The Effects of Covid-19 Health Crisis and 2008 Global Financial Crisis on Labor Markets: A Comparative Analysis by Income Groups of Countries

Yıl 2022, Cilt: 13 Sayı: 1, 60 - 80, 25.01.2022

Esat Daşdemir

Öz

This study investigates the Covid-19 Health Crisis and the 2008 Global Financial Crisis effects on the labour markets of high-income countries (HICs) and middle- and low-income countries (M-LICs). As a result of the research, it has been determined that crises have different effects on country groups. In study determined two crises have different effects on country groups. The main reasons for the different effects of the Covid-19 Health Crisis to country groups are; a- Labour mobility reduction due to Covid-19 public health interventions, b- There are fewer sectors that can adapt to remote work in M-LICs production structure, c- SME intensive production structure of M-LICs. The study is a leading source in the literature that reveals the impact of the Covid-19 Health Crisis and the 2008 Global Financial Crisis on the labour markets of HICs and M-LICs.

Anahtar Kelimeler

Covid-19, Employment Rate, Income Distribution, Remote Work, Labour Market

Covid-19 Sağlık Krizi ile 2008 Küresel Finansal Krizin İşgücü Piyasalarına Etkisi: Ülkelerin Gelir Gruplarına Göre Karşılaştırmalı Bir Analiz

Öz

Bu çalışma, Covid-19 Sağlık Krizi ve 2008 Küresel Finansal Krizinin yüksek gelirli ülkelerin (YGÜ) ve orta ve düşük gelirli ülkelerin (O-DGÜ) işgücü piyasaları üzerindeki etkilerini karşılaştırmalı olarak incelemiştir. Yapılan ekonometrik analiz sonucunda iki krizin farklı ekonomik sonuçlar yarattığı anlaşılmıştır. Covid-19 Sağlık Krizinin ülke gruplarına farklı etkilerinin başlıca nedenleri; a- Covid-19 halk sağlığı müdahaleleri nedeniyle işgücü hareketliliğinin azalması, b- O-DGÜ'lerin üretim yapısında uzaktan çalışmaya uyum sağlayabilecek sektörlerin daha az olması, c- O-DGÜ'lerin KOBİ yoğun üretim yapısı. Covid-19 Sağlık Krizi ve 2008 Küresel Finansal Krizinin YGÜ'lerin ve O-DGÜ'lerin işgücü piyasaları üzerindeki etkisini ortaya koyan çalışma, literatüre önemli bir katkı sunmaktadır.

Anahtar Kelimeler

Covid-19, Covid-19, İstihdam Oranı, Gelir Dağılımı, Uzaktan Çalışma, İşgücü Piyasası

Kaynakça

• Bovenberg, A. L., & Van Der Ploeg, F. (1998). Tax Reform, Structural Unemployment and the Environment. The Scandinavian Journal of Economics, 100(3), 593–610. https://doi.org/https://doi.org/10.1111/1467-9442.00124
• Brown, M. B., & Forsythe, A. B. (1974). Robust Tests for the Equality of Variances. Journal of the American Statistical Association, 69(346), 364–367. https://doi.org/10.2307/2285659
• Ceylan, R. F., Ozkan, B., & Mulazimogullari, E. (2020). Historical Evidence for Economic Effects of COVID-19. The European Journal of Health Economics, 21(6), 817–823. https://doi.org/10.1007/s10198-020-01206-8
• Choi, I. (2001). Unit Root Tests for Panel Data. Journal of International Money and Finance, 20(2), 249–272.
• Clark, K. B., & Summers, L. (1982). The Dynamics of Youth Unemployment. In The Youth Labor Market Problem: Its Nature, Causes, and Consequences (pp. 199–234). National Bureau of Economic Research, Inc.
• Cowling, M., Brown, R., & Rocha, A. (2020). Did you save some cash for a rainy COVID-19 day? The crisis and SMEs. International Small Business Journal, 38(7), 593–604. https://doi.org/10.1177/0266242620945102
• Daşdemi̇r, E. N. (2017). Göçün Piyasalara Etkisi ve Faktör Hareketliliğini Açıklama Gücü: Emek Piyasalarının Küreselleşmesi ve Maliyetleri. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(2), 676–700. https://doi.org/10.26745/gaziuiibfd.418588
• Dey, M., Frazis, H., Loewenstein, M. A., & Sun, H. (2020). Ability to Work from Home: Evidence from Two Surveys and Implications for the Labor Market in the COVID-19 Pandemic. Monthly Labor Review, June, 1–19.
• Driscoll, J. C., & Kraay, A. C. (1998). Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data. The Review of Economics and Statistics, 80(4), 549–560. http://www.jstor.org/stable/2646837
• Durbin, J., & Watson, G. S. (1971). Testing for Serial Correlation in Least Squares Regression. III. Biometrika, 58(1), 1–19. https://doi.org/10.2307/2334313
• Fırat, S., & Daşdemir, E. (2021). Kripto Paralarda Miktar Teorisi Uygulaması: Bitcoin Örneği ve Covid-19 Salgının Etkisi. İstanbul İktisat Dergisi, 71(1), 81–102.
• Freeman, R. (1982). Economic Determinants of Geographic and Individual Variation in the Labor Market Position of Young Persons. In The Youth Labor Market Problem: Its Nature, Causes, and Consequences (pp. 115–154). National Bureau of Economic Research, Inc.
• Frees, E. W. (2004). Longitudinal and Panel Data. Cambridge University Press.
• Gourinchas, P.-O., Kalemli-Özcan, Ṣebnem, Penciakova, V., & Sander, N. (2020). COVID-19 and SME Failures (Working Paper Series, Issue 27877). https://doi.org/10.3386/w27877
• Gourinchas, P.-O., Kalemli-Özcan, Ṣebnem, Penciakova, V., & Sander, N. (2021). COVID-19 and SMEs: A 2021 “Time Bomb”?
• Handwerker, E. W., Meyer, P. B., Piacentini, J., Schultz, M., & Sveikauskas, L. (2020). Employment recovery in the wake of the COVID-19 pandemic. Monthly Labor Review, December, 1–24.
• Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. https://doi.org/10.2307/1913827
• Im, K. S., Pesaran, M., & Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53–74.
• Lama, R., & Medina, J. P. (2019). Fiscal austerity and unemployment. Review of Economic Dynamics, 34, 121–140. https://doi.org/https://doi.org/10.1016/j.red.2019.02.007
• Levene, H. (1960). Robust Tests for Equality of Variances. In I. Olkin, G. S. Ghurye, W. Hoeffding, G. W. Madow, & B. H. Mann (Eds.), Contributions to Probability and Statistics (pp. 278–292). Stanford University Press.
• Mortensen, D. T., & Pissarides, C. A. (1999). Unemployment Responses to “Skill-Biased” Technology Shocks: The Role of Labour Market Policy. The Economic Journal, 109(455), 242–265.
• Naudé, W. (2009). The Financial Crisis of 2008 and the Developing Countries (Issue 2009/01). The United Nations University World Institute for Development Economics Research (UNU-WIDER).
• Özdemir, O., & Kayhan, F. (2019). The Effect of Global Financial Crisis on Securities Portfolio of Deposit Banks: A Difference-In-Differences Method for Turkey. Business & Management Studies: An International Journal, 7(1), 444–466. https://doi.org/10.15295/bmij.v7i1.1082
• Pedauga, L., Sáez, F., & Delgado-Márquez, B. L. (2021). Macroeconomic lockdown and SMEs: the impact of the COVID-19 pandemic in Spain. Small Business Economics. https://doi.org/10.1007/s11187-021-00476-7
• Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Faculty of Economics, University of Cambridge.
• Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.1093/biomet/75.2.335
• Sikiru, A. A., & Salisu, A. A. (2021). Hedging with financial innovations in the Asia-Pacific markets during the COVID-19 pandemic: the role of precious metals. Quantitative Finance and Economics, 5(2), 352–372.
• Tunalı, H., Guz, T., & Sengun, G. (2017). Efficiency of ICT Development Indicators in OECD Countries. Journal of Economics Finance and Accounting, 4(2), 121–128. https://doi.org/https://doi.org/10.17261/Pressacademia.2017.441
• World Bank. (2021). World Development Indicators. World Bank. https://databank.worldbank.org/