Financial Constraints: Models and Evidence from International Data

28 Pages Posted: 14 Jul 2009

See all articles by Monica H. Maestro

Monica H. Maestro

University of Salamanca - Department of Economic Analysis and Accounting

Alberto de Miguel

University of Salamanca - Administration and Business Economics

Julio Pindado

University of Salamanca - Administration and Business Economics

Abstract

This paper suggests a two-stage methodology to classify firms as financially constrained or unconstrained. First, we develop a financial constraints model that objectively separates over 50% of all firms, and enables us to classify the remaining firms by using logit analysis. Our methodology yields classification results in agreement with the financial development of the economic areas studied (the US, Japan and the EU). Furthermore, the suggested methodology substantially improves the classification of firms, since whatever the correct classification percentage yielded by logit analysis, previous application of our Financial Constraints Model allows the researcher to obtain a good final classification.

Keywords: Firm investment, Financial constraints, Logit analysis

JEL Classification: G31

Suggested Citation

Hernández Maestro, Monica and de Miguel Hidaldo, Alberto and Pindado, Julio, Financial Constraints: Models and Evidence from International Data. EFMA 2001 Lugano Meetings, Forthcoming, Available at SSRN: https://ssrn.com/abstract=274690 or http://dx.doi.org/10.2139/ssrn.274690

Monica Hernández Maestro

University of Salamanca - Department of Economic Analysis and Accounting ( email )

Salamanca, 37008
Spain
+34 (9)23 294400 (Phone)
+34 (9)23 294715 (Fax)

Alberto De Miguel Hidaldo

University of Salamanca - Administration and Business Economics ( email )

Campus Miguel de Unamuno
Salamanca, ES-37007
Spain
+34 923 294640 (Phone)
+34 923 294715 (Fax)

Julio Pindado (Contact Author)

University of Salamanca - Administration and Business Economics ( email )

Campus Miguel de Unamuno
Salamanca, ES-37007
Spain
+34 923 294640 (Phone)
+34 923 294715 (Fax)

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