Does management of working capital enhance firm value? Empirical analysis of manufacturing enterprises in India

  • Received June 23, 2023;
    Accepted August 23, 2023;
    Published September 5, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(3).2023.19
  • Article Info
    Volume 20 2023, Issue #3, pp. 224-238
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The long-term financial health of a corporation is assessed by its capacity to meet short-term financial commitments. Optimum working capital that maximizes enterprise value varies across companies. The purpose of this paper is to investigate whether Indian manufacturing enterprises’ firm values are influenced by working capital management efficiency. The data are taken from 2016 to 2022 (a seven-year period) for 223 top BSE-listed manufacturing companies. Firm value (explained variable) is proxied using Tobin’s Q, and the constituents of working capital, which include the net trade cycle, inventory period, debtors’ collection period, and creditor payment period, are taken as explanatory variables. The study also controls for any differences in firm characteristics and economic conditions by employing firm size, age, current ratio, net profit ratio, sale growth and GDP growth rate. Balanced-panel data analysis is conducted by employing a two-step generalized method of moment technique. Net trade cycle, inventory period and debtors’ collection period are found to have a strong and significant positive impact on Tobin’s Q. The findings however did not report any evidence of the significant relationship between creditor payment period and Tobin’s Q. Additionally, the outcomes also evidenced that firm value is positively impacted by company size, net profit ratio, sales growth and GDP, whereas negatively affected by firm age. This paper suggests that manufacturing firms may potentially enhance their firm value by prolonging the net trade cycle, period of inventory and lengthening the credit period to customers till the level of attainment of an optimum working capital.

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    • Table 1. Explained, explanatory and control variables
    • Table 2. Variance inflation factor
    • Table 3. Calculated descriptive statistics
    • Table 4. Results of two-step GMM regression
    • Table A1. Pearson сorrelation сoefficient
    • Conceptualization
      Rupali Gupta, Sunita Jatav, Gagan Prakash
    • Data curation
      Rupali Gupta, Gagan Prakash
    • Formal Analysis
      Rupali Gupta, Sunita Jatav, Gagan Prakash
    • Methodology
      Rupali Gupta, Sunita Jatav, Gagan Prakash
    • Software
      Rupali Gupta, Sunita Jatav
    • Supervision
      Rupali Gupta, Sunita Jatav
    • Validation
      Rupali Gupta, Sunita Jatav, Gagan Prakash
    • Visualization
      Rupali Gupta, Gagan Prakash
    • Writing – original draft
      Rupali Gupta, Sunita Jatav, Gagan Prakash
    • Writing – review & editing
      Rupali Gupta, Sunita Jatav, Gagan Prakash
    • Resources
      Gagan Prakash