How might deep determinants matter today?

1. Disease Control, Demographic Change and Institutional Development in AfricaMargaret S. McMillanDepartment of Economics, Tufts Universityhttp://margaretsmcmillan.com/William A. MastersDepartment of Food and Nutrition Policy, Tufts Universityhttp://sites.tufts.edu/willmastersHarounan KaziangaDepartment of Economics, Oklahoma State Universityhttp://www.hkazianga.org/NEUDC 2012Revised version of NBER Working Paper No. 17718, entitled “Rural Demography, Public Services and Land Rights in Africa: A Village-Level Analysis in Burkina Faso”

2. Disease, Demography and Institutional Development Motivation | Data | Method | Results • How might deep determinants matter today? • Timing of historical transitions and demographic change • Conditioning production response and investment returns • Conditioning policy response and institutional development • Tropical disease control as natural experiments • Geographic endemicity overcome with postwar technologies • Control of river blindness (Onchocerciasis) offers: • Magnitude and variance (Africa-wide, 60% of Burkina Faso) • Exogeneity(foreign technology, uniform treatment) • Speed and timing (1975-2002) between census years and in living memory permits our difference-in-difference test

3. Disease, Demography and Institutional Development Motivation | Data | Method | Results • How river blindness works • A species of blackfly (Simulium damnosum) • breed in rivers, bite people and pick up Onchocerca larva • transmits the Onchocerca to its next victim • A species of worm (Onchocerca volvulus) • grow in nodules under your skin, live for about 14 years • release millions of microfilarial larva that live or up to 2 years in the human host, who they maim and blind, and viable for 6-8 days in the blackfly during transmission to next victim • = > Endemic in hot, tropical places near to rivers (up to 40 km?), with low population density (under 35-50 people/km2)

4. Disease, Demography and Institutional Development Motivation | Data | Method | Results • The West Africa Onchocerciasis Control Program (OCP) • Step 1: Spray larvacide in rivers, to stop blackfly reproduction In the late 1950s, French researchers mapped the blackfly larva and showed that killing them would stop transmission From 1975, World Bank and other donors paid for helicopters to spray larvacide over rivers in Oncho areas across Africa Source: WHO (n.d.), African Programme for Onchocerciasis Control. http://www.who.int/apoc/onchocerciasis/control/en. Source: IRD (2010), Onchocerciasis. http://en.ird.fr/all-the-current-events/news/onchocerciasis-an-exemplary-control-programme.

5. Disease, Demography and Institutional Development Motivation | Data | Method | Results • The West Africa Onchocerciasis Control Program (OCP) • Step 1: Spray larvacide in rivers, to stop blackfly reproduction • Step 2: Distribute deworming meds, to kill microfilaria • In the 1980s, a veterinary deworming drug called ivermectin (Mectizan) was found to control Onchocerciasis symptoms in people • Since 1987, Merck has given the drug freely for distribution by aid agencies in affected areas Source: Merck (2012), www.mectizan.org

6. Disease, Demography and Institutional Development Motivation | Data | Method | Results • The West Africa Onchocerciasis Control Program (OCP) • spraying stopped in 1989, after 14 years (no new transmission) • ivermectin distribution stopped in 2002 (and continues elsewhere)

7. Disease, Demography and Institutional Development Motivation | Data | Method | Results OCP Results in West Africa How did people respond? Estimated Onchocerciasis Prevalence in West Africa Prior to control (1974) After control (2002) Burkina Faso Burkina Faso Source: WHO, Onchocerciasis Control Programme (www.who.int/apoc/onchocerciasis/ocp).

8. Disease, Demography and Institutional Development Motivation | Data | Method | Results How did people respond? • Demographic change • Migration and settlement in previously Oncho-affected areas • Private investment in farm and nonfarm activity • Institutional development • Land rights over cropland, grazing and forest areas • Public and private investment in local amenities • Here we focus on land rights…

9. Disease, Demography and Institutional Development Motivation| Data | Method | Results Villages’ Location, Population Growth 1975-85 and Oncho Status

10. Disease, Demography and Institutional Development Motivation| Data | Method | Results Survey Method • From the Burkina Faso Office of Agricultural Statistics • Sample of 747 villages, nationally representative in 2010 • Drop 118 subject to central planning (AVV) • Drop 14 missing from census data • We use 615 villages, representing non-AVV areas • We asked focus groups of elders to recall: • the status of the village’s land rights and distance to various public amenities, • now and in the past, • recording the year of each change. • Responses permit construction of 3-step time series • we use only the situation in 1975, 1985, 1996 and 2006 • some villages did not report some data, so samples vary

11. Disease, Demography and Institutional Development Motivation| Data | Method | Results Questionnaire design: land rights

12. Disease, Demography and Institutional Development Motivation| Data | Method | Results Questionnaire design: distance to services

13. Disease, Demography and Institutional Development Motivation| Data | Method | Results Our measures of property rights • Are (or were) land rights assigned to individuals? • Do (or did) cropland transactions occur? • Is (or was) pasture access regulated? • Is (or was) forest access regulated? • Do (or did) cropland transactions require a permit?

14. Disease, Demography and Institutional Development Motivation| Data | Method | Results Our measures of public amenities • Road • Bus Stop • Bank • Electricity • Telephone • Public Market • Livestock Market • Private Shop • Water Well • Borehole • Dam • Primary School • Secondary Sch. • Health Clinic • Church • Mosque • Temple Distance (km) from village to nearest:

15. Disease, Demography and Institutional Development Motivation| Data | Method | Results Descriptive statistics: property rights in census years Source: Table 1: Mean, standard deviation, and sample size for all variables in each year

16. Disease, Demography and Institutional Development Motivation| Data | Method | Results Descriptive statistics: distance to amenities Source: Table 1: Mean, standard deviation, and sample size for all variables in each year

17. Disease, Demography and Institutional Development Motivation| Data | Method | Results Descriptive statistics: distance to amenities (cont’d) Source: Table 1: Mean, standard deviation, and sample size for all variables in each year

18. Disease, Demography and Institutional Development Motivation| Data | Method | Results Do treated and control villages differ at baseline? Population and land rights Table 2: Mean, standard deviation and difference between treated and control areas in 1975

19. Disease, Demography and Institutional Development Motivation| Data | Method | Results Do treated and control villages differ at baseline? Transport and infrastructure Table 2: Mean, standard deviation and difference between treated and control areas in 1975

20. Disease, Demography and Institutional Development Motivation| Data | Method | Results Do treated and control villages differ at baseline? Markets and water sources Table 2: Mean, standard deviation and difference between treated and control areas in 1975

21. Disease, Demography and Institutional Development Motivation| Data | Method | Results Do treated and control villages differ at baseline? Schooling, health and religious services Table 2: Mean, standard deviation and difference between treated and control areas in 1975

22. Disease, Demography and Institutional Development Motivation| Data | Method | Results Regression specification Our regressions are: Where: Pop is population of the village, I is the institutional outcome of interest for the village,  are fixed effects for all villages, and β11 and β21 are the diff.-in-diff. estimator of treatment effects In Equation (3), Pop is endogenous so we instrument it with the predicted value from equation (1), using 2SLS.

23. Disease, Demography and Institutional Development Motivation| Data | Method | Results OLS estimates of equation (1) Table 3: OLS results for village population on Onchocerciasis treatment status and time

24. Disease, Demography and Institutional Development Motivation| Data | Method | Results OLS estimates of equation (2) Main results for land rights only Table 4: OLS results for property rights on Onchocerciasis treatment status and time

25. Disease, Demography and Institutional Development Motivation| Data | Method | Results OLS estimates of equation (3) Main results for land rights only Table 5: OLS results for property rights on village population and time

26. Disease, Demography and Institutional Development Motivation| Data | Method | Results 2SLS estimates of equation (3) Main results for land rights only Table 6: 2SLS results for property rights on predicted village population and time

27. Disease, Demography and Institutional Development Motivation| Data | Method | Results Conclusions • Oncho-affected villages had been smaller, with similar or less market-oriented institutions before 1975 • After OCP treatment (after 1975-1985) treated villages: • expanded population by 25-33% faster than other villages, • became 4-5% more likely to assign property rights to individuals, and 4-5% less likely to require permit before transactions • some of that may have been due to population growth alone, in addition to increased productivity for those already there • treated villages also came to be more closely served by rural amenities, especially public markets and also primary schooling and telephone service (results not shown in slides) • Methodologically, villagers’ recall data can work for recent history