A Spatial Model of the Impact of Bankruptcy Law on Entrepreneurship 1. Aparna Mathur 2 Department of Economics, University of Maryland at College Park

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1 A Spatal Model of the Impact of Bankrptcy Law on Entreprenershp 1 Aparna Mathr 2 Department of Economcs, Unversty of Maryland at College Park Abstract Ths s the frst paper that hghlghts the role of spatal nteractons, n the context of bankrptcy laws, n the entreprenershp decson. The focs of the paper s on small bsnesses. Small and medm enterprses represent between 96%-99% of all enterprses n most OECD economes, and play a large role n entry and ext n the OECD economes. However, as compared to some Eropean contres, the US stands ot as havng sgnfcantly hgher rates of entry and ext, especally for small frms. At the same tme, nlke the Eropean economes, the US has tradtonally had pro-debtor bankrptcy laws. Ths paper asks whether laws that facltate easy ext are an mportant consderaton n entry of small bsnesses. Ths paper stdes the decson of an ndvdal to begn (or end) a bsness n a partclar state, as a fncton of bankrptcy reglatons and other macroeconomc and bsness varables n that state as well as those n neghborng states. I se spatal econometrc technqes to model these nteractons. The stdy ses longtdnal data from the SIPP dataset. Model estmaton s comptatonally challengng de to the large nmber of observatons and the presence of a lagged endogenos varable, ndvdal random effects and state dmmes. The paper fnds that hgher bankrptcy exemptons n neghborng states lower the probablty of startng a bsness n the state of resdence. The bankrptcy exempton n one's own state has a sgnfcant and postve mpact on entreprenershp. Keywords: Entreprenershp, Bankrptcy law, Small frms, Spatal Econometrcs JEL Classfcaton: M13, K35, C21, C23 1 I wsh to express my grattde to my advsors Prof. Harry Kelejan, Prof. John Shea, Prof. Gnger Jn and Prof. Gelbach for ther advce and comments. Thanks also to Kartkeya Sngh, Dr. Devesh Roy and semnar partcpants at the Internatonal Atlantc Economc Conference, Chcago, for sefl comments. All errors are mne. The research was fnded by the Small Bsness Admnstraton and was condcted whle the athor was a stdent at the Unversty of Maryland, College Park. 2 Emal:mathr@econ.md.ed

2 1 Introdcton Ths paper analyzes the mpact of bankrptcy law on brths and closres of small bsnesses. The reason why we stdy small frms s that the OECD Small and Medm Enterprses (SMEs) Otlook 2002 reports that SMEs represent between 96%-99% of all enterprses n most OECD economes. The rates of gross job creaton and destrcton are hghest among small frms. Haltwanger, Davs and Schh (1993) fnd that the rate of gross job creaton n US manfactrng s nearly doble for frms wth less than 100 employees as compared to frms wth more than employees. However, there s no clear relatonshp between net job creaton rates and frm sze, snce small frms destroy a dsproportonately large share of exstng jobs. 3 Ths small bsnesses are responsble for mch of the chrnng or trnover n the US economy. Overall from 1989 to 1995, 2.9 mllon small frms were born, and 2.6 mllon small frms ded. 4 In Erope, too, employment growth s strongest n small enterprses. 5 Small frms play a large role n entry and ext n the OECD economes. If we defne overall job trnover as the sm of openngs and expansons, pls contractons and shtdowns, then another nterestng fndng emerges. As the OECD Jobs Stdy (1995) reports, openngs accont for the majorty of job gans n the US whle closres accont for the majorty of job losses. In other OECD economes, lke Italy and Germany, however, the majorty of job creaton and destrcton s acconted for by expanson and contracton of exstng establshments. Ths fndng s docmented by Bartelsmann, Scarpetta and Schvard (2003) as well, who fnd that entry rates n the US are sgnfcantly hgher than entry rates n Germany and Italy. Also, entry rates for small frms (less than 20 employees) are sgnfcantly hgher than for other sze classes of frms across these contres. 3 Between 1990 to 1995, 90.1% of the 371,547 net new establshments n the US were small frms (less than 500 employees), and very small frms (less than 20 employees) acconted for 68.4% of these. Drng the same perod, small frms created 76.5% of the 6.85 mllon net new jobs, whle the very small frms created 49%. 4 Small Bsness Growth by Major Indstry (SBA). 5 The report of the Eropean Observatory on SMEs (No.7, 2003) ctes contry stdes by Gallagher and Stewart (UK,1986), Heshmat (Sweden, 2001) and Hoht (Fnland, 2000), whch sggest that small frm dynamcs are smlar to the US n Eropean economes, and n some contres lke Sweden, Denmark and Fnland, there s a smlar negatve lnk between gross job creaton rates and frm sze. 2

3 A qeston that arses therefore s whether laws that determne the costs and benefts of ext, sch as bankrptcy laws, are mportant to entry of small bsnesses. The US s nsal n havng very pro-debtor bankrptcy laws. For example, whle US bankrptcy law provdes for dscharge of debts of faled bsnesses when the bsness owner fles for bankrptcy, German bankrptcy law does not. The owner of a faled bsness n Germany who fles for bankrptcy contnes to be lable for the bsness' debts and can be forced to repay these debts from ftre earnngs for many years after flng. The dfferental mpact of bankrptcy law s evdent from the fact that among the ndstralzed contres, only the US has a hgh and rapdly rsng bankrptcy flng rate. 6 The focs of ths paper s on US personal bankrptcy law. The US personal bankrptcy system fnctons as a bankrptcy system for small nncorporated bsnesses as well as consmers. If a frm fals, the entreprener has an ncentve to fle for bankrptcy nder Chapter 7, snce both bsness debts and the entreprener s personal debts are dscharged. The entreprener mst gve p assets above a fxed bankrptcy exempton level for repayment to credtors. However, ftre earnngs are entrely exempt. 7 These exempton levels are set by the states and vary wdely across states and over tme. Ths the US provdes a natral panel to analyze the mpact of bankrptcy law on entreprenershp. The effect of hgh exemptons, as docmented n the lteratre, s twofold. Fan and Whte (2003) have shown that the wealth nsrance effect of exemptons encorages entreprenershp, whle Berkowtz and Whte (2004) fnd that small frms are more lkely to be dened credt f they are located n states wth nlmted exemptons. My reslts confrm those of Fan and Whte (2003), that despte the possblty of a negatve credt access effect, entrepreners wold prefer to be n states wth hgh, rather than low exemptons. 6 Fan and Whte (2003) 7 Proposed changes n the law (Blls HR333 and S420) make t harder for ndvdals above a certan medan ncome to fle for bankrptcy, and place a cap on the maxmm exempton lmt. Only wage earners whose hosehold ncomes are below ther state's medan (the U.S. medan for a famly of for was recently $59,981) wll be permtted to fle nder Chapter 7. 3

4 The nqe contrbton of ths paper s that t stdes the effect of bankrptcy law n a spatal settng, whereby entrepreners choose the optmal locaton of ther bsness from a choce of locatons ncldng one s own, and neghborng states. Ther decson to start (or end) the bsness s therefore a fncton of bsness condtons n these competng locatons. Introdcng spatal effects s not wthot bass. Holmes (1998), Karvel, Msl and Sebastan (2002) and other athors, provde evdence that bsness relocaton decsons cold be prompted by competng bsness condtons n neghborng states. I make se of a detaled longtdnal dataset that tracks ndvdals over a perod of three years and has monthly nformaton on labor force characterstcs, state of resdence and demographc characterstcs. Hence I am able to know the exact locaton of the ndvdal at the tme of startng (or endng) a bsness. That frther allows me to se state bsness condtons, sch as the bankrptcy exempton level, as factors affectng the transton to entreprenershp. The paper fnds that hgher bankrptcy exemptons n neghborng states lower the probablty of startng a bsness n the state of resdence. The bankrptcy exempton n one's own state has a sgnfcant and postve mpact on entreprenershp. The plan of the paper s as follows. The next secton provdes an overvew of the stdy. Secton 2 provdes a lteratre revew and evdence for spatal effects. Secton 3 develops a theoretcal model, and provdes detals of the emprcal methodology. Secton 4 provdes reslts for bsness starts and closres. Secton 5 otlnes dfferent specfcatons and Secton 6 concldes. 4

5 1.1 Overvew In ths paper, I propose a two-part stdy. The frst part of the paper wll focs on job creaton throgh the brth of small bsnesses. The second wll focs on job destrcton throgh the death of small bsnesses. In partclar, I look at the decson of a cross sectonal nt (an ndvdal or a famly) to ether begn or end a bsness n a partclar state, as a fncton of bankrptcy reglatons and other bsness and macroeconomc varables n that state as well as those n neghborng states. I propose to expand pon models n the lteratre, most notably Fan and Whte (2003), n a nmber of ways. Frst, I wll allow for spatal nteractons. There has been no paper to my knowledge that has looked at spllover effects from adjonng states on the probablty of startng or endng a bsness n a partclar state. I beleve that these effects are mportant, snce ndvdals have the opton to move and locate ther bsnesses n states that offer better condtons, sch as hgher exemptons or lower tax rates 8. To allow for these nteractons, I wll ntrodce a weghtng matrx that pts a postve weght on bsness condtons n adjonng states. We expect that the probablty of startng (endng) a bsness n a partclar state s nversely (drectly) related to bsness condtons n adjonng states. Second, I wll be sng addtonal varables that have not been consdered n prevos lteratre. To the extent that some ndvdals move from nemployment to startng a bsness, polces relatng to the level of nemployment benefts wll also be mportant. Self-Employment Assstance programs for people recevng nemployment benefts vary by state and may also play a role n an ndvdal s decson to start a bsness n a partclar state. 9 Fnally, I examne f the cost of health nsrance for the entreprener has an mpact on the decson to start a bsness. 8 I assme that ndvdals start or end bsnesses n the state n whch they resde. 9 Self-Employment Assstance programs offer dslocated workers the opportnty for early re-employment. The program s desgned to encorage and enable nemployed workers to create ther own jobs by startng ther own small bsnesses. Under these programs, States can pay a self-employed allowance, nstead of reglar nemployment nsrance benefts, to help nemployed workers whle they are establshng bsnesses and becomng self-employed. Ths s a volntary program for States and, to date, fewer than 10 States have establshed and crrently operate Self Employment Assstance programs. (Sorce: US Department of Labor) 5

6 Thrd, my stdy s based on Srvey of Income and Program Partcpaton data relatng to two panels: and In ftre drafts, I ntend to extend the paper by sng data relatng to the perod In 1978, a new Federal Bankrptcy code allowed each US state to set ts own bankrptcy exempton level, whch they all dd by It may be nterestng to look at 1983 data to see the mmedate mpact of these exemptons on ndvdal decsons to start or end a bsness. 10 Moreover, by poolng data for these years wth , I get more varaton n state polces over tme. My formlaton of the model allows for state dmmes and ndvdal random effects. I specfcally test to see whether the state dmmes are sgnfcant. My formlaton of the model has a rcher set of state level varables than other stdes to flly captre all of the state level effects. Fan and Whte (2003) n ther panel data model consdered only a random effects specfcaton. They dd not nclde state dmmes, and dd not test to see f ther state varables were sffcent to captre all the state effects. Fnally, I ntrodce a lagged dependent varable to control for the possblty that ndvdals who owned (or dd not own) a bsness n the past may be more lkely to start (end) a bsness today. The contrbton of the paper s also methodologcal. As descrbed n detal n Appendx A.1, the estmaton of a probt model contanng random effects, a lagged dependent varable and state dmmes, wth a large nmber of cross sectonal nts and a relatvely short tme dmenson, reqres specal manplatons and programs for emprcal mplementaton. In partclar, separately dentfyng the effect of the lagged dependent varable and nobserved heterogenety (the random effect) reqres modelng of ntal condtons, whch frther complcates the estmaton procedre. None of the papers srveyed here have ntrodced all of these featres n a sngle model. 10 If possble, I wll try to obtan data for before 1978, and see f reslts are sgnfcantly dfferent. 6

7 2 Lteratre Revew In ths secton, I wll revew some of the theoretcal and emprcal lteratre that has researched the role of varos demographc, hman captal, and fnancal consderatons n the decson to become an entreprener. Most prevos stdes have examned the mportance of the earnngs dfferental between entreprenershp and pad employment, taxaton, lqdty constrants, and ntergeneratonal transfers. As ths revew shows, there has been relatvely lttle research on the role of bankrptcy law as an mportant factor n spawnng nnovaton and employment, and frther, there has been no paper, to or knowledge, that has sed a spatal econometrc model to stdy the same. There have been two papers of note that have looked at the role of bankrptcy exemptons. The frst s Fan and Whte (2003) and the other s Georgells and Wall (2002). Fan and Whte (2003) consder the mpact on entrepreneral actvty of bankrptcy exemptons, along wth other varables that have been sed extensvely n the lteratre. They fnd a sgnfcant and postve relatonshp between the probablty of startng a bsness and the exempton level. The probablty of startng a bsness rses by abot 22% from the lowest exempton states to the hghest exempton states. Ther reslts also sggest that the probablty of endng a bsness s hgher n states wth hgh bankrptcy exempton levels, ncreasng by abot 18% between the lowest exempton states and the nlmted exempton states. However the reslts for endng a bsness are not statstcally sgnfcant. As ponted ot before, Fan and Whte do not consder spatal effects. For nstance, f neghborng states have hgher exemptons, ths may nflence a famly s decson to start or end a bsness n ther own state. They also dd not test to see f state fxed effects are mportant. In my model I fnd that ncldng the spatal exempton varables cases the own exempton to become nsgnfcant. Hence what appears to be mportant s not the exempton level per se, bt the own exempton relatve to neghbor exemptons. Georgells and Wall (2002) do not look at mcro data on ndvdals or famles. Instead they defne the rate of entreprenershp n a state as the proporton of the workng age poplaton that s classfed as non-farm propretors. They regress ths on state polcy 7

8 measres, controllng for state and tme dmmes and for measres of bsness and demographc condtons, sng US state panel data for The bsness condton measres nclde the state s nemployment rate, per capta real ncome and ndstry employment shares. The polcy measres nclde the maxmm margnal tax rate and the bankrptcy homestead exempton. The reslts ndcate that at very low and hgh ntal levels, an ncrease n the homestead exempton redces the nmber of entrepreners. In the md-range of homestead exempton rates, there s a postve relatonshp between the exempton level and entreprenershp. Frther, only for relatvely hgh homestead exempton rates wll the level of entreprenershp be hgher than f there were no exempton at all. Ths reslt s dfferent from that of Fan and Whte (2003), who fnd the relatonshp between the exempton level and homeowners probablty of ownng a bsness to be monotoncally ncreasng. Georgells and Wall (2002) also fnd sgnfcant state fxed effects. Snce ther paper deals wth data aggregated at the state level, Georgells and Wall are nable to analyze factors that may be more relevant at the ndvdal level, sch as famly wealth, the age of the entreprener and so on. Moreover, even at the macro level, they do not consder factors sch as the percentage of non workers n each state, whch I ncorporate. 11 Other papers n ths lteratre test for lqdty constrants, controllng for macroeconomc varables. Holtz-Eakn, Jolfaan, Rosen (1994), Evans and Leghton (1989) and Evans and Jovanovc (1989) fnd that hgher nhertances and lqd assets ncrease the lkelhood of entreprenershp. Another strand of research has focsed on the dfferental tax treatment of ncome earned whle workng for others verss ncome from selfemployment. Some noteworthy papers nclde Cllen and Gordon (2002) and Brce (1998), who fnd a postve relatonshp between personal tax rates and entreprenershp. The role of race and work hstory has also been consdered n the lteratre on selfemployment. Meyer (1990) and Blanchflower and Meyer (1992) fnd that blacks are sgnfcantly less lkely to be self-employed than whtes, whle older, marred, male workers are more lkely to be self-employed. Moreover, Evans and Leghton (1989) 11 Prevos research has shown that the probablty of movng from a wage and salary occpaton to ownng a bsness s lower for non members (Brce,1998 ). 8

9 conclde that people who have had low earnngs n the past or who have shorter job tenres are also more lkely to be self-employed. There are other papers that have looked specfcally at the factors leadng to closre of bsnesses. These are very smlar to factors that are sgnfcant for startng bsnesses, sch as avalablty of fnancal captal, hman captal n the form of sklls of the entreprener and the relatve attractveness of beng a wage earner verss ownng a bsness. Kangasharj and Pekkala (2001) fnd that frms rn by more edcated ndvdals have a hgher probablty of srvval. Also, the probablty of ext s lower for frms rn by more edcated ndvdals drng recessons, bt hgher drng booms. One reason for ths may be that hghly edcated ndvdals face a hgher otsde demand for ther labor drng economc ptrns than less edcated ndvdals. In another paper, Pfeffer and Reze (1998) fnd that frm srvval rates are lower f a prevosly nemployed ndvdal fonded the frm. None of these papers have looked at the role of bankrptcy exemptons, and they do not consder the role of regonal dfferences and spatal nteractons n determnng ths probablty. 2.1 Evdence for Spatal Effects The Censs Brea (2000) report on state-to-state mgraton flows between states that the largest mgratons were to adjacent or nearby states. For nstance, Arzona s largest mgraton nflow was from Calforna and ts largest otflow was to Calforna. Smlarly, there were large flows between New York and New Jersey, Calforna and Nevada, and so on. A Goldwater Polcy Insttte Report (2004) frther fnds n censs data that states wth the hghest total tax brdens sffered a net loss of more than 1,700,000 resdents between 1995 and 2000 and that bsness clmate sgnfcantly nflenced mllons of hosehold decsons to move across state lnes drng the 1990s. Moreover, Ell and Sbramanan (1999) fnd that consderatons of bankrptcy laws nflence nterstate mgraton. They estmate that roghly 1% of moves to states wth hgher exempton lmts are motvated by consderatons of dfferences n bankrptcy 9

10 laws. Ths corresponds to approxmately moves. These fgres are roghly the magntde of the estmates obtaned by other athors for welfare related mgraton. Karvel, Msl and Sebastan (1998) stded bsness ot mgraton from Mnnesota. Of the 183 frms srveyed, eghty-two (44.8 percent) went to Wsconsn, forty-sx (25.1 percent) went to Soth Dakota, thrty-for (18.6) percent went to North Dakota, and twenty-one (11.5 percent) went to Iowa. Bsness taxaton (workers compensaton rates, commercal-ndstral property taxes, corporate ncome taxes, and sales taxes) consttted the prmary reason for relocaton. Local and state government ncentves from neghborng states comprsed the next most mportant reason for bsness otmgraton decsons, whle the absence of Mnnesota state and local government ncentves to compete n retanng or expandng bsnesses were the thrd most mportant set of reasons for the respondents decsons to leave Mnnesota. Karvel et al (1998) also cte a prevos small-scale stdy carred ot by the Center for Bsness Research, whch examned a sngle border cty Hdson, Wsconsn. Hdson was selected becase t was known that a nmber of Mnnesota bsnesses had relocated or started bsnesses there. The major fndng of the Hdson stdy was that the two most mportant reasons for locatng a bsness n Hdson rather than Mnnesota were hgh workers compensaton rates and commercal-ndstral property taxes n Mnnesota. Fnally, Holmes (1998) provdes evdence that state polces play a role n the locaton of ndstry. The paper classfes a state as pro-bsness or ant-bsness dependng on whether or not the state has a rght-to-work law. The paper fnds that on average there s a large abrpt ncrease n manfactrng actvty when crossng a border from an antbsness state nto a pro-bsness state. Other papers, lke Glaeser (2001) and Breckner (1999), also stdy the effect of bsness ncentves, sch as taxes, on locaton decsons by frms. 10

11 3 Detals of Proposed Stdy 3.1 Theoretcal Model In ths secton, I develop a theoretcal model for my stdy, whch ses the basc framework n Fan and Whte (2003) as a startng pont. However, nlke that paper, ths model consders bsness condtons n neghborng states and demand condtons. The model analyses an ndvdal consderng whether to start p a new bsness n the home state, h, or to locate n another, neghborng state, n. Prodcton costs are assmed to be the same n each locaton. We assme, however, that there s a cost of movng from the home state to the neghborng state, whch s proportonal to the dstance moved. There are two perods. In perod 1, the ndvdal nvests n a project that has a cost of I. The potental entreprener s ntal wealth s gven by W, whch he nvests n the project n perod 1, and he ncrs a fxed amont of debt B>0. The debt s nsecred, has an nterest rate r (where ndexes the state), and s de n perod 2. The retrn on the project s realzed n perod 2 and s ncertan at the tme of nvestment de to ncertan demand condtons n perod 2. The nverse demand fncton for perod 2 s gven by p 2 = a-q 2 + =h,n ~f() (3.1.1) Where p and q denote prce and qantty n locaton, a s a postve constant, and є [, ] s a stochastc demand component, wth E[]=0 and var[]=v. We assme that the movng decson s made pror to the realzaton of demand shock,. We also assme that <X, where X s the bankrptcy exempton n state. The cost of prodcton s gven by C = cq 2 =h,n (3.1.2) Frms wll not prodce f p < c Ths can be shown as follows: 11

12 Let π = (a-q 2 +-c)q 2 denote the level of profts. (3.1.3) The vale of q 2 that maxmzes ths proft fncton s gven by * q2 a + c = (3.1.3a) 2 Ths s monotoncally ncreasng n. If the entreprener fles for bankrptcy then the debt of B(1+r ) wll be dscharged bt he has to gve p all assets above the fxed exempton lmt X, to be sed for repayment to credtors. Then, θ = W-I+B+π -fd (3.1.4) represents the realzed gross wealth of the ndvdal at the end of perod 2. Note from (3.1.3a) that both the maxmsed level of profts, π ( q * 2 ) and θ, are monotoncally ncreasng n. fd represents the cost of movng, whch s zero f the ndvdal does not move.e d h =0 for home state. The entreprener's net wealth at the end of perod 2 s θ -B(1+r ) f they don t fle for bankrptcy, and X f they do. Ths the level of gross wealth at whch he s ndfferent between flng and not flng s gven by θ =X +B(1+r ) (3.1.5) Hence f θ < θ, the ndvdal wll fle for bankrptcy. Gven ths, the wealth that the ndvdal wll end p wth n perod 2 wll be determned both by the decson to fle for bankrptcy, as well as the exempton level. If the ndvdal fles for bankrptcy and hs wealth s greater than the exempton level, he wll be left wth exactly the exempton amont. If he fles and hs wealth s less than the exempton level, he wll be left wth hs p < c 2 < c a + q2. However, snce the vale of q 2 that maxmzes the proft fncton s gven a + c by, ths = c a + 2q2, contradctng the above statement. 2 12

13 actal wealth. Ths nformaton can be smmarzed n the followng way. The entreprener has wealth θ f θ <X, (3.1.6) X f X θ θ, (3.1.7) θ -B(1+r ) f θ > θ (3.1.8) Snce θ, s monotoncally ncreasng n, correspondng to θ, s a nqe realzaton of, whch we denote by *. Ths f s less than *, the ndvdal wll fle for bankrptcy, and f t s hgher than *, he wll not. Frther, f the ndvdal does fle for bankrptcy, condtons (3.1.6) and (3.1.7) ndcate that he can ether be left wth the exempton amont, or hs actal wealth. We denote by θˆ the level of wealth sch that θ = X. Agan, correspondng toθˆ there s a nqe realzaton of, whch we denote by û. If < û, the level of wealth s below X and the ndvdal s left wth exactly θ, and f > û, the ndvdal s left wth X. CREDIT MARKET The lenders n the credt market are assmed to be rsk netral. They face a fxed opportnty cost of fnds denoted by r f, and they are wllng to lend as long as they earn zero expected profts. If the realzaton of s between û and *, the ndvdal fles for bankrptcy and the lenders receve ( θ X ), whle f < ˆ, lenders receve nothng. Ths the lenders zero proft condton s gven by * L ( θ X ) f ( ) d + B(1 + r ) f ( ) d B(1 + r ) = 0 ) * f =h,n (3.1.9) Lenders set the nterest rate to satsfy ths eqaton, otherwse they do not lend. To stdy the effect of changes n exemptons on the rate of nterest charged by credtors, we take the total dervatve of (3.1.11) to get It can be shown that other terms, nvolvng dervatves of the lmts, cancel ot. 13

14 dr dx = * * ˆ f ( ) d Bf ( ) d >0 =h,n (3.1.10) Hence lenders wll charge hgher rates of nterest on loans as exemptons ncrease, snce the amont that they can reclam at the tme of bankrptcy s lower. INDIVIDUALS The ndvdal chooses whether to start a bsness at home, to start a bsness n the neghborng state, or to start no bsness and receve U(W`). The expected tlty from startng a bsness n state s gven by, ˆ * U ( θ ) f ( ) d + U ( X ) f ( ) d + U ( θ B(1 + r )) f ( ) d =h,n ˆ * where the lmts are as defned before. (3.1.11) The ndvdal wll be wllng to move f the expected tlty from movng (EU M ) s greater than U(W') and greater than the expected tlty from not movng (EU NM ). Assmng that entreprenershp s more attractve than wage employment, the ndvdal moves f EU=EU M - ˆ * n n EU NM = U ( θ ) f ( ) d + U ( X ) f ( ) d + U ( θ B(1 + ˆ h n * ˆ n n * U ( h ) f ( ) d + U ( X h ) f ( ) d + U ( θ h B(1 + h ˆ h * h n h n r )) f ( ) d θ r )) f ( ) d >0 (3.1.12) n - Note that the the cost of movng s nclded n the defnton of θ n.next we consder how changes n the exempton level n the neghborng state affect the attractveness of 14

15 movng, gven by EU. To do ths, we take the total dervatve of (3.1.14) and sbsttte for dr from (3.1.12) and fnd, 14 dx d EU dx n Smlarly for the home state: f ( ) d n* ˆ n = U ( X n ) f ( ) d U ( θ n B(1 + rn )) f ( ) d (3.1.13a) ˆ n n* f ( ) d n* n* d EU dx h = - ( U X ) ( h h* f ) d U ( h B(1 + ˆ h h* h h* ˆ h h* f ( ) d ( θ r )) f ( ) d ) (3.1.13b) f ( ) d The sgn of these expressons are, respectvely, the sgns of U ( X n U ( θ n B(1 + rn )) f ( ) d n* ) n* f ( ) d > 0 (3.1.14a) - ( U ( X h U ( θ h B(1 + rh )) f ( ) d h* ) ) < 0 (3.1.14b) h* f ( ) d The effect of neghbor's exempton on the attractveness of movng s postve. The expresson (3.1.14a) eqals the entreprener's margnal tlty of wealth when they fle for bankrptcy and keep X n mns ther average margnal tlty of wealth when they avod bankrptcy and keep θ B 1+ r ). For rsk averse entrepreners, ths expresson n ( n mst be postve, snce wealth when flng for bankrptcy s lower than wealth when avodng bankrptcy, so ther margnal tlty of wealth mst be hgher when they fle for bankrptcy. Ths as long as credt s avalable, an ncrease n the neghbor s exempton 14 Note that the total dervatve nvolves other terms, lke dervatves of the lmts, whch cancel ot. 15

16 level ncreases the attractveness of becomng a bsness owner n the neghborng state, even thogh credt s more expensve when the exempton lmt s hgher. 15 In other words, ndvdals are less lkely to start bsnesses n own state f bsness condtons n neghborng state are better. At the same tme, expresson (3.1.14b) sggests that an ncrease n own state exemptons redces the attractveness of movng. 3.2 Emprcal Model In ths paper I do a two-part emprcal stdy. I frst examne small bsness openngs, and then consder small bsness closngs. I se the same strctre for both parts. I adopt a probt formlaton wth a latent varable specfcaton, allowng for ndvdal random effects and testng the sgnfcance of the state dmmes n dfferent specfcatons. Snce the strctre of the model s the same for openngs and closres, for expostonal prposes I dscss only the model for small bsness openngs. Model estmaton s dscssed flly n the appendx. My model can be specfed as * Y t = δ 0 + δ 1 D t1 + δ 2 D t2 + + δ 44 D t39 + X t B 1 + (W t. Z t )B 2 +(Y t-1,2 )B 3 +ε t ; =1,..,N, t=3..t (3.2.1) * Y t =1 f Y t > 0 Y t =0 f Y * t 0 ε t = α + t For vales n years t=1,2, data on Y t-1,2 s not avalable. For these observatons, I specfy: Y * t = γ 0 + γ 1 D t1 +γ 2 D t2 + +γ 44 D t39 +X t B 4 + (W t. Z t )B 5 +ε t ;=1,.,N, t=1,2 (3.2.1a) Y t =1 f Y * t >0 Y t =0 f Y * t 0 ε t = α + t 15 One can also show that the model mples that the net expected tlty s decreasng n the cost of movng (or dstance moved) and that hgher expected profts, or better demand condtons n neghborng state, ncrease the attractveness of movng. 16

17 The sbscrpt relates to the cross sectonal nt. The sbscrpt t relates to the tme perod. My latent varable s Y t * and my observed dependent varable s Y t. Y t relates to a cross sectonal nt s decson (for expostonal prposes) to start a bsness n year t. In partclar, Y t =1 f the th cross sectonal nt starts a bsness n year t, and 0 otherwse. Note that the sample conssts only of people who dd not own a bsness at the begnnng of year t. The lagged dependent varable Y t-1,2 ndcates whether the hosehold owned a bsness at some pont n the precedng two years. 16 The cross sectonal nt s assmed to start a bsness n the state n whch t resdes. Y t s explaned n terms of the latent varable Y t *, whch captres the factors responsble for the decson. X t s the vector of explanatory varables relatng to cross sectonal nt n year t. These varables nclde both state-level varables, sch as nemployment beneft varables and bankrptcy exempton measres, and also famly level varables sch famly wealth, entrepreners labor or bsness ncome, and other demographc characterstcs. These are explaned n detal below. B 1 s a coeffcent vector. W t. s a 1x40 row vector that assgns a postve weght to neghbor states, as defned below. The weght assgned to all other states s zero. The reason why there are only 40 states s that the SIPP dataset dentfes 41 ndvdal states and the Dstrct of Colmba. The nne other states are aggregated nto three grops. 17 However, n my model, I drop observatons for Hawa (snce no neghbors can be defned), and New Mexco and DC. 18 Frther, I add New Hampshre to the state nt comprsng Mane and Vermont, and defne Rhode Island and Connectct as one state nt. 19 Neghborng states are defned as those that are adjacent to the state n whch the cross sectonal nt resdes. I assme that the th nt wll not consder movng to states that are not adjacent, and I assgn these 16 Snce the data s avalable monthly, I defne a bsness start as a person who dd not own a bsness n Janary of that year, bt dd own a bsness at some pont drng the year. 17 These grops are (1) Mane and Vermont; (2) Iowa, North Dakota and Soth Dakota; (3) Alaska, Idaho, Montana and Wyomng. 18 These states are dropped de to nsffcent observatons, and they cannot be merged wth neghbors snce ther polces are not smlar. 19 New Hampshre les between Mane and Vermont, so t forms a natral nt. Rhode Island has few observatons and s smlar to Connectct n ts polces. 17

18 states a weght of zero. In dfferent specfcatons of the model, I experment wth assgnng a postve weght to all neghbor states or only to those neghborng states that have more favorable bsness condtons than the state n whch the cross sectonal nt s crrently located, snce these are argably the only states the th nt wold consder as an alternate locaton for the bsness. The formlaton of the weghtng matrx s explaned n detal below. Z t s a 40xK matrx of observatons on K state-level macroeconomc varables. These varables vary across tme and state. They are explaned n more detal below. B 2 s a Kx1 parameter vector. ε t s the dstrbance term n the latent varable formlaton. It has an error components strctre, where the process { t } s d over and t, and the cross sectonal component α s d over. Fnally, D t1,., D t39 are dmmy varables for ndvdal states or gropngs of states. 3.3 Defnton of Varables The vector of explanatory varables ncldes state-level varables as well as demographc varables 20. In partclar, X t ncldes the followng: 1. Bankrptcy Exempton: These are the bankrptcy exemptons that the cross sectonal nt faces n ts home state. I se the homestead exempton as well as the personal property exempton. The homestead exempton s an exempton for eqty n owner occped hosng. As shown n Fgre 1 for the year 1996, ths vares wdely among states, wth some states havng no exempton and seven states havng nlmted exemptons. Most states also have exemptons for hosehold belongngs, eqty n vehcles, retrement acconts, and a wldcard category that can be appled to any type of asset. The exempton levels have changed over tme n many states. For nstance between , 28 states effected changes to ther homestead and/or property exemptons. These 20 For the groped states, I se sample poplaton weghted averages of these varables. 18

19 exemptons provde partal wealth nsrance to entrepreners, and are therefore expected to encorage entreprenershp. 2. State per capta ncome: Ths varable has been changng over tme for all states. Hgh state ncomes may be assocated wth hgh demand, encoragng entreprenershp. At the same tme, ths may mean hgher ncomes for crrent job earners, and ths transtons to entreprenershp may be redced. 3. The top margnal state ncome tax rate, whch has changed over tme for 25 states n the perod Most stdes fnd that hgh personal taxes encorage transtons to entreprenershp, except for Georgells and Wall (2002), who fnd the relatonshp to be U-shaped. 21 Hgh personal taxes encorage tax avodance whch s easer for bsness owners than for salary workers. 4. State nonzaton rate, state nemployment rate and the proporton of poplaton n non farm employment. Hgh state nonzaton rates may dscorage entreprenershp as wages may be hgher, whle dfferent stdes fnd dfferng effects of nemployment rates. The nonfarm employment rate s entered to correct for the fact that bankrptcy law s dfferent for farmers. 5. The self employment or nemployment assstance benefts for each state. For the nemployment benefts, I consder the replacement rate (the rato of the average nemployment beneft pad ot to the average weekly wage) n each state. Ths varable vares over tme for 25 states n the sample. The data s avalable from the US Department of Labor. The sgn on ths coeffcent s ambgos snce the avalablty of generos benefts may dscorage any knd of movement ot of nemployment, bt at the same tme, the fnancal assstance provded may encorage entreprenershp. 6. Indvdal and famly level varables, ncldng martal stats, age, race, health nsrance coverage, employment stats and edcaton level, as well as famly ncome from wealth and whether the famly owns ther home. The matrx Z t ncldes observatons on state-level varables that may be mportant for startng a bsness n neghborng states, sch as 21 Cllen and Gordon (2002), Brce (1998) 19

20 1. The bankrptcy exempton varable 2. Per capta ncome 3. The maxmm margnal state ncome tax rate Fnally, I descrbe the Nx40 spatal weghts matrx, W t =[W' 1t.,..,W' Nt. ]'. At any tme t, the th row of ths matrx s gven by W t., whch specfes neghborhood sets for each observaton. The j-th element of W t, namely, w j,t, s postve f j s a neghbor of, and s zero otherwse. I consder dstance and poplaton weghted averages of exemptons, per capta ncomes and tax rates n neghborng states, and also smple averages of these varables. For nstance, for dstance weghts, 1 dstjt wjt = where k s the nmber of neghbor states for ndvdal. 1 dst k kt By conventon, a cross sectonal nt s not a neghbor to tself, so that the dagonal elements of W t are all zero.e w,t =0. I wll be sng a scale normalzed verson of the weghtng matrx. I also experment wth assgnng a postve weght to only those neghbors that have the hghest exemptons. 3.4 Data Sorces and Descrpton In my stdy, I se longtdnal datasets avalable from the Srvey of Income and Program Partcpaton (SIPP), pblshed by the Censs Brea. I se the SIPP longtdnal datasets for and , and I present reslts for the pooled panel , as well as for the sb-sample SIPP s a mlt-panel longtdnal srvey of adlts, measrng ther economc and demographc characterstcs over a perod of approxmately three years. Persons selected nto the SIPP sample contne to be ntervewed once every for months over the three years of the panel. At the tme of the ntervew they are asked qestons relatng to the prevos for months. Ths the data s avalable monthly for each person n the panel. For nstance, the 1993 SIPP panel conssts of approxmately 120,000 ndvdals who were ntervewed n 1993, 1994 and I wll look at a balanced panel of cross sectonal nts that have data avalable for all three 20

21 years. Thogh the data s avalable at an ndvdal level, t s possble to nqely dentfy a famly or a hosehold, and constrct famly level varables. The data gves nformaton abot the state (thogh not the conty) n whch the ndvdal s located at the tme of the ntervew. Ths SIPP records movement of members n the sample and changes n the hosehold composton. The smmary statstcs n Table 1 reveal sample characterstcs for the panel. SIPP ntervews all ndvdals above 15 years of age n the sample hosehold. The sample has a larger proporton of whtes, whle Blacks form only 13% of the sample. Abot 30% of the sample has attended college, whle abot 38% are marred. Abot 59% of the overall sample (and 70% of the bsness owners) own a home, ths jstfyng the se of the homestead exempton as an mportant factor n the analyss. Over the entre perod, abot 1.5% of the sample started a bsness, whle 1.9% ended one. Fgre 3 profles bsness owners n the sample. Controllng for sample shares of the relevant grops, a large fracton of bsness startps are by whte males. College edcated ndvdals and marred men are more lkely to start bsnesses, as are people yonger than 50. The correspondng statstcs for bsness closres (not shown) are the reverse of those for bsness startps; whte, college edcated, yong and marred males are less lkely to close down ther bsnesses. As shown n Fgre 2 and Table 2, there appears to be a large and postve correlaton between bsness starts and closres across states n dfferent years. In partclar, even controllng for poplaton sze, states wth hgh start p rates, sch as Calforna and Florda, also have hgh closre rates. Frther, Fgre 2 sggests a mld postve correlaton between exemptons and startps (.0139), and exemptons and closres (.0036) (controllng for sample state sze). 21

22 4. Regresson Reslts Bsness Start Reslts In ths secton, I present regresson reslts for bsness starts, estmated wth the random effects probt descrbed n detal n the appendx. I defne a dmmy eqal to one f the cross sectonal nt dd not own a bsness at the begnnng of the year, bt does own a bsness at some pont drng the crrent year. The sample s ths restrcted to all ndvdals who dd not own a bsness at the begnnng of the year. Table 3 presents reslts wth the lagged dependent varable and the health nsrance varables, bt wthot the spatal varables. Table 4a presents reslts wth the spatal varables for the pooled panel and for the panel separately. 23 The sample sze s 120,219 ndvdals over the perod , and 312,845 for the pooled panel. 24 Estmaton Technqe The estmaton strategy nvolves the followng steps. Step 1: Followng the specfcaton otlned n Appendx A.1, we pool data across the years , bt allow for dfferent coeffcents n 1995 for whch we have data on lagged bsness ownershp avalable. Note that the effect of state-level condtons on entreprenershp can be captred by pttng n ether state-level varables, or state dmmy varables for each year for the 40 state nts defned n the sample. My hypothess s that my state varables, whose vales vary over tme, are sffcent to accont for all the state effects. There are overall 40 state nts, and I have a tme ntercept and 16 state varables, whch leaves 23 degrees of freedom. Ths, I specfy the regresson eqaton n each year wth all the demographc varables, 16 state varables (own state and weghted neghbor state), a tme ntercept, and 23 state dmmes. The tme ntercept s consdered becase I allow the ntercept to change along wth the coeffcents of all the state dmmy varables. The frst hypothess 22 The state nts are as defned n Table The estmated varances for the panel were larger than for , hence poolng mposes the arbtrary restrcton of eqal varances. That s why I report reslts for the panel separately as well, rather than jst the pooled panel. 24 Note that the 1993 panel covers the perod October 1992-Dec 1995, so I have only three years of fll data. 22

23 that we test s whether the (23 3) coeffcents relatng to the state dmmy varables for each year, are jontly sgnfcant n a regresson whch ncldes all of my 16 state varables. 25 The jont test of sgnfcance of the state dmmy coeffcents revealed the state dmmy varables to be nsgnfcant, ths the model s specfed wthot them. A frther test of the model nvolved testng for eqalty of the coeffcents on state-level varables n 1995 and The ch sqare statstc was small, leadng s to accept the hypothess that the coeffcents are dentcal. Ths the model s specfed wth tme varyng coeffcents for the demographc varables, bt tme-nvarant coeffcents for the state-level varables for all three years. Step 2: The procedre for model estmaton and the treatment of state dmmes was replcated for the panel. Testng revealed the state dmmes to be jontly nsgnfcant. I then tested for smlarty of the coeffcents on state-level varables n 1998 and , and conclded that they were nsgnfcantly dfferent from each other. Step 3: Fnally, I pooled across the two panels. The coeffcents on state-level varables for were not sgnfcantly dfferent from , hence the pooled model allowed for tme-nvarant coeffcents for state-level varables for all sx years. Reslts I frst estmated the model wthot the spatal varables, as shown n Table 3. The coeffcent on exemptons s sgnfcant and postve at the 1% level, smlar to Fan and Whte (2003), and Georgells and Wall (2002). The predcted probablty of startng a bsness s ncreasng n the exempton level. 26 I also get good reslts for the lagged dependent varable (postve and sgnfcant), as well as the health nsrance varables. 25 The sal Hasman specfcaton test dd not work de to nmercal problems. Also, nclson of all state dmmes n ths specfcaton wold have lead to collnearty problems. 26 On average, an ncrease n the exempton lmt by $50,000 ncreases the probablty of a bsness start by 20%. 23

24 Snce these reslts are smlar n the model wth spatal varables, I dscss these n greater detal n the followng secton. Reslts wth the spatal varables are presented n Table 4a. The model performs well, n that t confrms prevos fndngs on the demographc varables, and also prodces sgnfcant estmates of the spatal varables. The explanatory varables nclde whether the ndvdal s male, has attended college and s marred, all of whch have a postve and sgnfcant mpact on bsness formaton. I also nclde race and ethncty effects, whch confrm earler reslts (Meyer, 1990) that Blacks and other ethnc mnortes are less lkely to start bsnesses. The postve lnear and negatve qadratc terms n age mply that the effect of age s U-shaped. Yonger ndvdals are more lkely to start bsnesses. The effect of famly wealth s postve and sgnfcant, sggestng that hgh wealth redces credt constrants that the bsness owner may face (Holtz-Eakn et al, 1994, Evans and Jovanovc, 1989). Indvdals who have hgh earnngs from crrent jobs may be less lkely to swtch to startng a bsness (Evans and Leghton, 1989). At the same tme, ndvdals wth hgh ncomes may have the fnancal means to start a bsness. Ths coeffcent s sgnfcant, bt prodces mxed reslts for the two samples, as shown n Colmn 1 and Colmn 4. Fan and Whte (2003) srprsngly do not fnd a statstcally sgnfcant effect of earnngs or wealth on entreprenershp. Ths paper fnds two new nterestng reslts on the role of health nsrance n entreprenershp. If a person s n a wage and salary occpaton and receves employer nsrance, he s less lkely to move towards self-employment, whereas f the ndvdal has self-prchased nsrance, he s more lkely to start a bsness. Holtz-Eakn et al (1996) dd not fnd a statstcally sgnfcant mpact of health nsrance varables on transtons to entreprenershp, sng SIPP 1984, 1986 and 1987 panels. 27 The margnal effects sggest that employer nsrance redces the probablty of transton by 5%, 27 They controlled for other job characterstcs, lke whether the job offered dental nsrance, penson etc, and whether the spose had nsrance. I control for ncome from job, and whether the person was selfnsred. SIPP 1993 panel does not specfcally ask whether the spose had nsrance. 24

25 whereas self-nsrance ncreases the lkelhood by nearly 1%. 28 If the person s nemployed, he s sgnfcantly less lkely to start a bsness. I defned a dmmy for whether the person was nemployed, and (n some specfcatons, as shown n Colmn 4) nteracted that dmmy wth the average nemployment beneft for that state and a dmmy for whether the state had a Self Employment Assstance (SEA) program. The coeffcent on the nteracton term s nsgnfcant, bt the coeffcent on SEA s postve and sgnfcant at 15%, provdng some evdence on the effectveness of these programs n transtons to entreprenershp ot of nemployment. The above mentoned reslts are robst to dfferent specfcatons. Apart from the demographc varables, I control for the level of state per capta ncome, (PCI), whch serves as an ndcator of demand condtons, and for the maxmm margnal state ncome tax rate. The sgn on the tax coeffcent s postve, thogh nsgnfcant, whch s n accordance wth Brce (2000), who fnds that hgh tax rates ndce ndvdals towards self-employment de to the tax avodance ncentve. State PCI s also postve and sgnfcant n some specfcatons, ths better economc condtons ndce transtons to entreprenershp. I se state nemployment rates, state nonzaton rates and nonfarm employment as addtonal controls. In some specfcatons, the state nemployment rate s postve and sgnfcant, sggestng that a lack of job opportntes may psh people towards entreprenershp. The man varables of nterest are the bankrptcy exemptons n one's own state as well as n neghborng states. To stdy the effect of own state exemptons, I se the sm of the actal homestead and personal property exempton level, by settng a vale of for the nlmted homestead exempton. I now examne the spatal varables more closely. I defne the varable, AVGNBEX, as a weghted average of exemptons of all neghborng states. Hgh average exemptons n neghborng states may have two opposng effects on entreprenershp. Frst, f we look at Fgre 1, there appears to be 28 For the panel, the correspondng vale for employer nsrance s 7%, and for self-prchased nsrance, 6%. 25

26 some clsterng of states across dfferent exempton ranges. So hgh average neghbor exemptons mply that the ndvdal's own state s lkely to be located n a "hgh exempton" regon, and ths has a postve effect on entreprenershp. However, at the same tme, the ndvdal cold presmably be better off movng to a neghborng state wth hgher exemptons than n own state, whch lowers the probablty that the entreprener wll start a bsness n hs own state. To captre the second effect clearly, I defne a separate dmmy varable, DUMAVEX, for whether the average exempton of the neghborng states s hgher than one's own exempton. In Colmn 1, I report reslts for the fll set of state varables, sng the pooled panel. Own state exempton s nsgnfcant n ths specfcaton. DUMAVEX s sgnfcant and negatve at 5%, sggestng that f the average neghbor exempton s hgher than one's own, ths sgnfcantly lowers entreprenershp n one's own state. Interpretng the margnal effect, ths redces the probablty of startng a bsness by abot 1% (gven the base probablty of 1.51%), whch s economcally sgnfcant. 29 I also pt n dmmy varables, DUMAVPC and DUMAVTX, whch eqal one f neghbor PCI s hgher, or neghbor tax rate s lower, respectvely, than n one's own state. DUMAVTX and DUMAVPC are the rght sgn, bt nsgnfcant. I also control for average condtons n neghborng states, by sng dstance weghted averages of condtons n neghbor states. Dstance between any two states s defned as dstance between ther respectve captal ctes. The greater the dstance between neghborng states, the lower wll be the effect of hgh exemptons n that state on entreprenershp n one s own state. Dstance weghted AVGNBEX s nsgnfcant. Other spatal varables nclded n the model are average neghbor per capta ncomes, AVGNBPC, and average neghbor tax rates, AVGNBTX. AVGNBPC s negatve and sgnfcant at 10%, ths hgh average ncomes n neghborng states redce entreprenershp n own state. 29 Note that the total nmber of bsness starts n my sample s approxmately 4600, ot of the total sample of 312,000 (approx.). If the probablty s redced by 1%, ths mples that there are roghly 50 less starts. Weghtng these nmbers by the total US poplaton, ths redces bsness starts by approxmately 50,

27 Reslts n Colmn 1 sggest that controllng for DUMAVEX redces the sgnfcance of own state exemptons. I test to see f the reslts change when I drop own state exemptons and average neghbor exemptons from the model. Colmn 2 reports reslts wth ths specfcaton. The estmated margnal effect for DUMAVEX does not change and s negatve, bt the sgnfcance level mproves to 1%. I also drop AVGNBPC and AVGNBTX from the model. In ths specfcaton, the effect of hgher neghbor ncomes captred by DUMAVPC, s sgnfcantly negatve on entreprenershp n one s own state. Estmates of other varables are smlar to those n Colmn 1, thogh t s worth notng that the nemployment rate s postve and sgnfcant. In colmn 3, I ntrodce the own state exempton varable, EXEMPTION, nto the model, bt not AVGNBEX. DUMAVEX s stll sgnfcant, bt EXEMPTION s not. DUMAVEX redces the probablty of bsness formaton n own state. Ths even controllng for own state exemptons does not redce the sgnfcance of DUMAVEX. AVGNBPC n negatve and sgnfcant as n Colmn 1.In ths specfcaton, PCI s also postve and sgnfcant. In Colmn 4, I present reslts for the sb-sample , sng poplaton weghted averages of neghbor condtons. Reslts are smlar to those otlned n Colmn 1. Poplaton weghts captre the dea that ndvdals are more lkely to move to more poplos states (snce n general these are also the states wth more job opportntes, larger markets, etc). The sgns on the demographc varables do not change. The coeffcent on the exempton level s not sgnfcant, bt DUMAVEX s negatve and sgnfcant as before. Smmarzng the reslts on the effect of exemptons, t s nterestng to note that when the spatal varables are nclded n the model of Table 3, the effect of own state exemptons s nsgnfcant. Ths t appears that whle exemptons are mportant to entrepreners, they care more abot the relatve exempton n ther state vs-à-vs the neghborng states. Ths s plasble snce as ponted ot n the ntrodcton, small frms are sbject to hgh 27