Effect of Off-farm Income on Smallholder Commercialization: Panel Evidence from Rural Households in Ethiopia

Transcription

1 Effect of Off-farm Income on Smallholder Commercalzaton: Panel Evdence from Rural Households n Ethopa Tesfaye Berhanu Woldeyohanes 1, Thomas Heckele 1 and Yves Surry 2 1 Insttute for Food and Resource Economcs, Unversty of Bonn, Germany 2 Swedsh Unversty of Agrcultural Scence, Department of Economcs Abstract. Ths paper nvestgates how off-farm ncome affects crop output market partcpaton decson and marketed surplus of smallholder farmers n Ethopa. A double-hurdle model s estmated usng three waves of panel data from Ethopan Rural Household Survey (ERHS). The artcle controls for unobserved heterogenety usng correlated random effect procedure and potental endogenety of off-farm ncome usng a control functon approach. Results show that off-farm ncome has no sgnfcant nfluence on household output market partcpaton. But condtonal on postve market partcpaton, each addtonal earnng from off-farm work has negatve and statstcally sgnfcant effect on marketed surplus. Ths ndcates farmers use earnngs from off-farm source rather for consumpton purpose than as a source of lqudty to nvest n agrcultural producton and ncrease marketable surplus. Our result has polcy mplcatons that expandng hgher earnng rural enterprses through capacty buldng and human captal nvestment s vtal. Ths could mprove the returns to labor for off-farm work partcpatng land-poor households n the process of smallholder agrcultural commercalzaton.

2 1. Introducton Commercalzaton of smallholder agrculture s part of agrcultural transformaton n whch a gven farm household shfts ts producton from a hghly subsstence-orented producton towards more commercalzed producton targetng market for ts nput demand and output supply (Jaleta et al., 2009; Pngal and Rosegrant, 1995). It s consdered as an ndspensable pathway towards economc growth and development for most low ncome countres relyng on the agrcultural sector (von Braun, 1995; Pngal and Rosegrant, 1995; Tmmer, 1997). Accordng to Pngal (1997), subsstence producton may not be vable to acheve sustanable household food securty and welfare n the long run. The Ethopan agrcultural sector s stll domnated by subsstence-orented smallholders characterzed by low levels of productvty. In the last two decades, the government has adopted an agrcultural-based development strategy for natonal economc transformaton n whch commercalzng smallholder agrculture was the focal pont (MoFED, 2003; MOFED, 2010). More emphass was gven to ntensfcaton of smallholder agrculture through the use of new technologes, nfrastructure development and better access to servce nsttutons (Gebremedhn et al., 2006; MoFED, 2003; MOFED, 2010). Ths s because ncreasng productvty and producton of marketable surplus of staple food crops to lnk farmers up wth output market s the most common form of agrcultural commercalzaton at the early stage of commercal transformaton (Gebre-ab, 2006; Pngal and Rosegrant, 1995). However, smallholder farmers are often constraned by lack of lqudty to fnance the nputs typcally needed to ncrease productvty, partcularly when agrcultural credt s lackng or not easly accessble to poor (Carter et al., 2004). Ethopa s not an excepton: although the government provdes some credt servces through dfferent mcrofnance nsttutons, t s not easly accessble to all farmers. There were strands of lterature that shows off-farm ncome can be a crucal means to overcome workng captal constrants to nvest n agrculture partcularly f credt markets are thn or mssng whereas off-farm optons can be accessed easly (Barrett et al., 2001; Hernandez et al., 2010; Osen and Wnters, 2009; Reardon et al., 1994; Woldehanna, 2000). Osen and Wnters ( 2009) found a postve effect of off-farm ncome on farm nvestment by compensatng mssng or mperfect credt markets (Osen and Wnters, 2009). Even though agrculture s the man source 2

3 of lvelhoods n rural Ethopa, households also engage n varous forms of off-farm employment drven by dfferent push and pull factors (van den Berg and Kumb G.E., 2006; Rjkers et al., 2008; Woldehanna and Oskam, 2001). There s, however, far less lterature on how off-farm work partcpaton and ncome from ths source nteracts wth smallholder commercalzaton at household level. Some theoretcal reasonng suggests that off-farm ncome could have both postve and negatve effects on smallholder commercalzaton. For nstance, accordng to Woldehanna (2000) offfarm ncome can enhance smallholder commercalzaton f used as a lqudty source for farm nvestment that wll ncrease productvty and producton of marketable surplus. Ths n turn may ncrease the proporton of crops sold by smallholder farmers. Ths s more lkely f household engages n hgher earnng wage or self-employment actvtes and savng rate s hgher (Woldehanna, 2000; Woldehanna and Oskam, 2001). Off-farm ncome may also assst farmers n consumpton smoothng when there s producton and market related rsks followng agrcultural commercalzaton (Evans and Ngau, 1991; Holden et al., 2004; Reardon et al., 1994). Ths may help them to develop a wllngness to move from safety frst food croppng to rsky but hgh value croppng wth a buffer of cash from nonfarm actvtes (Reardon et al., 1994). In contrast to ths, off-farm ncome can have a negatve effect on smallholder commercalzaton f t leads to an ncrease household s demand for both agrcultural and non-agrcultural consumpton goods (Kan et al., 2006; Woldehanna, 2000). In ths case, farmers that have prevously used ncome from product sales to purchase non-agrcultural consumpton goods may replace ths wth cash ncome from off-farm employment and now consume what they produce and become self-suffcent. Hence, the marketed surplus mght be lower than what t would be otherwse. At the macro level, the lnkage between agrcultural commercalzaton and off-farm employment can be explaned through growth lnkages. That means advancement n agrcultural commercalzaton creates rural off-farm employment opportunty for the poor (Bnswanger and von Braun, 1991; von Braun, 1995). Although ths s very crucal for rural development, nformaton on the nature of nteracton that could exst at the household level s more benefcal for the desgn of pro-poor publc polces. Thus, ths study looks at factors affectng smallholder 3

4 farmers decson to partcpate n crop output market and how much they sell focusng on role of off-farm ncome. Ths paper makes two contrbutons to the exstng lterature on smallholder commercalzaton. We test emprcally the drecton of relatonshp between off-farm ncome and smallholder commercalzaton to provde nformaton that s relevant to current agrcultural polcy n Ethopa. Prevous studes on the determnants of smallholder commercalzaton consdered level of commercalzaton n ts statc form measurng level of output and nput market partcpaton at a gven pont n tme and reled on cross-sectonal data. However, smallholder commercalzaton could be seen as a dynamc process, as the decson to partcpate n the crop market and amount to sell could change due to changng crcumstances. In ths study we use three waves of household panel data from Ethopan Rural Household Survey (ERHS) to analyze determnants of smallholder commercalzaton controllng for unobservable ndvdual heterogenety. The other contrbuton of ths paper s applcaton of control functon approach to deal wth suspected endogenety n nonlnear panel models. In ths study, we thnk off-farm ncome could be correlated wth tme-varyng unobservables due to smultanety. We use the control functon approach to test and control for endogenety followng the procedure by Papke & Wooldrdge (2008) n fractonal response model and extend t to double-hurdle model. The rest of the paper structured as follows. The conceptual framework s presented n secton 2. Secton 3 presents the emprcal strategy followed by data presentaton n secton 4. Results and dscussons are presented n secton 5, whle secton 6 presents conclusons and polcy mplcatons. 2. Conceptual Framework We use the basc non-separable farm household model (Sngh et al., 1986) to drve household market supply. The basc assumpton of non-separable farm household model s that mperfect market condtons for product and factor markets make the producton and consumpton decsons of farm household non-separable (Sadoulet and de Janvry, 1995; Sngh et al., 1986). In ths case, not only the producton decson affects the consumpton decsons but also the consumpton decson affects the household producton and ultmately output market supply decsons. Ths study recognzes n the Ethopan context the assumpton of non-separablty s lkely to hold so 4

5 that households soco-demographc characterstcs wll affect ts desred level of output supply (de Janvry and Sadoulet, 2006). In addton to household demographc characterstcs, n ths settng household output supply decson s also affected by off-farm ncome. Gven these assumptons, households are assumed to maxmze utlty wth respect to consumpton ( c ), producton ( q ), nput use ( k ), sales ( s ) and purchase ( b ) of each good 1, 2,...N. The goods nclude all self-produced agrcultural commodtes, other market commodtes and lesure. Household produces agrcultural goods ( q ) usng land, labor and other varable nputs ( k ). The optmzaton problem s to maxmze utlty functon (1) subject to the lqudty (2), commodty balance (3), productontechnology (4) and non-negatvty (5) constrants. (1) max U ( c, z ) q, s, b, c, k u Subject to (2) p m ( s b ) p k W 0 (3) q k E c b s 0 (4) G( q1... qn, k1... qn; z q) 0 (5) q, s, b, c, k 0 ; for = 1,,N Where m p denotes the market prce for commodty, E s endowment of commodty, W s exogenous off-farm ncome whch could be earned or unearned and 5 zu and z q represents household demographc and producton characterstcs, respectvely. The cash budget constrant (2) states that households purchase has to be less than or equal to sales of any or all th crops plus lqudty form off-farm ncome. The commodty balance n the constrant equaton (3) states that total quanttes consumed, used for nput and suppled to market equals or less than total quantty produced, endowed and purchased from market of each commodty. The producton technology

6 constrant (4) corresponds to a well-behaved producton functon that relates all the nputs to outputs. Equaton (5) s the non-negatvty constrant. The above conceptual framework holds under the absence of transacton costs. However, recent emprcal work on smallholder market partcpaton and agrcultural supply response consdered transacton costs as one possble factor underlyng heterogeneous market access by smallholders (Alene et al., 2008; Barrett, 2008; Bellemare and Barrett, 2005; Holloway et al., 2001; de Janvry et al., 1991; Key et al., 2000). Hgh transacton costs may wden the prce margn between the effectve prce pad by buyers and effectve prce receved by sellers and ultmately determne households market postons (Barrett, 2008; de Janvry et al., 1991; Key et al., 2000; Sadoulet and de Janvry, 1995). Dfferences n transacton costs and access to assets and servces to mtgate ths transacton costs can explan why some farmers partcpate n market whle others become smply self-suffcent. Let us consder a gven household faces crop and household specfc transactons costs per unt c of quantty sold and bought, whch are equal to ( Z, A,G,W ). Ths nvolves both the proportonal and fxed transactons costs that may depend on vector household demographc characterstcs, Z, access to publc goods and servces, G, asset holdng, A, and lqudty from offfarm ncome, W. Then, the cash budget constrant accommodatng varable ( v ) 1 f and fxed ( ) transactons costs can be rewrtten as: m (6) [( ( v ) f m s p b ( p v ) f )] p k W 0 takes value 1 for the seller households and 0 for autarkc households for each good, whle takes value 1 for buyer households and 0 for autarkc. Ths constrant equaton suggests that when transactons costs are nvolved, the prce receved by the seller household s lower than the market prce p m by the amount of transacton costs. Whereas, for buyng households the market prce for each unt bought ncreases by the amount of transacton cost ncurred. Buyng and 1 v f Both varable ( ) and fxed ( ) transacton costs are a functon of household demographc characterstcs, Z, access to publc goods and servces, G, asset holdng, A, and lqudty from off-farm ncome, W. 6

7 sellng transacton costs are assumed to be dfferent for the same household and the same commodty. The frst order condtons of the maxmzaton problem of utlty functon wll yeld the reducedform output market supply (8), condtonal on the market partcpaton (7) (Goetz, 1992; Key et al., 2000) 2. Output market partcpaton decson: mp m f v (7) q ( p,,, z, z, W) s u q Output market supply decson: m v (8) q ( p, z, W) s q In equaton (7) mp q s s households dscrete market partcpaton decson whch s determned by comparson of the expected utlty form alternatve marketng regme (.e., partcpaton vs autarky). Ths wll be affected both by fxed and proportonal transactons costs; market prces; household demographc and producton characterstcs; commodty endowment and off-farm ncome. For those who partcpate n market, the volume traded ( q s ) n equaton (8) s unaffected by the fxed transacton cost. Once the fxed cost of partcpaton n the market s pad, farmers v can sell any volume of output wthout addtonal cost except varable transacton cost,, that vares proportonally wth traded volume. 3. Emprcal Model Prevous studes have modeled farmers market partcpaton as a two stage decson process. Ths s because farmers market partcpaton s assumed to nvolve two separate decsons: the decson to partcpate n market or not and the level of partcpaton. The two stage decson process n our conceptual model (7) and (8) s specfed along wth the error terms as gven n equatons (9) and (10). The dependent varable n (10) s the aggregate quantty of food crops 2 Optmal quantty consumed and nput demand equatons are also part of the frst order equatons, but here we nclude only the optmal quantty suppled that we are nterested n. 7

8 sold by household at tme t. The man reason to use aggregate quantty s to make the most out of data,.e. to use all the avalable nformaton n the data by ncludng the aggregate of all food crops produced and sold by households n that partcular perod. Aggregatng over multple crops makes t mpractcal to work wth physcal quanttes snce dfferent crops produced and sold cannot be aggregated drectly. Hence, we aggregate the weghted physcal quanttes of each crop sold usng vllage level prce as a weght. (9) * Mt wt X ' t c1 ut and (10) * St wt Z' t c2 vt and M t * 1f M t 0 0otherwse S t * * St f St 0and M 0 otherwse t 1 ; 1,2,..., N t 1,2,..., T Equaton (9) s a bnary choce whether to partcpate n market as seller, whereas equaton (10) represents the decson on the amount to sell condtonal on frst decson. The correspondng observed varable * M t s a latent varable. M t takes value 1 f household partcpate n crop output market as seller at tme t and 0 otherwse. The actual quantty of crop sold by household at tme t, s gven by S t. * S t s the latent varable ndcatng potental quantty supply to market. The key varable of nterest, off-farm ncome earned, s represented by w. The coeffcent estmates of and and ther correspondng standard errors provde the estmate of the effect of off-farm ncome on smallholders crop output market partcpaton decson and value of crop sold, respectvely. The vector of other explanatory varables that affect smallholders crop market partcpaton decson and value of crop sold are represented by represents the vector of correspondng parameters. t X and Z, respectvely; and t t We have two knds of error terms. The frst knd s tme nvarant unobserved heterogenety, represented by c 1 and c 2 n (9) and (10), respectvely. These are tme nvarant ndvdual characterstcs whch affect households crop output market partcpaton decson and volume traded. These factors mght nclude preferences, sol qualty, the farmer s management ablty and degree of rsk averson whch are commonly unobservable or dffcult to measure due to ts qualtatve nature. The second component of the error term s tme varyng unobserved shocks 8

9 affectng households market partcpaton decson and marketed supply represented by ut and v t, respectvely. The selecton of vector of explanatory varables X t and Z t s based on related prevous works (Alene et al., 2008; Gebremedhn et al., 2009) and lteratures on the determnants of smallholder commercalzaton (Von Braun, 1994; Jaleta et al., 2009; Sadoulet and de Janvry, 1995). Accordngly, value of crop producton; vector of households resource endowments; household and household head related demographc characterstcs; vector of varables related to proportonal and fxed transacton costs and regonal dummes for agro-ecologcal dfference between regons are ncluded (see table 1 below for full lsts of explanatory varables) Specfcaton Issues and Estmaton Prevous studes used ether Heckman s (1979) sample selecton (Alene et al., 2008; Bellemare and Barrett, 2006; Boughton et al., 2007; Ehu et al., 2003; Gebremedhn et al., 2009) or double hurdle and swtchng regresson models (Goetz, 1992; Omt, 2009) to estmate smallholder market partcpaton n (8) and (9). Some other consdered t as a sngle decson process and used a more restrctve Tobt model (Holloway et al., 2000). Selecton of an approprate econometrc model partly depends on how we treat zero observatons n quantty of crop suppled to market. Zero observatons may occur due to dfferent reasons. Even though households may be potental sellers they may not be able to supply to market constraned by dfferent factors such as fxed transacton costs. Households may prefer to be autarkc f shadow prce les between the mark-up sellng and buyng prce due to hgh transacton costs (Key et al., 2000). In such a case zero observaton s a corner soluton whch s an optmal choce by the farmers not to partcpate n the crop output market. Therefore, the corner soluton model s more approprate than a selecton model. Tobt estmator proposed by Tobn (1958) s a corner soluton model that could be used to model the household s market supply decson. However, n the Tobt model t assumes that the partal effect of partcular covarate on the probablty of partcpaton and the expected value of quantty suppled must have the same sgns (Wooldrdge, 2010). Moreover, t assumes that the relatve effects of two contnuous covarates on the probablty of partcpaton and the expected value of 9

10 quantty suppled are dentcal. These assumptons are consdered as farly restrctve (Wooldrdge, 2010), especally when the factors that affect household market partcpaton decson are dfferent from factors that affect the ntensty of partcpaton. Two part model relaxes these restrctve assumptons of the Tobt model by allowng dfferent mechansms to determne the partcpaton and amount decsons. It may seem justfable that Heckman selecton model would be used n ths study. However, Heckman selecton model s desgned for ncdental truncaton, where zeros are unobserved values whch s not the case n ths study. In our case, a corner soluton model s more approprate than a selecton model because, due to fxed transacton costs and other constrant factors, we assume that many of the farmers choose not to partcpate n output markets as sellers. That means the zeros n the data reflect rather farmers optmal choce not to partcpate n markets as crop sellers than representng mssng values. Therefore, n our case, a corner soluton model s more approprate than a selecton model. Double Hurdle model (DH) relaxes the restrcton mposed by Tobt model by allowng dfferent mechansms to determne the dscrete probablty of partcpaton and volume of transacton condtonal on partcpaton. The DH model s more flexble and fts our problem better than the Tobt model because t allows for the fact that fxed transacton costs may affect a farmer s decson to partcpate n the crop market, but once the decson to partcpate has been made, fxed costs may not affect the quantty sold. Therefore, the DH model proposed by Cragg (1971) s used n ths study to estmate the effect of off-farm ncome on smallholder crop market partcpaton and ntensty of sale. In hurdle 1 a household s head decdes whether or not partcpate n the crop output markets, and f she choose market partcpaton, hurdle 2 consders the quantty of crop sold. The maxmum lkelhood estmator (MLE) n the hurdle 1 can be obtaned usng a probt estmator. Then, the MLE for hurdle 2 can be estmated from truncated normal regresson model. The orgnal assumptons by Cragg (1971) on errors from hurdle 1 and hurdle 2 that assume ndependence, normal dstrbuton and zero covarance between the two errors condtonal on the explanatory varables s mantaned n ths study. The approprateness of the DH aganst the Tobt estmator can be evaluated usng a lkelhood rato test. 10

11 3.2. Controllng for Endogenety There could be potental smultanety of off-farm work wth crop output market partcpaton decson and amount of sale. Whle smallholder commercalzaton could be affected by off-farm earnngs, ncreased ncome as a result of hgher commercalzaton could also help farmers to overcome captal constrant and engage n own off-farm busness that would ncrease off-farm ncome. In that case, off-farm ncome s lkely to be endogenous and correlated wth unobserved tme varyng shocks. The use of conventonal methods lke Fxed Effect Two Stage Least Square (FE2SLS) to control potental endogenety s not approprate when both the dependent varable n the structural model and potentally endogenous covarates are non-lnear (Wooldrdge, 2010). In ths study, we apply control functon approach (CFA) to test and control for potental endogenety of off-farm ncome. The CFA requres some strctly exogenous covarates excluded from the structural model to be used as nstrumental varable wth other covarates n the reduced form of potentally endogenous covarates same as for fxed effect two stage least square n lnear model (Papke and Wooldrdge, 2008). The estmaton procedure nvolves regressng off-farm ncome on nstruments and all other covarates n the structural model of smallholder commercalzaton. Then, we take resduals from reduced form model and nclude them as addtonal covarate n the structural model. In the CFA, the sgnfcance of the coeffcent of the resdual n the structural model both tests and controls for ndgenety of off-farm ncome (for more detals on CF approach see Papke and Wooldrdge, 2008; Rvers and Vuong, 1988; Smth and Blundell, 1986; Vella, 1993). The reduced-form model for off-farm ncome s estmated usng one step tobt model. The CFA requres an nstrumental varable (IV) to be used n a reduced-form model but excluded from the structural model of crop output market partcpaton and volume sold. The requrement s that, the (IV) should be correlated wth the potentally endogenous off-farm ncome but should not be correlated wth unobserved tme varyng shocks, ut and vt n the structural model. We use household labor supply measured as the total number of adult equvalents per household as an IV n the reduced form model. It measures the amount of labor avalable to partcpate n off-farm work and determnes earnngs from off-farm source. After condtonng on other covarates, we beleve household labor supply would not be correlated wth other tme varyng unobserved 11

12 shocks n the structural models. Hence, t s reasonable to beleve the nstrument tself s exogenous Controllng for Unobserved Heterogenety c In a nonlnear panel data model, the covarates must be ndependent of unobserved heterogenety c 3 to obtan unbased and consstent estmates for parameters. Ths s often a strong assumpton, leadng to based coeffcent estmates f not controlled. We use of correlated random effects (CRE) followng Mundlak (1978) and Chamberlan (1984) approach to relax the assumpton of ndependence between covarates and unobserved heterogenety, c. The CRE estmator, unlke the standard random effects, allows for the correlaton between unobserved heterogenety ( c ) and vector covarates across all tme perods by assumng the correlaton takes the form of c X a, where X s tme average for all tme varyng covarates n equaton (9) and (10) above. These varables have the same value for each household n every year but vary across households. and are constants and a s an error term for constant wth normal dstrbuton, 2 X ~ Normal 0, a a. In practce to mplement CRE, we specfy a model for the dstrbuton of unobserved heterogenety n equatons (9) and (10) as a lnear functon of tme average of tme varyng explanatory varables, w t, x t and zt whereas s absorbed n to the ntercept term. The CRE approach has more benefts than the tradtonal random effect estmator n panel data analyss. Frst, by ncludng the vector of tme-averaged explanatory varables we can control for tme nvarant unobserved heterogenety as wth fxed effects wthout encounterng the ncdental parameters problem n nonlnear models. Second, t allows measurng the effect of tme nvarant explanatory varables just as n tradtonal random effect estmator (Rcker-Glbert et al., 2011; Wooldrdge, 2002) Obtanng Condtonal and Uncondtonal Average Partal Effects (APEs) After estmatng the CRE double hurdle model, we have estmated the average partal effect (APE) of changes n the explanatory varables on the probablty of beng market partcpant and 3 c represents the unobserved heterogenety equaton (10), respectvely. c 1 and c 2 n partcpaton decson, equaton (9) and volume decson, 12

13 on condtonal as well as uncondtonal expected value of quantty of crop sold. To obtan APE frst we have to derve average partal effect of every explanatory varable of nterest for every observaton at partcular tme t n the dataset. Then, the APE s just an average of all partal effects for every observaton n the dataset. For nonlnear models and f dscrete varables exst n the model, the APEs are consdered of greater nterest and more representatve than the partal effects at the average (Papke and Wooldrdge, 2008; Rcker-Glbert et al., 2011; Wooldrdge, 2010). The standard errors for APEs are obtaned usng delta method and bootstrappng followng the procedure proposed by Burke (2009) The Data Ths study s based on Ethopan Rural Household Survey (ERHS) panel data collected by Adds Ababa Unversty n collaboraton wth Oxford Unversty, UK and the Internatonal Food Polcy Research Insttute (IFPRI), USA. The survey was started n 1989, vstng 450 households n seven farmng vllages n Central and Southern Ethopa (Dercon and Hoddnot, 2004). In 1994, the survey was expanded to 15 vllages so as to cover the man agro-clmatc zones and man farmng systems n the country. Farmng systems were consdered as an mportant stratfcaton bass n selectng vllages. A household was then proportonately and randomly selected after stratfyng, based on gender of household heads (Dercon and Hoddnot, 2004). In total, about 1477 households are covered n the 1994 survey. These households have been re-ntervewed n the late 1994 as well as n 1995, 1997, 1999, 2004 and The households are from 15 peasant assocatons of four major regons of Ethopa,.e. Oroma, SNNP 5, Amhara, and Tgray. The data covered vllages n most rural parts of Ethopa. For ths study, the data s compled from 1997, 1999 and 2004 survey rounds. The three survey rounds were selected because they contan suffcent observatons on varables of nterest for our study. The sample attrton s low, wth only 12.4 percent between 1994 and 2004 (or 1.3 per cent per year) (Dercon and Hoddnot, 2004). Lmted access to land for cultvaton n other areas could be one of the plausble reasons for low attrton rate. Fnally we have managed to have a balanced panel data for 1,184 households. 4 To obtan the uncondtonal APE n hurdle 2 we have estmated the DH model usng craggt command s Stata followng procedure descrbed n (Burke, 2009). The standard error for uncondtonal APE effect s obtaned va bootstrappng 100 tmes. 5 SNNP refers to the Southern Naton Natonaltes and Peoples regon of Ethopa 13

14 4.1. Varable Descrpton Summary statstcs of varables used n ths study for pooled data are shown n Table 1 n the Appendx. The dependent varable n hurdle 1- the dscrete crop output market partcpaton decson s a dummy varable whch takes value of 1 f household sold any food crop at perod t. The pooled data contans 3552 farm households of whch 67.8% partcpated n crop market as sellers. Total value of crops sold, the dependent varable n hurdle 2, s the aggregate value of all crops sold by household at perod t. We construct ths varable by aggregatng quantty of each crop sold usng vllage level prce 6 as a weght. In the dataset, the quantty for each crop sold was reported n a local unt whch s converted n to klogram usng a converson factor provded n the data. On average, household sells about Brr worth crop produce. Because of food market mperfectons n developng countres, producton and consumpton decsons are usually non-separable (Sadoulet and de Janvry, 1995). Partcularly at the early stage of commercalzaton, surplus producton of staple food crops s more common than producton of cash crops exclusvely for market. As a result most of the crops suppled to market are surplus products after satsfyng household subsstence requrements. In such crcumstances, ncreasng producton level s expected to have postve mpact on market partcpaton and volume sold. Thus, we nclude total quantty of crop produced as addtonal explanatory varable n the econometrc model. The pooled data shows slghtly above 42% of households partcpated n off-farm employment ether as self-employed or wage worker. Off-farm ncome s the amount of total earnngs n ETB from wage work ether sklled or unsklled and/or self-employment n own busness actvtes. Payments are made ether n cash or n knd and we have converted t to cash usng converson factor provded n the data. Average off-farm ncome for the whole sample household s ETB per household. Head of household s average age, measured n years, for the total sample household s About 74% of households n the sample are male headed household. The average famly sze s 5.7 wth household labor supply of 2.93 persons whch also mples dependency rato of All monetary values are n 2004 constant prce Ethopan Brr (ETB) smply called Brr; 1USD = Ethopan Brr n Oct

15 Educaton of household head s a dummy varable that takes value of 1 f a household head partcpated at least n any level of prmary educaton. Ths s because majorty of households were not attendng any schoolng and the number of household heads attendng schoolng above prmary educaton s almost nl. Hence, n ths study, head of household s consdered as lterate f he/she has enrolled n any level of prmary educaton and able to read and wrte. Average land holdng per household for the panel sample household s 1.47 hectare whch s larger than the current natonal average land holdng of 1 hectare per household. The amount of lvestock owned by household durng the survey perod s measured by tropcal lvestock unt (TLU). The average lvestock owned per household s 3.05 TLU, whle 40.7 % of the sample household owned at least one transportaton anmals. The average dstance from vllage to the nearest market n klometers s 10.66, rangng from a mnmum of 1 km to 25 km. Ths ndcates there are wde varatons n terms of access to close agrcultural markets. Agrcultural extenson programs are expected to mprove access to nformaton by facltatng smallholder lnkages wth nput and output markets. The dummy varable for partcpaton n extenson program that take value 1 f household partcpated ether n government or Sasakawa Global 2000 extenson program s ncluded n the model. The pooled data ndcates only slghtly above 10% of the sample households partcpated n extenson program durng the three survey rounds. Ths mght be due to the low level of publc extenson coverage untl the late 1990s. For nstance, when the government launched the extenson program called Partcpatory Demonstraton and Tranng Extenson System (PADETS) n 1995, the number of partcpants n extenson program where only The coverage was ncreased to 4.2 mllon n 2002 (Gebremedhn et al., 2006). It s expected that surplus producton and the level of commercalzaton to be affected by agro-clmatc and other geographcal dfferences. Hence regonal dummes for Oroma, Amhara and SNNP regonal states s created and added to the explanatory varables. Tgray regon s left out to be used as a reference n the analyss. 5. Results and Dscussons 5.1. Specfcaton tests As prevously mentoned, the double hurdle model s an alternatve to the tobt specfcaton, thus tobt model s nested n double hurdle model. We check approprateness of double hurdle model 15

16 aganst Tobt model usng a lkelhood rato (LR) test. The LR statstc comparng the two model s wth a p-value equal to The result reveals the null hypothess that the farmer s market partcpaton conssts of just one decson process can easly be rejected n favor of the double hurdle model. To test for endogenety of off-farm ncome, we have estmated the reduced-form model from whch the resduals are derved. Tobt estmator results from the reduced-from model of factors affectng amount of off-farm ncome s gven n Table 2 n the Appendx. In lnear models, there are a number of tests for weak nstrumentalty (Stager and Stock, 1997; Stock et al., 2002). These tests uses partal correlaton between the IV and potentally endogenous varable derved from the lnear reduced-form model. In our case, however, the reduced-form model s a nonlnear corner soluton model. We are unaware of tests for weak nstrumentalty n case of nonlnear model. Therefore, the only opton to check for strength of our nstrument s to look at the partal correlaton of our IV, labor supply per household, n the reduced form model. The result shows there s strong partal correlaton between labor supply and potentally endogenous off-farm ncome whch s statstcally sgnfcant at 1% level. There s also lttle to beleve that our IV wll be correlated wth the error term n the structural model after condtonng on other covarates. Thus, we feel confdent that labor supply s a strong and vald nstrument for potentally endogenous varable, off-farm ncome. The next step s to test for endogenety of our key varable, off-farm ncome, usng the control functon approach. The resdual from the reduced form model s ncluded as addtonal covarate n both hurdle 1 and hurdle 2. In the CFA, the test of endogenety s the statstcal sgnfcance of the coeffcent of the resdual n both decson models. Falure to reject the null hypothess of exogenety based on the t statstc mples that off-farm ncome can be treated as f t were exogenous to output market partcpaton and quantty sold. The test results from p-value for both hurdles ndcate that the resdual term s not sgnfcant as shown n the Table 3. Hence, there s no evdence n the data to reject the null hypothess of no correlaton between off-farm ncome and the error terms n the structural models. We therefore estmated the CRE double hurdle model wthout ncludng the resdual term as addtonal covarate. 16

17 5.2. CRE Double Hurdle Model Estmaton Results Table 4 n the Appendx presents the results from CRE double hurdle model of factors nfluencng households decson of output market partcpaton and amount of crop sold. The coeffcents of hurdle 1 are the average partal effects (APEs) of each explanatory varable on the probablty of market partcpaton. Whereas the condtonal average partal effect (CAPEs) n hurdle 2 s the margnal effect of each explanatory varable on the quantty of crop sold condtonal on frst stage partcpaton decson has been made. The uncondtonal margnal effect (UAPE) captures the jont mpact of a varable on the changes n the probablty of market partcpaton and n the level of marketed supply. It s more nterestng and of practcal mportance as t combnes both effects uncondtonally. As shown n the Table 4, the coeffcent on off-farm ncome n hurdle 1 s postve but not statstcally sgnfcant. Ths mples, holdng other factors constant, an ncrease n off-farm earnng has no nfluence on the probablty of farmer s output market partcpaton. However, condtonal on postve partcpaton n the frst stage, off-farm ncome has negatve effect on household marketed supply and statstcally sgnfcant at 10% level. The economc effect ndcates that on average each addtonal ETB 100 off-farm ncome earnngs decreases the value of crop sold by ETB 11.9, all other factors beng constant. The UAPE ndcates the overall nfluence of off-farm ncome on household market supply s not sgnfcant at any conventonal sgnfcance level. The negatve nfluence of off-farm ncome on household market supply condtonal on postve partcpaton decson s consstent wth the noton that off-farm ncome slows down smallholder commercalzaton due to ts ncome effect. Meanng, an ncrease n off-farm ncome may negatvely nfluence market supply by ncreasng household s consumpton demand for own producton (Woldehanna, 2000). Moreover, f off-farm ncome s geared toward consumpton nstead of nvestng n farm captal, then off-farm work ends up competng wth agrculture for labor and other resources than beng a complement. Ths n turn lowers producton and marketable surplus. Research fndngs by Alene et al. (2008) and Omt et al (2009) for Kenyan smallholder farmers also support ths results. Ths s more evdent partcularly f the poor s pushed n to off-farm actvtes due to small land holdng and drought ncdence, for nstance. 17

18 Our emprcal fndng doesn t support the hypothess that off-farm ncome promotes smallholder commercalzaton through captal nvestment n agrculture and rsk dversfcaton. Perhaps partcpaton n off-farm actvtes does help smallholder farmers to overcome lqudty constrants. Partcularly when agrcultural growth s hampered by credt constrants, the addtonal resources can be used by farmers for the adopton of nnovatons and the purchase of nput. Such postve effect of off-farm ncome n provdng lqudty to agrculture was recently shown by Osen and Wnters (2009). But, t depends on types of actvty, amount of ncome earned and the way that lqudty s used. Regardng other determnants of smallholder commercalzaton, our results show that degree of partcpaton n crop market s nfluenced by the value of crop produced, gender, famly sze, the sze of lvestock owned and land holdng sze, all wth expected sgns. Smlarly, the degree of market partcpaton and the volume of crop sold are sgnfcantly nfluenced by regonal dummes and dummes for survey rounds. On average each addtonal ETB 1000 value of crop producton makes a household about 10 percentage ponts more lkely to partcpate n the output market, other factors held constant. Condtonal on postve partcpaton decson n hurdle 1, on average an ncrease n value of crop produced by ETB 100 ncreases quantty of crop sold by 23.5 ETB, other factors beng constant. The result s statstcally sgnfcant at 1% level. Ths fndng confrms that most of the tme crops marketed by smallholders are surplus product after satsfyng household subsstence requrement and ncreased producton means more surpluses to sell. Land sze, whch can be consdered as household s wealth, has postve and statstcally sgnfcant (10% sgnfcance level) nfluence on the probablty of market partcpaton. On average, each addtonal hectare of land ncreases the quantty of crop sold by ETB condtonal on the fact that partcpaton decson has been made, whch s also statstcally sgnfcant at 1% level. The UAPE coeffcent also ndcates nfluence land holdng sze on the quantty of crop sold s estmated to be ETB 79 whch s statstcally sgnfcant at 1% level. Ths result confrms that land s a key constrant nput for rural household and land holdng per capta s declnng manly because of rapdly growng populaton. Moreover, land market for smallholder farmers s nonexstent n Ethopa as land s state property and farmers have only usufruct rght. Our result s also consstent wth what others found elsewhere n developng countres (e.g. Alene et al., 2008). Sze of lvestock owned s related wth hgher probablty of market partcpaton whch s sgnfcant at 5% level. Whereas the CAPE coeffcent shows one 18

19 TLU more lvestock on average reduces the value of crop sold by ETB 58, gven the household s partcpatng n crop market. It s statstcally sgnfcant at 5% level. Ths s what would be expected a pror. Ths result also supports the dea that more lvestock offers alternatve fnancal ncome for household so that marketed surplus would be lower. A smlar effect of lvestock ownershp on quantty of crop sold was found n Ethopa by Gebremedhn et al. (2009). Gender of household head ndcates probablty of output market partcpaton s hgher by 4 percentage ponts f the household s male-headed. The UAPE also ndcates that beng a maleheaded household on average ncreases the quantty of crop sold by ETB 70, other factors beng constant. Ths mght be due to the cultural nfluence that male farmers have better access to nformaton and well networked wthn the communty that helps them to trade at lower cost and partcpate more n output market than ther female counterpart. Ths fndng may suggest that any polcy actons desgned to strengthen smallholder market ntegraton has to brng the gender aspect nto the center of dscusson so that equal partcpaton of female farmers would be ensured. Contrary to what we expected, condtonal and uncondtonal nfluences of famly sze on the quantty of crop sold are not statstcally sgnfcant, although t has a negatve effect on the probablty of market partcpaton. Smlarly, our emprcal fndng does not show any sgnfcant nfluence of educaton of household head both on household market entry and marketed surplus. Ths mght occur because the majorty of household heads was not attendng any schoolng and the proporton of household heads attendng schoolng above prmary educaton was qute small. The coeffcents of transport anmals and dstance to nearby markets, whch are ncluded to control for the effect of varable transactons costs, s not sgnfcant n the hurdle 1. But both of them have the pror expected sgn. Condtonal on the partcpaton decson that has been made, one km dstance from nearest market on average decreases the quantty crop sold by ETB whch s statstcally sgnfcant at 10% level. The negatve nfluence of dstance from market also makes sense and supports the dea that nfrastructure development strength smallholder s market ntegraton by reducng marketng cost. Perhaps because 41 % of households n the panel data own transport anmals, ownng more of transport anmals does not have a separate nfluence on market partcpaton and quantty of crop sold. Partcpaton n extenson program has no sgnfcant nfluence on the probablty of market partcpaton. But t has a postve effect on marketed surplus condtonal on partcpaton decson has been made n frst stage and statstcally sgnfcant at 10 % level. Ths result contradcts our pror expectaton of extenson 19

20 program s role n mprovng access for marketng nformaton through smallholder lnkages wth nput and output markets. The result may suggest the need for extenson servces to strength the marketng extenson n addton to nput and credt servce supply. Both probablty of market partcpaton n hurdle 1 and CAPE n hurdle 2 s hgher for households n Oroma, Amhara and SNNP regons compared to those n Tgray regon. The result also shows that the magntude of nfluence on the value of crop sold s also qute stronger and the dfference s statstcally sgnfcant at 1% level. Ths could be due to the fact that Oroma, Amhara and SNNP are located n ago-ecologcal zones more favorable for agrcultural producton. The probablty of household market partcpaton s lower by 5 percentage ponts n the survey round 1997 and 1999 compared to Condtonal on postve partcpaton decson n the frst stage and compared to the 2004 round, the quantty of crop sold declnes on average by 359 and ETB for the 1997 and 1999, respectvely. These effects are statstcally sgnfcant at 5% level. Ths fndng may suggest that there has been an mprovement n terms of smallholder market ntegraton over the course of perod. 6. Conclusons and Polcy Implcatons Several studes have been conducted on the lnkage of farm and off-farm employment and ther contrbuton n poverty reducton. However, the nature of nteracton between ncome from offfarm employment and smallholder commercalzaton has receved lttle attenton n the emprcal work. More specfcally, there exsts mnmal emprcal lterature on possble drecton of relatonshp between off-farm ncome and smallholder commercalzaton at household level. Regardng the lnkage between agrcultural commercalzaton and off-farm employment at the macro level, advancement n agrcultural commercalzaton can create rural off-farm employment opportunty for the poor. Although ths s very crucal for rural development, nformaton on the nature of the nteracton that could exst at the household level s more benefcal for the desgn of pro-poor publc polces. Dfferent studes also ndcate there s a growng mportance of rural off-farm employment n rural Ethopa followng rapd populaton growth and declnng land per capta. Thus, understandng the drecton of relatonshp between off-farm ncome and smallholder commercalzaton has mportant mplcatons for publc polcy to support rural communtes durng the process of economc transformaton. 20

21 In ths study, we use three waves of panel data from Ethopan Rural Household Survey (ERHS) to test emprcally the effect of off-farm ncome on household s output market partcpaton as seller and volume of crop sold. We fnd off-farm ncome has no dscernble nfluence on household output market partcpaton decson. Nevertheless, condtonal on postve market partcpaton, each addtonal earnngs from off-farm work has negatve and sgnfcant effect on household market supply. Although the magntude of economc effect on marketed surplus s small, t seems consstent wth the noton that off-farm ncome slows down smallholder commercalzaton due to ts ncome effect. Indeed, our emprcal fndng ndcates there s no evdence to support the hypothess that off-farm ncome promotes smallholder commercalzaton by relaxng lqudty constrant to nvest and rase productvty and marketable surplus. Ths mght be due to the fact partcpaton n off-farm actvtes by land poor households s due to lack of optons not as a choce. They may partcpate n lower earnng actvtes such as wage work and ther savng rate would be small. The polcy mplcaton of our fndng s that expandng hgher earnng rural enterprses through capacty buldng and human captal nvestment s vtal. Ths may help to mprove the returns to labor for off-farm work partcpatng land-poor households as Ethopan smallholder commercalze. Our results also show that ncreased crop producton per household s a major determnant of both probablty of partcpaton n crop market as a seller and the extent of market partcpaton. Ths fndng supports the dea that most of the crops marketed by smallholders are surplus product after satsfyng household subsstence requrement and ncreased producton means more surpluses to sell. Gebremedhn et al. (2009) also found the same effect of ncreased crop producton on smallholder market ntegraton. We found that extenson program partcpaton s nsgnfcant n determnng the probablty of market entry. Nevertheless, t has a postve nfluence on the quantty of crop sold condtonal on the partcpaton decson has been made. Smlarly, our result ndcates land holdng has sgnfcant and postve nfluence on household market partcpaton and quantty of crop sold. These effects altogether have wder polcy mplcatons to strengthen the lnkage between smallholder household and output market. Frst, gven the current small land holdng system n Ethopa, the possble opton s ntensfcaton of agrculture by expandng and strengthenng the nsttutonal support servces va extenson program. Second, strength the marketng extenson servce and make them more easly and wdely accessble. 21

22 We fnd dstance to the nearest market negatvely and sgnfcantly affect how much values of crop a household sells once the partcpaton decson has been made. Ths ndcates household s access to rural nfrastructure s qute crtcal to lnk them up wth crop output markets by reducng marketng cost and need publc polcy attenton. Our fndng also ndcates male headed household more partcpate n output market and the overall nfluence on value of crop sold s also postve. The mplcaton s that any polcy acton desgned to strength smallholder lnkage to output market has to consder the gender aspect and empower female farmers. References Alene, A.D., Manyong, V.., Omanya, G., Mgnouna, H.D., Bokanga, M., and Odhambo, G., Smallholder market partcpaton under transacton costs: Maze supply and fertlzer demand n Kenya. Food Polcy 33, Barrett, C., Smallholder Market Partcpaton: Concepts and Evdence from Eastern and Southern Afrca. Food Polcy 33, Barrett, C.B., Reardon, T., and Webb, P., Nonfarm ncome dversfcaton and household lvelhood strateges n rural Afrca: concepts, dynamcs, and polcy mplcatons. Food Polcy 26, Bellemare, M.F., and Barrett, C.B., An Ordered Tobt Model of Market Partcpaton: Evdence from Kenya and Ethopa (Cornell Unversty, Department of Appled Economcs and Management). Bellemare, M.F., and Barrett, C.B., An Ordered Tobt Model of Market Partcpaton: Evdence from Kenya and Ethopa. Am. J. Agrc. Econ. 88, Van den Berg, M., and Kumb G.E., Poverty and the rural non-farm economy n Oroma, Ethopa. Agrc. Econ. 35, Bnswanger, H.P., and Braun, J. von, Technologcal Change and Commercalzaton n Agrculture: The Effect on the Poor. World Bank Res. Obs. 6, Boughton, D., Mather, D., Barrett, C.B., Benfca, R., Abdula, D., Tschrley, D., and Cunguara, B., Market Partcpaton by Rural Households n a Low-Income Country: An Asset-Based Approach Appled to Mozambque (Rochester, NY: Socal Scence Research Network). Von Braun, J., Agrcultural commercalzaton: mpacts on ncome and nutrton and mplcatons for polcy. Food Polcy 20, Von Braun, J., Introducton, n J. Von Braun, and E. Kennedy, eds., Agrcultural Commercalzaton, Economc Development, and Nutrton. Baltmore, MD: Johns Hopkns Unversty Press, pp