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LONG TERM IMPACT OF 19TH CENTURY MISSIONARY SCHOOLING INVESTMENT ON
HOUSING QUALITY IN NIGERIA.
MUSILIU ADEOLU ADEWOLE*1
DEPARTMENT OF ECONOMICS
SCHOOL OF SOCIAL SCIENCES
COLLEGE OF DEVELOPMENT STUDIES
COVENANT UNIVERSITY.
(Results are tentative, another version forthcoming)
A Paper Submitted to 2014 Royal Economic Society Conference, University of Manchester, UK.
Abstract
In this study, we explore the empirical relationship between contemporary housing quality and long
term indicator of missionary human capital investment. We use OLS and IV identification
strategies to investigate the causal relationship. In OLS and IV regressions, locations with greater
missionary human capital investment between 1843 and 1910 have less crowded houses today and
the houses there are built with better construction materials. IV estimates turn out to significantly
higher than OLS estimates. Robustness check shows omitted variables bias is not responsible for
observed outcomes. IV estimates are robust to the falsification test and a number of other exclusion
restriction tests. Three stage least squares are used to establish the channels through missionary
human capital investment impact on housing quality. Both individual schooling attainment and
wealth are strong channels through which missionary human capital investment affect housing
quality. This study demonstrates one important instance in which the involvement of the private
sector has considerable indirect positive spillovers on neighbourhoods. When the enabling
environment is available, non-profit private sector can help fast-track economic development.
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Introduction & Background
Rewrite this section-starting off with role of missionaries in economic development and narrowing
down to
Good quality housing affords protection from hazards and discomforts of the external environment and
provides an appropriate atmosphere for living and human activity (WHO, 2006). The quality of housing
and the general conditions of the housing environment are instrumental to good health, well-being and
social integration (Hornberg and Pauli, 2011). Findings from Glaeser and Sacerdote (2000) show that
apartment structure determines the degree of social interactions among residents in the neighbourhood.
Residents of large or multi-unit apartments are more likely to be socially connected to their neigbbours
and more likely to be involved in local politics. In studies reviewed by Leventhal and Newman (2010),
the consensus is that physical housing quality and degree of crowding have important effects on a broad
range of outcomes, including physical health and schooling, achievement and economic attainment of
children. Goux and Maurin (2005) study shows that children from large families, living in overcrowded
houses, perform much less than children from small families in examinations. Urban disadvantage, an
important part of which is the failure of national and urban housing, has contributed tremendously to the
dramatic rise in under-5 child mortality in Nigeria (Antai and Moradi, 2010).
Though housing quality determines a range of socio-economic outcomes, it is surprising that not much
has been done in terms of investigating the determinants of housing quality. Apart from the studies that
investigate the causal impact of housing quality on various outcomes, the other strand of studies have
concentrated on the impact of neighbourhood environment on a broad range of socio-economic outcomes
(Cutler and Glaeser , 1997 : Durlauf, 2004)2 producing mixed results. While there is a general tendency to
paint a gory picture of urban slums in developing countries such as Nigeria (Olutuah and Adesiji, 2007),
facts from the 2006 Nigerian Population and Housing Census indicate significant variation exist in the
distribution of good quality houses as we move from one geo-political location to the other. Table 1.0a
indicates that when housing quality indicators such as the quality of material used in making walls, roofs,
floors and toilet facility are considered in housing quality classifications, the odds are stacked against the
north, except for the North-Central. Both North-East and North-West are below the national average
when we consider the percentage of houses which used quality materials in making walls, floors, roofs
and toilet. The story is the same when we count the percentage of houses with access to pipe-borne water
within and in their immediate neighbourhood. The important question is what factor(s) determines good
quality housing? Why is good quality houses spatially concentrated in certain geopolitical zones?
Fiadzo (2004) study of the determinants of housing quality suggests that individual characteristics such as
income status, age, marital status, sector and household factors such as household size, sex of household
head, number of rooms in the household could explain variation in housing quality among individuals.
But these factors can hardly speak to situations with significant spatial disparity as presented in table 1.0a.
Another probable reason could be that middle-nineteenth century Christian missionaries were spatially
concentrated in selected locations. Since missionaries could not live in traditional houses available in their
areas of settlement they had to build European style houses suitable for their habitation. Thus, an
important part of their contribution involves the introduction of high quality European houses built as
living apartments, mission houses, schools and vocation or industrial training centres in areas where they
settled. Their investment in education contributed to the emergence of elite class (Ade Ajayi, 1965).
Beneficiaries of missionary education enjoyed better living standards than the rest of the population.
Thus, these high-quality houses became associated with the elite class which built European style houses
close to the missionary locations and began to spread from there (Ade Ajayi, 1965). Casual observation of
table 1.0a indicates that regions with above average values of housing quality also have greater number of
Christian missionary primary schools at 1923. The last column of table 1.0a indicates the number of
2 Durlauf (2004) is an excellent review of the literature in this field.
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schools built per 100 squared Km. This elite class were deliberately cultivated as part of its civilizing
activities of the missionaries. As far we know, no empirical study has attempted to connect this important
historical event to contemporary indicators of housing quality in Nigeria.
Rather, a study (Fiadzo, 2004) of the determinants of housing quality in Ghana has concentrated on the
personal characteristics of individual occupants of various houses. Assuming Fiadzo (2004) study does
not have identification problem for the purpose of causal inference, the study still fails to address the
reason for spatial concentration of high quality houses. Factors such as schooling attainment and income
might be more proximate determinants of housing quality, more or less transmitting the influence of an
historical factor, which affects these variables. Thus, omitted variables bias might determine outcome.
More importantly, Fiadzo study adopts an econometric approach that fails to resolve the issue of causality
between endogenous variables (such as schooling and income or wealth) and housing quality.
Table 1.0a: Regional Distribution of Housing Quality & Missionary Human Capital Investment in
Nigeria
Region % Wall % Roof %floor %water %wc %room3 m1923
National 47.1427
(23.4608)
64.27407
(23.1988)
55.6534
(22.2424)
23.4754
(11.5409)
13.1790
(10.6866)
0.6958
(.101938)
3.0985
(3.8487)
North-
Central
49.6729
(15.7525)
71.1406
(16.6591)
60.9234
(15.0475)
19.6129
(10.9977)
13.9117
(13.6163)
0.7297
(0.110219)
0.2449
(0.3293)
North-
East
21.4969
(4.5169)
38.3558
(7.2364)
31.4328
(7.4346)
17.3400
(6.3329)
4.6630
(1.0841)
0.7458
(0.0376)
0.3365
(0.8150)
North-
West
21.1121
(8.7545)
36.5289
(13.4866)
(31.1926)
(12.5285)
19.0478
(9.7520)
6.0264
(2.7302)
0.6637
(0.0488)
0.8729
(2.2610)
South-
East
62.5631
(18.1984)
80.2808
(12.0188)
70.7470
(20.3682)
29.8760
(12.9494)
18.1683
(8.5991)
0.6992
(0.0561)
6.7
(1.5297)
South-
South
59.9141
(9.4837)
78.9811
(8.3705)
68.5906
(8.4783)
30.1868
(10.1212)
17.0408
(6.763585)
0.6827
0.1009
2.3667
(1.2111)
South-
West
74.5838
(10.6741)
86.50489
(5.1961)
76.74801
(9.9880)
27.23697
(14.7490)
21.1651
(14.3538)
0.6542
(0.1868)
9.5167
(2.4186)
Data Source: National Population Commission & National Bureau of Statistics
To tackle the issue of the determinant of housing quality with respect to its spatial concentration, we
hypothesize that location intensity of exposure to more than a century old investment in human capital
can explain both housing quality and their unequal spatial distribution in Nigeria. The hypothesis rests on
the fact that significant variation exists in the exposure of various locations to early Christian
missionaries. They made the initial investment in human capital in pre-colonial and colonial Nigerian
communities and introduced European style architecture through the construction of schools, mission
stations and vocational centres. The vocational centres created by the early missionaries trained the first
batch of craftsmen in various technical vocations, including masons that built European style houses in
locations close to where the missionaries work and reside (Ade Ajayi, 1965). The historical account of
Brown (1864) asserts that Africans under the care of missionaries built convenient houses for themselves,
some made of stones, in place of the unhealthy smoky apartments which were then prevalent in most
African communities. Morgan (1959) gives detailed account of how European contacts with Southern
Nigeria influenced her landscape. A more detailed account of the positive impact of independent religious
movements on the modernization of Africa is given by Turner (1969). Similarly, mass movements of
Europeans to the new world with their human capital endowments and good institutions have been
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proposed as the reasons why their countries surge ahead of others in economic development (Acemoglu,
Johnson and Robinson, 2001: Glaeser, La Porta, Lopez-De-Silanes and Sheleifer, 2004).
It would be interesting exploring the empirical relationship between such large-scale private schooling
investment in pre-colonial Nigeria and contemporary indicators of modern housing quality. As far as we
know not much attention has been devoted to investigating the impact of long term human capital
investment on housing quality. This study fills this gap. Beyond the mere investigation of the causal
impact of long term effect of human capital on housing quality, the study seeks to show how private
initiative could produce significant positive externalities, even if indirectly. The imperfect nature of
housing markets in virtually all economies, and much more so in the economies of less developed
countries has been one vital justification for government involvement in provision of housing facilities.
As in many areas of public sector involvement in the provision of goods and services in less developed
countries, government involvement in the production and provision of large-scale houses has produced
disappointing results (Ogu, 1999, Ikejiofor, 1999, 1998; Ukoha and Beamish, 1997). A recent study by
Ibem (2009) demonstrates that community-based organizations can foster the provision of infrastructure
in their respective communities.
OLS and IV estimates3 reveal positive and significant impact of early missionary schooling investment on
contemporary housing quality indicators, even after introducing a good number of control variables. One
notable finding is the impact of missionary schooling investment on house density; the number of persons
per room. It has a significant and negative effect on house density. That is local government areas (LGAs)
that receive more missionary schooling investment have less overcrowded houses today than those that
received less. It also has significant and positive impact on the quality of materials used in the
construction of houses. The impact of missionaries on house density is particularly significant because the
traditional construction of houses in the far north, with its system of purdah and the separation of boys
into separate hamlet after a particular age threshold should have made its households less dense than
similar households in the south with more Western Style houses.
More importantly, the study attempts to resolve to the knotty identification problem which potentially
might bias empirical results obtained in studies of this kind. The identification problem arises because
missionaries self-select into areas which either had better quality houses prior to the arrival of the
missionaries or the missionaries self-select into areas where better houses were more likely to built at a
later period. If certain locations in Nigeria were already ahead of others in terms of certain indicators of
economic development before the missionaries came along, then our hypothesis would turn out to be
false. In case observed and unobserved location characteristics might be driving our results. According to
Johnson (1967), early missionaries chose better locations with low altitude and latitude and areas with
ready access to coast for constant transportation of missionary personnel and receipt of supplies.
Though the specific characteristics of certain locations facilitated early contacts and makes self-selection
bias more likely, there is scanty historical evidence to back up the claims that economic development in
Northern Nigeria was behind those in the South prior to contact with Christian missionaries. However,
evidence that missionaries self-select into certain locations implies OLS estimates of human capital
variable will be biased. To strengthen the case for causal relationship between missionary human capital
investment and housing quality, we use the IV approach. Latitude, which is one of the important factors
influencing missionary choice of locations, is used to instrument for long term indicator of human capital
investment. Our IV results reinforce confidence in our OLS estimates for virtually all indicators of
housing quality, and in actual fact several magnitude bigger than OLS estimates. We draw on recent
advancements in the econometrics of exclusion restriction or instrument validity testing literature to
provide more convincing evidence on the validity or exogeneity of our chosen instruments. These
3 Since OLS and Probit techniques gave similar results, we report only OLS results because of the easy of
interpretation.
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strategies are implemented in addition to the conventional over-identification test. Taken along with
Altonji, Taber and Elder (2005) suggested test for omitted variable bias, we provide evidence that
unobserved characteristics of these locations are not confounding factors biasing our human capital
estimates. To carry out overidentification test and provide evidence of instrument validity, we added
altitude and longitude as additional instruments. Results are in favour of instrument validity. While
traditional overidentification test is not decisive, and come along with its peculiar challenges, it is at least
in favour of our instrument validity story.
Finally, we test the possibility that individual schooling and wealth status could be the mediating channels
through which long term human capital investment variable affect housing quality. Because both
individual schooling and wealth status are endogenous variables, estimates of both variables could be
biased and inconsistent if only OLS technique is used. Similarly, if 2SLS is used without taking due
account of the endogeneity of both variables, estimates of the long term indicator of human capital
investment as the those of schooling and wealth status variables will be biased. Therefore, we implement
the three Stage Least Squares (3SLS) strategy to correct for potential sources of bias. To instrument for
schooling variable, we use years of exposure to 1976 UPE programme in Nigeria. This is quasi-natural
experiment and represents exogenous intervention in the supply of educational services. Following
Glaeser and Saks (2006), we instrument for wealth by using the linear and square values of latitude and
longitude. This approach allows us to produce relatively unbiased estimates of the impact of long term
indicator on housing quality. Furthermore, we established both schooling and wealth status as proximate
causes and important channels through which human capital has long term effects on housing quality.
Our results, while in line with recent literature studying the long term impact of early Christian
missionaries on a range of current outcomes (Woodberry, 2004; Gallego and Woodberry, 2010; Nunn,
2010), contrast sharply with results of empirical studies investigating how Europeans contact with
Africans through slave trade and colonialism impact on current outcomes (Acemoglu, Johnson and
Robinson, 2001; Sherwood, 1997 and Nunn, 2008). In a recent study of the current impact of the Nazis-
led holocaust across cities in former Soviet Union during the Second World War, Acemoglu, Hassan and
Robinson (2011) find that districts more severely affected by the holocaust have grown less and report
worse political outcomes today than less affected cities4.
This study also failed to confirm, in the specific case of Nigeria, the historical account of a number of
scholars (Mcfarlan, 1946; Ayandele, 1966; Nair, 1972; Olutola, 1977; Manji and 0’Coill, 2002) on the
negative role played by Christian missionaries in various African locations. One central lesson of this
paper is that positive human capital externalities can be generated by private investment activity, though it
is difficult to assert if the level of investment was socially optimal. For a profit-maximizing colonial
government, which came shortly after the arrival of the missionaries, there was no incentive to invest in
this kind of socially beneficial activity. This illustrates the success of private initiative, which often could
work when public sector intervention will not produce the desired results. While public sector remains
important in economic development, private sector in selected cases can produce better results, even with
minimal resources. This much has discussed in the delivery of basic education in less developing
countries such as India and Nigeria (Kingdon, 1996; Tooley, Dixon and Olaniyan, 2005). While limited
financial allocations were later made by colonial government to many of these mission schools (Fafunwa,
1974), the principal investment were undertaken by the missions.
The rest of this study is organized as follows. In section two, we emphasize the relationship between
missionaries and modern housing in Nigeria. We provide a brief description of the data and data sources
used in this study in section three. Both OLS and IV results are presented in section four. In section five,
we address concerns about instrument validity bringing bias into our estimates. Two important channels,
4 A recent review on the role of history in shaping contemporary economic development is found in Nunn (2008).
To save space, detailed literature review is omitted from this paper.
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education and wealth, through which missionary human capital investment affects housing quality are
explored in section six. In section seven, we summary the study and draw important conclusions.
2.0 Background of the Study
2.0.1 Christian Missionaries and Modern Housing in Nigeria5.
The first missionary journey to the Niger Delta started in 1515, while on the whole unsuccessful, left
European architectural imprints on the Nigerian soils of time. These were relics like the huge cross in the
centre of Warri town and a few church decorations among numerous traditional shrines. About this time,
items of household use and luxury from Europe were adopted by the local wealth people. By the
beginning of the 19th century, it was not uncommon in Calabar and Bonny locations, for those who can
afford them to import wholesale pre-fabricated houses, which are filled with European furniture. While
the missionaries were denied access to the interior, they were allowed to build houses in Benin and Lagos.
Portuguese and Brazilian traders built barracoons and tenements on the beach (Ade Ajayi, 1965). The
reach of their influence was limited on the first missionary journey by their inability to move into the
interior among other reasons. It is therefore not surprising why at the onset of second missionary journey
into the Nigerian territory, the missionaries had a poor impression of the quality of local houses in
Badagry, its first point of call in Nigeria. Houses were built without regard for order and convenience.
The second missionary efforts changed all of that.
According to Ade Ajayi (1965), early Christian missionaries made some important contributions to
economic development in Nigeria. These included educational development, building and architecture,
printing and medicine. Its contribution to educational development in Nigeria probably encapsulates other
areas in which the missionaries touched lives of Nigerians. The areas which received the most attention
from the missionaries derived essentially from the broader agenda drawn up by Buxton on the deliberate
cultivation of a class of persons in African societies. Buxton, among other things, had advocated the use
of Christianity to reduce the main languages of western and central Africa into writing, prevent or
mitigate the prevalence of disease and suffering, encourage practical science in all its various branches,
investigate the system of drainage best suited to the humid tropics, assist in the formation of roads and
canals and manufacture of paper, and assist with information on best agricultural practices, and the
cultivation of crops using the best kinds of seeds and marketing of these commodities.
The initial missionary spur came from the return of exiles, who are freed slaves rescued by British naval
vessels enforcing the bans on slave trade. According to Ade Ajayi, the vision of home had a great power
of attraction for the liberated Africans in Sierra Leone, the location of many of the freed slaves. While in
the colony of Free Town, some enlisted in West Indian regiment, some were serving apprentices to
professional craftsmen and some ally with traders. Others were engaged in farming under superintendents
and the younger ones were attending mission schools. A sizeable number became Christians. The
educated among sought public sector employment, worked with Christian missions or commercial outfits.
By the time they had spent twenty years in the colony, some have already become successful traders,
particularly those from the southern parts of Nigeria. Generally, the human capital endowment of
Nigerians in this colony was considerably higher than that of the average citizen back home. Seeking
economic opportunities beyond what the colony could afford, some individuals, singly or collectively,
sailed back to Badagry and Lagos. From then on, the pressure to finally return home from the colony
began to build up from the converted Christians and by 1841, a batch of emigrants supported by the
Methodist Church arrived the shores of Badagry.
5 This section of this paper benefitted immensely from the seminal contributions of Ade Ajayi ‘s (1965) on the
impact of early Christian missionaries on the economic development of Nigeria.
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Some ex-slaves joined from Cuba and Brazil. Other missionaries that arrived shortly after built mission
houses, churches and schools, with building patterns, with some adjustments for local environments,
much after the European styled houses. This started in Badagry and later moved further into the interior of
the South-West and South-East. Much later, attempts to move into the Northern axis were not successful
because of 600 years of previous exposure to Islamic religion. Variation in the intensity of the presence of
European architecture depended on a number of factors, the least of which is not geographic features that
facilitated interactions with home country. Also noteworthy is the fact that emigrants, ex-slaves, were
well received and regarded as honourable members of society and their human capital endowments in
writing skills and special aptitudes in building, dress-making and sawing of timber were been used in
various ways.
Rev. Thomas Birch Freeman, the head of the Methodist Expedition team, bought a small piece of land,
built a makeshift bamboo house and a more elaborate mission house fit for his European family. At ten to
twelve feet from the ground, resting on twenty-two short but strong coconut pillars, it stood as an
extraordinary piece of architecture, often attracting the attention of anyone not a long distance away. A
number of Mission Houses were built in larger towns. This was to serve as a model for the community in
which the Mission House is located. In a typical mission house, all materials used are essentially
imported. The house is an airy box standing on stilts, with all round balconies and a conspicuous flight of
stairs in front of the house. Though mission houses located in the interior were far less elegant, the
introduction of brick-making in the late 1850s and the 1860s by Cuba and Brazilian masons began to
influence the architecture of the interior areas. The large planned and fitted windows and doors, which
replace the traditionally carved, became more widely used. Tools were imported from England and
professional sawyers and carpenters were recruited from Sierra Leone, for building mission houses and
houses for the local rulers. The traditional windowless rooms and smoked roofs were regarded as
unhygienic by missionaries, and had to provide alternatives which were durable, cool, resistant to rain and
cheap.
There were attempts at industrial training of the indigenous in an effort to create a middle class, from the
church and the state can draw for their development. Success was limited by the extent to which financial
resources could be drawn upon. Furthermore, European artisans in partnership with missionaries trained
African youths in English factories. This approach was favoured because of the high mortality rates of
Europeans working in many stations in Africa. Venn, one of most important missionary figure of his time,
encouraged merchants and mission agents to send their children to England for practical industrial
training. A good number of young people were trained in various vocations and professions as
engineering, medicine, cotton cleaning and packing, navigation and seamanship, brick-and tile-making
and building construction. In a particular instance, 12 Yoruba boys, taken to Wydah after their capture in
Dahomey in 1862, alongside 12 others were sent abroad for training in carpentry, masonry, shoemaking,
tailoring, iron-making, cookery and gardening.
The spatial concentration of the emigrant Africans helped them to make great impact, either in Sierra
Leone, where they were segregated in colonies, or back at home, where they remained in a few centres as
catechists, evangelists and schoolmasters. What further the course of spatial concentration was that
mission houses hardly stand alone. They were often out-houses, for school masters, interpreters, boarders,
redeemed slaves, as well as carpenters’ workshops and other industrial establishments. The schools and
the churches were not too far away. Returned slaves also built their houses close by. Both European style
houses and their town planning approach were taking roots in Nigeria. Unlike traders, who were persons
in transit, missionaries came to settle, build houses and interact with the indigenous people. Therefore,
their impact was more lasting. In building their European-Style houses, they use expertise which is often
not locally available. While causal inference is difficult to draw, the historical account here suggest we
could move from missionary schooling investment to higher quality houses.
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3.0 Data Description and Analysis
To accomplish the objective of this paper, we draw heavily on 2008 Nigerian Demographic &
Demographic Health Survey (DHS) and data from a variety of sources. The fourth in its series, the 2008
NDHS is a national sample survey designed to provide up-to-date information on background
characteristics of the respondents; fertility levels; nuptiality; sexual activity; fertility preferences;
awareness and the use of family planning methods; breastfeeding practices; nutritional status of mothers
and young children; early childhood mortality and maternal mortality; maternal and child health; and
awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The target
groups were women age 15-49 years and men age 15-59 years in randomly selected households across
Nigeria. Information about children age 0-5 years was also collected, including weight and height.
A vital part of the 2008 DHS is information on the quality of housing environment. This information on
the physical characteristics of household dwellings captures individual and household quality of life. The
data on housing quality cover the source of drinking quality, type of sanitation facilities, type of flooring,
walls, and roofs and the number of rooms in the house.
The main independent variable, the number of primary schools established by missionaries between 1843
and 1910 (called the missionary human capital investment variable) in each LGA is obtained from the
2008 Nigerian School Census Survey. The census contains the names and addresses of all public and
private primary and secondary schools, their year of establishment, the physical facilities available and
information on a number of teachers’ characteristics, among other things. From this census, we estimated
the number of primary schools established in each LGA between 1843 and 1910. To normalize this
variable across all LGAs, we estimate the number of schools per square kilometre. To reduce the
skewness of the variable because a large number of observations are zeros, we find natural logarithm of
one (1) plus the number of schools per LGA per square kilometre.
To these data sources, we use historical data collected by Murdock (1967) on a number of characteristics
of ethnic groups prior or about the time missionaries set their feet on Nigeria. Eight pre-missionary
indicators of economic development are selected from Murdock data. In addition, four indicators of
political institutions measuring state public sector’s capacity to provide public service, extent of
communication and transparency in conduct of state capacity, budget and fiscal policy process and
general policy effectiveness. These data are obtained from Applied Institute for African Economies
(AIAE). We cover tenants and home owners who are at least 25 years old. Eight post-independent
economic development indicators are selected 2008 UNDP report on Nigeria. Table 1.0 is a summary
statistics of the variables used in this study.
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4.0 Econometric Model and OLS Empirical Results.
0 1 1910i j XjHQ HC
ijHQ is the quality of the house individual i resident in LGA j lives in. There are two indicators of
housing quality. First is the number of persons per rooms, which measures the extent of overcrowding in
the household in which individual i in LGA j is resident. The other is a combination of the quality of
materials used in the construction of houses. These materials include those used in the making of floors,
walls, and roofs. For each of the materials used in constructing the second measure of housing quality, a
ranking is done from 1 to 10. Higher values imply better housing quality. Principal component analysis is
used to get a single measure of housing quality. 1910 jHC is the indicator of missionary human
capital investment. This is the number of primary schools established by missionaries between 1843 and
1910. X is a vector of variables including age, age-squared, sex dummy, Yoruba dummy, Hausa dummy,
Igbo dummy, English dummy, English-Speaking dummy, marital status dummy, household size, LGA
population density and other important variables.
For the first indicator of housing, OLS estimates of missionary human capital investment from model 1 to
model 2 are negative and insignificant for the first indicator of housing quality but become significant
from models 3 to 6 though estimates are still negative. The results imply that LGAs with higher
missionary human capital investment have houses that are less crowded today. While this particular result
is not surprising, the rationale could be that LGA with considerably higher missionaries promoted
European style houses which allowed individuals to live individually in multi-room apartments. It would
appear that the addition of variables such as LGA number of secondary schools per square kilometer,
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LGA primary school enrollment rates, percent of those tertiary education, distance to state capital, cohorts
fixed effects, state fixed effects and indicators of state political institutions only increase the absolute
values of missionary human capital investment.
For the second indicator of housing quality, OLS estimates of missionary human capital investment are
positive and significant at 10 percent for all regressions in models 1 to 5, after introducing all relevant
variables as in the first indicator of housing quality. A percentage increase in LGA number of primary
schools per square kilometer increase house quality by 0.2813. This is an important impact of missionary
human capital investment as at 1910 has impact on current house quality. Curiously, the same 1 percent
increase in the LGA number of primary schools per square kilometer decrease overcrowding indicator of
housing quality by 0.2887.
Younger persons live in less crowded houses as do the males relative to the females. Thus, both age and
sex dummy variables are significant determinants of house density. Except for those who identified
themselves as English, who estimates are not significant at 10 percent, ethnic groups such Hausa, Igbo
and Yoruba live households that less dense compared to other ethnic groups. Larger households live in
more crowded houses and the coefficients of household are positive and significant, even at 1 percent.
LGAs with greater population density have more overcrowded houses. The provision of public goods
such as electricity, dams and water supply facilities at the LGA level, probably because of its spatial
concentration, have strong and positive impacts on house density outcome. Households in LGAs with
more public goods have less crowded houses.
Cohort fixed effect dummies did not make much difference to the original estimates of the missionary
human capital investment. During the second republic, 19 state governments embarked on mass housing
programmes, which can impact on the quality of houses available in the state. Thus, 19 state fixed effects
dummies, using the Federal Capital Territory (F.C.T) as a base dummy variable, are introduced into the
econometric model. This did not change the missionary human capital estimates in all specifications. The
four indicators of political institutions such as policy effectiveness, budget and fiscal process,
communication and transparency and quality of service delivery are introduced into the model. In spite of
the addition of these variables the missionary human capital investment variable estimates remain
significant. Of the four variables that measure political institutions, service delivery quality and budget
and fiscal policy, are significant at 1 percent. Policy effectiveness and transparency indicators are
insignificant, though policy effectiveness measure is negative and transparency indicator is positive.
OLS estimates show that missionary human capital investment has significant impact on indicators of
housing quality. However, there is a problem of distinguishing between correlation and causation because
of bias introduced by omitted variables. Unobserved variables, which might bias estimates of human
capital investment, complicate the causal inference. For instance, family background variables such as
parental wealth status, occupational status and parental house ownership status could impact on housing
quality. However, information on these variables is not available. To be sure omitted variables are not
driving outcomes, we adopt the identification strategy of Altonji, Elder and Taber (2005) whose method
provides a measure of the extent to which unobserved variables are responsible for observed outcomes.
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(Assuming that the set of observed variables is chosen randomly from a full list of variables and that the
number of observed and unobserved variables is large enough that none of the elements dominates the
distribution of outcome variable, Altonji’s et al strategy estimates the extent to which selection on
unobserved variables relative to observed variables could be responsible for outcome, which in this case
is housing quality. The relevant formula is /( )F R FB B B . RB stands for estimated coefficient for the
variable of missionary human capital investment for the regressions with restricted set of variables. FB is
the estimate of missionary human capital investment for regressions with full set of variables. The logic
behind the formula is simple. The denominator, ( )R FB B , decreases because of estimates from
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regressions with full set of variables approach estimates of regressions with restricted set of regressions.
The smaller is the difference between these set of estimates, the less is the estimate influenced by
selection on observed variables. Consequently, the selection on unobserved relative to observed variables
needs to be stronger to account for the entire outcome of housing quality.
To implement this strategy, we choose two sets of restricted covariates, denoted by models 2 and 3 in
table 2.0c. In addition, we select two full sets of covariates denoted by models 5 and 6. Intuitively, if
omitted variables are biasing outcome, the Altonji ratio should be less than one (1). Our results are
presented in table 3.0 for the two indicators of housing quality. For all ratios generated, there is no
evidence that observed variables are driving the outcomes.
There is equally the problem of selective migration impacting on observed outcomes. A good number of
the people sampled in the LGAs might be recent or long term migrants, who built houses according to the
tradition in their origin communities. Thus, the houses in specific LGAs might just reflect the cultural
influence of other LGAs. Missionary human capital investment which brought European style houses in
its wake will not be the reason for the concentration of high quality houses in certain locations. If
migration is selective and exclusively restricted to those likely to build houses in host communities in line
with the tradition in their origin communities, then our estimates of the effects of missionary human
capital investment on housing quality will be biased.
The literature on migration does not give us much cause to worry, because long distant inter-state or inter-
regional migration is barely significant (Osili and Long, 2008; Oyelere, 2010). Migration at a fairly
massive scale is essentially within states, or at best within regions, with locations sharing similar cultural
characteristics. If long distance migrants tend to make housing investment in their origin communities,
there might be no reason to worry about potential bias to our estimates. However, the DHS data cover all
states of the federation, including states like Lagos, and to a small extent the Federal Capital Territory
(F.C.T), with significant urban representations and greater number of long distance migrants. Other states
in South-western Nigeria have more developed urban locations than the other regions of the country.
Thus, modest migration might undo our estimates of missionary human capital investment variable. To be
sure migration is not biasing our estimates, we controlled for migration by introducing a dummy variable
for migration. Furthermore, we ran IV regressions for non-migrants. If any significant difference exists
between the two estimates, then selective migration will be biasing our estimates. Results show that
European contact with Nigerians through missionary human capital investment, and not other cultural
influence is influencing outcomes. Table 2.0d shows the cultural influence from non-indigenes is not
responsible for observed outcomes.
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4.1 Instrumental Variable (IV) Results
OLS results indicate that in nearly all regressions, a statistically strong relationship exists between
missionary human capital investment variable and the indicators of housing quality. When we attempt to
correct for potential bias from selective migration, estimates of missionary human capital investment
remain essentially unchanged. Omitted variables appear not to be part of the problems. However, bias of
missionary human capital investment estimates could come from measurement error. Data from this
important missionary human capital investment variable is drawn from Nigerian School Census Survey
which should contain information on all public and private primary and secondary schools in Nigeria.
However, there is a possibility that some schools may not have participated, introducing measurement
error which induced bias into our missionary human capital investment variable. Measurement error bias
pushes estimates towards zero. There is added possibility that missionaries may have self-selected into
locations with better houses, inducing a spurious relationship between missionary human capital
investment variable and housing quality. To confront potential biases from these sources, IV
identification strategy is adopted.
The relevant instrument is LGA latitude. As stated in the introduction to this piece, early missionaries
choose locations close to the sea-level (low-altitude) and within specific latitude range as well as areas
with ready access to coast for constant transportation of missionary personnel and receipt of supplies (
Johnson, 1967). We select latitude from the geographic dataset accompanying the 2008 Nigerian DHS. A
bivariate regression of missionary human capital investment variable on latitude yields negative and
statistically significant estimate of -0.0014303. It is significant at 1 percent.
Tables 3.0A and 3.0B display the results for the second stage of IV regressions. Like OLS regressions, we
have five models (1-6) listed in increasing order of covariates included in the model. Model 1 has
covariates such as age, age-squared, four ethnic dummy variables, English-Speaking dummy to capture
willingness to communicate in English language which reflects personal preference for European style of
living, marital status dummy, household size and LGA population density (measured as the number of
persons per square kilometer of land). Model 2 is model 1 plus the fraction of persons using electricity in
each LGA and the natural logarithm of the number of dams and water supply facilities. Model 3 include
all covariates in model 2 in addition to the number of private secondary schools per square kilometer
(which measures the extent to which the presence of private schools could be responsible for higher
quality houses), LGA enrolment rates in 1970, percentage of LGA residents with complete tertiary
education and distance to the state (indicating the extent to which modern buildings spring up in and
around the state capitals). In model 4, we add 9 cohort fixed effects dummies to reflect the exposure of
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different time-bound influences to all covariates already in model 3. State fixed effects variables are
added to model 4 to have model 5. This is done to pick up the effects different state government housing
policies will have on housing quality across the states of the federation. In model 6, we add four
indicators reflecting the quality of political institutions across the 36 states of the federation to all
variables included in model 5.
In all IV regressions, missionary human capital has significant effects on the two indicators of housing
quality. Though the estimates for the first three models are implausibly large, the addition of more
variables reduced these estimates considerably. However, the estimates are still significant at 1 percent.
Though IV estimates are not precise, they are nine to ten times the size of the OLS estimates. This implies
that downward bias due to measurement error is stronger than upward bias due to self-selection. While
OLS regression of model 6 shows missionary human capital investment reduces the number of persons
per room by 0.28, the corresponding IV regression shows that the reduction will be by 10.03. For the
second indicator of housing quality, missionary human capital investment increases the quality of
building materials by 0.26 for OLS regression and by 5.35 for IV regression.
Age, gender factor, four ethnic dummies, marital status dummy, English-Speaking dummy, household
size, fraction of persons in each LGA using electricity, LGA enrolment rate, distance to state capital and
fraction of LGA with tertiary are all significant in the second-stage regression. Older persons live in better
houses, and surprisingly, females live in better houses than the males. Larger households live in high
quality houses, but beyond a point, house quality decreases with household size. The availability of public
goods such as electricity increases house quality though state wide presence of water and dams facilities
reduces it. The cohort fixed effects dummies are essentially insignificant determinants of the two
indicators of housing quality. Most state fixed effects variables are significant determinants of housing
quality. For the house density outcome variable, age, Yoruba dummy, igbo dummy and distance to state
capital are insignificant at 10 percent.
While a number of identification problems remain, results from IV regressions reveal that missionary
human capital investment in the 19th century has effects on contemporary indicators of housing quality.
The results imply that missionary self-selection into better locations cannot account for the observed
outcomes. The IV estimates are several magnitudes bigger than OLS estimates, they are less precisely
estimated. Accounting for the large standard errors of IV estimates still leave a big difference between
OLS and IV estimates. Analysis in the first-stage regressions show that biasness from weak instrument is
unlikely because reported F-Statistic for all IV regressions is far above the benchmark value of 10.
However, IV estimates reported here are likely to be biased by latitude instrument not meeting the
validity condition. Validity concern is strongest where latitude instrument is highly correlated with pre-
missionary indicators of economic development. In the following section, we take a number of steps to
show that reported IV estimates are not biased by invalid instrument.
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5.0 Validity Concerns for Latitude Instrument:
5.0.1 Historical Evidence
It is not in doubt that early Christian missionaries self-selected into Southern parts of Nigeria (Johnston,
1967) for a number of reasons. While factors such as proximity to the coast, elevation or altitude, latitude
and other geographic features may have influenced choice of initial locations, these geographic variables
are also known as important causal factors in economic development (Sachs 2001).
Thus, if the geographic endowments of the south are important drivers of economic development, choice
of initial residential choice may have been influenced by the advanced state of economic development in
the southern regions of Nigeria relative to the northern regions. Thus, the more urbanised parts of Nigeria
with better quality houses might be more attractive to Christian missionaries who are setting on their feet
on the Nigerian soils for the first time. If that were the case, then our instrument will be invalid because of
potential correlation with socio-economic variables in the error term. The violation of exclusion
restriction condition is obvious because these socio-economic variables have independent impact on
outcome: the quality of housing.
In the absence of pre-missionary historical data on the volume of economic activities on different regions,
we rely on historic analysis of the degree of urbanisation prior to the coming of Christian missionaries in
the mid-nineteenth century. Though the analysis of the extent of urbanisation in different parts of Nigeria
is in part due to lack of quantitative data on the actual volume of economic activities, urbanisation and per
capita income are often highly correlated (DeLong and Shleifer, 1993; Acemoglu, Johnson and Robinson,
2005). Thus, urbanisation is itself a good proxy for per capita income (Nunn and Qian, 2011).
Urbanisation of different parts of Nigeria is intertwined with trade and manufacturing activities taking
place in this urban centers. The degree of urbanisation and accompanying trade and manufacturing
activities, from our historical analysis, should reveal whether exclusion restriction is likely to be violated.
Evidence from historical analysis, complemented with additional econometric evidence, should provide
conviction for our exclusion restriction story.
Urbanisation, and the trade that goes with it in Nigeria dates far back to the medieval period and is not
unconnected with the recrudescence of trade in the old world during this time. A set of Arab geographers
and historians have stressed the role played by Sudan Belt of West Africa in the trade of this period. Their
accounts indicate that various items of trade such as gold, ivory and slaves were commonly and
extensively traded. From the middle ages to the discovery of America, Sudan was one of the principal
suppliers of gold to Europe. In fact the econometric prosperity of the Arabs of Barbary during the
medieval period cannot be divorced from trade with Italy on one hand, and with West Africa Sudan on
the other (Mabagunje, 1965).
Northern Nigeria was directly connected to this trade, for Kanem Empire of Bornu, was already well-
developed empire during the medieval period. By the 15th century, the various Hausa states which has
emerged with merged into a larger Kebbi Empire. Both Kanem and Hausa states formed a network of
traders from North Africa. The two major trading routes were involved in exchange of salt and slaves.
With specialisation in crafts and agricultural production, trade relations were also forged with other parts
of Sudan Empire. Account by Leo, a visitor to the West and East ends of Hausaland, reveals these
locations had great artificers and linen weavers, whose shoes were comparable to what obtains in old
Roman Empire. Zamfara, Katsina, Kano and Zaria, even in their desolate states after the attack by army
of the Songhai Empire, maintained some semblance of economic prosperity (Leo, 1896). Specifically,
Leo describes inhabitants of Kano as rich merchants and of civil disposition. Kanem, which had come
under the attack of the Songhai army, trade in horses with the Barbary and had a king whose cutleries
were made of gold.
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Clapperton, the first European to travel across the south and north of Nigeria in 1825, observed the
enormous amounts of trading going on across the South/North divide. He noted that several locations
across the Southern and Northern Nigeria were major trading posts (Clapperton, 1929). Their trade
involved the exchange of goods with goods and the use of currency as well. Barth (1957) also gave a
more detailed account of economic activities and urbanisation in Northern Nigeria. He estimated that no
fewer than 300 camel loads of cloth, worth about £5000 British pounds, were exported from Kano to
Timbuktu. The total exports of Kano dyed-cottons stood at about 300 million Kurdi. If a whole family can
live at ease in the Kano country with between fifty to sixty thousand Kurdi a year, then we can imagine of
the amount involved in this trade alone. Kano country produce not only clothes for export but has fertile
soils, able to produce sufficient corn for internal consumption and for exports in addition to lands for
pasture. With a population between 30,000 and 60,000, it was a major centre of craft production. Markets
were well-developed in Katsina axis.
To large extent, the Yoruba country has a network of towns, which were founded between 7th and 8
th
century. This network of towns was involved in trade, which connected those in far flung northern cities.
Trade within each Yoruba town involved the exchange of craft products. Trade relations involved
contacts with traders from other ethnic groups. Clapperton again noted that trona or natron from Bornu
was traded in Oyo and sold in various parts of the coast where it is in great demand. Lander as cited by
Mabogunje (1965) noted the extensive nature of trading activities in that part of Nigeria. He found within
the Yoruba country a company of Kano merchants who are still on their way to Gonja which is the Selga
of Cape Coast Castle and Accra.
The observation of Townsend, one of first few missionaries to set their feet on the Nigerian soils, was that
the Yoruba country are populated by commercial people involved in international trade and exchange
commodities of different countries. Trade items include cloth, cotton, natron, indigo, ivory, Shea butter,
gum, palm oil, salt and slaves. Ibadan, reputed as a town of warriors, also had craftsmen such as weavers,
tailors, tanners, leather dressers and saddlers, professional iron-smelter and blacksmith, sawyer and
carpenters and potters. There were also manufacturers of palm, nut oil and soap in all parts of Ibadan
town. It has extensive network of markets which in commodities such as yams, beans, corn, cotton and
food preservatives. There is one big market where European articles, brought from Lagos and Badagry
through the Egba and Ijebu country.
Finally, there is the South-East, which did stands out as a region with extensive network of urban towns
before the colonial period (Mabogunje, 1965). However, a good number of towns had emerged in the
wake of trans-Atlantic slave trade around the mouths of the various distributaries of Niger Delta and
along the lower course of the Niger River itself. Important trading areas include Bonny, old Calabar, New
Calabar and Brass. A number of urban centers, which sprang up as a result of slave trade and trade in
legitimate commodities, emerged along the lower Niger. The people in this region are described as being
hardworking, producing vast quantity of yams (Laird and Oldfield, 1837) for sale along the coast and up
the river. There was also extensive trade in oil palm and slaves as well. Trade in this region involved men,
women and children. Traders brought clothes of native manufactures, beads, ivory, rice, straw-hats and
slaves, which were sold in exchange for cowry currency. In turn, they bought European goods brought
from Portugal and Spain.
The description of urbanisation and trading within South-West suggest scale of economic activities that
probably approximate that of its northern neighbours, but in no way exceed it. It system of towns are not
as well developed as the commercial cities of the north. While trading activities are well-developed in
South-East prior to the advent of missionaries, the scale of activities never exceeded that of both the
North and the South-West. The South-East would be a close third after the North and South-West. What
is perhaps apparent from the brief historical review undertaken here is that proximity to the coast and
interactions with European traders by South-East and South-West men and women of commerce never
gave these regions any head-start in the economic development.
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If pre-missionary southern and northern Nigeria were not fundamentally different in terms of economic
development indicators, it is possible that colonial rule and private business interests which frequently
supported favoured the coastal south than the far flung northern areas. But we must that proximity to the
coast meant more slaves could be taken from coastal communities than those in far flung places. Thus,
coastal communities at the time the missionaries arrived were probably less developed than those further
away from the coast (Nunn and Puga, 2011). Colonial regime and the trade activities that overlap with the
regime of missionary operations in Africa and Nigeria, particularly in the coastal areas, did not help
matters either. The genesis of underdevelopment of West Africa according to Sherwood (1997) is
traceable to adverse activities of Elder Dempter group of companies, a firm that held sway during the
colonial period.
While comparable data are not available, it is doubtful of any family in the regions of the South had living
standard that approximated that of an average family in the Kano city described previously.
Contemporary divergence in living standards, stacked against the regions of the North, could be causally
related to events that occurred just before colonial rule began. Colonialism could have its own
independent effect apart from the missionary effects on current housing outcomes, but it is a constant
factor for all regions of the country. If it did at all, it probably would be through the ways it supported
British private business interests relative to its colonies domestic business communities. This hurts the
south more than the north. The implication is that colonial rule cannot be a confounding factor inducing
spurious correlation between missionary schooling investment and housing quality. Berger (2009) study,
which reveals that institutional differences across limited locations in Nigeria matter for quality of public
service delivery, covers a very small part of the country. Thus, it is difficult to generalise the study
findings.
However, comparable current and historic maps (figures 1 & 2) of Nigeria help to show the spread of
dense network of people across the North-South divide of Nigeria.
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From figure 2, it is clear that the distribution of dense population is relatively even throughout the
Northern and Southern regions of Nigeria. The second figure depicts population dennsity as at 1931,
nealy a century after the first successful missionary journal into Nigeria.
If this brief discussion is taken along with the previous analysis of the role of missionary in the emergence
of European-style housing in Nigeria, it would not be difficult accepting the results of our ordered Probit
and IV regressions about the missionary schooling investment and contemporary housing quality. For the
same reason, it will not be difficult to appreciate why our instrument will fulfill the exclusion restriction
condition. In other words, unobserved variables prompting economic development in the regions are not
having independent impact on outcome indicators.
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Figure 2: 1931 Population Density and 1923 Main Mission Stations in Nigeria (Source:
Horacio, 2011)
While pre-colonial level of economic development across the regions of the North and South may not
pronounced, missionary activity in Africa and Nigeria was far from random. To get as many converts as
possible, missionaries selected areas with high population density and those with better historic records of
economic performance (Johnston, 1967; Frankema, 2010). They selected highland regions with minimal
presence of deadly diseases, areas which often attracted European migrants with high human capital
endowment and institutions that property rights and limit public abuse of power (Acemoglu et al, 2001;
Glaeser et al 2004). They chose regions closer to the coasts and areas with prior contacts with European
explorers and traders (Banerjee, et al 2010; Bleakley and Lin, 2010: Fryer, 2011). Figure 2 reveals that
apart from the far North, mission stations tend to constructed in densely populated areas. This applies to
entire Southern Nigeria and the middle belt. Mission stations in 1923 track closely population density of
1900, implying the missionaries in order to maximize the number of Christian converts establish stations
around densely populated communities. Missionary activities in many communities are most often
preceded few centuries of contacts with European traders and explorers, OLS estimates are compounded
by high quality institutions and human capital brought into these communities by these Europeans
(Acemoglu et al. 2001, Glaeser et al. 2004). Though missionaries preceded the colonial rulers, their
rapid expansion often depended on activities of the colonial government. One important colonial
activity in Nigeria is the construction of railways along different parts of Nigeria. The
educational activity of missionaries also depended on the length of colonial governance. The
span and quality of colonial rule affects long run economic development (Bertocchi and Canova
2002; Grier, 1999).
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Without additional econometric evidence, it will be difficult to conclude whether missionaries positively
or negatively self-selected into the regions that hosted their mission stations and schools based on
indicators of economic development. Negative self-selection would imply they settled in regions with
comparatively lower level of economic development. Positive self-selection would mean the very
opposite. But negative self-selection will still be in line with our argument that human capital endowment
of each LGA due to missionary schooling investment caused the emergence and spatial concentration of
high quality houses in the regions of the south but the exclusion restrict condition may not be fulfilled.
The validity of instrument will rest crucially on no significant correlation, positive or negative, between
the instrument and each of the indicators of pre-missionary economic development.
5.0.2 Econometric Evidences for Instrument Validity
Though historical analysis suggest that the latitude instrument may not violate exclusion restriction
condition because the south was not more developed than the north despite prior contacts with traders
from Europe, a more convincing case could be made for instrument validity if additional econometric
evidences could be provided. If historical data on indicators of economic development prior to the onset
of the missionaries in Nigeria could be found, regressing these indicators on latitude could be revealing. If
missionaries settled in more developed LGAs, then latitude instrument should be more strongly correlated
with these development indicators. We drew on a number of pre-colonial development indicators
compiled by Murdock (1967).
One indicator is the settlement patterns of ethnic groups which moves through migratory, semi-
nomadic, semi-sedentary, compact and impermanent settlements, dispersed family homes, disparate
hamlets creating single community, compactness of permanent settlements and complexity of settlements
in order of increasing economic and social development. Second is a measure of ethnic group’s political
institutions represented by the number of jurisdictional hierarchies that extends beyond the local
community. The ranking starts from no level, one level, two levels, three levels and four levels in that
order of increasing complexity. Third, we mean size of local communities. A value of 1 is assigned to
communities fewer than 50, 2 to those in the range of 50-99, 3 to 100-199, 4 to 200-399, 5 to 400-1000, 6
to 1001-4999, 7 to towns of 5000-50,000 and 8 to cities of more than 50,000. An alternative measure of
community size, colonial population density, which probably is not radically different from the years
before the adventure of missionaries started in Nigeria started is another important indicator.
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The fourth indicator is the intensity of agriculture. The ranking of this indicator in order of increasing
complexity starts from no agriculture, casual agriculture, extensive or shifting agriculture, horticulture,
intensive agriculture and intensive irrigated agriculture. The fifth one is the extent of class stratification,
ranging from the absence of stratification among freemen, wealth distinctions, elite, dual and
complex. The sixth measure is the degree of reliance on fishing, measured as the fraction of food coming
from fish, is also another good indicator of economic development6. Two other indicators of political
institutions are added: Succession to the Office of Local Headman and political integration. For
succession to the office of local headman, it starts with patrilineal heir, matrilineal heir, appointment by
higher authority, seniority or age, influence, wealth or social status, election or other formal consensus
and informal consensus. Political integration measures include absent at the local level, autonomous
local communities, peace groups transcending local communities, minimal states, little states and matured
states.
Higher values of these indicators mean greater level of economic development. Since missionaries settled
essentially in low latitude areas, instrument exclusion restriction condition will be violated if estimates of
latitude are strong and negative. This implies that missionaries settled in more developed low-latitude
LGA areas. These results reported in table 4.0 show the latitude instrument is insignificantly related to all
indicators of economic development. Thus, it is unlikely that missionaries settled in more prosperous
LGAs, where the better quality houses existed or would have been built. Secondly, if low-latitude
instrument is invalid, it should be unrelated to the indicators of current economic development. To
measure current economic development, we select indicators such as state unemployment rates, state
education index, adult literacy rate, crude birth rate, crude death rate, percentage of children less than a
year yet to receive immunization (2001-2005), reported malaria cases as a fraction of state population in
2006, and state GDP per capita. Latitude is positively and significantly related to each of these indicators.
For instance, low-latitude areas have lower level of current unemployment rates and vice versa. If we
move from 13-latitude areas to 4-latitude locations, unemployment rates drop from 39 to 8 percent.
Similarly, low-latitude areas are currently negatively correlated with state education index, higher literacy
rates and greater GDP per capita. Latitude is positively and significantly correlated with unemployment
6 The various categories considered include 0-5%, 6-15%, 16-25%, 26-35%, 36-45%, 46-55%, 56-65%, 66-75%,
76-85%, 86-100%.
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rate, fraction of 1-year old not immunized, fraction of state with reported cases of malaria, crude birth
rates and crude death rates. This reinforces confidence in the validity of our instrument.
Mid 19th century missionaries from Europe were severely restricted in their access to the northeast and
northwest. However, there are pockets of success stories in specific locations of these two locations. In
Kaduna state of northwest and Gombe and Taraba states of northeast, limited incursions were made by
early missionaries. If there were limited presence of missionary settlements in these two states, then
contacts with missionaries should impact on the quality of houses. We ran IV regressions for each of the
three states. From table 6.0, it is easy to see from the reported F-Statistics of the first-stage regression that
our instrument is highly correlated with the indicator of human capital investment, with the latter variable
impacting positively on housing quality. Northeast without Gombe and Taraba, and Northwest with
Kaduna should provide contrary results because substantial number of observations of missionary human
capital variable should be or approaching zero. The entire Northeast and Northwest without Kaduna,
Taraba and Gombe states should provide the same results. In the last three IV regressions, there is no
substantial relationship between missionary human capital investment and current housing quality.
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Exclusion restriction condition is satisfied if the latitude instrument affects housing quality only through
the missionary human capital investment variable. To test this, we run reduced form regressions with
instrumental variable as an explanatory variable and indicators of housing quality as dependent variables.
Introducing all set of covariates in the reduced form regressions, latitude instrument appears not to have
direct impact on housing quality. Alternatively, the instrumental variable must be significantly correlated
with missionary human capital investment variable. In the first set of regressions, the coefficients of
instrumental variable are completely statistically insignificant. In the second set, instrumental variable has
significant impact on missionary human capital investment (Table of results not shown).
Additional test of instrument validity suggested by Becker and Woessmann (2009) is implemented here.
The test examines the extent to which to which pre-missionary indicators of economic development are
correlated with indicators of housing quality. In all, the eight indicators of economic development are
significantly correlated with current 6 indicators of housing quality. Except for house density, a measure
of the number of persons per room in a household, the correlation is positive and significant. While these
pre-missionary indicators are significantly correlated with current measures of housing quality, both
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indicators of economic development and housing quality are uncorrelated with our latitude instrument.
We could infer that our instrument is plausibly valid.
Over-identification Test:
If we have more than the latitude instrument for the variable measuring missionary human capital
investment, then we can execute over-identification test, which under some conditions, would allow us to
provide additional proof of instrument validity. If additional instruments are exogenous, estimates from
the 2SLS will be more efficiency than that observed under IV regressions with one instrument.
To generate extra instrument for our overidentification test, we add elevation or altitude instrument. This
is because early missionaries settled in locations closer to the coasts, where they can easily get supplies
from Europe and where transportation can easily be facilitated (Johnston, 1967; Woodberry et al 2010).
Areas closer to the coasts have considerably smaller incidence of malaria than those further away.
According to Woodberry et al 2010, the intensity of malaria incidence was a major factor determining
missionary choice of locations. This is because malaria accounts for nearly all recorded deaths of
Christian missionaries from mid-18th century to early 19
th century Sub-Saharan Africa (Acemoglu,
Johnson and Robinson, 2001).
Because standard over-identification tests cannot strictly apply in the presence of heterogeneity, we carry
out the heteroskedasticity-robust version of the over-identification test on regressions with full set of
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covariates as depicted by model 6 in panel A of table 8.0. For both indicators, the instruments prove not
to be significantly correlated with the error term.
However, we have been warned about the practice of conducting over-identification test to assess the
validity of the moment conditions. The test in it self does guarantee instrument validity. Passing the test
is neither sufficient nor necessary for the validity of the moment conditions implied by the underlying
model (Parente and Silva, 2011). This is more so because all instruments used in our over-identification
test share similar rationale (Murray, 2006). Thus, the mere fact that the model passes the test of over-
identification is not an assurance that the instruments are valid. When Parente and Silva (2011) used
education of mothers and education of fathers to instrument for individual years of schooling in order to
estimate returns to schooling, IV estimate shows a return to education of about 7 percent, a robust
Hansen’s J-test statistic has a p-value of 0.22. Thus, we could easily imply that the instruments are valid.
Using the same data with instruments such as ‘living with a single mother at the age of 14 and ‘living
with stepparent at the age of 14 yields a return to schooling of 23 percent and robust Hansen’s J-test
statistic has a p-value of 0.30. Again it passes the over-identification test, proving that our instruments are
valid. However, re-estimating the model with simultaneous use of the four instruments yields robust
Hansen’s J-test statistic p-value of 0.01, hardly passing the test of over-identification at 5 percent.
To see whether validity of the over-identifying restrictions provides little information on the ability of
instrument to resolve the identification problem at hand, we add an another instrument, the number of
schools established in 1900 per square kilometer. We re-estimate our model simultaneously with these
three instruments. We implemented the over-identification test all over again. Our IV estimate is not
substantially different from what we have before and our instruments are valid with a p-value of 0.432.
The final validity test explores the implication of some correlation between instruments and unobserved
variables in the error term. This is because it is highly unlikely that latitude instrument is completely
orthogonal to the error term. When the instrument is plausibly exogenous, confidence in IV estimates are
biased to some extent. However, the extent to which the violation of exogeneity condition affects
inference cannot be determined. To determine the extent to which the violation of instrument exogeneity
makes unlikely it the IV estimates are biased, we adopt the strategy of Conley, Hansen and Rossi (2008).
Their approach involves adding the instrument to the second stage of the IV regression, and examines
bounds that we can place on the actual effect of missionary human capital investment on housing quality
as move away from complete orthogonality. IV estimates after these adjustments are reported in the panel
B of table 8.0. We are not still too far away to lose confidence in our previous estimates.
6.0 Channels of Causation:
Schooling and Wealth Channels.
Nigeria, being a British colony, received missionary visitors from the middle of the 19th century. The
missionary journey started in Nigeria with the arrival of the Wesleyan Christian Missionaries at Badagry
in 1842 (Fafunwa, 1974). The same year, Church Missionary Society (C.M.S) arrived. In 1853, the
American Baptist joined, and Roman Catholic Mission (R.C.M) arrived in the 1860s (Yahya, 2001). By
1914, ten other different Christian missions had joined. Though there was initial scepticism in some
southern parts of the country, Christian missionary activities spread much more easily as the provision of
some services, particularly education, increases the economic value of membership (Ajayi, 1965: 133;
Ekechi, 1971; Berman, 1974)7. In short, missionaries utilized their schools as inducements to lure
7 According to Berman (1974), “Africans were no less adverse to using missionaries for their (the Africans) own purposes than the missionaries
were for theirs. African reasons for attending mission schools varied, but most were related to well-defined political, social, or economic
consequences. The recent studies reveal that few Africans attended mission schools for the eschatological message espoused; the Africans'
spiritual needs were well provided for through traditional belief systems”.
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Africans into the missionary orbit (Berman, 1974). Added to this was the tendency of the missionaries to
locate in places with clean water supply, with high altitude and mild temperatures, and in places with
unhindered access to external trade routes with Europe in order to receive supplies (Johnson, 1967). This
gave the south an initial head-start in the education race.
And to win converts and train some of them in missionary work, the various Christian missions built
schools and sometimes hospitals. But the geographical spread was far from being even across the
Nigerian landscape. This is because Nigeria, like many countries in Africa, has differing geographic
endowments, diverse cultures and religions which either facilitated or inhibited settlements of visiting
missionaries. This area of least resistance had been the Southwest of Nigeria. This is probably on account
of the fact that Western influence, in the form of literacy and use of technological skills and Christianity,
had arrived through Abeokuta in the 1830s through Egba slaves, who were liberated in Sierra Leone
(Pallinder-Law, 1974).
In Igbo-Speaking Southeast, the first attempt at winning converts started in 1857 (Ekechi, 1974). Like in
the Southwest, the initial missionary activities were undertaken by C.M.S. Nearly thirty years later, the
Catholic Church joined. By the turn of the 19th century, the evangelistic efforts did not yield considerable
dividends. Though there initial setbacks for the missionaries, the subsequent atmosphere of insecurity
occasioned by the rampaging British military, combined with the safety that Christian membership
offered the Igbos at the time, made the mass conversion to Christianity possible by the onset of the 20th
century. One other decisive factor was the intense rivalry between Catholic and Protestant denominations,
which compelled the denominations to provide what the Igbos desired most; western education.
According to Ekechi (1974), “It was this desire for education, coupled with the competition between the
denominations, rather than the ambition to embrace the new faith, that led to the rapid spread of the
Christian churches in Igboland”.
The story starts to change as we move up North. In both Ghana and Nigeria, the British kept missionaries
out of the Muslim North. Emir Shitta, and later, Emir Aliyu declined the establishment of missionary
stations in IIorin, a city located in the North-Central, Nigeria. By 1959, only nine primary schools had
been established in IIorin by six Christian missions (Yayha, 1998). Long before colonialism, the Kano
emirate had fiercely opposed the incursion of Christian missionaries (Bray, 1981).
Thus, from the initial stage, the core Northern Nigeria was at a disadvantage. This was to have a knock on
effect on subsequent educational attainment and economic development of the far North. According to
Mustapha (2006), of the 26 boys who made it to Standard VI from the initial number of 2000 pupils in
1926, not a single one is from the North. In 1958, only 9 per cent of school age children were enrolled in
the North while the South enrolled over 80 per cent of its own school age children. From the data
provided by Adamu (1973), as at 1912, there were no secondary schools in the whole North and there
were no students from that part of the country in any of the 10 secondary schools located in the South
which had 67 students. When the North eventually established one secondary school in 1937 with 65
pupils, the south had increased to 26, with student population rising more dramatically to 4,285. Though
the North increased its secondary schools to 77 in 1965 with 15,276 students, the South now had 1,305
schools and total enrolment of 180,907 students. Enrolment at the University College, Nigerian first
University, in 1960 has the North at a big disadvantage with only 8.4 per cent of the entire student
population.
Consequently, the distribution of medium to high level manpower was skewed against the North. The
bulk of the academic and professional personnel right down to those with intermediate and sub-
professional training is from the South. The South dominated most professions except veterinary
medicine. Drawing on Mustapha (2006) account, not much has changed as at the 1990s. In 1990, only 2
per cent of registered engineers are of Northern extraction. The distribution of registered lawyers left the
entire North with only 14.6 percent of the total lawyers called to the bar in 1990. The North share of
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manufacturing outfits for the most periods between 1962 and 1967 was never above 40 per cent of the
total; was as low as 19.6 percent in 1963, peaking at 38.6 in 1966.
To show individual and LGA average schooling attainment as a channel through which missionary human
capital investment in 19-century Nigeria affects current housing quality, we use model 6 employed in
both OLS and IV regressions. To show this channel, we start from latitude influencing the degree of
missionary human capital investment, and missionary human capital investment affecting individual
schooling attainment, and the latter variables affecting housing quality. We use the 3-Stage Least Squares
to track the channel of transmission. The results are reported in table 9.0A
The divergence in schooling outcomes between the north and north was bound to accentuate inter-
regional differences in several other ways. The initial spatial concentration of schools implies other
factors of productions would flow in the same direction as the schooling capital. The initial beneficiaries
of missionary education would be better off than non-beneficiaries. Thus, the spatial concentration of
schools and human capital in few locations added in no small measure to this divergence. The bulk of the
returning freed slaves are predominantly from the southern parts of Nigeria. Since they are comparatively
better off than the indigenous because of their education and skills, it was not difficult convincing others
about the benefits of free education. A good number of those who returned were also businessmen (Ade
Ajayi, 1965). There is also the added fact that missionary strategy involves not just converting the
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indigenes to Christianity, but making successful businessmen out of them so that they can replace the
traditional chiefs and become agents of civilized Africa which Buxton had envisaged (Ade Ajayi, 1965).
A World Bank report (World Bank, 2002) indicates that as at 2002, Northern Nigeria accounts for only 10
per cent of manufacturing employees, Southeast has 21 per cent and Southwest about 40 per cent (World
Bank, 2002). We use LGA longitude and altitude in linear and square forms to instrument for wealth as
suggested in Glaeser and Sak (2006).
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Summary and Conclusion
In this study, we explore the empirical relationship between contemporary housing quality and long term
indicator of missionary human capital investment. We use OLS and IV identification strategies to
investigate the causal relationship. In OLS and IV regressions, locations with greater missionary human
capital investment between 1843 and 1910 have less crowded house today and houses there are built with
better construction materials. IV estimates turn out to significantly higher than OLS estimates. Robust
check show omitted variables bias is not responsible for observed. IV estimates are robust to the
falsification test and a number of other exclusion restriction tests. Three stage least squares are used to
establish the channels through missionary human capital investment impact on housing quality. Both
individual schooling attainment and wealth are strong channels through which missionary human capital
investment affect housing quality. This study demonstrates one important instance in which the
involvement of the private sector has considerable indirect positive spillovers on neighbouhoods.
This section has shown that some form of correlation exist between areas of Nigeria which came under
heavy foreign missionary influence from the late 19th century to the early 20
th century and contemporary
economic development parameters. In the spirit of the new economic history, we would gain much if we
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could go back in time to investigate the long term impact of missionary activities8 which started in the
19th century in on location differences in housing quality Nigeria.
8 This study explores collectively and separately the early 20th missionary activities of Catholic and Protestant churches on
current health outcomes such height, BMI and child mortality.
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