Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach
| Autor: | Muhammad Zahid Naeem, Maryam Batool, Ramona Birau, Cristi Spulbar, Muhammad Azmat Hayat, Abdullah Ejaz, Huma Ghulam |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Inflation
growth–inflation dynamics growth-inflation dynamics media_common.quotation_subject Industrial production cross-wavelet transform 0211 other engineering and technologies COVID-19 pandemic Context (language use) 02 engineering and technology Granger causality 0502 economics and business Econometrics Economics ddc:330 021108 energy maximum overlap discrete wavelet transform 050207 economics media_common continuous wavelet transform Short run Cointegration 05 social sciences Causality economic growth Interest rate cross-wavelet coherence HD61 HG1-9999 Risk in industry. Risk management Finance |
| Zdroj: | Journal of Risk and Financial Management Volume 14 Issue 6 Journal of Risk and Financial Management, Vol 14, Iss 277, p 277 (2021) |
| ISSN: | 1911-8074 |
| DOI: | 10.3390/jrfm14060277 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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