0 00
500000

Oe,00

4e+0S

Oe+OO

8e+0S

Longitude

4e+05

8e+0S

Longitude

Figure 12: Agricultural commodity production in colonial Nigeria

48

Electronic copy available at: https://ssrn.com/abstract=3635484

1995

Table 2: Rainfall shocks and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates

Rainfall Dev

Mean of outcome

49

Electronic copy available at: https://ssrn.com/abstract=3635484

Rainfall Dev Sq

District FE
Year FE
Observations
Clusters

All Penal

Short-Term

Medium-Term

Long-Term

All 1971-95

(1)

(2)

(3)

(4)

(5)

14.147∗∗
(6.041)
[0.038]
−3.569
(2.479)
[0.246]

11.995∗
(6.433)
[0.065]
−4.884∗
(2.816)
[0.068]

1.796
(1.276)
[0.212]
0.205
(0.387)
[0.629]

0.759
(1.227)
[0.655]
0.752
(0.739)
[0.494]

−6.237
(8.570)
[0.454]
34.275∗∗∗
(9.692)
[<.001]

162.032

134.659

16.556

10.175

104.802

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
556
36

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial
province for colonial data, and postcolonial state for postcolonial data. Wild cluster bootstrap (by district) p-values are
in brackets. Observations are provinces. Dependent variables in (1)-(5) are prisoners per 100,000 population (1939 pop.)
by province in Nigeria broken down by all prisoners, penal imprisonment, custody/awaiting trial, short-term (less than 6
months) sentence and medium-term (between 6 months to 2 years) sentence and long-term (greater than 2 years) sentence
over 1920-1938. Dependent variable in (6) is prisoners per 100,000 population (1990 pop.) by state in Nigeria. Results
remain unchanged when we replace the denominator for the incarceration rates with the adult population of the province
only. Rainfall deviation as defined in text. District FE are colonial province fixed effects in (1)-(5), and postcolonial state
fixed effects in (6). ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent
level based on clustered standard errors in parentheses.

Table 3: Rainfall shocks and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates by region
Short-Term
All
Rainfall Dev

Mean of outcome

50

Electronic copy available at: https://ssrn.com/abstract=3635484

Rainfall Dev Sq

District FE
Year FE
Observations
Clusters

Long-Term

All 1971-95

South

North

All

South

North

11.995∗
(6.433)
[0.065]
−4.884∗
(2.816)
[0.068]

18.884∗
(11.046)
[0.142]
−8.686∗∗
(4.235)
[0.046]

1.978
(1.234)
[0.205]
0.860∗∗∗
(0.309)
[<.001]

0.759
(1.227)
[0.655]
0.752
(0.739)
[0.494]

−0.071
(2.201)
[0.989]
1.381
(1.346)
[0.541]

0.236
(0.338)
[0.544]
0.062
(0.098)
[0.675]

134.659

217.517

18.657

10.175

14.743

3.781

Yes
Yes
324
21

Yes
Yes
189
10

Yes
Yes
135
11

Yes
Yes
324
21

Yes
Yes
189
10

Yes
Yes
135
11

All
−6.237
(8.570)
[0.454]
34.275∗∗∗
(9.692)
[<.001]
104.802
Yes
Yes
556
36

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial province for colonial data, and postcolonial
state for postcolonial data. Wild cluster bootstrap (by district) p-values are in brackets. Dependent variables are prisoners per 100,000 population (1939 pop.) by province
in Nigeria broken down by short-term (less than 6 months) sentence and long-term (greater than 2 years) sentence over 1920-1938, for all provinces and Southern and
Northern Provinces separately; and prisoners per 100,000 population (1990 pop.) in the postcolonial era from 1971-1995 by state in Nigeria in the last column. District
FE are colonial province fixed effects for colonial data, and and postcolonial state fixed effects for postcolonial data. ∗∗∗ Significant at the 1 percent level, ∗∗ Significant
at the 5 percent level, ∗ Significant at the 10 percent level based on clustered standard errors in parentheses.

Table 4: Rainfall shocks (by type) and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates breakdown
Short-Term
(1)
Positive rainfall shock (M)

(2)

16.727∗∗∗

51

Electronic copy available at: https://ssrn.com/abstract=3635484

−20.290∗∗
(9.484)
[0.057]

Positive rainfall shock (E)

Mean of outcome
District FE
Year FE
Observations
Clusters

(3)
12.142∗

(5.456)
[0.016]
Negative rainfall shock (E)

Long-Term

(6.964)
[0.093]
−17.225∗
(10.259)
[0.139]
−0.404
(13.973)
[0.977]

134.659

134.659

134.659

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

(4)

(5)

−1.638
(1.319)
[0.336]

All 1971-95
(6)

(7)

(8)

(9)

−4.387
(4.132)
[0.320]

−1.060
(2.894)
[0.762]

−0.695
(1.437)
[0.683]
−0.429
(3.530)
[0.886]
3.358
(2.654)
[0.293]

10.175

10.175

10.175

104.802

104.802

104.802

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
556
36

Yes
Yes
556
36

Yes
Yes
556
36

22.722∗∗∗
(7.814)
[0.016]

−2.320
(4.564)
[0.620]
22.545∗∗∗
(7.807)
[0.012]
20.423∗∗
(8.268)
[0.046]

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial province for colonial data, and postcolonial state for postcolonial data. Wild cluster
bootstrap (by district) p-values are in brackets. Observations are districts. Dependent variables in (1)-(6) are prisoners per 100,000 population (1939 pop.) by province in Nigeria broken down by short-term (less
than 6 months) sentence( (1)-(3))and long-term (greater than 2 years) sentence((4)-(6)) over 1920-1938. Dependent variable in (7)-(9) is prisoners per 100,000 population (1990 pop.) by state in Nigeria. Positive
rainfall shock (M) where (M) is moderate, and (E) is extreme as defined in text. District FE are colonial province fixed effects in (1)-(6), and postcolonial state fixed effects in (7)-(9). ∗∗∗ Significant at the 1 percent
level, ∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent level based on clustered standard errors in parentheses.

Table 5: Rainfall shocks and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates by region
Short-Term
All
Positive rainfall shock (M)

District FE
Year FE
Observations
Clusters

52

Electronic copy available at: https://ssrn.com/abstract=3635484

Mean of outcome

16.727∗∗∗
(5.456)
[0.016]

South
24.826∗∗∗
(7.795)
[0.009]

134.659

217.517

Yes
Yes
324
21

Yes
Yes
189
10

Long-Term
North

All

All 1971-95

South

North

0.392
(1.086)
[0.729]

−1.638
(1.319)
[0.336]

−2.609
(2.127)
[0.408]

−0.573
(0.446)
[0.174]

18.657

10.175

14.743

3.781

Yes
Yes
135
11

Yes
Yes
324
21

Yes
Yes
189
10

Yes
Yes
135
11

All
−4.387
(4.132)
[0.320]
104.802
Yes
Yes
556
36

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial province for colonial data, and postcolonial
state for postcolonial data. Wild cluster bootstrap (by district) p-values are in brackets. Observations are provinces. Dependent variables in (1)-(6) are prisoners
per 100,000 population (1939 pop.) by province in Nigeria broken down by short-term (less than 6 months) sentence( (1)-(3))and long-term (greater than 2 years)
sentence((4)-(6)) over 1920-1938. Dependent variable in (7) is prisoners per 100,000 population (1990 pop.) by state in Nigeria. Positive rainfall shock (M) where (M)
is moderate as defined in text. District FE are colonial province fixed effects in (1)-(6), and postcolonial state fixed effects in (7). ∗∗∗ Significant at the 1 percent level,
∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent level based on clustered standard errors in parentheses.

Table 6: Agricultural commodity prices and colonial incarceration rates
Short-Term
(1)
Palm oil x Palm oil price

Groundnut x Groundnut price

Mean of outcome

53

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Cocoa x Cocoa price

District FE
Year FE
Observations
Clusters

72.530∗∗

(2)

Long-Term
(3)

(4)

68.649∗∗

(29.037)
[0.065]
29.450
(21.660)
[0.219]
−11.989
(27.752)
[0.694]

(25.441)
[0.049]

134.659

134.659

Yes
Yes
324
21

Yes
Yes
324
21

(5)

(6)

(7)

(8)

4.151
(3.416)
[0.271]

−49.111∗
(27.060)
[0.245]

1.588
(4.355)
[0.724]
−7.111
(4.520)
[0.166]
−9.858∗
(5.419)
[0.145]

134.659

134.659

10.175

10.175

10.175

10.175

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

4.146
(17.959)
[0.824]

−6.535∗∗
(2.722)
[0.086]
−9.130∗∗
(3.505)
[0.119]

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial province for colonial data. Wild cluster bootstrap (by district) p-values are
in brackets. Observations are provinces. Dependent variables are prisoners per 100,000 population (1939 pop.) by province in Nigeria broken down by short-term (less than 6 months) sentence and
long-term (greater than 2 years) sentence over 1920-1938. Prices are in logs. District FE are colonial province fixed effects. ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level,
∗ Significant at the 10 percent level.

Table 7: Effect of wages and distance to railroad on colonial incarceration rates

Short-Term
(1)

Long-Term

(2)

(3)

(4)

−0.301∗
(0.158)
[0.005]

−1.479∗∗
(0.681)
[0.010]
0.401∗∗
(0.191)
[0.038]

−0.018
(0.023)
[0.440]

−0.029
(0.099)
[0.807]
0.004
(0.033)
[0.927]

Mean of outcome

46.198

46.198

3.990

3.990

District FE
Year FE
Observations
Clusters

Yes
Yes
938
21

Yes
Yes
938
21

Yes
Yes
822
21

Yes
Yes
822
21

Distance to railroad

Distance x Log wages

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district
is colonial province for colonial data. Wild cluster bootstrap (by district) p-values are in brackets. Observations
are individual prisons. Dependent variables in (1)-(4) are prisoners in each prison per 100,000 population of the
province broken down by short-term (less than 6 months) sentence and long-term (greater than 2 years) sentence
over 1920-1938. Covariates are distance to railroad in km and log urban unskilled wages. District FE are colonial
province fixed effects in (1)-(4). ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant
at the 10 percent level based on clustered standard errors in parentheses.

54

Electronic copy available at: https://ssrn.com/abstract=3635484

Table 8: OLS Estimates: Relationship between colonial imprisonment and present-day trust in historical legal Institutions
versus interpersonal trust
Trust in Historical Legal Institutions

Interpersonal Trust

Courts

Tax

Neighbors

Relatives

Local Gov

(1)

(2)

(3)

(4)

(5)

(6)

−0.013∗∗∗
(0.004)
[0.003]

−0.007∗
(0.004)
[0.080]

−0.015∗∗∗
(0.005)
[0.063]

−0.010
(0.011)
[0.442]

0.007
(0.010)
[0.604]

−0.000
(0.004)
[0.954]

Mean of outcome

0.630

1.107

1.308

0.849

1.896

0.855

Population Density
Individual Controls
Geographic Controls
Disease Controls
Precolonial and Colonial Controls

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
8,349
21

Yes
Yes
8,256
21

Yes
Yes
3,063
21

Yes
Yes
3,415
21

Yes
Yes
3,261
21

Yes
Yes
6,578
21

Prisoners per 100,000 pop.

55

Electronic copy available at: https://ssrn.com/abstract=3635484

Police

District FE
Year FE
Observations
Clusters

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by colonial province. Wild cluster bootstrap (by district) p-values
are in brackets. The unit of observation is an individual. Prisoners per 100,000 pop. are averages of long-term (>2 years sentence) prisoners per 100,000
population (1939 pop.) over 1920 to 1938. Trust variables are from the Afrobarometer samples over 2003 to 2014 and as defined in the main text.
Trust outcomes are reported trust levels on a scale of 0-3, where “Not at all”= “0”, “Just a little”=“1”, “Somewhat”=“2”, “A lot”=“3”. All regressions
use district fixed effects at the current state level in Nigeria, year fixed effects, educational attainment fixed effects and controls for sub-district or local
government area population density in 2006. Individual controls include age, age squared and gender. Geographic controls at the sub-district level include,
ruggedness, indicators for petroleum, seacoast and mean land suitability for agriculture and mean elevation in alternate specifications. Disease controls
at the sub-district level include malaria suitability and tse tse fly suitability in alternate specifications with results unchanged. Precolonial and colonial
controls at the ethnicity-level include the level of precolonial centralization and total exports of slaves from the region during the Atlantic slave trade.
∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent level.

Table 9: First and second-stage estimates for interacted instrument and effect of colonial
imprisonment on trust in police (legal) and trust in relatives (interpersonal)
Panel B: Second-Stage 2SLS Estimates
Trust in Police
Trust in Relatives
(1)
Prisoners per 100,000 pop.

(2)

−0.021∗∗∗
(0.005)

−0.022∗∗∗
(0.005)

(3)

(4)

0.016
(0.024)

0.005
(0.035)

Panel A: First-Stage Estimates
Soil Suitability for Palm Oil
x Colonial Palm Oil Production

F-Stat of Excluded Instrument
Population Density
Individual Controls
Geographic Controls
Disease Controls
Precolonial and Colonial Controls
District FE
Year FE
Observations
Clusters

0.191∗∗∗
(0.050)

0.187∗∗∗
(0.040)

0.214∗∗∗
(0.053)

0.227∗∗∗
(0.045)

14.80

21.65

16.13

25.21

Yes
Yes
No
No
No

Yes
Yes
Yes
Yes
Yes

Yes
Yes
No
No
No

Yes
Yes
Yes
Yes
Yes

Yes
Yes
10,693
21

Yes
Yes
8,349
21

Yes
Yes
4,355
21

Yes
Yes
3,415
21

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by colonial province. The unit of
observation is an individual. Prisoners per 100,000 pop. are averages of long-term (>2 years sentence) prisoners per 100,000
population (1939 pop.) over 1920 to 1938. Trust variables are from the Afrobarometer samples over 2003 to 2014 and
as defined in the main text. Trust outcomes are reported trust levels on a scale of 0-3, where “Not at all”= “0”, “Just a
little”=“1”, “Somewhat”=“2”, “A lot”=“3”. All regressions use district fixed effects at the current state level in Nigeria,
year fixed effects, educational attainment fixed effects and controls for sub-district or local government area population
density in 2006. Individual controls include age, age squared and gender. Geographic controls at the sub-district level
include ruggedness, indicators for petroleum, seacoast and mean elevation in alternate specifications. Disease controls at
the sub-district level include malaria suitability and tse tse fly suitability in alternate specifications with results unchanged.
Precolonial and colonial controls at the ethnicity-level include the level of precolonial centralization and total exports of
slaves from the region during the Atlantic slave trade. ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent
level, ∗ Significant at the 10 percent level.

56

Electronic copy available at: https://ssrn.com/abstract=3635484

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A

Appendix (For Online Publication)

Contents
1 Introduction

2

2 Prison Labor in Colonial Africa

8

2.1

A History of Forced Labor . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8

2.2

Prison Labor in British Colonial Nigeria . . . . . . . . . . . . . . . . . . . .

10

3 Estimating the Value of Prison Labor

15

3.1

Historical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15

3.2

Empirical Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

16

3.3

Value of Prison Labor Results . . . . . . . . . . . . . . . . . . . . . . . . . .

18

3.3.1

Comparing Imputed Estimates of the Value of Prison Labor to Reported Colonial Estimates . . . . . . . . . . . . . . . . . . . . . . . .

20

4 The Effects of Economic Shocks on Incarceration Rates and the Use of
Prison Labor

21

4.1

Data on Incarceration Rates and Economic Shocks . . . . . . . . . . . . . .

21

4.2

Summary Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

23

4.3

Estimating Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

24

4.3.1

Nonlinear Effects of Economic Shocks on Incarceration Rates . . . . .

25

4.3.2

Identifying the Effects of Positive Rainfall Shocks on Incarceration Rates 27

4.3.3

Effects of Cash Crop Price Shocks on Colonial Incarceration Rates . .

29

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

30

4.4.1

30

4.4

Nonlinear Effects of Economic Shocks on Incarceration Rates Results

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4.4.2

Identifying the Effects of Positive Rainfall Shocks on Incarceration
Rates Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.4.3

4.4.4

31

Effects of Cash Crop Price Shocks on Colonial Incarceration Rates
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33

Railroad, Wages and Incarceration Rates . . . . . . . . . . . . . . . .

34

5 Discussion: Colonial Imprisonment and Contemporary Trust in Legal Institutions

35

6 Conclusion

39

A Appendix (For Online Publication)

67

A.1 Data and Archival Materials . . . . . . . . . . . . . . . . . . . . . . . . . . .

71

A.2 A Further History of Forced and Prison Labor in Colonial Africa . . . . . . .

72

A.3 North-South Differences in the Distribution of Colonial versus Native Prisons

77

A.4 Value of Prison Labor Specification Checks . . . . . . . . . . . . . . . . . . .

80

A.4.1 Value of Prison Labor: Adjusting for Inflation . . . . . . . . . . . . .

80

A.4.2 Value of Prison Labor: Measuring Bias in Estimates . . . . . . . . . .

83

A.4.3 Relative Value of Prison Labor: Comparison to Recurrent Maintenance
Public Works Expenditure . . . . . . . . . . . . . . . . . . . . . . . .

84

A.5 Suggestive Evidence of Sentence-Switching in Response to Short-Term Economic Shocks: Custody and Short-Term Incarceration Rates and Further Robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

85

A.6 Relationship between Colonial Imprisonment and Trust in Colonial Institutions versus Interpersonal trust . . . . . . . . . . . . . . . . . . . . . . . . .

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88

List of Figures
1

Top 40 countries/territories for incarceration rates, 2018 with Nigeria incarceration rates in red (year 1940) and blue (year 2018). Source: World Prison
Brief . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

41

Share of total convictions in colonial courts and share of total prison admissions in postcolonial period by crime in Nigeria, 1920-1993. Source: see text

42

3

Composition of tax revenue in Nigeria, 1930-1980 . . . . . . . . . . . . . . .

42

4

Example of archival data on prisons and wages from the British Blue Books
(1922) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5

Nigeria provinces with colonial prison locations and railroad network shown
(left) and regions (right) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6

43

43

Wages, prisoner costs and daily average number in prisons in colonial Nigeria,
1920-1959 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

44

7

Relative value of prison labor, 1920-1959 . . . . . . . . . . . . . . . . . . . .

44

8

Value of wages for different skill categories in prison and market sectors, 19191925 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45

9

Mean number of prisoners per 100,000 population, 1920-1995 . . . . . . . . .

46

10

Prison populations in colonial (1920) and postcolonial (1980) Nigeria . . . .

46

11

Prisoners and agricultural commodity prices, 1920-1995, Nigeria . . . . . . .

48

12

Agricultural commodity production in colonial Nigeria . . . . . . . . . . . .

48

A1

Breakdown of estimated public works expenditure, Northern (NP) and Southern (SP) Provinces, 1920 and 1935

. . . . . . . . . . . . . . . . . . . . . . .

76

A2

Native administration prisons, 1940 . . . . . . . . . . . . . . . . . . . . . . .

78

A3

Native prison incarceration rates, 1940 and 1945 . . . . . . . . . . . . . . . .

79

A4

Value of prison labor, real vs nominal estimates . . . . . . . . . . . . . . . .

80

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A5

Alternate prison and value of labor coercion measures, 1920-1938

. . . . . .

84

A6

Relative value of prison labor, 1920-1959 . . . . . . . . . . . . . . . . . . . .

85

List of Tables
1

Summary Statistics: Economic shocks and incarceration rates . . . . . . . .

2

Rainfall shocks and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

50

Rainfall shocks (by type) and colonial (1920-1938) and postcolonial (19711995) incarceration rates breakdown . . . . . . . . . . . . . . . . . . . . . . .

5

49

Rainfall shocks and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates by region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4

47

51

Rainfall shocks and colonial (1920-1938) and postcolonial (1971-1995) incarceration rates by region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

52

6

Agricultural commodity prices and colonial incarceration rates . . . . . . . .

53

7

Effect of wages and distance to railroad on colonial incarceration rates . . . .

54

8

OLS Estimates: Relationship between colonial imprisonment and present-day
trust in historical legal Institutions versus interpersonal trust . . . . . . . . .

9

55

First and second-stage estimates for interacted instrument and effect of colonial imprisonment on trust in police (legal) and trust in relatives (interpersonal) 56

A1

Relationship between precolonial centralization and number of colonial vs native prisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

79

A2

Value of prison labor, 1920-1959 . . . . . . . . . . . . . . . . . . . . . . . . .

81

A3

Value of prison labor, real estimates . . . . . . . . . . . . . . . . . . . . . . .

82

A4

Rainfall shocks (by type) and colonial (1920-1938) incarceration rates by custody/awaiting trial category . . . . . . . . . . . . . . . . . . . . . . . . . . .

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86

A5

Effect of agricultural commodity prices and distance to railroad on colonial
incarceration rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

87

A6

Summary Statistics: Afrobarometer Results . . . . . . . . . . . . . . . . . .

91

A7

Falsification Test: OLS Estimates of relationship between postcolonial imprisonment and present-day trust in historical legal Institutions versus interpersonal trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

A8

OLS Estimates: Relationship between colonial and postcolonial imprisonment
and present-day crime outcomes . . . . . . . . . . . . . . . . . . . . . . . . .

A9

92

93

IV Estimates: Effect of relationship between colonial imprisonment and presentday trust in historical legal Institutions versus interpersonal trust . . . . . .

94

A10 OLS Estimates: Colonial palm oil suitability and production instrument does
not predict postcolonial imprisonment . . . . . . . . . . . . . . . . . . . . . .
A.1

95

Data and Archival Materials

• Primary data from British Online Archives, Nigeria [Colony and Protectorate] Blue
Book, 1914-1940. British Foreign and Commonwealth Office
• Nigeria, Annual Report on the Prisons Department, Northern and Southern Provinces,
1914-1960
• NAI, CSO 26/2 09591 Vol.1 ‘Lieutenant Governor Southern Province to Resident Calabar Province: Memorandum on Prison labor’ 23rd April 1923
• Annual Report on the Treatment of Offenders, 1947, Nigeria
• Nigeria Annual Abstract of Statistics, 1975-1997

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A.2

A Further History of Forced and Prison Labor in Colonial Africa

Prison labor was a small part of a larger regime of domestic forced labor in colonial Africa.
A small but rich and growing labor history of colonial Africa has documented the ways in
which the so-called “revenue imperative” of colonial governments, whose objectives were to
maximize revenue extraction while minimizing costs of administration in Africa, led to the
establishment of coercive labor contracts in the region (Freund, 1984; Maul, 2007; Okia, 2012;
Gardner, 2012; Cooper, 1996; Harris, 1914; Trevor, 1936; van Waijenburg, 2018; Alexopoulou
and Juif, 2017). Following the signing of the Final Act of Congress of Vienna in 1815
to abolish slavery, a series of contentious debates about the nature of forced labor, and
particularly the extent to which forced labor could be employed to fulfill the revenue demands
in Europe’s African colonies continued through the middle of the 20th century (Maul, 2007).
The debates highlighted a number of responses to Europe’s so-called “Africa labor question”,
where, faced with the realities of labor scarcity, increased demand for labor from both private
and public sector employers and an indigenous labor force with their own preferences for
work, the discussions shifted from questions about how to institute European systems of
wage labor and private property ownership in the colonies to the amount of coercion a
“civilized government” could use (Cooper, 1996).
Faced with these options - low pay for often dangerous, back-breaking work on railroads
or in mines, under sometimes racist40 , difficult employers - many Africans preferred selfemployment in subsistence farming to working in the colonial wage labor market (Frankema
and Van Waijenburg, 2012; Harris, 1914). To address these constraints, colonial governments
enacted a series of strategies to meet labor and revenue demands. Among these strategies
40 Harris (1914) reports of the comments of a white employer, Mr E Tarlton in Kenya who, in complaining
about labor shortages he faced, told the 1912 labor Commission in the East Africa Protectorate that “this
is my busiest season and my work is entirely upset, and it is hardly surprising if I am in a red-hot state
bordering on a desire to murder everyone with a black skin who comes within sight”, p. 821.

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included the use of direct taxation like hut and poll taxes requiring cash payment to press
Africans into the wage labor market, the use of labor tax legislation to force Africans to
donate a certain number of hours of often unpaid labor to private and public sector work,
and the use of precolonial communal labor requirements to compel Africans, under the
direction of the chiefs, to provide unpaid labor for private and public works projects (Okia,
2012; Harris, 1914; Trevor, 1936; van Waijenburg, 2018; Cooper, 1996).
In colonial Nigeria, forced labor regulation included the Native House Rule Ordinance
of 1901 and the Roads and Creek Proclamation of 1903, both of which mandated labor for
‘public purposes’ for all men between 15 and 50 years old and all women between 15 and
45 years old (Ofonagoro, 1982). The Masters and Servants Proclamations of 1901 and 1903
also instituted forced labor in colonial Nigeria, granting Native Administrators or chiefs the
authority to coerce local laborers for up to 24 working days in a year or 1 out of 12 months.
Laborers were frequently employed on public works projects and physically intensive manual
tasks like porterage, carrying pounds of baggage for British officials through often dangerous
environments like military expeditions for “miserable” below market-wage pay (Ofonagoro,
1982; Okia, 2012).
Following a series of forced labor scandals, one of which was the sanctioning of torture, mutilation and murder of millions of Congolese for the rubber extraction trade under
Belgium’s King Leopold through the 1890s, another debate on the labor question led to
the passing of the Slavery Convention by the League of Nations in 1926 (Hochschild, 1999;
Lowes and Montero, 2020a). The Convention urged European powers to abolish slavery “in
all its forms” and the League requested that the International Labor Organization (ILO)
investigate the “best means of preventing forced or compulsory labor from developing into
conditions analogous to slavery” (Cooper, 1996). p. 29. These exchanges led to the passing
of the Forced Labor Convention at the 1930 ILO conference which forbade the use of forced

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labor for private industry where forced labor was defined as “all work or service which is extracted from any person under the menace of any penalty and for which the said person has
not offered himself voluntarily” (Cooper, 1996). p. 2941 . The Convention made exceptions
for the use of forced labor for public works, ‘penal and communal labor in the public sector
and compulsory military service’ (Kunkel, 2018; Killingray, 1989).
While Britain was the first to sign the ILO article, followed by France and a few other
European governments in the mid 20th century, it, and its colonial peers continued, and in
some cases intensified forced labor practices through the use of ‘unofficial’ communal labor
for public works projects (Kunkel, 2018). The practice is exemplified in a 1944 statement
made by the then district commissioner of Northern Ghana’s Builsa district, who, in showing
the chief commissioner of the Northern territories the new projects the colonial government
had started funding in the region over the past years, among which were schools, rural
roads, bridges and dams, argued for the financial viability of the district by informing the
commissioner that the chief had supplied the government with unpaid communal labor:
“nearly all the labourers I find whom your Honour saw working in the new Sandema dam
are ‘voluntary’ workers, there are only seven names on the time sheet which is encouraging.”
(Wiemers, 2017), p.239. Many of these coercive labor practices continued through the end
of the 1930s and as late as the 1950s in some regions, when African workers began to
actively organize labor unions and strikes to protest labor contracts with fixed low wages
amidst rising food prices in the mid to late part of the 1930s after the Depression (Cooper,
1996). Among the most famous strikes were the 1935 Copperbelt strike of African miners in
Northern Rhodesia, the Mombasa general strike, the Dar es Salam dock strike and a number
of strikes on the railways of the Gold Coast in 1939 (Cooper, 1996).
In Nigeria, although prisoners were most often employed on public works, public works
41 ILO

29, Article 2 s 2a, c, e, Articles 4 and 5

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expenditure was a small fraction of overall colonial expenditures between 1920 and 1940,
composing an average of 2.8% of colonial expenditures over the period42 . As of 1920, 30%
of expenditure was on railways, 12% on servicing public debt, and 19% of expenditure was
devoted to defense spending on ‘marine, political and West African Frontier Force’. The
majority of revenues in 1920 were from customs (46%) and railways (23%). By 1936, the
share of expenditure on railways had dropped to 8% of overall expenditure, with public debt,
and pensions and gratuities remaining as the top spending categories for the colonial regime.
Public works expenditure in both years remained low at around 2%. While revenue from the
railway could be used to service railroad expenditure, only 2.8% of colonial expenditures,
on average, was allocated for less costly public works projects, like spending on civil roads,
canals, bridges and “buildings not of a military nature” (e.g. court houses and hospitals). A
breakdown of the top ten, where available, categories for estimated public works expenditure
in 1920 and 1935 for the Northern and Southern provinces is shown in Figure A143 . In the
Northern provinces in 1920, roads, public offices, hospitals and court houses accounted for
80% of overall public works expenditure, while government quarters, industrial plants and
roads accounted for 68% of overall public works expenditure in Southern provinces in the
same year. By 1935, the major public works expenditure categories in both the Northern
and Southern provinces were waterworks, electricity infrastructure projects and government
offices with 100% and 95% of overall public works expenditure in Northern and Southern
Provinces respectively. Convict labor, by colonial officials’ own admissions, was an essential
part of funding these public works projects (Foreign and Office, 1960). The use of prison
labor for colonial public works projects continued through the 1950s in British colonial Africa
with an estimated between 1 in 300 and 1 in 500 Africans imprisoned over 1930 through the
42 Author’s

estimates from Annual Report on Prisons Data over 1920 to 1940.
use estimated rather than actual expenditure in a given year to reflect colonial government expectation around expenditure and to account for unfinished projects and multiple missing entries in the ’spending
to date’ values provided in the Blue Books records.
43 We

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1950s, in contrast with 1 in 2000 British natives in Britain (Hynd, 2015).

--1,

Public works estimated expenditure breakdown, SP 1920

Category

Category

Public works estimated expenditure breakdown, NP 1920

Zaria Sokoto Road
Public Offices, Kaduna
Joinery and Machine Shops, Kaduna
Jos−Bauchi Road
European Hospital and Fittings, Kaduna
1 European Quarters (Type II), Jos
Native Hospital, Minna
Office for Station Magistrate and Court House, Kaduna
Four European Quarters (Type VII) −Kaduna
Offices and Court Room, Kano

0.0

0.1

0.2

0.3

Ten Quarters, Type IV of 1920, Lagos
Brick and Tile Plant, Ishiago
Four Quarters, Type IV, Benin
Four Quarters, Type IV, Port Harcourt
Customs Shed "I", Lagos
Produce Wharves, Lagos
Enugu−Abakaliki Road
Igbara−Oke−Igbara−Odo−Ikere Road
Completion of Agege−Lafenwa Road
Akure Ondo Road

I
0.00

Public works estimated expenditure breakdown, NP 1935

Category

Category

Landing Ground − Kano

Landing Ground − Minna
Landing Ground, Kaduna

Electricity Scheme − Kaduna
Landing Ground − Maiduguri
Butchers’ Stalls − Zaria Township

0.4

0.15

Public works estimated expenditure breakdown, SP 1935

Quaters and Offices, New Protectorate Court

0.2

0.10

Share of total estimated expenditure

Waterworks Scheme − Okene

0.0

0.05

Share of total estimated expenditure

0.6

Share of total estimated expenditure

Tank & Non−tank Latrines, Lagos
Electricity Supply Works − Lagos
Electricty Scheme − Abeokuta
Waterworks Scheme − Benin City
Waterworks Scheme − Abeokuta
Waterworks Schemes − Ife
Waterworks Scheme − Calabar
Mamfe − Bamenda Road
Workshop and Lecture Hall, Higher College, Yaba
Electricity Supply Works − Enugu

-

0.00

I
0.05

0.10

0.15

Share of total estimated expenditure

Figure A1: Breakdown of estimated public works expenditure, Northern (NP) and Southern
(SP) Provinces, 1920 and 1935

76

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0.20

A.3

North-South Differences in the Distribution of Colonial versus Native Prisons

There was a dual system of prison administration in Nigeria, under the Native Administration, overseen by local chiefs under indirect rule. Under indirect rule, areas with more
centralized precolonial institutions were granted more autonomy to oversee local administration, including on the creation and administering of Native Authority prisons. Results
from Table A1 confirm a significant positive correlation between the level of precolonial centralization and the numbers of native prisons (Archibong, 2019). Although we don’t have
detailed Native Administration prisons data over the 1920 to 1938 period, Figure A2 shows
the distribution of Native Administration prisons in 1940, for the first year of available data
in the colonial archives.
Native Authority or Administration prisons were more heavily concentrated in the
Northern provinces, which had a more extensive history of organized precolonial institutions
around courts than their southern counterparts (Killingray, 1999). Precolonial political institutions are proxied using Murdock’s (1967) “Jurisdictional Hierarchy Beyond the Local
Community Level” called the precolonial centralization index here. The precolonial centralization index or “Jurisdictional Hierarchy Beyond the Local Community Level” variable is an
index of “political complexity” that assigns a score between 0 to 4 to each ethnic region unit
and describes the number of political jurisdictional hierarchies above the local community
level for each unit. The score is defined as follows: 0 represents so-called “stateless societies”,“lacking any form of political organization”, 1 and 2 are petty and larger paramount
chiefdoms, 3 and 4 are large, more organized states. Table A1 provides suggestive evidence
of the positive correlation between precolonial centralization and the number of native prisons in a colonial province. While prison labor was a feature of all colonial era prisons, both
Native Administration and colonial government prisons, since Native Authority prisons were
77

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more numerous than colonial prisons44 , Native Authority prisons processed more prisoners
than colonial prisons in the north, with the share of prison labor coming primarily from
Native Authority prisons in the Northern provinces.

Legend
•

++
D

NativeAdministration Prisons
Railroad

Provinces

Figure A2: Native administration prisons, 1940

44 On

average there were 18 colonial prisons over 1920 to 1938 in the Northern provinces vs 56 Native
Authority prisons in 1940. The ratio for Southern provinces over those periods was 54 to 9. Source: colonial
archives.

78

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Table A1: Relationship between precolonial centralization and number of colonial vs native
prisons
Native prisons

Colonial prisons

(1)

(2)

0.599∗
(0.316)
1.447∗∗∗
(0.265)
22
0.124

Precolonial centralization
Constant
Observations
R2

0.515
(0.339)
2.112∗∗
(0.969)
19
0.026

Notes: Regressions estimated by OLS. Robust standard errors in parentheses.
Unit of observation is Murdock ethnic region. Precolonial centralization is
Murdock centralization index as defined in text.
∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level,
∗ Significant at the 10 percent level.

Prisoners per 100,000 pop., 1940 native

Prisoners per 100,000 pop. , 1945 native

1500000

1500000

1250000

1250000

240
200

1000000

160

i
~ 1000000
~

120
80

750000

750000

500000

500000
Oe•OO

4e+05

8e+05

Oo•OO

Longitude

4e+05

Longitude

Figure A3: Native prison incarceration rates, 1940 and 1945

79

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A.4

Value of Prison Labor Specification Checks

A.4.1

Value of Prison Labor: Adjusting for Inflation

The measures of values of prison labor used so far have been calculated using nominal values
as shown in Figure A4(a) and Table A2. One potential side effect of using nominal values
when observing trends over time is that is it difficult disentangle the difference between
changes in the observed variable and changes in the price level. To ensure that the trends in
our measure of prison labor are not driven by changes in the price level, we convert the values
into real values using 1920 as the base year, following the technique outlined in Frankema
(2011)45 . Figure A4(b) and Table A3 show trends in the value of prison labor, adjusted for
inflation. The trends remain unchanged using real versus nominal estimates of prison labor
and the value of prison labor is not driven by changes in the price level.
(a) Va lue of prison labor - nominal estimates

(b) Value of prison labor - real estimates

1500000

-;;;~

g
,,.8

1000000

category

-~

.

-s"

500000

ca tegory

-

Net value less food costs

-

Nelvaluelessprisoncosts

,,.8
il

-

Totalvalue,estimate

-~

-

Total value,reported

O

,

-

.

.....,. Totalvalue.estimate
.....,. Totalvalue.reported

1e+06

,

">

">

0.•00

1940

1940

Year

Year

Figure A4: Value of prison labor, real vs nominal estimates

45 Using

Net value less food costs

.....,. Nelvalue lessprisoncosts

Feinstein (1972)’s British price index data.

80

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Table A2: Value of prison labor, 1920-1959

81

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Year

Total
value
of
prison labor (PL),
estimate

Net value of PLless food costs

Net value of PLless prison costs

1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959

178, 498.10
176, 260.50
170, 936.80
145, 679.00
176, 716.20
185, 745.60
184, 522.30
188, 665.80
142, 465.90
134, 080.40
117, 659.00
113, 460.70
102, 978.70
97, 714.65
102, 992.10
94, 803.18
124, 892.90
115, 976.10
121, 687.10
135, 812.80
107, 276.90
101, 133.10
100, 486.60
103, 498.80

80, 740.86
79, 406.14
66, 501.46
112, 860.10
120, 236.40
108, 556.80
110, 374.10
69, 713.27
73, 090.61
57, 097.79
55, 957.54
54, 870.35
55, 956.14
59, 841.23
62, 325.81
89, 130.29
79, 873.06
80, 217.16
93, 269.02
61, 833.98
59, 647.90
60, 091.00
61, 346.58

55, 889.37
27, 912.67
19, 618.41
-11905.93
42, 908.14
47, 427.82
29, 269.52
32, 701.03
-14, 449.62
8, 683.13
-20, 521.35
-12, 285.62
-14, 204.48
-2, 798.60
133.75
-343.81
26, 931.63
19, 874.01
18, 640.54
29, 920.89
-4, 521.68
-11, 764.46
-30, 949.88
-34, 436.89

176, 359.10
242, 852.30
285, 395.90
285, 624.40
302, 473.20
401, 825.60

116, 201.00
169, 618.00
210, 935.60
208, 625.30
176, 454.90
284, 397.10

-1, 372.28
-127, 471.50
42, 200.86

53, 661
57, 312
64, 244
62, 222
60, 492
66, 052
67, 859
62, 358
60, 851
62, 408
59, 090
54, 415
52, 434
53, 956
50, 216
44, 767
44, 393
49, 536
54, 167
51, 517
50, 495
51, 780
50, 397
50, 640
50, 744
56, 525
52, 581
53, 208
70, 781
100, 942

431, 855.70
518, 616.60
631, 327.40
740, 092.80
992, 023.60
1, 023, 998.00
1, 133, 155.00
1, 532, 634.00

288, 159.40
352, 824.50

-15, 199.55
21, 240.32

118, 364
130, 981

513, 126.50

100, 460.50

146, 406

745, 241.50
818, 992.30
1, 196, 574.00

234, 187.20
177, 577.90
446, 565.70

179, 610
83, 461
91, 417

0
28, 666.32

Total value of PL,
reported

Share of total PL
value in public
works exp.

Share of net PL
value (food) in public works exp.

Share of net PL
value (prison) in
public works exp.

1.33
1.12

0.51

0.42
0.18

0.93
1.13
1.17
1.05
1.02
0.71
0.61
0.48
0.44
0.41
0.53
0.69
0.69
0.98
0.83
0.72
0.75
0.58
0.53
0.43
0.40

0.43
0.72
0.76
0.62
0.59
0.35
0.33
0.23
0.22
0.22
0.31
0.40
0.45
0.70
0.57
0.48
0.52
0.34
0.32
0.26
0.24

-0.08
0.27
0.30
0.17
0.18
-0.07
0.04
-0.08
-0.05
-0.06
-0.02
0.001
-0.002
0.21
0.14
0.11
0.17
-0.02
-0.06
-0.13
-0.13

0.60
0.73
0.59
1.43
1.44
1.77

0.39
0.51
0.43
1.04
0.84
1.25

0
0.09
-0.01
-0.61
0.19

2.49
2.49
2.20
1.71
1.24
1.09
1.19

1.66
1.69

-0.09
0.10

1.18

0.23

0.79
0.86

0.25
0.19

Table A3: Value of prison labor, real estimates
Year

1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959

Real total value of
prison labor (PL),
estimate
178, 498.10
160, 933.50
134, 452.30
107, 675.80
129, 917.90
136, 556.10
134, 927.40
134, 228.60
101, 359.10
94, 333.23
80, 454.55
74, 444.58
65, 938.95
61, 023.38
64, 319.20
59, 579.86
78, 983.62
76, 094.96
80, 804.11
92, 868.03
85, 651.90
89, 540.79
95, 323.28
101, 453.40

Real net value of
PL- less food costs

182, 632.70
259, 170.50
326, 005.60
351, 103.60
382, 574.80
524, 120.30

120, 334.70
181, 015.30
240, 950.10
256, 452.50
223, 184.10
370, 952.70

-1, 686.87
-161, 228.80
55, 044.60

48, 994.83
45, 079.40
47, 484.70
45, 744.24
44, 472.38
48, 298.89
48, 279.13
44, 365.37
42, 812.17
42, 674.24
38, 770.51
34, 842.81
32, 745.34
33, 695.84
31, 558.67
28, 311.15
29, 127.42
32, 893.47
37, 039.09
41, 132.15
44, 707.04
49, 119.37
49, 401.01
51, 040.32
52, 549.12
60, 323.12
60, 062.88
65, 405.88
89, 525.38
131, 663.50

670, 827.30
830, 196.60
1, 030, 586.00
1, 260, 790.00
1, 776, 232.00
1, 898, 242.00
2, 167, 774.00
2, 944, 111.00

447, 615.20
564, 798.20

-23, 610.36
34, 001.31

183, 861.90
209, 673.10

874, 140.40

171, 140.20

249, 411.00

1, 381, 495.00
1, 566, 768.00
2, 298, 557.00
82

434, 125.80
339, 714.30
857, 829.70

332, 952.90
159, 664.50
175, 607.40

73, 719.91
62, 457.80
49, 153.25
82, 972.27
88, 395.16
79, 379.46
78, 527.04
49, 598.37
51, 423.43
39, 043.15
36, 715.22
35, 134.37
34, 944.94
37, 371.20
39, 169.19
56, 366.98
52, 406.83
53, 266.73
63, 776.84
49, 369.43
52, 810.79
57, 003.32
60, 134.20

Real net value of
PL- less prison
costs
55, 889.37
25, 485.49
15, 431.08
-8, 800.04
31, 545.12
34, 867.89
21, 402.61
23, 265.56
-10, 280.36
6, 109.08
-14, 032.38
-8, 060.92
-9, 095.36
-1, 747.74
83.53
-216.07
17, 031.86
13, 039.86
12, 377.91
20, 459.74
-3, 610.20
-10, 415.97
-29, 359.57
-33, 756.32

Real total value of
PL, reported

0
30, 592.51

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A.4.2

Value of Prison Labor: Measuring Bias in Estimates

Using the daily average number of prisoners might not properly capture the entire sample
of prisoners whose labor was appropriated by the colonial government. Those who were
charged but sent out on bail for instance would still have to commit their labor but would
not be counted as being in prison.
As an alternative measure to the daily average in prison, we use the number of people
committed to penal imprisonment in each year, that is the number of people who were
arrested and sent to jail for one reason or another and who were expected to serve penal
labor. The number of people committed to prison however does not imply that they spend
the entire year there. Since the Blue Books break down sentences into 3 categories: those
committed for over 2 years, those committed for between 6 months and 2 years, and those
committed for less than 6 months, we weight the number of people committed to prison by
the categories of their duration of stay. Specifically, we assume that those with more than
two-year sentences spend 2 years in prison, those between six-month and two-year sentences
spend 1 year and 3 months in prison, and those with less than six-month sentences spend
3 months in prison. Finally, we assume that imprisonment started at the beginning of the
year hence 1 year in prison would run from January 1st until December 31st.
Figure A5(a) compares the daily average number in prison to our weighted average
measure of people committed to prison for penal imprisonment in each year. The daily
average as measured in the Blue Books tends to be much lower than our weighted average
measure of those committed to prison. This is true especially in the earlier years of our
sample. There however seems to be a convergence in both measures over time.
Recalculating the value of prison labor using our weighted measure of people committed
to prisons shows that using the average number in prison underestimates the value of prison

83

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labor. At its peak the value of prison labor is more than 60% larger when using the weighted
average of people committed for penal imprisonment compared to using the average number
in prison as shown in Figure A5(b). The trend however remains the same with the value
declining over time.
(a) Daily average in prison vs Weighted number of committed prisoners

{b) Value of prison labor- incl. alternate prison measure

i

ii

12000
~

~

~

250

0

~

I

.§__ 10000

0

]

200

~

§
z

300

·g_ 150

8000

0

..
~

>
1920

1925

1930

1935

100
1920

1925

1930

Year

category -

Daily average number in prison

1935

Year
-

Estimated numb er in prison- alternate

category -

Prison labor -

Prison labor- alternate

Figure A5: Alternate prison and value of labor coercion measures, 1920-1938

A.4.3

Relative Value of Prison Labor: Comparison to Recurrent Maintenance
Public Works Expenditure

The relative value of prison labor measures, comparing the value of prison labor to public
works expenditure in the main results used expenditure on new public works construction as
the main category for comparison. The rationale is that new construction represents valueadding investment in productive public works, as opposed to just upkeep or maintenance.
The archival data also records information on recurrent maintenance public works expenditure, and, in some years between 1920 and 1938 only, an undefined category of public works
expenditure called “extraordinary” expenditure. We estimate the share of prison labor in
total (new and maintenance) public works expenditure and overall (new, maintenance and
the extraordinary category) public works spending. The results are in Figure A6.
Figure A6(c) reports estimates for the share of prison labor in total (new and main84

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tenance) public works expenditure from 1920 to 1959. The gross share average is 35% with
the share ranging from 12% to 119%. The net share including the most extensive measures
of prisoner maintenance costs is 3%, with a maximum of up to 24% during this period.
Figure A6(d) reports estimates for the share of prison labor in overall (new, maintenance
and extraordinary) public works expenditure. The gross share average is 25% with the share
ranging from 8% to 119%. The net share including the most extensive measures of prisoner
maintenance costs is 2%, with a maximum of up to 19% during this period.
(a) Value of prison labor

(b} Prison labor as a share of new public works expenditure

1500000

1

.9, 1000000

2

"~

·g_

500000

0
~

~

1920

1930

1940

1950

1960

1920

1930

1940

Year
category -

Net value less lood costs - - Net value less prison costs ....,. Total value, estimate ...... Total value. reported -

(c) Prison labor as a share of new and maintenance public works expenditure

category ......

1950

Year
category .....

Net value less food costslpublicworks exp

_..,. Net value less prison costsfpublic works exp

..... Tolal value/publicwork1

(d) Prison labor as a share of all public works expenditure, including extraordinary

Net value less food costs/public ...... Net value less prison costs/pubbc ...... Total value/public

category ......

Netvam lessfoodcostslpublic ...... Netvalue less prisoncosts/poblic ...... Tota! value/public

Figure A6: Relative value of prison labor, 1920-1959

A.5

Suggestive Evidence of Sentence-Switching in Response to Short-Term
Economic Shocks: Custody and Short-Term Incarceration Rates and Further Robustness

85

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Table A4: Rainfall shocks (by type) and colonial (1920-1938) incarceration rates by custody/awaiting trial category
Custody
(1)

(2)

5.623∗∗
(2.201)
[0.014]

1.774
(2.795)
[0.558]
−6.703
(6.396)
[0.371]
−6.734∗
(4.044)
[0.093]

Mean of outcome

71.727

71.727

District FE
Year FE
Observations
Clusters

Yes
Yes
324
21

Yes
Yes
324
21

Positive rainfall shock (M)

Positive rainfall shock (E)

86

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Negative rainfall shock (E)

Custody − Short-Term

Short-Term
(3)
16.727∗∗∗
(5.456)
[0.016]

(4)

(5)

(6)

12.142∗
(6.964)
[0.093]
−17.225∗
(10.259)
[0.139]
−0.404
(13.973)
[0.977]

−11.104∗∗
(4.554)
[0.040]

−10.368
(6.475)
[0.154]
10.523
(8.004)
[0.241]
−6.331
(13.161)
[0.615]

134.659

134.659

−62.932

−62.932

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Yes
Yes
324
21

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial province for colonial
data, and postcolonial state for postcolonial data. Wild cluster bootstrap (by district) p-values are in brackets. Observations are provinces.
Dependent variables in (1)-(2) and (3)-(4) are prisoners awaiting custody or trial per 100,000 population (1939 pop.) and short-term prisoners
with less than 6 months sentences respectively. Outcome in (5)-(6) is the difference between the custody/awaiting trial incarceration rate and the
short-term, less than 6 months sentence incarceration rate. Positive rainfall shock (M) where (M) is moderate, and (E) is extreme as defined in
text. District FE are colonial province fixed effects in (1)-(6). ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant
at the 10 percent level based on clustered standard errors in parentheses.

Table A5: Effect of agricultural commodity prices and distance to railroad on colonial incarceration rates
Short-Term
(1)
Distance to railroad

(2)

(3)

Long-Term
(4)

−0.458∗∗

−0.458∗∗

−0.409∗∗

(0.159)
[0.006]

(0.221)
[0.000]
0.215∗∗
(0.100)
[0.039]

(0.216)
[0.001]

(0.198)
[0.001]

Distance x Palm oil price

(5)
−0.018
(0.022)
[0.466]

(6)
−0.021
(0.023)
[0.425]
0.004
(0.019)
[0.884]

0.150∗∗
(0.069)
[0.037]

Distance x Cocoa price

(7)
−0.005
(0.023)
[0.845]

(8)
−0.017
(0.022)
[0.497]

−0.011
(0.018)
[0.835]
0.307∗∗
(0.134)
[0.020]

Distance x Groundnut price

87

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−0.301∗

−0.001
(0.028)
[0.995]

Mean of outcome

46.149

46.149

46.149

46.149

3.996

3.996

3.996

3.996

District FE
Year FE
Observations
Clusters

Yes
Yes
932
21

Yes
Yes
932
21

Yes
Yes
932
21

Yes
Yes
932
21

Yes
Yes
817
21

Yes
Yes
817
21

Yes
Yes
817
21

Yes
Yes
817
21

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by district, where district is colonial province for colonial data. Wild cluster bootstrap (by district) p-values are
in brackets. Observations are provinces. Dependent variables are prisoners in each prison per 100,000 population of the province broken down by short-term (less than 6 months) sentence and long-term
(greater than 2 years) sentence over 1920-1938 Prices are in logs, and distance to railroad in km. District FE are colonial province fixed effects. ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at
the 5 percent level, ∗ Significant at the 10 percent level.

A.6

Relationship between Colonial Imprisonment and Trust in Colonial Institutions versus Interpersonal trust

Given the rich literature on the long-term impacts of historical institutions, and coercive
labor institutions in particular, on contemporary attitudes and outcomes, to explore the
long-term impacts of exposure to colonial imprisonment driven primarily by economic motives around prison labor, on views of state legitimacy, we use geocoded data from all rounds
of the Afrobarometer surveys for Nigeria. We use Afrobarometer surveys from all 5 rounds
from 2003, 2005, 2008, 2012 and 2014. Our main outcomes of interest are, following previous
literature (Nunn and Wantchekon, 2011; Lowes and Montero, 2020b), respondent reported
trust in institutions or individuals variables. Specifically, we use data on trust in historical
legal institutions namely: trust in courts, police, and trust in tax administration and interpersonal trust: trust in neighbors, trust in relatives, trust in the president and trust in
the local governing council member to test the hypothesis that long-term exposure to colonial imprisonment centered around prison labor reduces views of state legitimacy through
lowered trust in legal institutions, with no effect on interpersonal trust.
In addition to individual level controls for age and gender and education fixed effects, to
control for potential covariates that could impact both exposure to long-term colonial imprisonment and trust in legal institutions, we combine the Afrobarometer data with population
density, geographic controls, disease controls and controls for precolonial and colonial institutions, with descriptions of the data and summary statistics shown in Table A6 and in the
Appendix. Precolonial political institutions are proxied using Murdock’s (1967) “Jurisdictional Hierarchy Beyond the Local Community Level” called the Precolonial centralization
index here. The precolonial centralization index or “Jurisdictional Hierarchy Beyond the
Local Community Level” variable is an index of “political complexity” that assigns a score
between 0 to 4 to each ethnic region unit and describes the number of political jurisdictional
88

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hierarchies above the local community level for each unit. The score is defined as follows: 0
represents so-called “stateless societies”,“lacking any form of political organization”, 1 and
2 are petty and larger paramount chiefdoms, 3 and 4 are large, more organized states. The
colonial institutions Nunn and Wantchekon (2011)’s total number of exported slaves in the
trans Atlantic and Indian ocean slave trades from 1400-1900. Disease controls are included
for malaria by using climatic suitability for malaria transmission from Adjuik et al. (1998)
to address the various hypotheses in the literature on the negative impacts of malaria on
African development outcomes (Gallup and Sachs, 2001) and tse tse fly suitability following
Alsan (2015). Geographic controls include land suitability for agriculture, mean elevation in
km, ruggedness, and indicators for sea coast and petrol, to control for access to trade routes
and mineral wealth on trust outcomes.
The results from the IV estimates for the other trust outcomes are in Table A9. The first
stage estimates significantly predict colonial imprisonment in all specifications. The second
stage estimates in Panel B of Table A9 are not significant, and hence the OLS estimates
should be interpreted with caution here.
Early qualitative evidence on Nigerian citizen displeasure with the colonial prison system can be found in newspapers from the 1940s and 1950s. Nigerian journalists often publicly denounced ‘human rights and unjust practices perpetrated by penal officials’, including
the use of corporal punishment in prisons and the lock up of political dissidents (Abiodun,
2017)46 . Other historical accounts include the story of Garrick Braide, an African preacher
with a large following whose anti-colonial preaching and anti-alcohol stance in 1916, angered
both the British colonial government and European merchants. This lead to his arrest and
sentence, after which he spent a 2 year period in prison and died shortly after, dissipating the
movement but not his followers’ memories, or their practice of his beliefs at a church which
46 The

Southerner Nigeria Defender, August 25, 1943.

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exists till today47 (Kalu, 1977). We also document significant positive correlations (0.47,
p < 0.05) between long-term colonial imprisonments and the average number of protests involving police as an opposition actor within a district in the postcolonial period, using data
from the Global Data on Events, Location and Tone (GDELT) database, which codes conflict
events from newspapers over 1979-1999. These pieces of evidence suggest that an important
channel explaining the lowered trust results may be the continuation of ‘extra-judicial’ or
perceived as unjust colonial-era legal and policing practices in Nigeria..

47 The

Christ Army Church of Nigeria.

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Table A6: Summary Statistics: Afrobarometer Results
Statistic

N

Mean

St. Dev.

Min

Max

Trust and Crime Outcomes
Trust in Courts
Trust in Police
Trust in Tax Admin.
Trust Relatives
Trust Neighbors
Trust Local Gov.
Fear Crime
Bribery (HHS)
Bribery (Doc)

11, 354
11, 486
4, 480
4, 596
4, 682
8, 961
11, 584
8, 082
7, 987

1.21
0.69
1.01
1.97
1.37
0.93
0.59
0.27
0.29

0.92
0.87
0.85
1.03
1.00
0.87
1.00
0.68
0.66

0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

3.00
3.00
3.00
3.00
3.00
3.00
4.00
3.00
3.00

Individual Controls and Fixed Effects
Age
Age Squared
Female
Education

11, 603
11, 603
11, 654
11, 629

31.94
1, 165.29
0.50
3.27

12.05
987.34
0.50
1.92

18.00
324.00
0
0.00

95.00
9, 025.00
1
7.00

Geographic and Disease Controls
Population Density 2006
Agricultural Land Suitability
Malaria
Ruggedness
Mean Elevation
Sea Coast
Petrol
Tsetse Suitability

11, 526
8, 453
9, 095
9, 095
8, 332
9, 095
9, 095
7, 147

450.97
4.71
1.00
0.26
248.09
0.29
0.34
0.91

693.01
0.76
0.02
0.22
234.70
0.45
0.47
0.46

41.04
1.80
0.79
0.03
−0.25
0.00
0.00
−0.78

2, 694.63
6.00
1.00
2.28
1, 284.11
1.00
1.00
1.45

Precolonial and Colonial Controls
Precolonial Centralization
Slave Exports

9, 095
9, 095

1.66
150, 841.30

0.78
206, 271.70

0.00
0.00

3.00
665, 966.00

0.00

32.34

Instrument
Soil Suitability for Palm Oil
x Colonial Palm Oil Production

11, 025

3.09

7.95

Notes: See text and online appendix for details.

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Table A7: Falsification Test: OLS Estimates of relationship between postcolonial imprisonment and present-day trust in
historical legal Institutions versus interpersonal trust
Trust in Historical Legal Institutions

Interpersonal Trust

Courts

Tax

Neighbors

Relatives

Local Gov

(1)

(2)

(3)

(4)

(5)

(6)

0.000
(0.001)
[0.419]

0.001
(0.001)
[0.410]

0.000
(0.001)
[0.734]

0.003∗∗
(0.001)
[0.123]

−0.000
(0.001)
[0.881]

−0.000
(0.001)
[0.620]

Mean of outcome

0.649

1.121

0.938

1.345

1.918

0.875

Population Density
Individual Controls
Geographic Controls
Disease Controls
Precolonial and Colonial Controls

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
8,792
36

Yes
Yes
8,691
36

Yes
Yes
3,243
36

Yes
Yes
3,601
35

Yes
Yes
3,438
36

Yes
Yes
6,933
36

Prisoners per 100,000 pop.

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Police

District FE
Year FE
Observations
Clusters

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by current state. Wild cluster bootstrap (by district) p-values
are in brackets. The unit of observation is an individual. Prisoners per 100,000 pop. are current state level averages of prisoners per 100,000 population
(1990 pop.) over 1971 to 1995. Trust variables are from the Afrobarometer samples over 2003 to 2016 and as defined in the main text. Trust outcomes
are reported trust levels on a scale of 0-3, where “Not at all”= “0”, “Just a little”=“1”, “Somewhat”=“2”, “A lot”=“3”. All regressions use district fixed
effects at the geopolitical zone level in Nigeria, year fixed effects, educational attainment fixed effects and controls for sub-district or local government
area population density in 2006. Individual controls include age, age squared and gender. Geographic controls at the sub-district level include ruggedness,
indicators for petroleum, seacoast and mean land suitability for agriculture and mean elevation in alternate specifications. Disease controls at the subdistrict level include malaria suitability and tse tse fly suitability in alternate specifications with results unchanged. Precolonial and colonial controls at
the ethnicity-level include the level of precolonial centralization and total exports of slaves from the region during the Atlantic slave trade.
∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent level.

Table A8: OLS Estimates: Relationship between colonial and postcolonial imprisonment
and present-day crime outcomes
Colonial Imprisonment

Postcolonial Imprisonment

Bribery Doc

Fear Crime

Bribery Doc

Fear Crime

(1)

(2)

(3)

(4)

−0.001
(0.003)
[0.644]

−0.002
(0.005)
[0.781]

0.001∗∗
(0.000)
[0.057]

0.001
(0.001)
[0.123]

Mean of outcome

0.225

0.229

0.571

0.225

Population Density
Individual Controls
Geographic Controls
Disease Controls
Precolonial and Colonial Controls

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
5,876
21

Yes
Yes
8,420
21

Yes
Yes
6,204
36

Yes
Yes
8,875
36

Prisoners per 100,000 pop.

District FE
Year FE
Observations
Clusters

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by colonial province in columns (1) to (2) and
by current administrative state in (3) to (4). Wild cluster bootstrap (by district) p-values are in brackets. The unit of observation
is an individual. Prisoners per 100,000 pop. are colonial province level averages of long-term (>2 years sentence) prisoners per
100,000 population (1939 pop.) over 1920 to 1938 in columns (1) to (2), and current state level averages of prisoners per 100,000
population (1990 pop.) over 1971 to 1995 in (3) to (4). Outcome variables are from the Afrobarometer samples over 2003 to 2016
and as defined in the main text. Bribery Doc and Bribery HHS is reported frequency of respondent bribery of government official
for document and household services respectively where “Never”=“0”, “Once or Twice”=“1”, “A Few Times ”=“2”, “Often”=“3”.
Fear Crime is how often respondent or family has feared crime in their home where “Never”=“0”, “Just once or twice”=“1”,
“Several times”=“2”, “Many times”=“3”, “Always”=“4”. Regressions in columns (1) to (2) use district fixed effects at the state
level in Nigeria, and in columns (3) to (4) use geopolitical zone fixed effects. All regressions include year fixed effects, educational
attainment fixed effects and controls for sub-district or local government area population density in 2006. Individual controls include
age, age squared and gender. Geographic controls at the sub-district level include mean land suitability for agriculture, ruggedness,
indicators for petroleum, seacoast and mean elevation in alternate specifications. Disease controls at the sub-district level include
malaria suitability and tse tse fly suitability in alternate specifications with results unchanged. Precolonial and colonial controls
at the ethnicity-level include the level of precolonial centralization and total exports of slaves from the region during the Atlantic
slave trade. ∗∗∗ Significant at the 1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent level.

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Table A9: IV Estimates: Effect of relationship between colonial imprisonment and presentday trust in historical legal Institutions versus interpersonal trust
Panel B: Second-Stage 2SLS Estimates
Trust in Historical Legal Institutions
Interpersonal Trust
Courts
Tax
Neighbors
Loc. Gov

Prisoners per 100,000 pop.

(1)

(2)

(3)

(4)

0.013
(0.016)

0.003
(0.010)

0.010
(0.054)

0.000
(0.012)

Panel A: First-Stage Estimates
Soil Suitability for Palm Oil
x Colonial Palm Oil Production

F-Stat of Excluded Instrument
Population Density
Individual Controls
Geographic Controls
Disease Controls
Precolonial and Colonial Controls
District FE
Year FE
Observations
Clusters

0.187∗∗∗
(0.039)

0.228∗∗∗
(0.038)

0.237∗∗∗
(0.056)

0.178∗∗∗
(0.037)

22.90

35.29

17.97

23.70

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes

Yes
Yes
8,256
21

Yes
Yes
3,063
21

Yes
Yes
3,415
21

Yes
Yes
6,578
21

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by colonial province. The unit of observation
is an individual. Prisoners per 100,000 pop. are averages of long-term (>2 years sentence) prisoners per 100,000 population (1939
pop.) over 1920 to 1938. Trust variables are from the Afrobarometer samples over 2003 to 2014 and as defined in the main text.
Trust outcomes are reported trust levels on a scale of 0-3, where “Not at all”= “0”, “Just a little”=“1”, “Somewhat”=“2”, “A
lot”=“3”. All regressions use district fixed effects at the current state level in Nigeria, year fixed effects, educational attainment
fixed effects and controls for sub-district or local government area population density in 2006. Individual controls include age,
age squared and gender. Geographic controls at the sub-district level include ruggedness, indicators for petroleum, seacoast and
mean elevation in alternate specifications. Disease controls at the sub-district level include malaria suitability and tse tse fly
suitability in alternate specifications with results unchanged. Precolonial and colonial controls at the ethnicity-level include the
level of precolonial centralization and total exports of slaves from the region during the Atlantic slave trade. ∗∗∗ Significant at the
1 percent level, ∗∗ Significant at the 5 percent level, ∗ Significant at the 10 percent level.

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Table A10: OLS Estimates: Colonial palm oil suitability and production instrument does
not predict postcolonial imprisonment

Colonial Imprisonment

Soil Suitability for Palm Oil
x Colonial Palm Oil Production

Population Density
Individual Controls
Geographic Controls
Disease Controls
Precolonial and Colonial Controls
District FE
Year FE
Observations
Clusters

Postcolonial Imprisonment

(1)

(2)

(3)

0.191∗∗∗
(0.050)

0.188∗∗∗
(0.040)

Yes
Yes
No
No
No

Yes
Yes
Yes
Yes
Yes

Yes
Yes
No
No
No

Yes
Yes
Yes
Yes
Yes

Yes
Yes
10,840
21

Yes
Yes
8,476
21

Yes
Yes
10,840
36

Yes
Yes
8,476
36

−0.266
(0.667)

(4)
−0.238
(0.569)

Notes: Regressions estimated by OLS. Robust standard errors in parentheses clustered by colonial province in columns
(1) to (2) and at the current administrative state level in (3) to (4). The unit of observation is an individual. Colonial
imprisonment measure is prisoners per 100,000 pop. which are averages of long-term (>2 years sentence) prisoners per
100,000 population (1939 pop.) over 1920 to 1938. Postcolonial imprisonment measure is prisoners per 100,000 pop. which
are current state level averages of prisoners per 100,000 population (1990 pop.) over 1971 to 1995. Regressions in columns
(1) to (2) use district fixed effects at the current state level in Nigeria, and in columns (3) to (4) use geopolitical zone
fixed effects. All regressions use year fixed effects, educational attainment fixed effects and controls for sub-district or local
government area population density in 2006. Individual controls include age, age squared and gender. Geographic controls
at the sub-district level include ruggedness, indicators for petroleum, seacoast and mean elevation in alternate specifications.
Disease controls at the sub-district level include malaria suitability and tse tse fly suitability in alternate specifications with
results unchanged. Precolonial and colonial controls at the ethnicity-level include the level of precolonial centralization and
total exports of slaves from the region during the Atlantic slave trade. ∗∗∗ Significant at the 1 percent level, ∗∗ Significant
at the 5 percent level, ∗ Significant at the 10 percent level.

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