Working capital management and bank performance: empirical research of ten deposit money banks in Nigeria

  • Received February 6, 2018;
    Accepted May 11, 2018;
    Published June 18, 2018
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  • Article Info
    Volume 13 2018, Issue #2, pp. 49-61
  • Cited by
    16 articles

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Working capital management is germane for the success of the banking industry in Nigeria, especially the current state of the sector, which is engulfed with the effect of the global decline in oil price that has resulted in non-performing loans, deterioration of the bank asset quality, laying-off of staff amongst others. This is one of the reasons why the profitability of the banking sector deeply depends on the efficient management of a bank’s working capital. Therefore, the objective of this study is to examine how profitability of banks can be enhanced through the working capital management. To empirically carry out the analysis, panel data which consist of ten (10) deposit money banks in Nigeria for seven years (2010–2016) employing the panel fixed effect, panel random effect and the pooled OLS for the two models, which were used as proxies for bank profitability, which includes return on asset (ROA) and return on equity (ROE) to examine the best measure for bank profitability, with the indicators of working capital; net interest income, current ratio, profit after tax, and monetary policy rate. Results of the study showed that working capital management has a significant effect on the profitability of the selected banks and that return on asset is a better measure for bank profitability. Therefore, the study recommends that there should be a periodic review of the minimum capital base of the Nigerian deposit money banks so as to mitigate the effects of inflation and inculcate the consequence of time value of money, because the purchasing power of one (₦1) naira or one ($1) dollar today would not be sufficient to purchase what it can purchase today for tomorrow.

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    • Table 1. Data source
    • Table 2. Summary statistics of variables
    • Table 3. Regression model estimates
    • Table 4. Robustness test
    • Table 5. Correlation test for multicollinearity