Are Land Policies Consistent with Agricultural Productivity and Poverty Reduction Objectives? T.S. Jayne, Jordan Chamberlin, Milu Muyanga, Munguzwe Hichaambwa World Bank Land and Poverty Conference Washington, DC, March 24, 2015 MICHIGAN STATE U N I V E R S I T Y

Botswana Burkina Faso Namibia Senegal Cameroon Congo, Rep. Cote d'Ivoire Guinea Guinea-Bissau Madagascar Malawi Mozambique Zambia Ethiopia Ghana Mali Nigeria Rwanda South Africa Tanzania Togo Avg annual agricultural growth Avg annual change in rural poverty Growth without poverty reduction Growth with poverty reduction.04.06

o Growth with poverty reduction o Growth without poverty reduction Country ag. growth pov. growth start year end yearyears Botswana-1.0%-5.3% Burkina Faso-1.2%-1.9% Cameroon2.9%0.4% Congo, Rep.1.0% Cote d'Ivoire1.1%1.2% Ethiopia2.0%-1.6% Ghana1.0%-1.0% Guinea0.9%0.3% Guinea-Bissau1.3%0.4% Kenya Madagascar0.6%0.2% Malawi2.7%0.1% Mali2.1%-1.2% Mozambique0.3%0.2% Namibia-0.4%-2.3% Nigeria0.6%-0.5% Rwanda3.2%-2.1% Senegal-2.6%-0.2% South Africa2.3%-1.4% Tanzania2.0%-0.6% Togo1.7%-0.2% Zambia2.3%0.0% Ag. growth = avg. annual change in value added per capita (agriculturally active population) Source: FAOStat Pov. growth = avg. annual change in rural poverty headcount, using national poverty lines Source: WDI

Purpose of study: To explore the role of land inequality in affecting how economic growth occurs To explore how land inequality affects labor productivity in agriculture and non-farm sectors

Purpose of study: To explore the role of land inequality in affecting how economic growth occurs (in areas that are still primarily agrarian) To explore how land inequality affects labor productivity in agriculture and non-farm sectors Main hypothesis: the initial distribution of assets affect the rate of economic growth it also affects the poverty-reducing effects of the growth that does occur

Theory Why should land concentration affect the link between ag growth and poverty reduction? Concept of “multiplier effects”

Applied evidence Ravallion and Datt (2002) the initial percentage of landless households significantly affected the elasticity of poverty to non-farm output in India. Vollrath (2007) Rate of agricultural productivity growth inversely related to the gini coefficient of landholdings Gugerty and Timmer (1999) (n=69 countries); in countries with an initial “good” distribution of assets, both agricultural and non-agricultural growth benefitted the poorest households. In countries with a “bad” distribution of assets, economic growth was skewed toward wealthier households

GINI coefficients in farm landholding 8 PeriodMovement in Gini coefficient: Ghana (cult. area)1992   0.70 Kenya (cult. area)1994   0.55 Zambia (landholding)2001   0.49 Source: Jayne et al (JIA)

Methods Dependent variables: (household-level) agricultural output per family adult labor time on farm (15-64 yrs) non-farm output per family adult labor time in non-farm activities total household income per family adult labor

Methods Estimated reduced form models of labor productivity Particular interest in the coefficient of land inequality measures at district- level Gini coefficient Measure of skewness Gugerty and Timmer’s measure Y it = f ( X it, C it, LandIneq jt-1 ) + e it Pooled OLS with Mundlak-Chamberlin device / fixed effects, applied to panel data

Data Nationwide panel data sets: Kenya (1997, 2000, 2004, 2007, 2010) (n=1,169) Tanzania (2009, 2011, 2013) (n=2,123) Zambia (2001, 2004, 2008) (n=3,398)

Tanzania

Magnitude of effect on labor productivity, Kenya LAND INEQUALITYEvaluated at GINI10 th pct of gini90 th pct of gini% difference log: hh farm labor productivity log: hh non-farm income per adult

Kenya results: w/ gini*asset wealth interaction terms

% change in household income per adult (with change in land gini from 25 th to 75 th percentile), Kenya

Summary 1.Landholding distribution influences both the rate and nature of household income growth – in both farm and non-farm sectors All other factors equal, households in districts at the 10 th percentile of farmland inequality (relatively low level of inequality) have 19 to 50% higher farm incomes 28 to 90% higher non-farm incomes significantly higher total incomes per resident adult member than households in districts at the 90 th percentile of farmland inequality (high inequality) Large majority of alternate specifications are highly statistically significant When switching from lagged measures of land concentration to contemporaneous measures, the effect of land inequality becomes more negative and statistically significant 2.Effects of land concentration are most adverse on the rural poor

Policy Questions: Farm structure in many African countries is changing rapidly becoming more concentrated should governments want to influence this?

GINI coefficients in landholding 21 PeriodMovement in Gini coefficient: Ghana (cult. area)1992   0.70 Kenya (cult. area)1994   0.55 Zambia (landholding)2001   0.49 Source: Jayne et al (JIA)

Policy questions: 1.Farm structure in many African countries is becoming more concentrated – should governments want to influence this? 2.Is rising land inequality contributing to concentration of marketed farm output? Can agric development still be small-farm led? 3.Implications for poverty reduction strategies? 4.Implications for structural transformation processes?

23 T.S. Jayne: Jordan Chamberlin: Milu Muyanga: M. Hichaambwa: