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Multiple market imperfections, firm profitability and investment

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Abstract

This paper investigates the impact of the interaction between product, labor and financial market imperfections on firms’ investment by using a panel data of European firms over the period 1994–2008. It studies the impact of product and labor market regulations on firm investment and how it changes with the degree of financial market imperfections. Findings show that product and labor market regulations negatively affect firm investment by lowering firm profitability. The presence of more efficient financial markets increases firm investment and lowers the negative effects of market regulations.

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Notes

  1. Peev (2014) analyzes the role of institutions and economic liberalization on growth of firms located in the European transition economies, while Audretsch et al. (Forthcoming) discuss the institutional drivers of entrepreneurships across countries.

  2. Example of papers that study the effects of the contemporaneous presence of markets imperfections are Nickell and Nicolitsas (1999); Belke and Fehn (2000); Arnold (2002); Blanchard and Giavazzi (2003); Spector (2004); Rendon (2004); Wasmer and Weil (2004); Povel and Raith (2004); Amable and Ekkehard (2005); Fiori et al. (2007); Griffith et al. (2007) . However, they are not concerned with investment decisions.

  3. http://ec.europa.eu/europe2020/pdf/themes/23_employment_protection_legislation.; Schmann (2014).

  4. Research on the role of product market regulation has mainly focused on its direct effects on economic performance, i.e: the allocation of resources between sectors and between firms; the productivity of existing firms; the pace of productivity growth Schiantarelli (2005). Regulatory reforms that imply a reduction in entry barriers, in the markup of prices over costs and in adjustment costs tend to increase investment Alesina (2005). Recently, Barone and Cingano (2011) find that lower service regulation has non-negligible positive effects on the value added, productivity and export growth rates of service-intensive users. For a survey of the literature on regulation and economic performance see Rincon-Aznar et al. (2010) and Arnold et al. (2011).

  5. Some authors are critical towards this popular approach. See Erickson and Whited (2000); Bond and Klemm (2004); Whited (2010), and Moyen (2004).

  6. These results are in line with Andrews and Cingano (2012), who examine the extent to which regulations affecting product, labour and credit markets influence productivity, via their effect on the efficiency of resource allocation, in the OECD countries. The authors find an economically and statistically robust negative relationship between policy-induced frictions and productivity, though the specific channel depends on the policy considered. In the case of employment protection legislation and product market regulations this is largely traceable to the worsening of allocative efficiency. By contrast, financial market under-development tends to be associated with a higher fraction of low productivity relative to high productivity firms.

  7. http://epp.eurostat.ec.europa.eu/portal/page/portal/european_business/data/database.

  8. Germany constitutes a special case in Amadeus. Most firms in this country have limited information on their balance sheets, including employment and very few financial items.

  9. The distribution of firms by sector of activity for the eight European countries refers to the year 2010, as it is the first year available with sectorial disaggregation in the Business Demography Statistics Database of Eurostat.

  10. Version 2 was excluded from this study, even though it also accounts for collective dismissal, because the series starts in 1998.

  11. See http://www.oecd.org/eco/reform/45654705 for a description of the RII indicator.

  12. However, Finland experienced a smaller contraction of its capital market than the other countries, given that it already witnessed a story of a credit-led boom-bust cycle during the 90 s and a strong financial crisis at the end of the 90 s.

  13. Profitability is modeled as characterized by random effects because the firm sample used to estimate model (1) was randomly drawn from a larger firm population. According to Green (2011, p. 371) ’..an intercountry comparison may well include the full set of countries for which it is reasonable to assume that the model is constant. If the individual effects are strictly uncorrelated with the regressors, then it might be appropriate to model the individual specific constant terms as randomly distributed across cross-sectional units. This view would be appropriate if we believed that sampled cross-sectional units were drawn from a large population’. The presence of random effects is tested by the Breusch and Pagan Lagrangian Multiplier (BP LM) test that fails to reject the null of no need of random effects (\(Var(u)=0\)), as shown at the bottom of Table 6 Green (2011).

  14. Garcia-Posada and Mora-Sanguinetti Garcia-Posada et al. (Forthcoming) analyze the impact of legal efficiency on firm dynamics, and find that higher judicial efficacy increases the entry rate of firms, while it has no effect on the exit rate. The authors argue that judicial (in)efficacy can be regarded as a fixed cost to be paid by the agents that litigate.

  15. SSchiefer and Hartmann (2013) identify four possible macroeconomic effects with regard to the EU: (1) EU-wide fluctuations, (2) national fluctuations, (3) EU-wide industry-specific fluctuations, and (4) national industry-specific fluctuations.

  16. A main concern, in addition to the Kaplan and Zingales critique, is the fact that cash flow depends on balance sheet policies, and therefore is more an accounting variable than an economic variable. Furthermore, financiers might see firms with a better liquidity position as less risky and charge them a lower interest rate. Moreover, investment may also depend on the availability of other, less volatile, financial resources Coluzzi and Ferrando (2012). See also Bond and Klemm (2004) for a discussion about measurement errors and the explanatory power of cash flow.

  17. Multiplicative interaction models are common in the quantitative social and political science literature. Institutional arguments frequently imply that the relationship between economic inputs and outcomes varies depending on the institutional context Brambor et al. (2006).

  18. This method uses equations in first-differences for which endogenous variables lagged two or more periods will be valid instruments, provided there is no serial correlation in the time varying component of the error term. This assumption is tested by performing tests for serial correlation in the first differences residuals. The equations in differences are combined with the equations in levels, for which lagged differences of the variables are used as instruments. AR(1) and AR(2) are the empirical realizations of the test statistics of first and second order residual autocorrelation. Significance means that the null hypothesis of no autocorrelation is rejected. The absence of AR(2) is the necessary condition for unbiased and efficient estimates (Blundell et al. 2000, 1998).

  19. To check whether this is an uniform pattern across the eight countries, we estimate an alternative model which controls for country differences by means of interaction terms (Country*FMD). Findings suggest that the negative impact of FMD on firm profitability is amplified for Italian, Spanish and Portuguese firms, and available upon request from the authors. Further, as Finland joined the European Union in 1995, while the other countries have been members from the 1980s and earlier, we also estimate model (1) without Finnish firms. Findings of Table 6 are confirmed and available upon request from the authors.

  20. Table 7 presents estimates for a a specification of Eq. (2) in which the interaction term PROF*FMD is left out of the model because its estimated coefficient is not statistically significant. Estimates are available upon request from the authors.

  21. The two models (1) and (2) generate a triangular system and one does not need to include all exogenous variables of Eq. (2) as instruments for the profitability Baltagi (2002).

  22. For robustness check purposes, we also draw a 15 % random sample from Amadeus to obtain an unbalanced panel of 117,072 firms and 569,980 firm-year observations, and estimate models (1) and (2) on this alternative sample. Findings of Tables 6 and 7 are confirmed and available upon request from the authors.

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Acknowledgments

This paper benefited from comments and suggestions from two anonymous referees, and participants at the international conferences: Beyond the short run: productivity growth, market imperfections and macroeconomic disequilibrium held in Rome on 11–12 May 2012; the Swedish Entrepreneurship Forum on Regulations, Entrepreneurship and Firm Dynamics held in Stockholm, 23–24 August 2013; the 34th Italian Conference on Regional Science, held in Palermo, 2–3 September 2013; the annual conference of the Italian Economic Association, held in Bologna, 24–26 October 2013; the annual conference of the Eastern Finance Association held in Pittsburgh, 9–14 April 2014. We are especially grateful to R. Chirinko, G. Maffini, E. Saltari, E. Sterken, and G. Travaglini. The usual disclaimers apply.

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Correspondence to Germana Giombini.

Appendix 1: variable definitions

Appendix 1: variable definitions

  • AGE is the number of years since incorporation;

  • ASSETS is the natural log of total assets (in mil), expressed in real value. It is used as a measure of firm size;

  • I/K is the ratio of capital expenditure at time t to tangible total assets at time t−1. Capital expenditure is computed as the annual change in tangible fixed assets plus depreciation;

  • LIQ is the ratio of cash and cash equivalents to total assets;

  • PROF is the ratio of operating profits to total fixed assets;

  • EPL is the Employment Protection Index, Version 1 (OECD 2004) . The index includes the costs for employers of firing workers with regular contracts and it is measured according to the strictness in the regulations for regular procedural inconvenience, notice and severance pay for no-fault individual dismissals, and difficulty of dismissals. It also includes the degree of strictness of labour regulations for temporary workers related to hiring practices such as type of contracts considered acceptable or number of successive contracts or renewals. The index is measured both for the fixed-term contracts and for temporary agency workers. The overall EPL index ranges theoretically from 0 to 6;

  • RII is the sectoral regulation impact index, based on OECD Regulation Impact indicators (Conway and Nicoletti 2006). This indicator measures the knock-on-effects of non-manufacturing regulation on the cost structures faced by firms that use the output of non-manufacturing sectors as intermediate inputs in the production process. The index is calculated as follows

    $$\begin{aligned} RII_{k,t}=\sum _{j} {NMR}_{j,t}*w_{j,k} \end{aligned}$$
    (6)

    where the variable \(NMR_{j,t}\) is an indicator of anti-competitive regulation in non-manufacturing sector j at time t and the weight \(w_{j,k}\) is the total input requirement of sector k for intermediate inputs from non- manufacturing sector j;

  • CAP MK is the Capital market size index. The measure is the sum of outstanding stocks, bonds and bank loans as a share of GDP (ECB 2013);

  • FIN EFF is the Financial Efficiency index. It is measured as private credit by deposit money banks and other financial institutions to GDP (from the World Bank Financial Structure Dataset);

  • FIN DEV is the Financial Development index. It is measured as Deposit Money to Central Bank Assets (from the World Bank Financial Structure Dataset).

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Calcagnini, G., Ferrando, A. & Giombini, G. Multiple market imperfections, firm profitability and investment. Eur J Law Econ 40, 95–120 (2015). https://doi.org/10.1007/s10657-014-9454-z

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