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New-firm formation in Italy: A first report
economics letters ELSEVIER
Economics Letters 48 (1995) 77-81
New-firm formation in Italy: A first report D a v i d A u d r e t s c h a, M a r c o Vivarelli b'* aWissenschaftszentrum Berlin fiir Sozialforschung, Berlin, Germany bUniversita' Cattolica del Sacro Cuore, Facolta' de Economia, via Emilia Parmense 84, Piacenza, 29100, Italy Received 2 September 1993; accepted 17 August 1994
Abstract
We find that greater profitability, lower wages, job dislocations, and the degree to which an entrepreneurial environment already exists, positively influence the extent of new-firm formation in Italian provinces.
JEL classification: L10
I. Introduction
While a recent interest has emerged in the industrial organization literature empirically identifying the determinants of entry into manufacturing industries (see Geroski and Schwalbach, 1991), virtually all of the studies link entry to profitability and entry barriers at the level of individual industries, and typically across all economic space within a nation. 1 However, several important new theories of economic geography have been proposed emphasizing the role that clusters of complementary industries within a distinct spatial area play (see Krugman, 1991). The purpose of this paper is to link new-firm formation to such spatial units of observation consistent, at least to some extent, with the notion of industry clusters. We examine new-firm formation in 78 Italian provinces. Perhaps the most striking feature of Italian industrial organization is the existence of industrial districts, where constellations of complementary industries combine to constitute a more or less cohesive unit of observation within a restricted geographic space. In using a new panel data base, we are able to identify
* Corresponding author. 1 For example, Carlton (1983, p. 440) concludes that, "Despite all the interest, economists know very little about the factors influencing new business location." 0165-1765/95/$09.50 (~ 1995 Elsevier Science B.V. All rights reserved SSDI 0165-1765(94)00587-7
78
D. Audretsch, M. Vivarelli / Economics Letters 48 (1995) 77-81
those characteristics of industries operating within provinces that are most conducive to new-firm entry.
2. The model of income choice
The theory of income choice, perhaps first introduced by Knight (1921) and later extended by Kihlstrom and Laffont (1979) and Evans and Jovanovich (1989), suggests that the likelihood of an individual starting a new firm is shaped by the gap between the wage (s)he expects to earn through employment and the profits that are expected to accrue from starting a new firm. This theory suggests that entry should be higher in provinces where profitability is greater but wages are lower. Evans and Leighton (1990) found that personal characteristics, and especially employment status, influenced the decision to start a new firm. In particular, they found unequivocal evidence that, at least for US young white males, the probability of starting a new firm tends to rise as a worker loses his job. This would suggest that provinces which have suffered from a greater extent of labor dislocation, or job losses, should exhibit a greater degree of new-firm formation. In proposing his new economic theory of geography, Krugman (1991) emphasizes spillovers across complementary firms within a spatial unit of observation, or what has been termed as network externalities. Such network externalities reflect the extent to which supplier and buyer networks exist and should serve to facilitate new-firm formation. Since the bulk of new firms are very small,2 the prevalence of such network externalities can be represented by the relative density of existing small firms within a given province. In addition, there is empirical evidence that most of the new founders come from small firms where they were dependent workers and where they learn about how to start and run a firm (see Vivarelli, 1991). A final influence is the degree to which a province is agglomerated. The notion that a pooled labor market yields increasing returns to a cluster of complementary industries dates back at least to Marshall (1920). Such agglomerations presumably increase the expected profitability to be earned from starting a new firm and thus are conducive to a greater degree of entry. We rely on a new major data base provided by the Network of Italian Chambers of Commerce to identify the number of new firms in manufacturing for 78 provinces (out of 95) over the period 1985-1988. The independent variables used to measure the above hypotheses are also measured over the same time period. These include gross profitability per employee, the average real wage rate, the number of people losing their jobs due to plant closures and contractions, the number of firms with fewer than ten employees, and a dummy variable taking on a value of one in those provinces in which the capital of a region is located, and zero otherwise, to measure the impact of agglomerations. In addition, we include the amount of manufacturing employment within each province to control for the relative size. 3 That is, 2 More than 90% of new Italian firms consist of either a single individual or else employ fewer than ten workers. 3 The data source for the measure of gross profitability, average wage rates, job losses and the small-firm density is the Italian Social Security System; the data source for manufacturing employment is the Italian Industrials Association.
D. Audretsch, M. Vivarelli / Economics Letters 48 (1995) 77-81
79
larger and more industrialized provinces would be expected to have a correspondingly greater amount of new firms, ceteris paribus.
3. Results
The logarithm of both the dependent and independent variables is taken to create a panel data over the period 1985-1988. The results for regression using within-group estimators are reported in Table 1. Following Hsiao (1986), a covariance test leads us to reject the hypothesis for overall coefficient homogeneity over time (with respect to both intercept and slope). However, a separate covariance test for slope homogeneity indicates that the null hypothesis cannot be rejected, so there is no need to assume that the slopes are heterogeneous (see actual figures of F tests in T a b l e 1.) 4 Thus, we include separate intercepts for four of the time periods to incorporate heterogeneity over time. As the positive coefficient of profits and the negative coefficient of wages indicates, there is considerable support for the underlying model of income choice. New-firm formation tends to be greater in provinces exhibiting higher profitability but where the wage rates are lower. Similarly, the importance of network externalities, represented by the relative density of existing small firms within the province, is confirmed by our regression results. There is at least some evidence suggesting that employment dislocation, precipitated from job layoffs, leads to an increase in the number of new firms. Finally, the coefficient of the dummy variable measuring the degree of agglomeration is positive but it cannot be considered statistically significant. To make sure that the results in specification (1) are not merely attributable to spurious correlation between the exogenous variables and broader regional tendencies, such as institutional, cultural and social differences, dummy variables for the three main Italian areas are included in specification (2).5 Not only do the results remain qualitatively very significant, but the regression coefficients are very similar. The insignificance of the coefficient of job losses in specifications (1) and (2) may be the result of a high degree of correlation (0.92) with the density of small firms in a province. Thus, omitting the degree of small-firm density from specification (3) results in a positive and statistically significant impact of the extent of job losses on new-firm formation.
4. Conclusions
The empirical evidence provides considerable support for the model of income choice in explaining why new-firm formation varies across Italian provinces. Individuals apparently have a greater incentive to start a new firm in those provinces where profits tend to be greater and wages tend to be lower. A response of a greater density of small enterprises- perhaps the 4 It should be pointed out that, in specification (2) of Table 1, the F-value is on the edge of the 95% confidence interval. s These three broad areas can be considered distinct from a sociologicalpoint of view (see Bagnasco, 1977).
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D. Audretsch, M. Vivarelli / Economics Letters 48 (1995) 77-81
Table 1 Startups of Italian manufacturing firms: Regression results (within-group estimator) a (1)
(2)
(3) b
Profits
0.147"* (2.353)
0.164"* (2.565)
0.317"* (5.299)
Wages
-0.566** (-3.492)
-0.635** (-3.697)
-0.962** (-7.125)
Job losses
0.055 (1.363)
0.041 (0.983)
Small firms
0.582* * (7.944)
0.509"* (6.724)
Agglomeration
0.010 (0.252)
0.052 (1.214)
0.061 (1.185)
Employment
0.322"* (4.648)
0.385"* (5.206)
0.758"* (13.735)
0.149"* (3.492) -
Northwest
-
0.228"* (2.477)
0.290"* (3.281)
Northeast-centre
-
0.296"* (3.372)
0.408"* (5.351)
South
-
0.192" (2.294)
0.218"* (2.762)
Intercept 1985
4.937* (2.131)
5.524" (2.101)
7.244* * (3.340)
Intercept 1986
4.857* (2.096)
5.443" (2.069)
7.163"* (3.301)
Intercept 1987
4.797* (2.066)
5.386" (2.043)
7.137"* (3.282)
Intercept 1988
4.686* (2.016)
5.276" (1.997)
6.994* * (3.210)
0.890
0.900
F
280.662"*
218.692"*
204.346"*
Covariance test for overall homogeneity
F(21; 284) = 2.36**
F(30; 272) = 2.42**
F(27; 276) = 1.79"
C o v a r i a n c e test for
F(18; 284) = 1.14
F(27; 272) = 1.59"
F(24; 276) = 1.00
Breusch-Pagan's test for heteroskedasticity
X2(9) = 12.79
X2(12) = 20.90
x 2 ( l l ) = 21.22"
Sample size
312
312
312
R2
0.880
slope homogeneity
"t-statistics in parentheses. bHeteroskedasticity- consistent covariance matrix. *Significant at 95% level of confidence. **Significant at 99% level of confidence.
D. Audretsch, M. VivareUi / Economics Letters 48 (1995) 77-81
81
m o s t p r o m i n e n t characteristic of Italian industrial d i s t r i c t s - is a h i g h e r d e g r e e of new-firm f o r m a t i o n . A n d t h e r e is at least s o m e evidence suggesting t h a t g r e a t e r j o b losses t e n d to be m o s t c o n d u c i v e to new-firm f o r m a t i o n .
References Bagnasco, A., 1977, Tre Italie, La problematica territoriale dello sviluppo italiano (II Mulino, Bologna). Carlton, D.W., 1983, The location and employment choices of new firms: An econometric model with discrete and continuous endogenous variables, Review of Economics and Statistics 65, 440-449. Evans, D. and B. Jovanovich, 1989, Estimates of a model of entrepreneurial choice under liquidity constraints, Journal of Political Economy 97, 808-827. Evans, D.S. and L.S. Leighton, 1990, Small business formation by unemployed and employed workers, Small Business Economics 2, 319-330. Geroski, P. and J. Schwalbach, eds., 1991, Entry and market contestability: An international comparison (Basil Blackwell, Oxford). Hsiao, C., 1986, Analysis of panel data (Cambridge University Press, Cambridge). Kihlstrom, R.E. and J.J. Laffont, 1979, A general equilibrium entrepreneurial theory of firm formation based on risk aversion, Journal of Political Economy 87, 719-748. Knight, F.H., 1921, Risk, uncertainty and profit (Houghton Mifflin, New York). Krugman, P., 1991, Increasing returns and economic geography, Journal of Political Economy 99, 483-499. Marshall, A., 1920, Principles of economics, 8th edn. (Macmillan, London). Vivarelli, M., 1991, The birth of new enterprises, Small Business Economics 3, 215-223.
Economics Letters 48 (1995) 77-81
New-firm formation in Italy: A first report D a v i d A u d r e t s c h a, M a r c o Vivarelli b'* aWissenschaftszentrum Berlin fiir Sozialforschung, Berlin, Germany bUniversita' Cattolica del Sacro Cuore, Facolta' de Economia, via Emilia Parmense 84, Piacenza, 29100, Italy Received 2 September 1993; accepted 17 August 1994
Abstract
We find that greater profitability, lower wages, job dislocations, and the degree to which an entrepreneurial environment already exists, positively influence the extent of new-firm formation in Italian provinces.
JEL classification: L10
I. Introduction
While a recent interest has emerged in the industrial organization literature empirically identifying the determinants of entry into manufacturing industries (see Geroski and Schwalbach, 1991), virtually all of the studies link entry to profitability and entry barriers at the level of individual industries, and typically across all economic space within a nation. 1 However, several important new theories of economic geography have been proposed emphasizing the role that clusters of complementary industries within a distinct spatial area play (see Krugman, 1991). The purpose of this paper is to link new-firm formation to such spatial units of observation consistent, at least to some extent, with the notion of industry clusters. We examine new-firm formation in 78 Italian provinces. Perhaps the most striking feature of Italian industrial organization is the existence of industrial districts, where constellations of complementary industries combine to constitute a more or less cohesive unit of observation within a restricted geographic space. In using a new panel data base, we are able to identify
* Corresponding author. 1 For example, Carlton (1983, p. 440) concludes that, "Despite all the interest, economists know very little about the factors influencing new business location." 0165-1765/95/$09.50 (~ 1995 Elsevier Science B.V. All rights reserved SSDI 0165-1765(94)00587-7
78
D. Audretsch, M. Vivarelli / Economics Letters 48 (1995) 77-81
those characteristics of industries operating within provinces that are most conducive to new-firm entry.
2. The model of income choice
The theory of income choice, perhaps first introduced by Knight (1921) and later extended by Kihlstrom and Laffont (1979) and Evans and Jovanovich (1989), suggests that the likelihood of an individual starting a new firm is shaped by the gap between the wage (s)he expects to earn through employment and the profits that are expected to accrue from starting a new firm. This theory suggests that entry should be higher in provinces where profitability is greater but wages are lower. Evans and Leighton (1990) found that personal characteristics, and especially employment status, influenced the decision to start a new firm. In particular, they found unequivocal evidence that, at least for US young white males, the probability of starting a new firm tends to rise as a worker loses his job. This would suggest that provinces which have suffered from a greater extent of labor dislocation, or job losses, should exhibit a greater degree of new-firm formation. In proposing his new economic theory of geography, Krugman (1991) emphasizes spillovers across complementary firms within a spatial unit of observation, or what has been termed as network externalities. Such network externalities reflect the extent to which supplier and buyer networks exist and should serve to facilitate new-firm formation. Since the bulk of new firms are very small,2 the prevalence of such network externalities can be represented by the relative density of existing small firms within a given province. In addition, there is empirical evidence that most of the new founders come from small firms where they were dependent workers and where they learn about how to start and run a firm (see Vivarelli, 1991). A final influence is the degree to which a province is agglomerated. The notion that a pooled labor market yields increasing returns to a cluster of complementary industries dates back at least to Marshall (1920). Such agglomerations presumably increase the expected profitability to be earned from starting a new firm and thus are conducive to a greater degree of entry. We rely on a new major data base provided by the Network of Italian Chambers of Commerce to identify the number of new firms in manufacturing for 78 provinces (out of 95) over the period 1985-1988. The independent variables used to measure the above hypotheses are also measured over the same time period. These include gross profitability per employee, the average real wage rate, the number of people losing their jobs due to plant closures and contractions, the number of firms with fewer than ten employees, and a dummy variable taking on a value of one in those provinces in which the capital of a region is located, and zero otherwise, to measure the impact of agglomerations. In addition, we include the amount of manufacturing employment within each province to control for the relative size. 3 That is, 2 More than 90% of new Italian firms consist of either a single individual or else employ fewer than ten workers. 3 The data source for the measure of gross profitability, average wage rates, job losses and the small-firm density is the Italian Social Security System; the data source for manufacturing employment is the Italian Industrials Association.
D. Audretsch, M. Vivarelli / Economics Letters 48 (1995) 77-81
79
larger and more industrialized provinces would be expected to have a correspondingly greater amount of new firms, ceteris paribus.
3. Results
The logarithm of both the dependent and independent variables is taken to create a panel data over the period 1985-1988. The results for regression using within-group estimators are reported in Table 1. Following Hsiao (1986), a covariance test leads us to reject the hypothesis for overall coefficient homogeneity over time (with respect to both intercept and slope). However, a separate covariance test for slope homogeneity indicates that the null hypothesis cannot be rejected, so there is no need to assume that the slopes are heterogeneous (see actual figures of F tests in T a b l e 1.) 4 Thus, we include separate intercepts for four of the time periods to incorporate heterogeneity over time. As the positive coefficient of profits and the negative coefficient of wages indicates, there is considerable support for the underlying model of income choice. New-firm formation tends to be greater in provinces exhibiting higher profitability but where the wage rates are lower. Similarly, the importance of network externalities, represented by the relative density of existing small firms within the province, is confirmed by our regression results. There is at least some evidence suggesting that employment dislocation, precipitated from job layoffs, leads to an increase in the number of new firms. Finally, the coefficient of the dummy variable measuring the degree of agglomeration is positive but it cannot be considered statistically significant. To make sure that the results in specification (1) are not merely attributable to spurious correlation between the exogenous variables and broader regional tendencies, such as institutional, cultural and social differences, dummy variables for the three main Italian areas are included in specification (2).5 Not only do the results remain qualitatively very significant, but the regression coefficients are very similar. The insignificance of the coefficient of job losses in specifications (1) and (2) may be the result of a high degree of correlation (0.92) with the density of small firms in a province. Thus, omitting the degree of small-firm density from specification (3) results in a positive and statistically significant impact of the extent of job losses on new-firm formation.
4. Conclusions
The empirical evidence provides considerable support for the model of income choice in explaining why new-firm formation varies across Italian provinces. Individuals apparently have a greater incentive to start a new firm in those provinces where profits tend to be greater and wages tend to be lower. A response of a greater density of small enterprises- perhaps the 4 It should be pointed out that, in specification (2) of Table 1, the F-value is on the edge of the 95% confidence interval. s These three broad areas can be considered distinct from a sociologicalpoint of view (see Bagnasco, 1977).
80
D. Audretsch, M. Vivarelli / Economics Letters 48 (1995) 77-81
Table 1 Startups of Italian manufacturing firms: Regression results (within-group estimator) a (1)
(2)
(3) b
Profits
0.147"* (2.353)
0.164"* (2.565)
0.317"* (5.299)
Wages
-0.566** (-3.492)
-0.635** (-3.697)
-0.962** (-7.125)
Job losses
0.055 (1.363)
0.041 (0.983)
Small firms
0.582* * (7.944)
0.509"* (6.724)
Agglomeration
0.010 (0.252)
0.052 (1.214)
0.061 (1.185)
Employment
0.322"* (4.648)
0.385"* (5.206)
0.758"* (13.735)
0.149"* (3.492) -
Northwest
-
0.228"* (2.477)
0.290"* (3.281)
Northeast-centre
-
0.296"* (3.372)
0.408"* (5.351)
South
-
0.192" (2.294)
0.218"* (2.762)
Intercept 1985
4.937* (2.131)
5.524" (2.101)
7.244* * (3.340)
Intercept 1986
4.857* (2.096)
5.443" (2.069)
7.163"* (3.301)
Intercept 1987
4.797* (2.066)
5.386" (2.043)
7.137"* (3.282)
Intercept 1988
4.686* (2.016)
5.276" (1.997)
6.994* * (3.210)
0.890
0.900
F
280.662"*
218.692"*
204.346"*
Covariance test for overall homogeneity
F(21; 284) = 2.36**
F(30; 272) = 2.42**
F(27; 276) = 1.79"
C o v a r i a n c e test for
F(18; 284) = 1.14
F(27; 272) = 1.59"
F(24; 276) = 1.00
Breusch-Pagan's test for heteroskedasticity
X2(9) = 12.79
X2(12) = 20.90
x 2 ( l l ) = 21.22"
Sample size
312
312
312
R2
0.880
slope homogeneity
"t-statistics in parentheses. bHeteroskedasticity- consistent covariance matrix. *Significant at 95% level of confidence. **Significant at 99% level of confidence.
D. Audretsch, M. VivareUi / Economics Letters 48 (1995) 77-81
81
m o s t p r o m i n e n t characteristic of Italian industrial d i s t r i c t s - is a h i g h e r d e g r e e of new-firm f o r m a t i o n . A n d t h e r e is at least s o m e evidence suggesting t h a t g r e a t e r j o b losses t e n d to be m o s t c o n d u c i v e to new-firm f o r m a t i o n .
References Bagnasco, A., 1977, Tre Italie, La problematica territoriale dello sviluppo italiano (II Mulino, Bologna). Carlton, D.W., 1983, The location and employment choices of new firms: An econometric model with discrete and continuous endogenous variables, Review of Economics and Statistics 65, 440-449. Evans, D. and B. Jovanovich, 1989, Estimates of a model of entrepreneurial choice under liquidity constraints, Journal of Political Economy 97, 808-827. Evans, D.S. and L.S. Leighton, 1990, Small business formation by unemployed and employed workers, Small Business Economics 2, 319-330. Geroski, P. and J. Schwalbach, eds., 1991, Entry and market contestability: An international comparison (Basil Blackwell, Oxford). Hsiao, C., 1986, Analysis of panel data (Cambridge University Press, Cambridge). Kihlstrom, R.E. and J.J. Laffont, 1979, A general equilibrium entrepreneurial theory of firm formation based on risk aversion, Journal of Political Economy 87, 719-748. Knight, F.H., 1921, Risk, uncertainty and profit (Houghton Mifflin, New York). Krugman, P., 1991, Increasing returns and economic geography, Journal of Political Economy 99, 483-499. Marshall, A., 1920, Principles of economics, 8th edn. (Macmillan, London). Vivarelli, M., 1991, The birth of new enterprises, Small Business Economics 3, 215-223.