Gender Preferences in Africa: A Comparative Analysis of Fertility Choices with Pauline Rossi

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The evolution of health standards in Africa

Describing what happened in Africa during the 20th century would contribute to shed light on what needs to be further done to improve health policies in the continent. Getting new insights on this question is particularly important in the context of recent health progress made in Africa. We know that Africa has the lowest level of health investments and the worst health conditions in the world today. What happened over the last decades, which could explain such a fact?
A first explanation is that the continent had extremely low health standards to start with, compared to the rest of the world. As a consequence, despite huge progress in health outcomes since colonial independence, it did not catch up with other regions of the world. The most salient example is the case of maternal mortality (Figure 0.1). Sub-Saharan Africa made huge progress from 1990. But it started from such high levels of risk that it was unable to catch up with other regions. The lifetime risk of maternal death was above six percent in 1990 in sub-Saharan Africa, followed by South Asia, with less than a 2.5% risk. The risk in sub-Saharan Africa is still 2.6% today, compared to 0.5% in South Asia. The same conclusion can be made about DPT (diphtheria, pertussis, and tetanus), or measles immunization rates (upper graphs in Figure 0.2). South Asia and sub-Saharan Africa experienced the same trends as other regions over the last 30 years. However, both regions started from much lower levels, and are still lagging behind. Similarly, in sub-Saharan Africa, the proportion of population with access to improved sanitation, or improved water source, did increase as much as in other regions from 1990 (lower graphs in Figure 0.2). Yet, today, only 65% of the sub-Saharan population has access to an improved water source (30% has access to improved sanitation facilities), compared to around 90% in South Asia (40% for sanitation), its closest region.
A second explanation for Africa’s low levels of health is that the continent experienced lower health progress than other regions of the world, for some health dimensions. These lower health progress could be related to the fact that welfare levels have been deteriorating in Africa. Chen and Ravallion (2004) estimate that the world poverty rate nearly halved between 1981 and 2001, declining from 40% to 21%. Meanwhile, the level of poverty in sub-Saharan Africa increased from 41.6% to 46.4% during the same period. While the under-five mortality rate decreased from 23% to 2.4% in Middle-East and North Africa from 1960 to 2013, the sub-Saharan mortality rate only decreased from 26% to 9.2% (upper graph in Figure 0.3). Similarly, sub-Saharan Africa and South Asia started from very close life spans in 1960: 40 years old in sub-Saharan Africa, and 42 years old in South Asia (lower graph in Figure 0.3). However, from the 1980’s, the rate of increase slowed sharply in Africa compared to other regions of the world. Today, life expectancy has reached 67 years old in South Asia, an increase of 57%, compared to only 56 years old in Africa, an increase of 40%.

Health provision across space

Figure A-1.3 in the Appendix shows the map of the number of all types of medical staff (nurses, midwives, physicians, medical assistants) per 100,000 capita, per district and period. One can observe huge inequalities between districts, with some districts getting less than 5 medical agents per 100,000 capita, while others get more than 15 agents. Similarly for other types of colonial investments, inputs are not evenly distributed across districts.
If health services are unequally distributed, who are they targeting? Is Feierman (1985) right in saying that “the continent’s rulers provided medical services to the cities but not the countryside, to men but not to women and children, and to the rich but not the poor”? Are health policies targeting specific populations in the same way as other colonial investments?

Colonial policies and Europeans

The second intuition which is tested here is whether colonial policies target districts where Europeans live. Regarding health, during the first years of colonization in Cote d’Ivoire, “small medical posts began to appear at the major administrative and military centers of the interior, wherever there was a European settlement and economic interests to protect” (Lasker, 1977). Concentration indexes are used to test for this assumption, following Kakwani, A.Wagstaff, and van Doorslaer (1997). Let Xi (i = 1…N) be the level of colonial inputs (medical staff, vacci-nations, teachers, etc, per current population) of the ith district. From there, Rieur is the relative rank of the ith district regarding European presence. The concentration index Ceur is defined as : N 2 Xi Ceur = XiRieur 1 N =1.
Where = PN Xi is the mean level of colonial investments. Ceur thus indicates how i=1 much colonial inputs are concentrated on observations with high ranks in Europeans’ propor-tion. If X is independent from European density, then Ceur = 0.
Concentration indexes are computed for each period and each colonial input variable and are graphed in Figure 1.9. These graphs show that concentration is well above zero for every dimension of colonial policies. For most dimensions of colonial investments, there are high but decreasing concentration indexes. The bias towards Europeans is not significantly decreasing for hospital admission and only slowly decreasing for consultations. Indexes are significantly positive for both smallpox and yellow fever vaccinations; but they are much higher for yellow fever vaccinations. For both diseases, indexes decrease a lot and become negative at the end of the period: vaccinations focus on non-European districts. The same pattern is true for public works, which get to null concentration indexes at the end of the period.

Health policies and other colonial policies: Context and empirical strategy

The first assumption of this work is that due to the scarcity of resources, all colonial ex-penses studied here – education, health, public works, conscription – 13 were bound by bud-getary constraints in former French West Africa. Consequently, for each category of colonial policies, some choices had to be made regarding the allocation of budget across policies, and across districts. Regarding health policies, the colonial power needed to decide what was pro-duced in the health system, and which districts were targeted. This section describes the con-text of health provision’s decisions, within colonial policies’ decisions. It discusses various potential scenarii regarding the allocation of colonial policies, and their implications. The em-pirical part will allow to rule out some of these scenarii and to identify the drivers of health policies’ allocation, in comparison to other colonial policies.

The decision-making chain of colonial investments

At each period t, the decision was taken to spend an amount N on the four types of colo-nial expenses considered here: conscription, education, health, and public works. A part Ph of N was then allocated to current health expenses in colonial French West Africa. At the same time, a decision could be taken to contract a loan in order to finance an important health infras-tructure investment, such as a hospital building. The General Governor of former French West Africa in Dakar was then in charge of dividing the amount Ph:N between the eight colonies.
At this point, the governor of each colony did some budget planning.14 The budget was shared between two types of spending: staff and equipment. Within each of these expenses, the budget could be further shared between various medical services: head of medical services and pharmacy, hospitals, Native Medical Assistance, vaccination services, etc. In the few evidence provided in the archives, the Native Medical Assistance budget amounted to around half of the total budget. The amount dedicated to the Native Medical Assistance was shared between colonial districts;15 and followed a “delegation” of decision from the colony governor to district governors. These district governors received a budget allowance for the local Native Medical Assistance, which they could allocate to various health inputs.
As a consequence, the final quantity of inputs provided in a given district and period was determined by a whole decision-making chain. It depended on the amount N allocated to colonial expenses, on the share of the budget that was devoted to each category of policy (health, education, conscription and public works), and then on the geographical allocation across space. The outcome of this decision-making chain is that each district z gets a quantity of investment Iz;t in period t. This paper considers health as multidimensional. It tries to ex-plain the provision of various health inputs: physicians, African staff, vaccines, etc. The main aim of this work is to describe the determinants of colonial health investments, as compared to other colonial policies. What are the underlying mechanisms leading to the allocation of health provision? To what extent are they similar to the mechanisms underlying other colonial policies? What kind of strategy did the colonial power implement?
In order to describe colonial policies’ drivers, a theoretical distinction can be made between two types of decisions. First, a binary “extensive investment” decision, by which the colonial administration decides to increase the number of inputs from 0 to y > 0 in district z. Second, an “extensive investment” decision, by which the number of inputs is decided, once it has already been decided to allocate a positive number of inputs. As discussed in the next section, the underlying mechanisms leading to these two types of decisions may not be the same. This distinction will sometimes allow to disentangle between various possible channels. Section 1.5.3 presents an empirical model which allows to make the distinction between the decision to go from zero to a positive number of inputs, and the decision to increase the number of inputs.

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The provision of colonial policies: what are the main drivers?

The first set of determinants for colonial policies are time and geography. Colonial admin-istrations’ decisions on investments varied a lot across time. As shown by descriptive statistics, there were increasing trends in colonial investments over the period. Furthermore, the target of colonial policies also changed over time (health policies aimed at curative, and then preventive action, for instance). As a result, the year t is expected to be a determinant of Iz;t. Also, each district has a preexisting colonial system, pre-colonial institutions, geographic patterns, etc. All of these districts’ characteristics have an impact on the provision of colonial inputs. This pa- per seeks to describe the local drivers of the colonial system’s development in former French West Africa. It thus focuses on colonial policies’ determinants other than fixed geographic or periodic characteristics.
The second set of determinants for colonial investments are preferences. The colonial ad-ministration can chose to provide a preferential treatment to some given districts, or to some specific populations. It can also chose to have a specific target in mind regarding the dynamic allocation of colonial policies.
The third set of determinants are related to the cost and benefit of colonial policies. It is in-deed very likely that a decisive aim of colonial investments was their productivity. Hence, “the allocation of health inputs outside of urban centers was determined by economic criteria (pro-ductivity, cost, etc)” (Becker and Collignon, 1998). Increased productivity can be an intrinsic motivation if the colonial power has a philanthropic goal. The productivity aim can also result from an economic incentive. For health and education policies, there is an incentive to provide a healthy and educated workforce. Dozon (1985) explains that from the 1930’s, the economic interest of colonies is put forward and thus becomes the main incentive to provide health ser-vices. For public works and conscription, the immediate interests of the colonial power are even more obvious. Furthermore, one can think of a “propaganda” motivation by which the colonial power wants to advertise the success of its colonial policies, notably in France. Either of these motivations – and the list is probably not exhaustive – would make the productivity of colonial policies an essential determinant of colonial services’ provision.

The colonial system

Four variables are built to describe the existing colonial system in the previous period. The first variable describes the logistical support for medical care: an indicator variable of whether there was a medical center is built.18 Second, the structure of the colonial system is described by an index of the quantity of colonial staff in district z and its neighbors G(z).19 Third, two dummy variables describe the presence of the colonial administration in district z and its neighbors. The dummy “strong presence of health administrations in t 1” is equal to one if there are at least three positive stocks for the following health inputs: vaccinations in z, medical staff in z, vaccinations in G(z) and medical staff in G(z). The dummy “strong presence of other administrations in t 1” is equal to one if three of these colonial inputs’ stocks are positive in t 1: teachers in z, public works in z, conscription in z, teachers in G(z), public works in G(z) and conscription in G(z).

Table of contents :

1 The Provision of Colonial Policies in Former FrenchWest Africa: Are Health Policies Specific? 
1.1 Introduction
1.2 Literature and historical context
1.3 Data
1.3.1 Colonial data
1.3.2 Colonial statistics: main challenges
1.4 Colonial policies: first descriptive evidence
1.4.1 Colonial health policies: what was done?
1.4.2 Increasing trends in colonial investments
1.4.3 Health provision across space
1.4.4 Colonial policies and urbanization
1.4.5 Colonial policies and Europeans
1.5 Health policies and other colonial policies: context and empirical strategy
1.5.1 The decision-making chain of colonial investments
1.5.2 The provision of colonial policies: what are the main drivers?
1.5.3 The empirical strategy
1.6 Results: what are the main determinants of health provision ?
1.6.1 Linear results
1.6.2 Intensive and extensive margins of colonial investments
1.6.3 Robustness checks
1.7 Conclusion
2 The Double African Paradox: Height and Selective Mortality in West Africa 
2.1 Introduction
2.2 Existing literature and contribution
2.2.1 Literature
2.2.2 Contribution
2.3 Data and descriptive results
2.3.1 Data
2.3.2 Descriptive statistics on the paradox
2.4 The height-mortality relationship
2.4.1 The mechanisms at stake
2.4.2 What are the potential biases?
2.4.3 The empirical strategy
2.4.4 A positive correlation?
2.5 A model of height differential between survivors and deceased
2.5.1 The adult height equation
2.5.2 The height differential between survivors and deceased
2.5.3 Identification assumptions of the model
2.6 Estimation of the model and implication for the “double African paradox”
2.6.1 Estimation of the height differential between survivors and deceased
2.6.2 The level paradox
2.6.3 The trend paradox
2.6.4 Adult heights, child heights: why do conclusions differ?
2.7 Robustness of the results and main implications
2.7.1 Robustness
2.7.2 Main implications
2.8 Conclusion
3 Gender Preferences in Africa: A Comparative Analysis of Fertility Choices with Pauline Rossi
3.1 Introduction
3.2 Gender preferences in Africa
3.2.1 Theoretical motives for gender preferences
3.2.2 Empirical evidence so far
3.3 Data
3.3.1 Data
3.3.2 Descriptive statistics
3.4 Empirical Strategy
3.4.1 A duration model of birth intervals
3.4.2 Relating durations to the proportion of sons
3.4.3 Identification assumptions
3.5 Results
3.5.1 Comparative descriptive analysis
3.5.2 Key drivers of gender preferences
3.5.3 Mechanisms: individual choices or social norms?
3.6 Robustness Tests
3.6.1 Testing the child mortality bias
3.6.2 Testing the sample selection of mothers
3.6.3 Investigating heterogenous effects across birth ranks
3.7 Conclusion


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