Abstract
Fostering a country’s competitiveness is crucial to provide a viable escape from the current crisis. Using a novel micro-level dataset (EFIGE dataset), this chapter analyzes the relationship between firm-level productivity and the ability of a firm to compete in international markets. Subsequently, the chapter investigates the link between productivity and access to external financing during the crisis. We found that more productive firms are less likely to apply for external financing, but once they do apply for extra credit, they experience a higher probability of obtaining the loan. This selection mechanism is, however, effective only at very low levels of productivity, and creates some friction when firms move up the productivity ladder. This evidence calls for renewed attention by policymakers to ensure that the implementation of new banking regulations is able to guarantee an allocation of credit and access to finance that correlates to firms’ underlying productivity.
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Notes
- 1.
Additional project information can be obtained from the official web site: www.efige.org
- 2.
See www.bvdinfo.com for further information on the dataset.
- 3.
- 4.
Annex shows the equations relative to each indicator.
- 5.
The indicators are not introduced together in the regression to avoid multicollinearity problems.
- 6.
The relationship estimated with respect to IFP and LevR is negative and decreases with TFP deciles because both indicators have a negative connotation.
- 7.
The definitions of weak and strong credit constraints are derived from those proposed by Minetti and Zhu (2011), who worked on a similar variable for Italy.
- 8.
Note that the percentages are computed over the number of firms that applied for extra credit, by country.
- 9.
Take note that the total number of credit rationed firms does not match the figure of 1,997 presented previously. This is because the 2008 TFP value for 736 firms is missing.
- 10.
The inclusion of R&D in the estimate has the function of exclusion restriction: it is a variable that is correlated with the selection term (probability of requesting extra credit) but not necessarily with the dependent variable of the outcome equation (TFP). Our results show that R&D is slightly positively and significantly correlated with TFP in our sample (+0.0377***), but much more with the probability of requesting credit (+0.2932***). The exclusion restriction helps the strong identification of the selection equation and thus of the model.
- 11.
Note that the original question in the survey concerns the use of the increased external finance, including different sources of financing, mainly bank loans and securities; given the purpose of the research we have considered only the firms that financed through the banking system. However, when considering both sources of financing the distribution of uses by TFP deciles is not affected by major structural changes.
References
Altomonte C, Barba Navaretti G, di Mauro F, Ottaviano G (2011) Assessing competitiveness: how firm-level data can help. Policy contributions 643, Bruegel
Forlani E (2010) Liquidity constraints and firm’s export activity. Development Working Papers 291, Centro Studi Luca d’Agliano, University of Milano
Heckman J (1976) The common structure of statistical models of truncation, sample selection, and limited dependent variables and a simple estimator for such models. Ann Econ Soc Meas 5:475–492
Kaplan S, Zingales L (1997) Do financing constraints explain why investment is correlated with cash flow? Q J Econ 112:169–215
Koenker RW, Bassett G Jr (1978) Regression quantiles. Econometrica, Econometric Society 46(1):33–50
Levinsohn J, Petrin A (2003) Estimating production functions using inputs to control for unobservables. Rev Econ Stud 70(2):317–341
Mayer T, Ottaviano G (2008) The happy few: the internationalisation of European firms. Intereconomics: Review of European Economic Policy 43(3):135–148
Melitz MJ (2003) The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica 71(6):1695–1725
Melitz MJ, Ottaviano GIP (2008) Market size, trade, and productivity. Rev Econ Stud 75(1):295–316
Minetti R, Zhu SC (2011) Credit constraints and firm export: microeconomic evidence from Italy. J Int Econ 83(2):109–125
Nickell SJ, Nicolitsas D (1999) How does financial pressure affect firms? Eur Econ Rev 43:1435–1456
Rajan RG, Zingales L (1998) Financial dependence and growth. Am Econ Rev 88(3):559–586
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Appendix: Description of the Financial Indicators
Appendix: Description of the Financial Indicators
Below is a list of the financial variables created. The subscripts indicate that each indicator is specific for firm i at time t.
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Altomonte, C., Saggiorato, L. (2013). Is a New Financial Model Necessary for Growth?. In: Kaji, S., Ogawa, E. (eds) Who Will Provide the Next Financial Model?. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54282-7_11
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