Off-farm Income and Smallholder Commercialization: Evidence from Ethiopian Rural Household Panel Data By Tesfaye B. Woldeyohanes

Content General Background Research problem objectives Hypothesis Methodology Results 2

General Background Agricultural sector is essential for overall economic transformation of low income countries (World Bank 2007) Transforming the sector from subsistence to more marketed oriented production system i.e smallholder commercialization Smallholder commercialization is not only supplying surplus product to market (Von Braun et.al. 1994; Pingali and Rosegrant 1995) It looks at both the output and input side of production 3 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Smallholder commercialization- concepts On the output side – could be possible with cash crop or staple food crops Input side – taded and owned inputs are valued at market price. It is a process which passes through subsistance, semi- commercial and fully commercial phases (Pingali and Rosegrant 1995) So, smallholder commercialization passes through these phases and may not imply immedaite move on to production of high value cash crops. 4 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Smallholder commercialization- concepts Production of marketable surplus of staple food crops over what is required for household consumption. smallholder farmers are constrained by a numerous factors to participate in exchange economy and materialize its potential welfare gains. 5 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

In Ehiopia, smallholder farmers produce 90% of total agricultural production on average land holding of less than 1 ha per HH (CSA 2011) They are highly subsistance oriented Policy intervention – to promote smallholder commercialization over the past two decades Information dearth – if there is induced behavioral change in terms of market participation and factors that determine degree of commercialization 6 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Previous studies are  regional (Woldehanna 2000)  focus on few crops (Gebreselassie and Sharp 2007)  or followed project intervention (Geberemedhin and Jaleta 2010)  relied on cross section analysis Is off-farm income help commercialization or slow down the process? Results of this study will help to better understand the situation, explore policy options and rationally address it 7 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Objectives To assess trends of output market participation and degree of commercialization of smallholder farmers To identify factors that explain the difference in degree of commercialization among households, with specific attention on the role of off-farm income. 8 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Hypothesis The main interest is to test if off-farm income enhances smallholder commercialization in Ethiopia Off-farm income can have either negative or positive impact on household degree of commercializtion 9 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Data and Emperical Models Data ERHS data is a unique longitudinal data conducted in seven rounds from 1989 to 2009 Farming systems were considered as an important stratification basis in selecting villages. Based on main agro-ecological zone and sub-zones 1-3 villages were selcted per strata. About 1477 randomly selected households were included in 1994 round and re-interviewed in 1995, 1997, 1999, 2004 and The households are from 15 rural villages of 4 major regions. 10 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Data and Emperical Models In this study, I use three waves of data (1997, 1999 and 2004). I have a balanced panel data observations for 1184 farm households Data on input and output price were collected at the community level during each survey year 2004 price is used as constant price for all rounds 11 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Emperical Model specification 12 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Emperical Model specification 13 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Table 1:Descriptive summary of variables used in estimations (panel) 14 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Model selection Modeling smallholder market participation can be a bit tricky because not all farm households sell their crop in market Excluding non-participation (zero values of crop sold and HCI) from the sample may lead to sample selection bias and biased regression parameters. 32% of sample households did not participate in crop market as seller, so it is not appropriate to estimate the linear model specified in equation (1) In cross section contex, most often Tobit model, Sample selection model or its variant like “Two tier” or “double Hurdle” are used. 15 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Model selection Sample selection and double hurdle model include two steps reflecting the dual decision making process: Decision 1: Whether to participate in market Decision 2: How much to sell (volume of transaction) Tobit model assumes the same set of variables and parameters determine both the probability of market participation and the volume of transaction zero values associated with non-participation are outcome of rational choice i.e. corner solution Somewhat restrictive assumptions 16 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Model selection 17 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Model selection 18 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Model selection In this study, Random Effect tobit model is estimated because the time series is short and we have substantial time invariant regressors in our model. However, RET makes strong assumptions like the individual effect is normally distributed and uncorrelated with regressors. FE could relax this assumption, however it is impossible to estimate the parameters independent of individual effects in panel data context. 19 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Model selection The other option is to estimate Pooled tobit model, which relaxes the strict exogeneity of regressors in RET model. This estimation approach also produces consistent (though inefficient) estimate as noted in Maddala (1987) The estimation is done by maximum likelihood estimation technique The conditional and unconditional marginal effect on actual volume transacted and HCI per unit change in the explanatory variables is calculated. 20 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Preliminary Results Table 2: Summary descriptive statistics for HH characteristics and market participation by year (n=1184) 21 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement

Preliminary Results Table 3: Summary descriptive statistics - HH and HH head characteristics by year (n=1184) 22 General Background Data and Emperical Models Objectves Hypothesis Results Problem statement Variables meanSDmeanSDMeanSD Age of household head Male household head Literate household head Family size (no) Available family labor Farm land owned(ha) Equine owned(no) Livestock owned(TLU) Distance to the nearest market (km) Involvement in extension program

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