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<p>This paper critically evaluates the most commonly used measures of firm financing constraint, namely, the Kaplan and Zingales (KZ), Whited and Wu (WW), and Hadlock and Pierce (HP) indices, as well as the Stochastic Frontier Analysis (SFA), in the context of India. Using panel data on Indian manufacturing firms from the Prowess database for the period 1996–2019, the study constructs the KZ, WW, and HP indices based on firm balance sheet data, assuming parameter stability. We also employ SFA to quantify time-varying financing constraints. Correlation and panel regression analyses are used to compare the effectiveness of these measures. The findings reveal weak correlations among the selected measures, indicating that they capture distinct dimensions of financing constraints and classify firms differently. None of the approaches consistently identifies financially constrained firms across all the contexts considered. The analysis further offers alternative explanations for the observed patterns, highlighting the importance of a broader understanding of the factors influencing firm behaviour. By analysing India’s distinct financial landscape, the paper underscores the need for a more refined approach to measuring financing constraints and offers valuable insights into firm-level financing dynamics.</p>

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A Critical Assessment of Measures of Financing Constraints: An Application to Indian Manufacturing

  • 期刊论文

  • 发表日期：

    2026年1月21日

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  • Meera Ancy Vincent,
  • Samaresh Bardhan,
  • Pranab Kumar Das

摘要

This paper critically evaluates the most commonly used measures of firm financing constraint, namely, the Kaplan and Zingales (KZ), Whited and Wu (WW), and Hadlock and Pierce (HP) indices, as well as the Stochastic Frontier Analysis (SFA), in the context of India. Using panel data on Indian manufacturing firms from the Prowess database for the period 1996–2019, the study constructs the KZ, WW, and HP indices based on firm balance sheet data, assuming parameter stability. We also employ SFA to quantify time-varying financing constraints. Correlation and panel regression analyses are used to compare the effectiveness of these measures. The findings reveal weak correlations among the selected measures, indicating that they capture distinct dimensions of financing constraints and classify firms differently. None of the approaches consistently identifies financially constrained firms across all the contexts considered. The analysis further offers alternative explanations for the observed patterns, highlighting the importance of a broader understanding of the factors influencing firm behaviour. By analysing India’s distinct financial landscape, the paper underscores the need for a more refined approach to measuring financing constraints and offers valuable insights into firm-level financing dynamics.