Does (average) size matter? Court enforcement, business demography and firm growth

Abstract

Previous literature finds that the quality of judicial enforcement has a positive impact on average firm size, but it has not disentangled its effect on the growth of incumbent firms from that on business demography. This distinction is crucial, as entrants are generally smaller than incumbents, but both high entry rates and high firm growth are associated with better economic performance. This paper fills this gap, finding that judicial efficacy fosters the growth of incumbents and promotes entry in Spain. The paper also shows for the first time that the specific type of judicial procedure that companies face in case of a conflict, rather than the overall functioning of courts, is the relevant matter. Specifically, judicial efficacy at the declaratory stage (when a debt is verified by a judge) has a positive impact on both firm growth and entry, while it has no impact at the execution stage (when the judge requires its payment).

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Notes

  1. 1.

    To the best of our knowledge, there are only two papers, Chemin (2009) and Lichand and Soares (2014), which study the impact of judicial efficacy on entry, but restricted to the probability of becoming self-employed.

  2. 2.

    The data used by Fabbri (2010) represent judicial performance from the old civil judicial system of Spain, which was abrogated in 2000.

  3. 3.

    As the Spanish government is drafting a bill (new Ley Orgánica del Poder Judicial, LOPJ) in order to reorganize some general aspects of the judicial system, this paper results may contribute to the current debate on the topic.

  4. 4.

    We do not explain an additional channel, the enforcement of employment protection legislations, as our database allows us to differentiate between different types of conflicts, and thus, we have focused the empirical analysis solely on civil cases. See Giacomelli and Menon (2013) for a discussion on the topic.

  5. 5.

    The basic organization of the Spanish judicial system is regulated by the above mentioned LOPJ. Following the National reform programme (2014), the government will present a draft bill to reform that Law.

  6. 6.

    A company may have also violated the public interest and therefore be criminally liable. However, such cases are quite rare under Spanish law.

  7. 7.

    In this study, we do not work with the second instance (i.e., appeals against the courts of first instance). The reason is that only 7.45 % of first instance cases are appealed to the second instance. Moreover, the problems of inefficacy of the Spanish judicial system (compared to other countries) seem to be concentrated in the first instance and not in the second, according to the results of the OECD (Palumbo et al. 2013).This does not rule out a possible future extension providing some analysis of the second instance.

  8. 8.

    Law 1/2000, of January 7th (Civil Procedural Law).

  9. 9.

    Two clarifications must be added. First, there are changes in this reasoning if the company has a conflict with a private subject which is foreign, but even in this case, the CPL may be used (depending on the case). Second, it must be noted that some extrajudicial solutions may be found by the parties, such as sending the case to arbitration. However, even in that case, only a judge can enforce an arbitral decision, always using the CPL and the judicial system.

  10. 10.

    Excluding Ceuta and Melilla (no information is available for those provinces).

  11. 11.

    Articles 50 and 51 of the CPL.

  12. 12.

    The competence at a more disaggregated level (i.e., the allocation of civil affairs within the same province) should not be a concern for the analysis. The allocation of cases among the courts of first instance of a particular province is made by the dean’s office on the basis of predetermined rules, which include, among others, random mechanisms (with several corrections). That is, firms cannot choose to litigate before a particular judge they may prefer.

  13. 13.

    The Spanish regions (Comunidades Autónomas) have some powers related to the administration of justice in Spain. Even though the judicial power is not properly transferred to the regions, management of judicial resources is influenced by the policies developed by the regions. For instance, they decide how much money is invested in new courts each year in their territories, even though the new courts are integrated into a system that is centrally governed.

  14. 14.

    The Pearson’s linear correlation coefficient between the two variables is 0.77.

  15. 15.

    The source of these data is generally the office of the Registrar of Companies.

  16. 16.

    Industries are defined at the two-digit level following the ISIC Rev.3 in STAN and the NACE Rev. 1.1. in SABI. There is a perfect matching between the two classifications.

  17. 17.

    We identify as an entrant a firm whose incorporation was in 2001 or later. To identify the firms that exited the market, we use SABI’s classification of companies into two main categories: “active” firms (i.e., currently operating in the market) and “inactive”.

  18. 18.

    Administrative courts (tribunales de lo contencioso-administrativo) instead of civil courts.

  19. 19.

    Specifically, they are often subject to Administrative Law, rather than Civil Law.

  20. 20.

    For instance, negative values in stock variables or observations that violate basic accounting norms.

  21. 21.

    According to the Spanish National Statistics Institute (INE), the average number of firms in the period 2001–2009 was 3,051,634 while the average number of plants in that period was 3,389,330, which implies that each firm had, on average, 1.1 plants.

  22. 22.

    Despite removing the firms that entered or exited the market, we have an unbalanced panel due to the uneven coverage across years. For instance, the last year of the period, 2009, has the lowest number of firms because the usual time lag in the submission of financial statements by firms is 2 years (Ribeiro et al. 2010) and the data from SABI were extracted at the end of 2010.

  23. 23.

    We could only construct entry rates (but no exit rates) at the province-industry level for limited liability firms with more than 50 employees. We then ran entry rates on congestion rates, our set of province-level controls, time dummies and province-industry fixed effects, i.e., a dummy for every province-industry combination. The results—see online Appendix E—are qualitatively the same as the ones displayed in this paper.

  24. 24.

    This figure seems to be partially driven by the high entry rate of firms in Cáceres in 2001. We have contacted the data provider, the Spanish National Statistics Institute, to check whether it was a mistake in the original source. As a robustness check, we have done all the econometric analyses substituting that figure by the province-mean in the period 2002–2009. The results have not qualitatively changed.

  25. 25.

    Unfortunately, the province-level GDP is only available in nominal terms, while it would be preferred to use it in real terms. But the fact that the GDP is strongly correlated (0.98) with an alternative real measure of market size, population, suggests that this problem is minor in our case.

  26. 26.

    By non-market services, we mean public administration and defense, compulsory social security, education, health and social services.

  27. 27.

    We have computed the HHI with all the available firms in our sample (890,000), i.e., we have included firms that entered or exited the market during the period of study, in order to increase the representativeness of the variable. We have computed two versions of the HHI, one at the province-industry level—where industry is defined at two digits using the NACE Rev. 1.1 classification—for the analysis of firm size and growth and one at the province level for the analysis of business demography.

  28. 28.

    Extraordinary positions are revenues or expenses that do not arise from the regular activities of a firm, such as insurance claims.

  29. 29.

    Notice that, as it was explained in Sect. 3.3, criminal cases are tried in separate courts than the civil cases that are analyzed in this paper, so we do not expect congestion rates to be influenced by the province’s degree of criminality.

  30. 30.

    The above regressions are estimated via the within-group estimator with clustered standard errors robust to heteroskedasticity and serial correlation. The fixed effects have been found jointly significant via cross-section poolability tests, while serial correlation has been found using the test of Wooldridge (2002). Results of both tests are available upon request.

  31. 31.

    For instance, most large corporations have their legal departments, while small businesses may choose to keep a lawyer or a staff of lawyers on retainer or hire them when their services are required.

  32. 32.

    In general, decisions at the firm level are not likely to affect judicial efficacy, macroeconomic performance or the provision of credit.

  33. 33.

    Although Giacomelli and Menon (2013) use a different variable, a litigation index, their aim is the same: to account for potential reverse-causality issues between size and judicial efficacy.

  34. 34.

    The above regressions are estimated via the within-group estimator with clustered standard errors robust to heteroskedasticity and serial correlation. The fixed effects have been found jointly significant via cross-section poolability tests, while cross-section correlation has been rejected using Pesaran’s CD test (2004). While the Wooldridge’s test (2002) has not been able to reject the null hypothesis of no serial correlation, note that the power of this test may be low when N is small, as it is in this case (N = 50). Drukker (2003) finds high power for samples between N = 500 and N = 1,000 and between T = 5 and T = 10.

  35. 35.

    The current bankruptcy law (Ley Concursal), which entered into force in September 2004, stipulated the creation of new courts (mercantile courts) that would be specialized in bankruptcy procedures. The procedures prior to that law were solved in the general civil courts.

  36. 36.

    Correlations among the regressors (see online Appendix C) suggest that there are no multicollinearity problems except for the case of Lawyers, which is highly correlated with GDP (0.81). In a number of experiments, we have tried other specifications, such as dropping some proxies for credit constraints and replacing GDP by GDP per capita. The size and significance of the coefficient on congestion rate was very similar. Results available upon request.

  37. 37.

    All the regressions in this section have a very low R 2, between 1 and 4 %. This is because most regressors, with the exception of age and tangibility, are province-level variables that attempt to explain the variation of a firm-level-dependent variable. We are not worried about this result because our main goal is to assess the effect of judicial efficacy via consistent estimates. Moreover, the use of the within-group estimator, rather than the least squares dummy variable estimator, to control for firm-level fixed effects, yields identical estimations of the coefficients but a much lower R 2. We have chosen the former because it is much less computationally expensive.

  38. 38.

    Two apparently striking results are, however, the negative coefficient on Foreigners and the positive one on crime rate, which contradict the findings of Giacomelli and Menon (2013). The reason is that the effect of those variables is very sensitive to the specific controls that are included in the regressions. In robustness checks—see online Appendix G—we have run the same regressions but substituting log (GDP per capita) for log (GDP). Then, the coefficient on Foreigners becomes positive and that on crime rate is insignificant or negative in most specifications.

  39. 39.

    The province with the best law enforcement (i.e., lowest value of congestion ratio) is Alava, with an average value of 1.65 for the period 2001–2009, while the province with the worst law enforcement (i.e., highest value of congestion ratio) is Alicante, with an average value of 2.80 for the same period. Therefore, the simulated change amounts to (1.65 − 2.80) × 100/2.80 = −41.2 %.

  40. 40.

    By relative change, we mean 100 × [X(1) − X(0)]/X(0), where X(0) and X(1) are the initial and final values, respectively.

  41. 41.

    Here, we mean a change in the level of the growth rate, a variable expressed in percentage, i.e., X(1) − X(0), where X(0) and X(1) are the initial and final values, respectively.

  42. 42.

    As we control for credit availability in our regressions, we expect those figures to be the lower bound of the total impact of judicial efficacy on firm size and growth, since previous literature has found a positive impact of judicial efficacy on credit availability (see Sect. 2).

  43. 43.

    The analyses of monitory and exchange—available upon request—also yield the same conclusion.

  44. 44.

    The interest rate applicable as punishment payment depends on the type of debt but it is, in any case, quite high. For example, the general punitive/judicial interest rate imposed as a result of court proceedings condemning payment of cash amounts is the legal interest rate (4 % in 2014) plus two percentage points, i.e., 6 %. Article 576 of the Civil Procedural Law.

  45. 45.

    The results are robust to specifying the dependent variables without the logarithmic transformation. Results available upon request.

  46. 46.

    As we control for credit availability in our regressions, we expect those figures to be the lower bound of the total impact of judicial efficacy on entry rates, since previous literature has found a positive impact of judicial efficacy on credit availability (see Sect. 2).

  47. 47.

    The results are robust to specifying the dependent variables without the logarithmic transformation. Results available upon request.

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Acknowledgments

We are grateful to Patricia Festa, Ildefonso Villán Criado, Fernando Gómez, María Gutiérrez, Juan Francisco Jimeno, Enrique Moral, Carlos Thomas and especially the editor and two anonymous referees for their useful comments and suggestions. We especially appreciate the work of Claire McHugh, who reviewed the manuscript in depth. We also wish to thank seminar participants, referees and discussants at two seminars of the Banco de España-Eurosystem, the III Annual Conference of the Spanish Association of Law and Economics (AEDE), the 2012 Annual Conference of the European Association of Law and Economics (EALE) and the 8th Annual Conference of the Italian Society of Law and Economics (SIDE-ISLE). We are also indebted to Marcos Marchetti, Paula Sánchez Pastor and Ángel Luis Gómez Jiménez for their assistance in the preparation of some of the variables and figures. The views expressed are those of the authors and should not be attributed to the Banco de España.

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García-Posada, M., Mora-Sanguinetti, J.S. Does (average) size matter? Court enforcement, business demography and firm growth. Small Bus Econ 44, 639–669 (2015). https://doi.org/10.1007/s11187-014-9615-z

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Keywords

  • Enforcement institutions
  • Judicial efficacy
  • Firm size
  • Firm growth
  • Business demography

JEL Classifications

  • D23
  • K41
  • K12
  • L11
  • L25
  • L26
  • O12
  • R12