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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.

1 gold_soad@yahoo.com or ade.adewole@covenantuniversity.edu.ng

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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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.

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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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