Access to Finance and Small Enterprise Growth: Evidence from East Java

Transcription

1 Access to Fnance and Small Enterprse Growth: Evdence from East Java Mchael A. McPherson, Jeffrey J. Rous The Journal of Developng Areas, Volume 43, Number 2, Sprng 2010, pp (Artcle) Publshed by Tennessee State Unversty College of Busness DOI: For addtonal nformaton about ths artcle Accessed 1 Jan :12 GMT

2 ACCESS TO FINANCE AND SMALL ENTERPRISE GROWTH: EVIDENCE FROM EAST JAVA Mchael A. McPherson* Jeffrey J. Rous* Unversty of North Texas, USA ABSTRACT The wdespread acknowledgement of the centralty of mcro and small busnesses n the development process has led to a prolferaton of projects and programs desgned to assst and promote these busnesses. Ths research examnes the common assumpton that access to credt from formal fnancal nsttutons s an mportant determnant of growth at the frm level. Our data are from a recent survey of 858 small busnesses n East Java. We employ a full nformaton maxmum lkelhood approach known as dscrete factor method. The results ndcate that access to credt s not a sgnfcant determnant of small frm growth; nstead, other observable and unobservable characterstcs of frms appear to cause growth. JEL Classfcatons: O1, O2 Keywords: Mcro and Small Enterprses, Credt, Growth Correspondng Author s Emal Address:jrous@unt.edu INTRODUCTION The centralty of mcro and small enterprses (MSEs) n the process of economc development s by now wdely recognzed and essentally beyond debate. Whle countres are heterogeneous n the regard, t s not uncommon for such busnesses to employ one quarter of the workng age populaton n developng countres. Estmates of the contrbuton of the sector to GDP are probably less relable, but typcally fall n the 10% to 15% range. 1 In addton, the MSE sector may serve as an entrepreneural tranng ground n whch tomorrow s busness leaders can fnd success and gan valuable experence. 2 As the role of the MSE sector has become clearer, polcy makers n developng countres, as well as donors and others organzatons, have expended ncreasng amounts of scarce development resources on MSE support and promoton. A tremendous and ncreasng amount of attenton has been pad n recent years to the legal and regulatory framework that may constran MSE expanson. Smlar attenton has been gven to programs promotng the tranng of entrepreneurs and workers that may enable MSEs to grow. Stll, although many programs and polces have been mplemented n these areas, perhaps even more attenton has been pad to the area of mcro and small frm fnance. The success of the Grameen Bank n Bangladesh and ts clones all over the world, as well as the awardng of the 2006 Nobel Peace Prce to Grameen Bank founder

3 160 Muhammad Yunus have made mcro and small frm fnance one of the prncpal development topcs of the day. Accordng to a recent specal report n the Economst, mcrofnance nsttutons worldwde may number n the hundreds of thousands. (The Economst, 2005). Indonesa s certanly no excepton to these trends. The Government of Indonesa, n conjuncton wth donors and nongovernmental organzatons, has been more dlgent than most developng country governments n promotng such programs, and by most accounts a hgher proporton of MSEs n that country has receved loans from formal fnancal nsttutons than s the case n many places. 3 Recent estmates clam that the government of Indonesa regulates some 60,000 mcrofnance nsttutons (The Economst, 2005). In recent years t has been taken as a gven that poor access to formal credt sources constrans MSE growth. However, for the most part, emprcal evdence supportng such an assumpton has been weak. Nevertheless, mllons of dollars have been spent on programs that seek to mtgate ths perceved obstacle. Typcal examples nclude programs that nvolve subsdzed credt for certan MSEs, programs that encourage banks to lend to MSEs by provdng repayment guarantees, and programs such as the Grameen Bank that channel loans specfcally to MSEs. Ths paper seeks to address emprcally the assumpton that frms wth access to formal credt sources are more lkely to grow as a result. Certanly, such an assumpton s ntutvely appealng, and there s at least some emprcal support for t. However, perhaps nstead MSEs tend to grow because of factors not related to credt, such as entrepreneural skll or the presence of human captal, opportuntes n the subsector n whch the frm operates, etc. Ctng evdence from Indonesa, Berry et al. (2001, p. 378) report frms that dd and dd not receve assstance show smlar patterns of development, suggestng that other factors explan frm growth. As Morduch (1999, p. 1598) asks n hs revew of the mcrofnance lterature, [w]ould the borrowers have done just as well wthout the programs? EARLIER LITERATURE Most emprcal work on the determnants of frm growth s based on Jovanovc s (1982) learnng model and ts extenson by Pakes and Ercson (1998). These allow managers to nfluence ther effcency level va human captal formaton. These theores predct that frm growth wll be nversely related to ntal frm sze and to frm age, and drectly related to the level of human captal emboded n the frm s entrepreneur. Examples of emprcal research that generally support the Jovanovc (1982) and Pakes and Ercson (1998) models nclude Blsen, et al. (1998), Ledholm, et al. (1994), McPherson (1995), McPherson (1996), and Parker (1994). Wth respect to the effects of credt on a frm s growth performance, much of the avalable evdence comes n the form of descrptve statstcs from natonal surveys of MSEs. Typcally, these studes compare the average growth rate of frms that had receved credt wth that of frms wthout access to credt. The obvous dsadvantage of ths smplstc approach s that t does not control for other factors. Danels and Ngwra (1993), Parker and Torres (1994), Mnot (1996), USAID (1998), and Ebony Consultng Internatonal (2000) are examples of ths approach, and each fnds that access to credt leads to better frm growth prospects for frms n varous developng countres.

4 161 When efforts are made to control for other factors by use of regresson analyss, results are more ambguous. Brown et al. (2003) and Hansen et al. (2004) fnd evdence that MSEs wth access to credt grow more rapdly. However, Danels and Mead (1998) and Johnson et al. (2000) fnd that credt s not a sgnfcant determnant of growth, and Cabal (1995) reports that access to credt may actually retard the growth of MSEs n the Domncan Republc. Few of these earler studes examnes the possblty that access to credt may be endogenous, although Parker and Torres (1994, p. 23) recognze the problem ndrectly. Brown et al. (2003) recognze t as a potental problem wth ther results, whle Morduch (1999) ponts out that falure to address the endogenety of credt may explan the contradctory fndngs n earler research. Wynne and Lyne (2003) and Banerjee and Duflo (2004) are representatve of the rare attempts n the lterature to address endogenety. Wynne and Lyne (2003) use a two stage approach, but because the credt varable s not a regressor n ther growth regresson, ther concluson that poor access to credt constrans growth can only be taken as evdence of an ndrect lnkage. Banerjee and Duflo (2004) attempt to address endogenety drectly. Ther panel of data comes from a natural experment settng. Ther analyss employs a dfference-ndfference-n-dfference approach, and they conclude that access to credt does lead to better frm-level performance. Our paper adds to ths small lterature nvolvng the examnaton of the nfluence of credt on growth whle accountng for unobservable characterstcs of entrepreneurs and ther frms. Such factors (for example, entrepreneural talent and zeal, or varous characterstcs of the communty n whch a gven frm may be located that affect ts growth prospects) are lkely to be mportant, and the falure of earler research to control for these casts some doubt on the valdty of ther fndngs. As part of the analyss, we wll also test for the endogenety of credt and growth. The purpose of ths paper s to examne the effect of access to credt on MSE growth n a statstcally rgorous manner. We make use of the dscrete factor method, a full nformaton maxmum lkelhood technque that allows us to control for unobservable characterstcs of frms and ther entrepreneurs that may affect frm growth. Ths method s deally suted for ths task, and to our knowledge ths paper represents ts frst applcaton n the area of small enterprse growth. We take advantage of a data set nvolvng more than 800 small busnesses n Indonesa collected as part of a survey n East Java n DATA AND ESTIMATION Samplng Methods The data were collected over a two-month perod n 2003 as part of a survey of 1,266 small busnesses n East Java. 4 In general, collectng representatve data on mcro and small frms n developng countres s complcated by the fact that there exsts no comprehensve lst of such busnesses from whch to draw a random sample. Because no samplng frame exsts, the survey employed a stratfed cluster samplng approach. In partcular, lsts of rural and per-urban areas (kabupaten) and urban areas (kotas) wth hgh concentratons of small busness actvty were constructed n consultaton wth experts employed n the local offces of the natonal statstcal offce (Badan Pusat Statstk). From these lsts some 26 areas n kotas and 23 n kabupatens were randomly

5 162 selected. 5 In each selected area, or cluster, an enumerator vsted every busness or dwellng, and those meetng the defnton of small busness (fve to 19 employees ncludng any workng owners 6 ) were enumerated. Because n some cases data on certan key questons could not be gathered, usable nformaton for the econometrc work that s descrbed n the followng sectons could only be collected n 858 cases. 7 Estmaton Equatons Gven the prevous theoretcal and emprcal work, we propose a two-equaton system. In equaton (1), frm growth s descrbed as a functon of frm age, frm sze, human captal emboded n the manager/owner and n the frm s workers, whether the frm has ever receved a loan from a formal fnancal nsttuton (and f so how long ago) and varous other characterstcs of the frm. Ths latter category ncludes the sector n whch the frm operates (e.g., food and beverage producton, retal, et al.), whether the frm regularly sells products on government contracts, and whether the frm operates n an urban area. That s, g GROWTH F( CREDIT, AGE, SIZE, HUMANK, OTHER), (1) In equaton (2), whether or not the frm has receved a loan s represented as a functon of the same exogenous varables n (1) as well as a varable that s correlated wth the probablty of beng awarded a loan, but uncorrelated wth growth. In the present case, the nstrument to be employed s TITLE. Ths s a dummy varable takng on the value of one f the owner has formal ttle to land or a buldng. In Indonesa, such ttle serves as collateral, and s very mportant n qualfyng for a loan. Specfcally, CREDIT F AGE, SIZE, HUMANK, OTHER, TITLE) c ( (2) There are several assumptons one can make regardng the error terms n these equatons, leadng to dfferent estmaton methods. These assumptons and methods are dscussed n the subsequent secton. It should be noted that there exsts the possblty of sample selecton bas n these data. That s, we do not observe busnesses that have not survved, and t s possble that ths ntroduces bas nto our estmates. Stll, usng a broadly smlar data set from sub-saharan Afrca, McPherson (1996) fnds no evdence of sample selecton bas n the growth equaton. In addton our data do not permt us to consder establshment bas. That s, mperfectons n fnancal markets may determne whch entrepreneurs are able to establsh busnesses. Fnally, our defnton of small busness (5 to 19 employees at the tme of the survey) necessarly excludes busnesses that were n the small busness category at some pont n the past and shrank to less than 5 workers, as well as busnesses that were small at some pont n the past but grew to szes larger than 19 by the tme of the survey. Descrpton of the Data Descrptve statstcs on these cases can be found n Table 1. GROWTH, whch s the endogenous varable n whch we are prncpally nterested, s defned as the average annual percentage growth rate n the number of employees 8 between 1998 and the tme of the survey n Although t would be deal to measure frm-level growth n terms of

6 163 assets or revenues, growth of employment s most often used snce relable data are more commonly avalable and relable. 10 For the frms n the sample, ths varable averages 5.7%, but vares over a consderable range. In partcular, one frm n the sample shrank by an average of 18.4%, whereas another frm averaged over 200% growth per year. Indeed, the average s to a large extent beng drven by a relatvely small number of rapdly growng busnesses. 184 (or 21.4%) of the frms n the sample shrank, and another 322 (37.5%) stayed the same sze. Among the 352 frms that dd grow, the average annual growth rate was 17.5%. TABLE 1. DESCRIPTIVE STATISTICS Varable Mean Standard Devaton Mnmum Maxmum GROWTH Sectoral Dummes FOOD TEXTILE WOOD METAL OTHMFG COMMERCIAL (Base Category) SERVICE Busness Characterstcs INITSIZE FIRMAGE Human Captal: Workers WKTRAIN PRIMEDWK (Base category) JRSECWK SRSECWK Human Captal: Owners FEMOWN MALEOWN (Base category) EXPERIENCE Other Busness Characterstcs GOVTSALE URBAN TITLE Credt Varables CREDIT TIMESINCE Sample Sze 858

7 164 The second varable that may be endogenous n the system presented above s CREDIT, a dummy varable that takes on a value of one f the busness had receved one or more loans from a formal fnancal nsttuton, and zero otherwse. As Table 1 ndcates, 47% of busnesses n the sample reported havng receved at least one such loan. It may also be mportant to control for the amount of tme that has elapsed snce the busness last receved a loan, snce loans receved many years n the past may not affect more recent growth. TIMESINCE s defned as the number of years snce the busness last receved credt from a formal fnancal nsttuton, condtonal on havng receved such a loan. In addton to TIMESINCE, the exogenous varables n the system can be grouped nto several categores. Frst, the sector n whch a busness operates s modeled by means of a seres of dummy varables. For example, 39% of busnesses are retalers, another 14% are engaged n food and beverage producton and processng, and 12% produce or process wood or forest based products. 11 As dscussed above, growth and probablty of recevng a loan may also be affected by the sze of a busness and ts age. For the present sample, the average ntal sze of frms (n terms of numbers of employees) s 5.4 and at the tme of the survey the average frm had exsted for 18.4 years. Another group of varables attempts to control for human captal emboded n workers and n owners at the tme of the survey. 12 WKTRAIN s a dummy varable that takes on a value of one f at least some of the workers have formal tranng. A seres of dummy varables models the educatonal level of workers n the frm: JRSECED equals one f most workers have an educaton through the junor secondary level; SRSECED equals one f most workers have completed at least senor secondary schoolng (the omtted category s frms n whch most workers have prmary or lower educaton). Regardng owners, 10.1% of busnesses n the sample are owned exclusvely by women: FEMOWN s a dummy varable that accounts for ths. EXPERIENCE measures the number of years of experence the owner has had n the present busness or n smlar work. 13 Several other varables may also explan frm-level growth. A small proporton of busnesses regularly have government contracts. Such frms mght be expected to grow more rapdly, ether because of the steady revenue streams from such contracts, or because of other benefts a close relatonshp wth the government mght mply. Some 20% of busnesses are located n urban areas. These busnesses may be more lkely to receve credt gven that banks and other fnancal nsttutons are concentrated n urban areas. Fnally, as noted above, n order to dentfy the system, TITLE s ncluded n the credt equaton. Ths varable measures whether or not the owner of the busness also holds formal ttle (certfkat) to land or buldngs that could be used as loan collateral. Ths varable should be correlated wth CREDIT, but not wth GROWTH. 14 In the present sample, 81% of busnesses report ownershp of such collaterable propertes. THE DISCRETE FACTOR METHOD In estmatng equaton (1) above, one could smply employ ordnary least squares (OLS), treatng CREDIT as an exogenous varable. Ths would mply that the error term n

8 165 equaton (1) s normally dstrbuted and that the covarance between that error term and the credt varable s zero. However, f n fact CREDIT s endogenous, OLS estmates wll be based and nconsstent. One possble soluton to ths problem would be to employ a two stage least squares (2SLS) approach. However, 2SLS assumes that the correlaton between error terms n the equatons of the system s dstrbuted multvarate normal. If n fact the error terms are not dstrbuted n ths manner, 2SLS estmates wll be neffcent. To jontly estmate the two equatons specfed above and to remove the unobserved heterogenety bases, we employ a dscrete factor method smlar to that descrbed n Heckman and Snger (1984), Akn and Rous (1997), and Mroz (1999). The technque s full nformaton maxmum lkelhood, but rather than makng a multvarate, parametrc assumpton about the error term correlaton (e.g., multvarate normal), we estmate a jont, dscrete, multvarate dstrbuton that approxmates the true dstrbuton of the unobservables responsble for error term correlaton. To account for ste and frm specfc unobservables correlated wth the error terms, we estmate separate frm and ste level dstrbutons. To facltate ths estmaton technque, we expand the error terms and assume the followng mxed error structures respectvely for the equatons for frm growth and loan acceptance (credt): g g g g (3) c j c j k c k (4) where c g ndcates elements of the error term n the growth equaton, c ndcates elements of the error term n the credt equaton, s each equaton s dsturbance term, are the factors that make up the part of the dstrbuton of unobserved frm j level varables that nfluence each equaton. These are random varables that follow a dscrete multvarate jont dstrbuton. are the factors that make up the part of the dstrbuton of unobserved ste k level varables that nfluence each equaton. These also are random varables that follow a dscrete multvarate jont dstrbuton. s the porton of each dsturbance term that s ndependent across cross sectons. The ste and frm level dstrbutons are made up of the and correspondng probablty weghts, all of whch are estmated wth the rest of the parameters n the model. The ste-level factors,, n each equaton are allowed to be correlated across k equatons. Smlarly, each equaton s frm level factors, j, are also correlated across equatons. g s assumed to be dstrbuted normally and c s assumed to be dstrbuted logstcally, as n the standard logt specfcaton. The error term correlaton allowed wth the dscrete factor method controls for any unobserved heterogenety problems caused by endogenety, and the cluster based

9 166 sample desgn used for collectng the data. The lkelhood functon s avalable from the authors upon request. The parameters n the model are dentfed techncally by the nonlnear functonal form of the model. However, the model gans further dentfcaton from the ncluson of the varable TITLE n the credt equaton whch, whch for theoretcal reasons, does not appear n the growth equaton. RESULTS A Hausman specfcaton test ndcates that CREDIT s n fact exogenous, and as a result we estmate equaton (1) by OLS. The results are found n Table 2. Whle several notable results emerge, we are especally nterested n the fndng that whle the estmated coeffcent on CREDIT s postve, t s not statstcally sgnfcant. In other words, when we apply standard estmaton technques to these data we do not fnd compellng evdence that access to formal credt sgnfcantly contrbutes to frm growth. However, the OLS method does not allow for unobserved ste specfc and frm specfc effects. In ths regard, the dscrete factor method s more effcent than OLS. The results from the dscrete factor method are presented n the thrd column of Table 2. Frst, the sgnfcance of the dscrete factor parameters suggests credt and growth are endogenous. Ths s somewhat surprsng gven the results of the Hausman test and may suggest the less restrctve dstrbutonal assumptons regardng the error structure made n the dscrete factor method may be more approprate for ths analyss. TABLE 2 REGRESSION RESULTS Explanatory Varable OLS Dscrete Factor Model CONSTANT *** (4.817) Sectoral Dummes FOOD (-0.537) TEXTILE (0.378) WOOD *** (-2.891) METAL *** (-4.389) OTHMFG (-1.289) SERVICE (-0.835) Busness Characterstcs INITSIZE *** (-4.007) FIRMAGE *** (-3.016) 8.199*** (6.450) (0.093) ** (-2.225) *** (-3.150) *** (-2.942) (-0.484) (-1.469) *** (-2.599) ** (-2.023)

10 167 Explanatory Varable OLS Dscrete Factor Model Human Captal: Workers WKTRAIN (1.526) JRSECWK 2.507* (1.765) SRSECWK 2.546*** (2.669) Human Captal: Owners FEMOWN (-0.994) EXPERIENCE (-1.526) Other Busness Characterstcs GOVTSALE (-0.265) URBAN (-0.516) Credt Varables CREDIT (0.580) TIMESINCE (-0.544) TIMESINCE (0.363) Ste level Unobservables 2.289*** (2.904) (1.366) 2.397** (2.071) (0.240) ** (-2.275) (-0.142) (0.532) (-0.354) (-0.825) (0.867) OMEGAk1 OMEGAk (1.539) OMEGAk (-0.118) Frm level Unobservables 3.438*** (3.169) ** (-2.095) OMEGA1 OMEGA (1.145) *** (10.991) OMEGA (0.433) Sample Sze t-statstcs are n parentheses; *:Sgnfcant at the 90% level; **:Sgnfcant at the 95% level ***:Sgnfcant at the 99% level; :Normalsed to zero

11 168 Table 2 contans nformaton on the ste and frm level parameters mentoned n equatons (3) and (4) above. Consderng frst the ste level unobservables, there seems to be three sorts of stes n whch frms n ths sample exst. 15 Consderng the estmated ste level parameters presented n Table 2 (OMEGA k1, OMEGA k2, and OMEGA k3 ), we observe that frms n the second and thrd sorts of stes grow more rapdly than frms located n the frst sort of ste. Ths mples that there s one or more unobserved characterstc of these stes that make growth more lkely. Whle by defnton we cannot know what characterstc or characterstcs mght be nvolved, t may be useful to speculate. For example, perhaps certan communtes have enjoyed stronger economc growth than others, whch has not affected credt access but has allowed more rapd frm level growth. There are n addton three types of frms when we group by unobserved frm level characterstcs. 16 The relatvely small number of frms of the second type grows dramatcally faster than frms of the frst type. What mght explan these results? After we control for observable characterstcs of frms, workers, and owners, there s evdently some characterstc partcular to frms that makes some more lkely to grow than others. For example, t mght be reasonable to suppose that entrepreneural talent or zeal has a strong effect on growth prospects. Smlarly, there s a substantal (and somewhat controversal) lterature on the relatonshp between cultural background and entrepreneural talent. If there are certan ethnc groups whose cultural backgrounds make them especally adept entrepreneurs, ths mght also be an unobservable characterstc that s leadng some frms to grow ndependent of access to credt. Regardng the observable characterstcs of frms, as a general rule the results from the OLS and the dscrete factor models dffer manly n terms of the magntudes of the coeffcents. Sector s an mportant determnant of growth. In partcular, busnesses engaged n textles, wood, and metalworkng sectors grew sgnfcantly more slowly than retalers. As expected from theory and earler lterature, both frm sze and frm age are nversely related to frm growth. Table 2 also reveals that human captal emboded n a frm s workers appears to have sgnfcant effects on that frm s growth prospects. Frms n whch the typcal worker has had formal tranng have average annual growth rates that are about 2.3 percentage ponts hgher than other frms. Smlarly, havng a better-educated workforce ncreases a frm s growth rate. Wth respect to owner characterstcs, frms wth female owners do not have sgnfcantly dfferent growth prospects from frms wth some male owners. Interestngly, an addtonal year of owner experence lowers the average annual growth rate by 0.08 percentage ponts. Whle ths s a rather small margnal effect (a busness run by an owner wth 30 years experence would have a growth rate about 1.6 percentage ponts lower per annum than an otherwse dentcal busness run by a propretor wth only 10 years of experence), the sgn s unexpected. Fnally, the dscrete factor model also provdes no evdence that access to credt has an apprecable effect on a frm s growth rate. That s, once we control for unobservable characterstcs of frms as well as other observable factors, credt does not make growth any more lkely. Evdently, growth s determned by the sector n whch a frm operates, ts ntal sze, ts age, and certan unobservable characterstcs of the frm and the communty n whch t operates. Ths suggests that factors such as entrepreneural zeal may be mportant for frm growth, but that access to credt s not.

12 IMPLICATIONS AND CONCLUSIONS 169 Gven the mportance of the mcro and small enterprse sectors to GDP and to natonal employment n most developng countres, t s mportant to consder what sorts of polces mght be undertaken to foster expanson of ths sector. One aspect of ths s growth of exstng MSEs. Our research suggests several lessons that may be of use to researchers and polcy makers. Frst, from a statstcal pont of vew t s mportant to account for unobserved heterogenety of frms and the stes n whch frms exst. Our results show that ths sort of heterogenety s statstcally mportant n the case of East Java, and t seems lkely that other data of ths nature from other countres would as well. Smple regresson seekng to explan frm growth may yeld msleadng results. In addton, our results suggest that polcy makers enthusasm for small frm credt could be msguded. Whle our data have some lmtatons, we see no evdence that frms wth access to credt grow more rapdly than those wthout such access. 17 Instead, frms n ths sample seem more lkely to grow as a result of the sector n whch they operate, ther ntal sze and age, human captal that has accumulated n frms workers, and unobservable characterstcs of frms and the communtes n whch they are located. The pont s that frms that grow may do so for other reasons than access to formal credt. If our results are correct, they suggest that donors and polcy makers mght better serve the goal of expanson of exstng small enterprses by reallocatng resources towards worker tranng programs, and towards mprovements n the natonal educaton system. Addtonal research on ths queston s certanly called for. For example, we do not know whether these results generalze to settngs outsde of East Java. In addton, the extent to whch access to nformal credt sources s a substtute for formal sources would add to the dscusson. Future research may also establsh whether access to formal credt sources helps the growth prospects of frms n sze categores outsde the fve to 19 worker category consdered here. ENDNOTES * The authors gratefully acknowledge the helpful comments of R. Todd Jewell and Jance Hauge 1. See, for example, Danels and Mead (1998). 2. For a summary of ths lterature, see Ledholm and Mead (1999). 3. See, for example, Tmberg (2003). 4. The survey was funded by the Japan Bank for Internatonal Cooperaton (JBIC), and was carred out by Development Alternatves, Inc. and the Regonal Economc Development Insttute. The feldwork began n late August and concluded n late September of Enumerators vsted kotas n the ctes of Surabaya, Malang, Madun, and Kedr and kabupatens n Malang, Jember, Madun, Lamongan, and Kedr. 6. There s no standard defnton of small enterprse n the lterature, although the World Bank s defnton s relatvely commonly used. A small enterprse by that standard s a frm wth as many as 50 workers, total assets as large as $3 mllon, and total sales up to $3 mllon. The defnton used n ths paper concdes wth that of the Government of Indonesa.

13 Our data are not part of a panel. Growth s calculated by means of retrospectve questons on the survey nstrument. Ths precludes the use of a dfference-ndfference approach such as that used by Banerjee and Duflo (2004). 8. The number of employees ncludes workng propretors, pad workers, unpad workers, and apprentces/tranees. Nearly 93% of all employees n the busnesses n ths sample are n the frst two categores only about 7% of the workforces of these frms comprse unpad workers. 9. Ths partcular tme perod s used because t represents the perod after the Asan fnancal crss of In partcular, most busnesses n our sample do not keep books. Recall bas s lkely to be a sgnfcant problem when usng revenues, profts, or assets as frm-level performance measures. Growth n terms of number of employees s much less lkely to suffer from ths weakness. 11. In order to examne the possblty that a lack of access to credt may have a larger effect on certan ndustres (e.g., captal-ntensve ones) than on others, we nteract the credt dummy wth the sectoral dummes. We fnd no evdence of any such effect, and so we exclude these regressors for reasons of parsmony. These results are avalable on request from the authors. 12. All human captal varables are measured as of the date of the survey. That s, our data preclude an examnaton of changes n human captal levels over tme. 13. Whle the survey dd gather nformaton on the educaton level and amount of tranng of the owner or owners of each busness, the large number of mssng values precluded the use of owner educaton dummes n the models. Therefore, we proxy human captal emboded n the owner by the years or experence he or she may have. 14. The smple correlaton (Pearson s) coeffcent between TITLE and CREDIT s (sgnfcant at the 99% level), whle the comparable correlaton coeffcent between TITLE and GROWTH s (not statstcally sgnfcant). 15. Approxmately 80.4% of the sample exsts n the frst sort of ste, 11.5% n the second sort, and 8.1% n the thrd. It s not possble to know whch partcular frms fall nto whch sort of ste. 16. Approxmately 80.2% of the sample s of the frst type, 1.7% s of the second type, and 18.1% s of the thrd type. As wth the ste-level factors, t s not possble to know whch partcular frms fall nto whch type. 17. Access to credt may allow mcro-frms to come nto exstence, even f the credt does not lead ndvdual frms to add employees. In ths manner, access to credt mght lead to aggregate employment growth n the MSE sector. REFERENCES Akn, J.S. and J.J. Rous Effect of Provder Characterstcs on Choce of Contraceptve Provder: A Two-Equaton Full Informaton Maxmum Lkelhood Estmaton. Demography 34, pp Banerjee, Abhjt V. and Esther Duflo (2004). Do Frms Want to Borrow More? Testng Constrants Usng a Drected Lendng Program. Draft Paper, Department of Economcs, Massachusetts Insttute of Technology. Berry, Albert, Edgard Rodrguez, and Henry Sandee (2001). Small and Medum Enterprse Dynamcs n Indonesa, Bulletn of Indonesan Economc Studes 37 (3):

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