Indian Journal of Finance

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Sensitivity of Non-Performing Assets to GDP and Inflation Rate Volatility


Affiliations
1 Research Scholar, Amity Business School, Amity University Uttar Pradesh, Lucknow Campus, Malhaur, Lucknow - 226 010, Uttar Pradesh, India
2 Assistant Professor, Amity Business School, Amity University Uttar Pradesh, Lucknow Campus, Malhaur, Lucknow - 226 010, Uttar Pradesh, India

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This research examined the impact of inflation rate and gross domestic product (GDP) and their volatility on the non- performing assets (NPAs) in the Indian scheduled commercial banks from 1996–1997 to 2016–17. It examined how the macroeconomic volatility in the inflation rate and GDP significantly impacted the gross NPAs in the sampled banks. An econometric autoregressive model was employed where the gross NPAs were used as the explained variable, while one-period lags of gross NPAs, GDP, and inflation rate were the regressors. Pearson’s correlation analysis was also employed. Secondary data analysis was done. The findings confirmed that the one-period lag of gross NPAs had a positive and highly statistically significant effect on the gross NPAs ; whereas, GDP and inflation rate had a highly statistically insignificant effect on the gross NPAs in the sampled banks. It is envisaged that future research studies will be accomplished by including bank-specific and other macroeconomic factors. Other categories of Indian banks can be also included in further studies.

Keywords

Sensitivity, Non-Performing Assets, NPAs,, Inflation Rate, GDP,, Macroeconomic Variables, Volatility, Scheduled Commercial Banks, Econometric Autoregressive Model, Correlation Analysis.
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  • Abdelbaki, H. H. (2019). Macroeconomic determinants of non-performing loans in GCC economies : Does the global financial crisis matter ? International Journal of Economics and Business Research, 17(4), 433–447. https://doi.org/10.1504/IJEBR.2019.099973

  • Abid, L., Ouertani, M. N., & Zouari-Ghorbel, S. (2014). Macroeconomic and bank-specific determinants of household's non-performing loans in Tunisia : A dynamic panel data. Procedia Economics and Finance, 13, 58–68. https://doi.org/10.1016/S2212-5671(14)00430-4

  • Agrawal, K., & Maheshwari, Y. (2014). Default risk modelling using macroeconomic variables. Journal of Indian Business Research, 6(4), 270–285. https://doi.org/10.1108/JIBR-04-2014-0024

  • Ali, A., & Daly, K. (2010). Macroeconomic determinants of credit risk : Recent evidence from a cross country study. International Review of Financial Analysis, 19(3), 165–171. https://doi.org/10.1016/j.irfa.2010.03.001

  • Apergis, I., & Eleftheriou, S. (2019). The impact of the 2008 financial crisis on the Greek banking system. International Journal of Economics and Business Research, 17(3), 333–341. https://doi.org/10.1504/IJEBR.2019.098879

  • Beck, R., Jakubik, P., & Piloiu, A. (2015). Key determinants of non-performing loans : New evidence from a global sample. Open Economies Review, 26(3), 525–550. https://doi.org/10.1007/s11079-015-9358-8

  • Berger, H., & Hefeker, C. (2008). Does financial integration make banks more vulnerable ? Regulation, foreign owned banks, and the lender-of-last resort. International Economics and Economic Policy, 4(4), 371–393. https://doi.org/10.1007/s10368-007-0093-5

  • Bonfim, D. (2009). Credit risk drivers : Evaluating the contribution of firm level information and of macroeconomic dynamics. Journal of Banking & Finance, 33(2), 281–299. https://doi.org/10.1016/j.jbankfin.2008.08.006

  • Boudriga, A., Taktak, N. B., & Jellouli, S. (2009). Banking supervision and nonperforming loans : A cross - country analysis. Journal of Financial Economic Policy, 1(4), 286–318. https://doi.org/10.1108/17576380911050043

  • Castro, V. (2013). Macroeconomic determinants of the credit risk in the banking system : The case of the GIPSI. Economic Modelling, 31, 672–683. https://doi.org/10.1016/j.econmod.2013.01.027

  • Chaibi, H., & Ftiti, Z. (2015). Credit risk determinants : Evidence from a cross-country study. Research in International Business and Finance, 33, 1–16. https://doi.org/10.1016/j.ribaf.2014.06.001

  • Cifter, A., Yilmazer, S., & Cifter, E. (2009). Analysis of sectoral credit default cycle dependency with wavelet networks : Evidence from Turkey. Economic Modelling, 26(6), 1382–1388. https://doi.org/10.1016/j.econmod.2009.07.014

  • Dhar, S., & Bakshi, A. (2015). Determinants of loan losses of Indian Banks : A panel study. Journal of Asia Business Studies, 9(1), 17–32. https://doi.org/10.1108/JABS-04-2012-0017

  • Dimitrios, A., Helen, L., & Mike, T. (2016). Determinants of non-performing loans : Evidence from Euro-area countries. Finance Research Letters, 18, 116–119. https://doi.org/10.1016/j.frl.2016.04.008

  • Eichengreen, B., & Gupta, P. (2013). The financial crisis and Indian banks : Survival of the fittest ? Journal of International Money and Finance, 39, 138–152. https://doi.org/10.1016/j.jimonfin.2013.06.022

  • Fainstein, G., & Novikov, I. (2011). The role of macroeconomic determinants in credit risk measurement in transition country : Estonian example. International Journal of Transitions and Innovation Systems, 1(2), 117–137. https://doi.org/10.1504/IJTIS.2011.039621

  • Ghosh, J., & Chandrasekhar, C. P. (2009). The costs of ‘coupling’: The global crisis and the Indian economy. Cambridge Journal of Economics, 33(4), 725–739. https://doi.org/10.1093/cje/bep034

  • Gulati, R., & Kumar, S. (2016). Assessing the impact of the global financial crisis on the profit efficiency of Indian banks. Economic Modelling, 58, 167–181. https://doi.org/10.1016/j.econmod.2016.05.029

  • India GDP Data Highlights | Q1FY21 GDP at -23.9%, worst contraction on record. (2020, August 31). Moneycontrol.com. https://www.moneycontrol.com/news/business/india-gdp-data-live-updatesindia-economy-coronavirus-covid-19-hit-business-5775151.html

  • Jabra, W.B., Mighri, Z., & Mansouri, F. (2017). The determinants of credit and insolvency risk of European commercial banks : A dynamic panel data analysis. International Journal of Monetary Economics and Finance, 10(2), 111–143. https://doi.org/10.1504/IJMEF.2017.084208

  • Kshetri, N. (2011). Emerging economies and the global financial crisis : Evidence from China and India. Thunderbird International Business Review, 53(2), 247–262. https://doi.org/10.1002/tie.20404

  • Louzis, D. P., Vouldis, A. T., & Metaxas, V. L. (2012). Macroeconomic and bank-specific determinants of nonperforming loans in Greece : A comparative study of mortgage, business and consumer loan portfolios. Journal of Banking & Finance, 36(4), 1012–1027. https://doi.org/10.1016/j.jbankfin.2011.10.012

  • Messai, A. - S., & Gallali, M.I. (2019). Macroeconomic determinants of credit risk: A P-VAR approach evidence from Europe. International Journal of Monetary Economics and Finance, 12(1), 15–24. https://doi.org/10.1504/IJMEF.2019.098638

  • Nachane, D. M., & Shahidul Islam, M. (2012). Post-crisis South Asia : Monetary management and macro-prudential regulation. South Asian Journal of Global Business Research, 1(2), 189–209. https://doi.org/10.1108/20454451211252732

  • Otašević, D. (2015). The influence of macroeconomic risks on credit risk in the Serbian banks’ loan portfolio. Neo Transitional Economics, 16, 219–243. https://doi.org/10.1108/S1569-376720150000016010

  • Reinhart, C. M., & Rogoff, K. S. (2011). From financial crash to debt crisis. American Economic Review, 101(5), 1676–1706. https://doi.org/10.1257/aer.101.5.1676

  • Reserve Bank of India. (2015). Master Circular–Prudential norms on income recognition, asset classification and provisioning pertaining to advances. https://rbidocs.rbi.org.in/rdocs/notification/PDFs/101MC16B68A0EDCA9434CBC239741F5267329.PDF

  • Reserve Bank of India. (2018). Handbook of statistics on Indian economy 2017–18. https://rbi.org.in/Scripts/AnnualPublications.aspx?head=Handbook+of+Statistics+on+Indian+Economy

  • Reserve Bank of India. (2021). Database on Indian economy : Bank wise and bank group-wise gross non-performing assets, gross advances and gross NPA ratio of scheduled commercial banks. https://dbie.rbi.org.in/DBIE/dbie.rbi?site=publications

  • Sharma, S. D. (2009). Dealing with the contagion : China and India in the aftermath of the subprime meltdown. China & World Economy, 17(2), 1–14. https://doi.org/10.1111/j.1749-124X.2009.01138.x

  • Syed, A. A., & Tripathi, R. (2019). Non - performing loans in BRICS nations : Determinants and macroeconomic impact. Indian Journal of Finance, 13(2), 22–35. http://doi.org/10.17010/ijf/2019/v13i2/141684

  • Syed, A. A., & Tripathi, R. (2020). Macroeconomic vulnerabilities and their effect on nonperforming loans in Indian commercial banks. Indian Journal of Finance, 14(2), 34–49. http://doi.org/10.17010/ijf/2020/v14i2/150555

  • Szarowska, I. (2018). Effect of macroeconomic determinants on non-performing loans in Central and Eastern European countries. International Journal of Monetary Economics and Finance, 11(1), 20–35. https://doi.org/10.1504/IJMEF.2018.090564

  • Tarchouna, A., Jarraya, B., & Bouri, A. (2019). To what extent the global financial crisis deteriorated loan quality of US commercial banks ? International Journal of Management and Enterprise Development, 18(1/2), 63–84. https://doi.org/10.1504/IJMED.2019.097801

  • Tiwari, D. (2017, May 16). IMF alert on NPAs may have made RBI seek more power. The Economics Times. https://economictimes.indiatimes.com/news/economy/policy/imf-alert-on-npas-may-have-maderbi-seek-more-power/articleshow/58689239.cms

  • Trading Economics. (2021a.). India GDP annual growth rate. https://tradingeconomics.com/india/gdp-growthannual Trading Economics. (2021b.). India inflation rate. https://tradingeconomics.com/india/inflation-cpi

  • Tsai, B. - H., Lee, C. - F., & Sun, L. (2009). The impact of auditors' opinions, macroeconomic and industry factors on financial distress prediction : An empirical investigation. Review of Pacific Basin Financial Markets and Policies, 12(03), 417–454. https://doi.org/10.1142/S0219091509001691

  • Upadhyaya, P., & Roy, S. G. (2017). Analysis of macroeconomic factors causing non-performing loans in India. International Journal of Business and Globalisation, 18(2), 182–193. https://doi.org/10.1504/IJBG.2017.081948

  • Uppal, R., & Khanna, P. (2015). Factors affecting NPAs of scheduled commercial banks : An empirical study based in Punjab. Indian Journal of Finance, 9(2), 7–16. http://doi.org/10.17010/ijf/2015/v9i2/71517

  • Viswanathan, P., & Muthuraj, M. (2019). Factors leading to non - performing assets (NPAs) : An empirical study. Indian Journal of Finance, 13(1), 55–64. http://doi.org/10.17010/ijf/2019/v13i1/141051

  • Welfens, P. J. (2008). Banking crisis and prudential supervision : A European perspective. International Economics and Economic Policy, 4(4), 347–356. https://doi.org/10.1007/s10368-007-0095-3

  • World Bank. (2018). GDP growth (annual %). https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG

  • Yurdakul, F. (2014). Macroeconomic modelling of credit risk for banks. Procedia-Social and Behavioral Sciences, 109, 784–793. https://doi.org/10.1016/j.sbspro.2013.12.544


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  • Sensitivity of Non-Performing Assets to GDP and Inflation Rate Volatility

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Authors

Tabassum
Research Scholar, Amity Business School, Amity University Uttar Pradesh, Lucknow Campus, Malhaur, Lucknow - 226 010, Uttar Pradesh, India
Sarveshwar Pande
Assistant Professor, Amity Business School, Amity University Uttar Pradesh, Lucknow Campus, Malhaur, Lucknow - 226 010, Uttar Pradesh, India

Abstract


This research examined the impact of inflation rate and gross domestic product (GDP) and their volatility on the non- performing assets (NPAs) in the Indian scheduled commercial banks from 1996–1997 to 2016–17. It examined how the macroeconomic volatility in the inflation rate and GDP significantly impacted the gross NPAs in the sampled banks. An econometric autoregressive model was employed where the gross NPAs were used as the explained variable, while one-period lags of gross NPAs, GDP, and inflation rate were the regressors. Pearson’s correlation analysis was also employed. Secondary data analysis was done. The findings confirmed that the one-period lag of gross NPAs had a positive and highly statistically significant effect on the gross NPAs ; whereas, GDP and inflation rate had a highly statistically insignificant effect on the gross NPAs in the sampled banks. It is envisaged that future research studies will be accomplished by including bank-specific and other macroeconomic factors. Other categories of Indian banks can be also included in further studies.

Keywords


Sensitivity, Non-Performing Assets, NPAs,, Inflation Rate, GDP,, Macroeconomic Variables, Volatility, Scheduled Commercial Banks, Econometric Autoregressive Model, Correlation Analysis.

References





DOI: https://doi.org/10.17010/ijf%2F2021%2Fv15i4%2F158672