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Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach

Muhammad Azmat Hayat, Huma Ghulam, Maryam Batool, Muhammad Zahid Naeem, Abdullah Ejaz, Cristi Spulbar () and Ramona Birau
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Muhammad Azmat Hayat: Department of Economics, University of the Punjab, Quaid-i-Azam Campus, Lahore 54590, Pakistan
Huma Ghulam: Department of Economics and Business Administration, University of Education, Lahore 54590, Pakistan
Maryam Batool: Department of Economics and Business Administration, University of Education, Lahore 54590, Pakistan
Muhammad Zahid Naeem: UBD Scholl of Business and Economics, University of Brunei Darussalam (UBD), Bandar Seri Begawan BE-1410, Brunei
Abdullah Ejaz: Bredin College of Business and Health Care, Edmonton, AB T5J 0K1, Canada
Ramona Birau: Faculty of Education Science, Law and Public Administration, C-Tin Brancusi University of Targu Jiu, 210135 Târgu Jiu, Romania

JRFM, 2021, vol. 14, issue 6, 1-22

Abstract: This research is the earliest attempt to understand the impact of inflation and the interest rate on output growth in the context of Pakistan using the wavelet transformation approach. For this study, we used monthly data on inflation, the interest rate, and industrial production from January 1991 to May 2020. The COVID-19 pandemic has affected economies around the world, especially in view of the measures taken by governmental authorities regarding enforced lockdowns and social distancing. Traditional studies empirically explored the relationship between these important macroeconomic variables only for the short run and long run. Firstly, we employed the autoregressive distributed lag (ARDL) cointegration test and two causality tests (Granger causality and Toda–Yamamoto) to check the cointegration properties and causal relationship among these variables, respectively. After confirming the long-run causality from the ARDL bound test, we decomposed the time series of growth, inflation, and the interest rate into different time scales using wavelet analysis which allows us to study the relationship among variables for the very short run, medium run, long run, and very long run. The continuous wavelet transform (CWT), the cross-wavelet transform (XWT), cross-wavelet coherence (WTC), and multi-scale Granger causality tests were used to investigate the co-movement and nature of the causality between inflation and growth and the interest rate and growth. The results of the wavelet and multi-scale Granger causality tests show that the causal relationship between these variables is not the same across all time horizons; rather, it is unidirectional in the short-run and medium-run but bi-directional in the long-run. Therefore, this study suggests that the central bank should try to maintain inflation and the interest rate at a low level in the short run and medium run instead of putting too much pressure on these variables in the long-run.

Keywords: COVID-19 pandemic; continuous wavelet transform; cross-wavelet transform; economic growth; cross-wavelet coherence; growth–inflation dynamics; maximum overlap discrete wavelet transform (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
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