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A methodological framework for exploring SME finance with SAFE data.

Marie Finnegan^1,2, Lucía Morales²

¹School of Business, Atlantic Technological University, Galway, Ireland.

|August 29, 2024

Summary

This study introduces a framework for selecting econometric models for small and medium-sized enterprises (SMEs) finance research using Survey on Access to Finance of Enterprises (SAFE) data. It highlights when the linear probability model (LPM) is suitable alongside probit and logit models.

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Analysis of SEC-SAXS data via EFA deconvolution and Scatter

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Published on: January 28, 2021

Area of Science:

Econometrics
Financial Economics
SME Finance

Background:

Small and medium-sized enterprises (SMEs) are crucial to the euro area economy, representing over half of GDP and employing 100 million people.
Research on SME access to finance often uses the Survey on Access to Finance of Enterprises (SAFE) data.
Existing studies predominantly use probit or logit models, with limited justification for model selection and a lack of robustness tests.

Purpose of the Study:

To address the research gap in econometric model selection for SME finance studies using SAFE data.
To introduce a robust methodological framework for choosing appropriate categorical dependent models.
To provide evidence-based criteria for model selection among LPM, probit, and logit models.

Main Methods:

Development of a methodological framework with four criteria for model selection.
Comparative analysis of Linear Probability Model (LPM), probit, and logit models.
Application of the framework to SAFE data for SME finance research.

Main Results:

The probit model is generally appropriate, but the LPM is suitable in specific cases involving interactions between monetary policy and debt-to-assets or innovation.
Identified four key criteria to guide the selection of appropriate econometric models.
Demonstrated the validity and utility of the proposed methodological framework.

Conclusions:

The study provides a robust approach to selecting econometric models for SME finance research using SAFE data.
The findings support the effective use of LPM in specific contexts, offering a simpler alternative for clearer communication.
The proposed framework enhances the reliability and comparability of research on SME access to finance.