By Tesfaye B. Woldeyohanes

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

2. Content • General Background • Research problem • objectives • Hypothesis • Methodology • Results

3. General Background 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 • Problem statement Objectves Hypothesis Data and Emperical Models Results

4. Smallholder commercialization- concepts General Background • 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. • Problem statement Objectves Hypothesis Data and Emperical Models Results

5. Smallholder commercialization- concepts General Background • 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. Problem statement Objectves Hypothesis Data and Emperical Models Results

6. Problem statement General Background • 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 Problem statement Objectves Hypothesis Data and Emperical Models Results

7. General Background • 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 Problem statement Objectves Hypothesis Data and Emperical Models Results

8. Objectives General Background • 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. Problem statement Objectves Hypothesis Data and Emperical Models Results

9. Hypothesis General Background • 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 Problem statement Objectves Hypothesis Data and Emperical Models Results

10. Data and Emperical Models General Background 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 2009. • The households are from 15 rural villages of 4 major regions. Problem statement Objectves Hypothesis Data and Emperical Models Results

11. Data and Emperical Models General Background • 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 Problem statement Objectves Hypothesis Data and Emperical Models Results

12. Emperical Model specification General Background • The underlying emperical model is specified as; (1) Where - is the household i HCI or value of crop sold to market in period t • Household commercialization Index (HCI) by Govereh et al (1999) and Strasberg et al (1999) is the most commonly used indicator of degree of commercialization. Problem statement Objectves Hypothesis Data and Emperical Models Results

13. Emperical Model specification General Background (1) - is the household i off-farm income earned in period t - is the household i total value of crop produced in period t - is a vector of household characteristics and resource endowmentsperiod t - is a vector of household and village level market access variables - is a regional dummy to capture the difference in terms of agro-ecology between regions ,, and are the corresponding parameters to be estimated • The model has two error components - time invariant ind. household heterogeneity, assumed to be normally distributed with mean zero and variance - idiosyncratic error term Problem statement Objectves Hypothesis Data and Emperical Models Results

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

15. Model selection General Background • 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. Problem statement Objectves Hypothesis Data and Emperical Models Results

16. Model selection General Background • 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) • Tobitmodel 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 Problem statement Objectves Hypothesis Data and Emperical Models Results

17. Model selection General Background • In this study, we assume variables that determine the household’s decision to participate in output market are also the ones responsible to determine the volume of transaction. So, the tobit model is specified as follows; (2) (3) (4) Problem statement Objectves Hypothesis Data and Emperical Models Results

18. Model selection General Background Where : is the latent variable which is the desired (or potential) market participation by households is the actual observed market participation ) and ) • My objective is to obtain consistent estimate of the parameter . • Unlike cross section data context, panel data tobit model introduces individual effect, that complicates estimation of parameters of interest Problem statement Objectves Hypothesis Data and Emperical Models Results

19. Model selection General Background • 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. Problem statement Objectves Hypothesis Data and Emperical Models Results

20. Model selection General Background • 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. Problem statement Objectves Hypothesis Data and Emperical Models Results

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

22. Preliminary Results General Background Table 3: Summary descriptive statistics - HH and HH head characteristics by year (n=1184) Problem statement Objectves Hypothesis Data and Emperical Models Results

23. Thank you for your Attention!