Araştırma Makalesi
BibTex RIS Kaynak Göster

RELATIONSHIP BETWEEN COVID-19 AND MONEY SUPPLY IN TURKEY: EVIDENCE FROM ARDL BOUNDS TESTING APPROACH

Yıl 2022, Cilt: 9 Sayı: 2, 82 - 94, 30.06.2022
https://doi.org/10.17261/Pressacademia.2022.1568

Öz

Purpose- COVID-19 has been a devastating process. During this period, there was a significant increase in the money supply. So, in this process,
is there a relationship between COVID-19 and the money supply? This study intends to investigate if COVID-19 and the money supply have both
a short- and long-term relationship.
Methodology- Logarithmic conversions were used to examine the number of COVID-19 new cases obtained from the Association of Public
Health Professionals (HASUDER) and the Turkey Republic Ministry of Health, as well as M2 weekly money supply data from the Central Bank of
the Republic of Turkey (CBRT) Electronic Data Distribution System (EVDS). For stationarity tests, the Augmented Dickey-Fuller (ADF), Phillips
Perron (PP), and Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) unit root tests were used. Due to the different degrees of stationarity of the
series, cointegration was not possible, so the long-term relationship was evaluated using Autoregressive Distributed Lag (ARDL). Short-term
analyzes included the VAR Model and the Granger Causality Test.
Findings- COVID-19 and the money supply, according to the findings, are not cointegrated in the long term. It has been discovered that the series
do not move together over the long run. But in the short term, COVID-19 is a Granger cause of the money supply.
Conclusion- The increase in COVID-19 cases positively affects the money supply. An increase in the money supply also leads to inflation. Therefore,
in order to cope with the inflationary process triggered by the pandemic, measures to prevent the increase in COVID-19 cases are important.
These findings will be "confirming" in the design of policies in this process. This study is also a contribution to the literature due to the lack of
studies investigating the response of the money supply to COVID-19.

Kaynakça

  • Anser, M. K., Khan, M. A., Zaman, K. Nassani, A. A., Askar, S. E., Abro, M. M. Q., & Kabbani, A. (2021). Financial development during COVID-19 pandemic: the role of Coronavirus testing and Functional labs. Financial Innovation, 7(1), 1-13. doi: 10.1186/s40854-021-00226-4
  • Buchholz, C. (2020). The Coronavirus and carceral capitalism. Developing economics. https://developingeconomics.org/2020/04/11/thecoronavirus-and-carceral-capitalism/
  • CBRT. (2013). Bulletin No.31. https://www.tcmb.gov.tr/wps/wcm/connect/23fa999c-481e-478b-ba87- 9f61951ca8e7/Bulten31.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-23fa999c-481e-478b-ba87-9f61951ca8e7-m3fB9EG
  • Çiğdem, G. (2020). A Double-edged sword: COVID-19 and emission: proofs from Turkey. Eurasian Journal of Researches in Social and Economics (EJRSE), 7(7), 1-12. Çil Yavuz, N. (2015). Finansal ekonometri. İkinci Basım. İstanbul: Der Yayınları
  • Dickey, D. A. & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.
  • Eğilmez, M. (2018). Para arzı nedir ve nasıl ölçülür? https://www.mahfiegilmez.com/2018/07/para-arz-nedir-ve-nasl-olculur.html
  • Elgin, C., Basbug, G. & Yalaman, A. (2020). Economic policy responses to a pandemic: developing the Covid-19 economic stimulus index. Centre for Economic Policy Research. https://voxeu.org/article/economic-policy-responses-pandemic-covid-19-economic-stimulus-index
  • Enders, W. (1995). Applied econometric time series. New York: Wiley.
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438. doi:10.2307/1912791
  • Granger, C. W. J. (1980). Testing for causality: a personal viewpoint. Journal of Economic Dynamics and Control, 2, 329-352.
  • Granger, C. W. J. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, 16(1), 121-130.
  • Keating, J. W. (1990). Identifying VAR models under rational expectations. Journal of Monetary Economics, 25(3), 453-476.
  • Kumar, V., Leone, R. P., & Gaskins, J. N. (1995). Aggregate and disaggregate sector forecasting using consumer confidence measures. International Journal of Forecasting, 11(3), 361-377.
  • Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root? Journal of Econometrics, 54(1-3), 159-178.
  • Mousina, D. (2020). Econosight: inflation in the COVID-19 world, https://www.ampcapital.com/americas/en/insightshub/articles/2020/july/inflation-in-the-covid-19-world
  • Orhan, O. Z. & Erdoğan, S. (2002). Para politikası. İstanbul: Avcılar Ofset.
  • Parasız, İ. (2003). Para politikası. 6. Basım. Bursa: Ezgi Kitabevi.
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
  • Phillips, P. C. B. & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346.
  • Roubini, N. (2020). Coronavirus pandemic has delivered the fastest, deepest economic shock in history. The Guardian. https://www.theguardian.com/business/2020/mar/25/coronavirus-pandemic-has-delivered-the-fastest-deepest-economic-shock-in-history
  • Saad-Filho, A. (2020). From COVID-19 to the end of Neoliberalism. Critical Sociology, SAGE Journals, 46(4-5), 477-485. https://doi.org/10.1177%2F0896920520929966
  • Saito, J. (2021). COVID-19 and money supply. Japan Center for Economic Research. https://www.jcer.or.jp/english/covid-19-and-money-supply
  • Schwert, G. W. (1989). Tests for unit root: a Monte Carlo investigation. Journal of Business and Economic Statistics, 7(2), 147-160.
  • Sims, C. A. (1972). Money, income, and causality. The American Economic Review, 62(4), 540-552.
  • Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48.
  • Tarı, R. (2006). Ekonometri. 4. Baskı. İstanbul: Avcı Ofset.
  • Taymaz, E. (2020). COVID-19 tedbirlerinin Türkiye Ekonomisine etkisi ve çözüm önerileri. Sarkaç. https://sarkac.org/2020/04/covid19- tedbirlerinin-turkiyeekonomisine-etkisi-cozum-onerileri/
  • Ugarteche, O. & Ocampo, A. (2020). COVID-19: the beginning of domino effect. Observatorio Economico Latinoamericano, OBELO Discussion Paper. http://www.networkideas.org/wp-content/uploads/2020/04/covid19_domino_effect.pdf
  • Voyvoda, E. & Yeldan, E. A. (2020). COVID-19 salgınının Türkiye Ekonomisi üzerine etkileri ve politika alternatiflerinin makroekonomik genel denge analizi, https://yeldane.files.wordpress.com/2020/05/covid_voyvodayeldan_v2_31mayis.pdf
  • WHO. Coronavirus (COVID-19) dashboard, https://covid19.who.int/?gclid=CjwKCAjw07qDBhBxEiwA6pPbHicJAt5BTH7UFUqyiqQZUWTqMNNq0d7KJweiIu3NNJ8QAmhVzvw3hoCuKsQAvD_BwE
  • WHO. (2020). Archived: WHO timeline-COVID-19, https://www.who.int/news-room/detail/27-04-2020-whotimeline---covid- 19?gclid=EAIaIQobChMIotiQ-rfh6gIVCIBQBh2Ciwm_EAAYASAAEgIimfD_BwE
Yıl 2022, Cilt: 9 Sayı: 2, 82 - 94, 30.06.2022
https://doi.org/10.17261/Pressacademia.2022.1568

Öz

Kaynakça

  • Anser, M. K., Khan, M. A., Zaman, K. Nassani, A. A., Askar, S. E., Abro, M. M. Q., & Kabbani, A. (2021). Financial development during COVID-19 pandemic: the role of Coronavirus testing and Functional labs. Financial Innovation, 7(1), 1-13. doi: 10.1186/s40854-021-00226-4
  • Buchholz, C. (2020). The Coronavirus and carceral capitalism. Developing economics. https://developingeconomics.org/2020/04/11/thecoronavirus-and-carceral-capitalism/
  • CBRT. (2013). Bulletin No.31. https://www.tcmb.gov.tr/wps/wcm/connect/23fa999c-481e-478b-ba87- 9f61951ca8e7/Bulten31.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-23fa999c-481e-478b-ba87-9f61951ca8e7-m3fB9EG
  • Çiğdem, G. (2020). A Double-edged sword: COVID-19 and emission: proofs from Turkey. Eurasian Journal of Researches in Social and Economics (EJRSE), 7(7), 1-12. Çil Yavuz, N. (2015). Finansal ekonometri. İkinci Basım. İstanbul: Der Yayınları
  • Dickey, D. A. & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.
  • Eğilmez, M. (2018). Para arzı nedir ve nasıl ölçülür? https://www.mahfiegilmez.com/2018/07/para-arz-nedir-ve-nasl-olculur.html
  • Elgin, C., Basbug, G. & Yalaman, A. (2020). Economic policy responses to a pandemic: developing the Covid-19 economic stimulus index. Centre for Economic Policy Research. https://voxeu.org/article/economic-policy-responses-pandemic-covid-19-economic-stimulus-index
  • Enders, W. (1995). Applied econometric time series. New York: Wiley.
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438. doi:10.2307/1912791
  • Granger, C. W. J. (1980). Testing for causality: a personal viewpoint. Journal of Economic Dynamics and Control, 2, 329-352.
  • Granger, C. W. J. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, 16(1), 121-130.
  • Keating, J. W. (1990). Identifying VAR models under rational expectations. Journal of Monetary Economics, 25(3), 453-476.
  • Kumar, V., Leone, R. P., & Gaskins, J. N. (1995). Aggregate and disaggregate sector forecasting using consumer confidence measures. International Journal of Forecasting, 11(3), 361-377.
  • Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root? Journal of Econometrics, 54(1-3), 159-178.
  • Mousina, D. (2020). Econosight: inflation in the COVID-19 world, https://www.ampcapital.com/americas/en/insightshub/articles/2020/july/inflation-in-the-covid-19-world
  • Orhan, O. Z. & Erdoğan, S. (2002). Para politikası. İstanbul: Avcılar Ofset.
  • Parasız, İ. (2003). Para politikası. 6. Basım. Bursa: Ezgi Kitabevi.
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
  • Phillips, P. C. B. & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346.
  • Roubini, N. (2020). Coronavirus pandemic has delivered the fastest, deepest economic shock in history. The Guardian. https://www.theguardian.com/business/2020/mar/25/coronavirus-pandemic-has-delivered-the-fastest-deepest-economic-shock-in-history
  • Saad-Filho, A. (2020). From COVID-19 to the end of Neoliberalism. Critical Sociology, SAGE Journals, 46(4-5), 477-485. https://doi.org/10.1177%2F0896920520929966
  • Saito, J. (2021). COVID-19 and money supply. Japan Center for Economic Research. https://www.jcer.or.jp/english/covid-19-and-money-supply
  • Schwert, G. W. (1989). Tests for unit root: a Monte Carlo investigation. Journal of Business and Economic Statistics, 7(2), 147-160.
  • Sims, C. A. (1972). Money, income, and causality. The American Economic Review, 62(4), 540-552.
  • Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48.
  • Tarı, R. (2006). Ekonometri. 4. Baskı. İstanbul: Avcı Ofset.
  • Taymaz, E. (2020). COVID-19 tedbirlerinin Türkiye Ekonomisine etkisi ve çözüm önerileri. Sarkaç. https://sarkac.org/2020/04/covid19- tedbirlerinin-turkiyeekonomisine-etkisi-cozum-onerileri/
  • Ugarteche, O. & Ocampo, A. (2020). COVID-19: the beginning of domino effect. Observatorio Economico Latinoamericano, OBELO Discussion Paper. http://www.networkideas.org/wp-content/uploads/2020/04/covid19_domino_effect.pdf
  • Voyvoda, E. & Yeldan, E. A. (2020). COVID-19 salgınının Türkiye Ekonomisi üzerine etkileri ve politika alternatiflerinin makroekonomik genel denge analizi, https://yeldane.files.wordpress.com/2020/05/covid_voyvodayeldan_v2_31mayis.pdf
  • WHO. Coronavirus (COVID-19) dashboard, https://covid19.who.int/?gclid=CjwKCAjw07qDBhBxEiwA6pPbHicJAt5BTH7UFUqyiqQZUWTqMNNq0d7KJweiIu3NNJ8QAmhVzvw3hoCuKsQAvD_BwE
  • WHO. (2020). Archived: WHO timeline-COVID-19, https://www.who.int/news-room/detail/27-04-2020-whotimeline---covid- 19?gclid=EAIaIQobChMIotiQ-rfh6gIVCIBQBh2Ciwm_EAAYASAAEgIimfD_BwE
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Finans, İşletme
Bölüm Articles
Yazarlar

Gulgun Cıgdem Bu kişi benim 0000-0001-5353-8638

Osman Zekayi Orhan Bu kişi benim 0000-0001-6885-0499

Yayımlanma Tarihi 30 Haziran 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 9 Sayı: 2

Kaynak Göster

APA Cıgdem, G., & Orhan, O. Z. (2022). RELATIONSHIP BETWEEN COVID-19 AND MONEY SUPPLY IN TURKEY: EVIDENCE FROM ARDL BOUNDS TESTING APPROACH. Journal of Economics Finance and Accounting, 9(2), 82-94. https://doi.org/10.17261/Pressacademia.2022.1568

Journal of Economics, Finance and Accounting (JEFA) is a scientific, academic, double blind peer-reviewed, quarterly and open-access online journal. The journal publishes four issues a year. The issuing months are March, June, September and December. The publication languages of the Journal are English and Turkish. JEFA aims to provide a research source for all practitioners, policy makers, professionals and researchers working in the area of economics, finance, accounting and auditing. The editor in chief of JEFA invites all manuscripts that cover theoretical and/or applied researches on topics related to the interest areas of the Journal. JEFA publishes academic research studies only. JEFA charges no submission or publication fee.

Ethics Policy - JEFA applies the standards of Committee on Publication Ethics (COPE). JEFA is committed to the academic community ensuring ethics and quality of manuscripts in publications. Plagiarism is strictly forbidden and the manuscripts found to be plagiarized will not be accepted or if published will be removed from the publication. Authors must certify that their manuscripts are their original work. Plagiarism, duplicate, data fabrication and redundant publications are forbidden. The manuscripts are subject to plagiarism check by iThenticate or similar. All manuscript submissions must provide a similarity report (up to 15% excluding quotes, bibliography, abstract and method).

Open Access - All research articles published in PressAcademia Journals are fully open access; immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Open access is a property of individual works, not necessarily journals or publishers. Community standards, rather than copyright law, will continue to provide the mechanism for enforcement of proper attribution and responsible use of the published work, as they do now.