Credit constraints in European SMEs: does regional institutional quality matter?

ABSTRACT

We analyse the investment-to-cash flow relationship in Europe using a sample of manufacturing small- and medium-sized enterprises (SME) over the period 2009–2016. We investigate the effect of regional institutional quality on the investment-to-cash flow sensitivity, finding that, although credit constraints remain a serious problem for European SMEs, high-quality regional institutions contribute to mitigate the dependency on internally-generated resources to finance new investments. Improvements in local institutional quality can therefore facilitate SMEs’ access to credit – e.g. through inter-firm trade credit relationships –, but are insufficient to overcome the credit restrictions faced by European SMEs.

KEYWORDS:

• Credit constraints
• small- and medium-sized firms
• manufacturing industry
• institutional quality
• Europe

JEL CLASSIFICATION:

• C23
• D25
• R50

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed here.

Notes

¹ SMEs are firms with 10 to 249 employees (European Commission Recommendation 2003/361/EC).

² Online Appendix A describes the data, cleaning procedure, and sample structure.

³ Investment-to-cash flow sensitivity is not a perfect proxy for credit constraints (Kaplan and Zingales 1997). However, and for lack of better alternatives, it has been regularly used to capture credit constraints since Fazzari, Glenn, and Petersen (1988).

⁴ The ECM presents several advantages over the alternative Q model (Rodríguez‐Pose et al. 2021). Its flexibility reduces misspecification problems. It maintains the long-run properties of the standard value-maximizing investment model, allowing for short-run dynamics in adjustment costs. It can also be estimated for both unlisted and listed firms.

⁵ Online Appendix B discusses how the variables for investments and capital stock are calculated, presenting insights on investment-to-cash flow sensitivity.

⁶ Online Appendix C discusses the computation and interpretation of the regional institutional quality variable, presenting insights on its geographical distribution.

⁷ Online Appendix D reports descriptive statistics and correlation coefficients.

⁸ Online Appendix E discusses the computation of the precipitation variability variable.

⁹ Online Appendix F presents robustness exercises.