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Volume 6 - Number 3 | November

Does growth of nonperforming loan ratio have a temporal impact on private credit growth in Bangladesh economy?

N.M. Ashikuzzaman

02/11/2022 59 0 0
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Growth of nonperforming loan ratio Growth of private credit Long-run equilibrium relationship Auto regressive distributed lag model

Abstract:

Purpose
This paper addresses the question “Does the growth of nonperforming loan ratio (GNPL) have a temporal impact on private credit growth (PCG)?” for the Bangladesh banking industry during and after the global financial crisis of 2008.
Design/methodology/approach
It employs the autoregressive distributed lag (ARDL) model to examine the temporal equilibrium relationship and causality between PCG and GNPL.
Findings
The results of ARDL bound tests confirm the existence of a single cointegrating vector and temporal equilibrium relationship between variables of interest. According to the error correction mechanism (ECM), there is unidirectional causality from GNPL to PCG in the long run and short run. In the long run, higher GNPL curtails PCG since bankers use the nonperforming loan ratio as a signal and indicator of credit risk in their loan decision-making. In the short run, GNPL positively impacts PCG. It may be because banks go through a rigorous process before declaring a loan as nonperforming that takes time. At the same time, bankers' loan decisions may also be guided by the banks myopic concern of reputation in the short run.
Practical implications
The paper recommends policy prescriptions for the bank risk management, regulatory bodies and the legal authorities. The lending policy of banks should consider the legacy of bad assets. The efficiency of the legal system can also aid in effectively implementing the regulatory guidelines.
Originality/value
The paper inaugurates a bivariate cointegration analysis between PCG and GNPL in the literature. It has utilized quarterly aggregate data in the context of a developing economy like Bangladesh.

References:

  1. Accornero, M., Alessandri, P., Carpinelli, L. and Sorrentino, A.M. (2017), Non-performing Loans and the Supply of Bank Credit: Evidence from Italy, Bank of Italy Occasional Paper Number 374.
  2. Arltova, M. and Fedorova, D. (2016), “Selection of unit root test on the basis of length of the time series and value of AR (1) parameter”, Statistika-Statistics and Economy Journal, Vol. 96 No. 3, pp. 47-64.
  3. Cucinelli, D. (2015), “The impact of non-performing loans on bank lending behavior: evidence from the Italian banking sector”, Eurasian Journal of Business and Economics, Vol. 8 No. 16, pp. 59-71.
  4. Dey, B.K. (2019), “Managing nonperforming loans in Bangladesh”, Asian Development Bank Briefs, No. 116, doi: 10.22617/BRF190507-2.
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  7. Jin, J.Y., Kanagaretnam, K., Liu, Y. and Liu, N. (2019), “Banks' loan growth, loan quality, and social capital”, Journal of Behavioral and Experimental Finance, Vol. 21, pp. 83-102.
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  9. Peric, B.S. and Konjusak, N. (2017), “How did rapid credit growth cause non-performing loans in the CEE countries?”, South East European Journal of Economics and Business, Vol. 12 No. 2, pp. 73-84.
  10. Pesaran, M.H. and Shin, Y. (1998), “An autoregressive distributed-lag modelling approach to cointegration analysis”, Econometric Society Monographs, Vol. 31, pp. 371-413.
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  12. Vinh, N.T.H. (2017), “The impact of non-performing loans on bank profitability and lending behavior: evidence from Vietnam”, Journal of Economic Development, Vol. 24 No. 3, pp. 27-44.

Further reading

  1. Bangladesh Bank Quarterly (2021), available at: https://www.bb.org.bd/en/index.php/publication/publictn/2/7.

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