The Determinants of Rural Self Employment

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tential entrepreneurs Even so using individual level data from the 1996 and 2001 Survey of. Income and Program participation waves Bates et al 2010 find no evidence to suggest that. capital access barriers prevent small business starts. In addition other locally varying predetermined variables have likely influenced changes. in self employment rates over time Here we focus on these variables as potential policy levers. Other policy constraints operating at the national level also have been cited in the literature as. restricting self employment or entrepreneurship These include the lack of a national health care. program and disincentives that render workers who want to start their own business ineligible to. receive unemployment compensation, The plan of this paper is as follows In the next section we motivate a regression model. to explain rural self employment growth drawing on the existing literature which is briefly re. viewed Then we discuss and define our data and present summary statistics This is followed. by the regression results along with a discussion One of the contributions of the paper is that. we study the impact of regressors on self employment or proprietorship formations across differ. ent types of rural areas as measured by the USDA s 2003 Rural Urban Continuum Code. RUCC 03 and we also examine the dynamics across rural areas for different years correspond. ing to the peaks and valleys of the most recent business cycles i e annually starting in 2003. Literature Synopsis and Regression Model, While there is a sizable literature on the individual level and geographic area level de. terminants of entrepreneurship e g Bates 1990 Acs and Armington 2006 Michelacci and Sil. ver 2007 Goetz and Rupasingha 2009 Doms et al 2010 few systematic and rigorous studies. explore the causes of self employment or entrepreneurship at the level of rural U S counties or. labor market areas and none considers the rural urban continuum defined below Because ru. ral areas are not homogeneous but differ in terms of key characteristics such as population densi. ty and access or proximity to cities we maintain that such an analysis is important to fully under. stand the process of self employment growth in those areas And no prior study examines rela. tionships in the current economic downturn at the rural county level. To motivate our regression analysis we draw primarily on two relatively recent studies. by Acs and Armington 2006 and Goetz and Rupasingha 2009 The book Entrepreneurship. Geography and American Economic Growth by Acs and Armington 2006 AA marked one of. the first applications of New Growth Theory concepts to understanding the determinants of new. establishment formations and sectors across 394 spatial units Labor Market Areas or LMAs. with varying economic characteristics the dependent variable was measured over the years 1995. and 1996 with regressors generally measured in levels in 1994 or changes over the period 1992. 1994 More specifically Acs Armington calculate new firm formation rates across LMAs as. new establishments in 1995 and 1996 per 1994 worker They are able to distinguish among six. sectors and model growth as a function of firm size sector specialization proprietor shares edu. cational attainment recent growth in income and population and the unemployment rate within. the LMA In general their coefficient estimates have expected signs discussed next and the ad. justed R square values are high for these types of studies generally above 63. Goetz and Rupasingha Determinants of Rural Self Employment 2. More specifically in the Acs Armington model p 65 ff a locality in which large firms. more employees per establishment dominate have fewer new firm formations because know. ledge is developed and applied within the firm rather than being allowed to spill over into the. community Further larger firms tend to crowd out smaller more competitive firms that may be. more entrepreneurial Counties with more specialized industries as measured by the number of. establishments per 1 000 population on the other hand provide greater exposure for potential. entrepreneurs to different management and technical production practices which could in turn. translate into new business ideas, Along these lines Acs Armington also suggest that a higher share of existing self. employed workers in the community and fewer high school dropouts and more college gra. duates are all associated with a higher rate of new establishment formation This reflects both a. more conducive existing entrepreneurial climate and more potential for innovation that builds on. human capital spillovers within a locality In addition the lagged compound population and. income growth rates from 1992 to 1994 are included to control for the desirability of a communi. ty for migrants and opportunities for selling products respectively The unemployment rate fi. nally measures the degree to which individuals are driven into self employment by a lack of al. ternative work opportunities, These authors caution that even though their independent variables are measured one or. two years before the period over which establishment growth occurs the regressors may not be. strictly exogenous and that the results therefore need to be interpreted with caution They also. note footnote 11 p 68 the exclusion of financial variables which are important factors in new. firm formation and which they hope to take into account in subsequent research In this pa. per we introduce a number of candidate variables to capture the potential effect of access to. adequate financing as explained below, In addition we draw on Goetz and Rupasingha 2009 GR for additional variables to.
include in the regression analysis Chief among these are the relative financial returns to poten. tial entrepreneurship the riskiness of those returns homeownership characteristics and basic. banking variables as proxies for access to capital income within the community as a measure of. demand beyond recent income growth an ethnic fractionalization index basic socioeconomic. and demographic variables natural amenities and economic policy variables measured at the. state level see Appendix In the present study we expand this vector by including measures of. liquidity available and competition among or availability of bank branch offices Goetz and. Rupasingha s paper is based on a utility maximizing choice between wage and salary and self. employment based on relative earnings and it uses 1990 as the base year and models the change. in the self employment rate between 1990 and 2000 They estimate a general spatial model. SAC after finding evidence of spatial dependence bias in the national data. Briefly we expect higher self employment earnings within the county to be associated. with higher increases in self employment shares as in AA and GR and greater variation in re. turns to self employment risk to depress the growth in such shares The percent of homes that. are owner occupied along with the median home value in 2000 are included to serve as basic. measures of collateral availability considering that homes are Americans largest source of. wealth these were both statistically significant and positive in GR Two other variables. Goetz and Rupasingha Determinants of Rural Self Employment 3. available at the county level are the value of bank deposits in the county and the number of bank. branch offices We include measures for these from the year 2000 normalized by population. As an alternative measure to bank deposits per capita which had a sign counter to expectations. in GR we consider here dividend rent and interest payments DRIPs into the county also per. capita Conceptually this is a pool of funds potentially available to local businesses. The ethnic fractionalization index is based on Alesina et al 1999 and captures the eth. nic diversity of a county A higher index means greater diversity in terms of ethnic groups and. our calculation takes into account all of the major races reported in the Census classification the. index has a correlation of about 90 with African American Black presence in counties and. thus in part captures potential opportunities or the lack thereof for minority and otherwise un. derserved populations We hypothesize this variable to have a positive effect reflecting greater. entrepreneurship among immigrants, Our socioeconomic variables from GR include median population age female labor. force participation rates per capita personal income net of DRIPs the unemployment rate and a. vector of employment shares by major industry These include construction manufacturing re. tail trade and finance insurance and real estate FIRE Briefly construction workers are more. likely to be self employed while for communities with manufacturing dominance the opposite is. often found to be the case likewise with the rise of big boxes retail workers are less likely to be. self employed whereas FIRE workers e g realtors financial advisors are again more likely to. be self employed We use these variables as proxies for the types of populations from which the. self employed are likely or not to emerge, In recent years there has been an explosion of interest in the role of natural amenities in. driving rural economic development the seminal paper is Deller Tsai and Marcouiller 2001 see. also Rupasingha and Goetz 2004 Although this variable from the USDA s Economic Research. Service McGranahan 1999 is not amenable to policy change it is an important control variable. In brief higher amenities have been associated with both faster income and population growth. and also faster increases in the rate of self employment over time beyond the income and popu. lation growth controls already included e g this captures higher end tourism of second homes. development which would not necessarily be reflected in the two growth variables. Recent research suggests that rural areas have lower firm entry rates relative to urban. areas cet par because lower salvage values of rural capital require higher expected profits Yu. et al 2011 also Johnson and Quance 1972 Unlike GR who include all US counties we cannot. use a Rural indicator variable given that we are working with only non metro rural counties. Instead we add population density to capture the presence of agglomeration economies or the. lack thereof Note that these agglomeration benefits can be offset by higher factor costs asso. ciated with density or congestion including for land and labor Moretti 2004 Last we include. state level economic freedom measures that are explicit policy variables As described in AP. PENDIX 1 they capture the relative size of government in the state s economy takings and dis. criminatory taxation and relative freedom in the labor market higher values of these variables. indicate more freedom, Perhaps most significantly Goetz and Rupasingha 2009 find that the self employed re. spond rationally to economic incentives at least over the period 1990 2000 In their study high. Goetz and Rupasingha Determinants of Rural Self Employment 4. er returns to self employment and lower wage and salary earnings and lower financial risks as. sociated with self employment all lead to subsequently higher rates of self employment or pro. prietorship formations over time In addition the self employed also respond rationally to state. level economic policy as elaborated below and greater access to collateral measured by home. ownership rates and median home values is also associated with higher increases in self. employment rates Together these results give us some degree of confidence to explore these. data further at a more exclusive level of geography rural or non metro only and using the most. recent data available to understand the effects of the 2008 recession. Data Definitions Preliminary Analysis and Summary Statistics. Our dependent variable in the regression model is defined as the simple change in the ra. tio of self employed to wage and salary jobs over time as discussed above set set wst i. where se is the number of self employed workers ws the number of wage and salary workers i. indexes the county with a total of N 1 991 rural counties t is the base year 2000 and is the. increment or lag in time over which the change is calculated e g when 9 the rate of change. is between the years 2000 and 2009 Of the different calculations available for expressing self. employment change this one most closely follows that used by Acs and Armington 2006 5. This self employment change measure differs from that used in Goetz and Rupsingha. 2009 who use change in the ratio set ws t for each year and county and which we also used in. our earlier discussion as well as our graphical analysis below Obviously the ratio used by GR. increases when se rises more rapidly than ws or when ws declines more rapidly than se Like. wise the AA ratio is positive as long as set set and it is increasing so long as set set wst. Figure 1 shows the self employment rate used by GR for the years 1969 2009 as the. green line ratio this is the self employment number divided by contemporaneous wage and. salary employment The structural break in the rate of change in the ratio in 2001 is noteworthy. Before this year the rural self employment rate on average increased by 0 20 percentage points. annually since 2001 it has grown at a robust pace of 0 72 percentage points annually This pace. was surpassed or matched only twice historically over the period show. terminants of entrepreneurship e g Bates 1990 Acs and Armington 2006 Michelacci and Sil ver 2007 Goetz and Rupasingha 2009 Doms et al 2010 few systematic and rigorous studies explore the causes of self employment or entrepreneurship at the level of rural U S counties or labor market areas and none considers the rural urban continuum defined below Because ru ral areas are not

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