How might deep determinants matter today?

Disease Control, Demographic Change and Institutional Development in Africa

Margaret S. McMillanDepartment of Economics, Tufts University

http://margaretsmcmillan.com/

William A. MastersDepartment of Food and Nutrition Policy, Tufts University

http://sites.tufts.edu/willmasters

Harounan KaziangaDepartment of Economics, Oklahoma State University

http://www.hkazianga.org/

NEUDC 2012

Revised version of NBER Working Paper No. 17718, entitled “Rural Demography, Public Services and Land Rights in Africa:

A Village-Level Analysis in Burkina Faso”

• 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

Disease, Demography and Institutional DevelopmentMotivation | 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)



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: IRD (2010), Onchocerciasis. http://en.ird.fr/all-the-current-events/news/onchocerciasis-an-exemplary-control-programme.

Source: WHO (n.d.), African Programme for Onchocerciasis Control. http://www.who.int/apoc/onchocerciasis/control/en.

http://en.ird.fr/all-the-current-events/news/onchocerciasis-an-exemplary-control-programme

http://en.ird.fr/all-the-current-events/news/onchocerciasis-an-exemplary-control-programme

http://www.who.int/apoc/onchocerciasis/control/en


The West Africa Onchocerciasis Control Program (OCP)Step 1: Spray larvacide in rivers, to stop blackfly reproductionStep 2: Distribute deworming meds, to kill microfilaria

Source: Merck (2012), www.mectizan.org

• 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

http://www.mectizan.org/


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)

http://www.cartercenter.org/news/multimedia/HealthPrograms/PreservingVisionforFutureGenerations.html


OCP Results in West Africa

Burkina FasoBurkina Faso

Estimated Onchocerciasis Prevalence in West AfricaPrior to control (1974) After control (2002)

Source: WHO, Onchocerciasis Control Programme (www.who.int/apoc/onchocerciasis/ocp).

How did people respond?

http://www.who.int/apoc/onchocerciasis/ocp


• 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…

How did people respond?


Villages’ Location, Population Growth 1975-85 and Oncho Status

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


Questionnaire design: land rights


N° Questions Réponse

VIII.1 Type de droit appliquée pour les terres de culture(si la réponse est non, mettre des croix à année de début d’application)

Type de droit appliquée (1=Oui ; 0=Non)

Année de début d’application

VIII.1.1 Propriété individuelle |____| |____|____|____|____|

VIII.1.2 Propriété collective-familiale |____| |____|____|____|____|

VIII.1.3 Propriété collective-communautaire |____| |____|____|____|____|VIII.2 Location, vente et prêts de terres de culture

(si la réponse est non, mettre des croix à année de début d’application)

Possibilité de transaction(1=Oui ; 0=Non)

Année de début d’application

VIII.2.1 Est-ce que la terre peut-être louée ? |____| |____|____|____|____|

VIII.2.2 Est-ce que la terre peut-être vendue ? |____| |____|____|____|____|

VIII.2.3 Est-ce que la terre peut-être prêtée ? |____| |____|____|____|____|

Questionnaire design: distance to services


N° Questions RéponseDistance (en km) Année d’établissement

V.1 Distance entre le village et l’administration centrale (pour les registres des naissances)

V.1.1 La situation actuelle |____|____|____| |____|____|____|____|

V.1.2 La situation précédente |____|____|____| |____|____|____|____|

V.1.3 La situation antécédente |____|____|____| |____|____|____|____|

V.2 Distance entre le village et la route praticable par car ou camion toute l’année

V.2.1 La situation actuelle |____|____|____| |____|____|____|____|

V.2.2 La situation précédente |____|____|____| |____|____|____|____|

V.2.3 La situation antécédente |____|____|____| |____|____|____|____|

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?


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:

Descriptive statistics: property rights in census years


Village population

(from census)

Land rights assigned to individuals

Land transactions

occurred

Pasture access is regulated

Forest access is regulated

Land transactions

require permit

Year = 1975 1,266 0.378 0.846 0.228 0.075 0.335

(1,248) (0.485) (0.361) (0.420) (0.263) (0.473)

Year = 1985 1,637 0.400 0.862 0.293 0.096 0.348

(1,561) (0.490) (0.346) (0.456) (0.294) (0.477)

Year = 1996 1,659 0.409 0.868 0.350 0.135 0.352

(1,413) (0.492) (0.339) (0.477) (0.342) (0.478)

Year = 2006 1,414 0.435 0.889 0.425 0.173 0.371

(2,597) (0.496) (0.314) (0.495) (0.378) (0.484) Observations 2,307 2,307 2,307 2,307 2,307 2,307 Villages 615 615 615 615 615 615 Source:Table 1: Mean, standard deviation, and sample size for all variables in each year

Descriptive statistics: distance to amenities


Transport . Services . Markets . Road Bus Stop Bank Electricity Telephone Public Livestock Private Year = 1975 3.79 17.60 49.03 57.17 40.84 7.85 20.67 5.63 (7.21) (22.86) (47.49) (43.69) (35.48) (16.80) (30.26) (10.08) Year = 1985 4.34 13.93 39.29 51.12 37.11 5.73 22.46 5.18 (13.92) (18.55) (35.52) (36.07) (31.71) (8.10) (29.82) (8.90) Year = 1996 4.91 12.99 35.12 46.91 28.28 5.28 20.55 4.68 (14.21) (17.43) (30.91) (33.86) (24.64) (8.12) (26.01) (9.02) Year = 2006 4.32 10.64 25.81 36.73 21.34 4.85 17.07 2.09 (13.44) (15.82) (24.21) (26.39) (19.67) (7.52) (20.57) (5.25) Observations 1,433 1,719 1,084 1,227 1,589 2,216 1,042 1,228 Villages 449 518 559 462 557 601 339 549

Source:Table 1: Mean, standard deviation, and sample size for all variables in each year

Descriptive statistics: distance to amenities (cont’d)


Water . Schooling and Health . Religious Services . Well Borehole Dam Primary Secondary Clinic Church Mosque Temple Year = 1975 1.11 1.52 18.59 10.73 51.74 16.30 8.95 5.46 9.48 (4.69) (4.95) (21.76) (12.84) (39.86) (17.33) (13.55) (11.40) (12.14) Year = 1985 0.74 0.63 18.12 6.94 40.14 12.70 4.88 3.92 5.09 (3.42) (2.90) (20.10) (11.74) (33.60) (13.83) (9.73) (7.30) (8.85) Year = 1996 0.89 0.57 16.91 3.73 26.07 8.79 4.97 3.88 5.09 (3.33) (2.69) (19.02) (8.46) (24.02) (10.56) (9.84) (7.29) (8.95) Year = 2006 0.30 0.33 15.41 1.14 17.32 5.91 3.55 2.63 3.01 (1.30) (2.07) (18.15) (4.43) (16.66) (6.76) (8.65) (5.73) (6.42) Observations 1,041 1,062 753 2,025 1,681 2,055 1,694 1,777 1,410 Villages 322 414 249 573 528 574 471 505 411

Source:Table 1: Mean, standard deviation, and sample size for all variables in each year

Do treated and control villages differ at baseline?


Treated Control Difference Village population 1130.703 1468.08 -337.378***

[70.242] [90.799] [114.797]

Indicators of agricultural land-use rights

Land rights assigned to individuals 0.328 0.452 -0.125***

[0.027] [0.035] [0.045]

Land transactions occurred 0.834 0.864 -0.030

[0.022] [0.024] [0.033]

Pasture access is regulated 0.206 0.261 -0.055

[0.024] [0.031] [0.039]

Forest access is regulated 0.084 0.06 0.024

[0.016] [0.017] [0.023]

Land transactions require permit 0.389 0.256 0.132***

[0.028] [0.031] [0.042]

Population and land rights

Table 2: Mean, standard deviation and difference between treated and control areas in 1975



Distance from village to nearest public amenity (km)

Road 4.196 3.192 1.004

[0.618] [0.639] [0.889]

Bus Stop 18.354 16.408 1.946

[1.627] [2.160] [2.704]

Bank 66.361 31.200 35.161***

[9.633] [3.998] [10.429]

Electricity 73.061 39.800 33.261***

[4.903] [4.133] [6.412]

Telephone 45.46 32.862 12.598***

[3.165] [2.934] [4.316]


Transport and infrastructure





Road 4.196 3.192 1.004


Markets and water sources

Distance from village to nearest public amenity (km) Public Market 9.092 5.934 3.158**

[1.194] [0.713] [1.390]

Livestock Market 25.140 15.013 10.127**

[3.584] [2.253] [4.233]

Private Shop 6.231 4.750 1.481

[1.470] [1.011] [1.784]

Water Well 1.658 0.429 1.230*

[0.694] [0.143] [0.709]

Borehole 0.833 2.154 -1.321

[0.833] [1.764] [1.951]

Dam 24.96 8.625 16.335***

[3.490] [1.823] [3.937]

Primary School 11.818 9.068 2.750**





Road 4.196 3.192 1.004


Schooling, health and religious services

[3.490] [1.823] [3.937]

Primary School 11.818 9.068 2.750**

[0.820] [1.112] [1.382]

Secondary Sch. 56.294 44.958 11.335**

[3.221] [4.190] [5.284]

Health Clinic 16.603 15.828 0.775

[1.086] [1.440] [1.803]

Church 9.692 8.000 1.692

[1.052] [1.146] [1.556]

Mosque 6.236 4.200 2.036*

[1.006] [0.657] [1.201]

Temple 10.189 8.580 1.610

[1.263] [1.119] [1.687] Table 2: Mean, standard deviation and difference between treated

and control areas in 1975

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.


Regression specification

)1()()( 1112111 jtjttjjt TimeTimeTreatPop

)2()()( 2222212 kjtkjtktjkkkjt TimeTimeTreatI

)3()()( 3332313 kjtkjtkjtkkkjt TimePopI


OLS estimates of equation (1)Dependent variable: Post-75 Post-85 Annual Data log of village population (1) (2) (3)

Treated X Post-75 (1985-2006) 0.33***Treated X Post-85 (1996-2006) 0.25***Treated X 1985 0.24***Treated X 1996 0.39***Treated X 2006 0.39***Post-75 (1985-2006) 0.09Post-85 (1996-2006) -0.09*Year = 1985 0.21***Year = 1996 0.17**Year = 2006 -0.11Constant 6.68*** 6.88*** 6.68***R-squared 0.47 0.45 0.48

Table 3: OLS results for village population on Onchocerciasis treatment status and time


OLS estimates of equation (2)

Dependent variable:


Land transactions occurred



Land transactions require permit

(1) (2) (3) (4) (5)Panel A: Post-1975 Treated X Post-75 (1985-2006) 0.02 0.04*** 0.02 0.03* -0.04***Time = 1985-2006 0.02** 0.00 0.11*** 0.04*** 0.04***Constant 0.39*** 0.84*** 0.23*** 0.08*** 0.34***

R-squared 0.96 0.92 0.83 0.83 0.96Panel B: Post-1985 Treated X Post-85 (1996-2006) 0.02** 0.04*** 0.05*** 0.02* -0.05***Time = 1996-2006 0.02*** 0.00* 0.09*** 0.05*** 0.04***Constant 0.39*** 0.85*** 0.26*** 0.09*** 0.34***

R-squared 0.96 0.93 0.84 0.84 0.96

Main results for land rights only

Table 4: OLS results for property rights on Onchocerciasis treatment status and time


OLS estimates of equation (3)

Dependent variable:






(1) (2) (3) (4) (5)Panel A: Post-1975 Population (log) -0.00 0.02*** -0.01 -0.00 0.00Time = 1985-2006 0.03*** 0.03*** 0.13*** 0.05*** 0.01**Constant 0.39*** 0.74*** 0.29*** 0.10** 0.34***

R-squared 0.96 0.93 0.83 0.83 0.95Panel B: Post-1985 Population (log) 0.00 0.02*** -0.00 0.00 0.00Time = 1996-2006 0.03*** 0.03*** 0.12*** 0.06*** 0.02***Constant 0.38*** 0.74*** 0.27*** 0.09** 0.34***

R-squared 0.96 0.93 0.84 0.84 0.96Panel C: Annual Data (reported in paper - not shown here)


Table 5: OLS results for property rights on village population and time


2SLS estimates of equation (3)

Dependent variable:






(1) (2) (3) (4) (5)Panel A: Post-1975

Population (log) 0.05 0.13*** 0.06 0.08* -0.13**Time = 1985-2006 0.01 -0.01 0.11*** 0.03* 0.05***

Panel B: Post-1985 Population (log) 0.08* 0.15*** 0.19** 0.09 -0.19***Time = 1996-2006 0.03*** 0.02*** 0.11*** 0.06*** 0.03***

Panel C: Annual Data (reported in paper - not shown here)


Table 6: 2SLS results for property rights on predicted village population and time

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

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How might deep determinants matter today?