Article Sidebar

Submitted
January 8, 2023
Accepted
April 5, 2023
Published
April 29, 2023
Download
Full Text PDF
Statistic
Read Counter : 699 Download : 1207

Downloads

Download data is not yet available.

Main Article Content

Abstract

Purpose – This paper examines factors that determine the unemployment rate in the Maldives.


Methods – This paper uses an Autoregressive Distributed Lag (ARDL) model in capturing long and short-run associations among the chosen variables. It uses some macroeconomic variables, namely unemployment rate, population, economic growth, foreign direct investment, external debts, inflation rate, and expatriate workers.


Findings – The empirical results suggest that except for expatriate workers, all the variables are significant determinants of unemployment rate in the long run. The study found that economic growth and inflation would negatively and significantly contribute to unemployment rate when they are combined. This explains the unemployment nexus which follows the Phillips curve and Okun’s law relationship provides the presence of both these hypotheses in the Maldives in the short-run and long-run. In addition, an increase in population and external debts worsens the unemployment situation in the Maldives. Although expatriate workers are not significant in the long run, the results reveal that they have a significant positive effect on unemployment in the short run.


Implications – This result implies that the Maldivian government should encourage locals in the country to participate in the labor force and limit the participation of expatriate workers in an industry that has a shortage of skilled expertise.


Originality – This study expands our understanding of key determinants of the unemployment rate in Maldives. To the best of the authors’ knowledge, this research is among the pioneer empirical study to assess the issue.

Keywords

unemployment factors long and short run labor force skill workers

Article Details

License

Copyright (c) 2023 Ali Irushad, Mohamed Asmy Mohd Thas Thaker, Hassanudin Mohd Thas Thaker

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

Creative Commons License

Economic Journal of Emerging Markets by Center for Economic Studies, Universitas Islam Indonesia is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

How to Cite
Irushad, A. ., Mohd Thas Thaker, M. A., & Mohd Thas Thaker, H. (2023). What drives the unemployment rate in Maldives? An Autoregressive Distributed Lag (ARDL) approach. Economic Journal of Emerging Markets, 15(1), 72–86. https://doi.org/10.20885/ejem.vol15.iss1.art6
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Al-Habees, M. A., & Rumman, M. A. (2012). The relationship between unemployment and economic growth in Jordan and some Arab countries. World Applied Sciences Journal, 18(5), 673–680. https://doi.org/10.5829/idosi.wasj.2012.18.05.16712
  2. Alamro, H., & Al-Dala’ien, Q. (2016). Validity of Okun’s Law: Empirical Evidence from Jordan. Administrative Sciences, 43(1), 2016–2315.
  3. Arslan, M., & Zaman, R. (2014). Unemployment and Its Determinants: A Study of Pakistan Economy (1999-2010). Journal of Economics and Sustainable Development, 5, 20–24. https://doi.org/10.2139/ssrn.2515075
  4. Bassanini, A., & Duval, R. (2006). Employment Patterns in OECD Countries, (35). https://doi.org/https://doi.org/https://doi.org/10.1787/702031136412
  5. Budha, B. B. (2013). Demand for Money in Nepal : An ARDL Bounds Testing Approach. NRB Economic Review, 25(1).
  6. Caroleo, F., & Pastore, F. (2007). The youth experience gap: Explaining differences across EU countries. Retrieved from https://econpapers.repec.org/RePEc:pia:wpaper:41/2007
  7. Cheema, A. A. (2014). Economic determinants of unemployment in Pakistan: Co-integration analysis. International Journal of Business and Social Science, 5(3), 209–222.
  8. Chowdhury, A., & Mavrotas, G. (2006). FDI and growth: What causes what? The World Economy, 29(1), 9–19. https://doi.org/10.1111/j.1467-9701.2006.00755.x
  9. David A. Dickey, W. A. F. (1979). Distribution of the estimators for Autoregressuve time series with a unit. Journal of the American Statistical Association, 74(427–431).
  10. Davidson, R., & MacKinnon, J. G. (2004). Instructor ’ s Manual to Accompany Econometric Theory and Methods. Oxford University Press. New York: Oxford University Press.
  11. Duasa, J. (2007). Determinants of Malaysian trade balance: An ARDL bound testing approach. Global Economic Review, 36(1), 89–102. https://doi.org/10.1080/12265080701217405
  12. Eksi, O., & Onur Tas, B. K. (2022). Time-varying effect of uncertainty shocks on unemployment. Economic Modelling, 110, 105810. https://doi.org/10.1016/j.econmod.2022.105810
  13. Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: Journal of the Econometric Society, 55(2), 251–276. https://doi.org/10.2307/1913236
  14. Fathih, M. S. (2015). Government claim of adding 70,000 jobs ridiculed. Retrieved March 1, 2022, from https://maldivesindependent.com/politics/government-claim-of-adding-70000-jobs-ridiculed-119938
  15. Franks, J. (1996). Labor market policies and unemployment dynamics in Spain. In S. G. B. Henry (Ed.), Economic Policies and Unemployment Dynamics in Europe. United States: International Monetary Fund.
  16. Friedman, M. (1968). The role of monetary policy. The American Economic Review, 58, 269–295.
  17. Ghosh, R. A. (1998). Cooking pot markets: An economic model for the trade in free goods and services on the Internet. Brazilian Electronic Journal of Economics, 1(1), 19–31.
  18. Gorry, A., Munro, D., & vom Lehn, C. (2020). Experience, skill composition, and the persistence of unemployment fluctuations. Labour Economics, 63, 101793. https://doi.org/https://doi.org/10.1016/j.labeco.2019.101793
  19. Gur, B. (2015). An analysis of unemployment determinants in BRIC countries. International Journal of Business and Social Science, 6(1), 192–198.
  20. Islam, A. (2007). Immigration unemployment relationship: The evidence from Canada. Australian Economic Papers, 46(1), 52–66. https://doi.org/10.1111/j.1467-8454.2007.00305.x
  21. Jayaraman, T., & Singh, B. (2007). Foreign direct investment and employment creation in pacific island countries: An empirical study of Fiji (Working Papers No. 3507).
  22. Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxford Bulletin of Economics and Statistics. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x
  23. Mauro, L., & Carmeci, G. (2003). Long run growth and investment in education: Does unemployment matter? Journal of Macroeconomics, 25(1), 123–137. https://doi.org/10.1016/S0164-0704(03)00010-7
  24. Moosa, I. (2008). Economic growth and unemployment in Arab countries: Is Okun’s law valid? Journal of Development and Economics Policies, 10(2), 20–32.
  25. Narayan, P. K. (2017). Reformulating critical values for the bounds F- statistics approach to cointegration: An application to the tourism demand model for Fiji. https://doi.org/10.4225/03/5938abda7b4ab
  26. National Bureau of Statistics. (2015). Statistical Pocketbook 2015. United States.
  27. Neumark, D., & Wascher, W. (2004). Minimum wages, labor market institutions, and youth employment: A cross-national analysis. Industrial and Labor Relations Review, 57(2), 223–248. https://doi.org/10.2307/4126618
  28. Noor, Z. M., Nor, N. M., & Ghani, J. A. (2007). The relationship between output and unemployment in Malaysia: Does Okun’s Law exist? International Journal of Economics and Management, 1(3), 337–344.
  29. Pesaran, M. H., & Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31, 371–413.
  30. Pesaran, M. Hashem, Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616
  31. Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.2307/2336182
  32. Quintini, G., & Manfredi, T. (2009). Going separate ways? School-to-work transitions in the United States and Europe (OECD Social, Employment and Migration Working Papers No. 90). Paris. https://doi.org/10.1787/221717700447
  33. Ryan, P. (2001). The school-to-work transition: A cross-national perspective. Journal of Economic Literature, 39(1), 34–92.
  34. Saboori, B., & Soleymani, A. (2011). CO 2 emissions , economic growth and energy consumption in Iran : A co- integration approach. International Journal of Environmental Sciences, 2(1), 44–53. https://doi.org/10.6088/ijes.00202010005
  35. Salih, A. (2013). The determinants of intention to work in resorts in the Maldives. The Hong Kong Polytechnic University.
  36. Sargan, J. D. (1974). Some discrete approximation to continuous time stochastic models. Journal of the Royal Statistic Society, 36, 74–90.
  37. Sarwar, M. N., Hussain, H., & Maqbool, M. B. (2020). Pass through effects of oil price on food and non-food prices in Pakistan: A nonlinear ARDL approach. Resources Policy, 69, 101876. https://doi.org/10.1016/j.resourpol.2020.101876
  38. Shahbaz, M. (2009). Nominal and real devaluations relation: An econometric evidence for Pakistan. International Journal of Applied Econometrics and Quantitative Studies, 9(1), 85–108.
  39. Subramaniam, T., & Baharumshah, A. Z. (2011). Determinants of unemployment in the Philippines. The Empirical Economics Letters, 10(12), 31–51.
  40. Tercek, D. (2014). Determinants of European and United States unemployment determinants of European and United States unemployment (Senior Honors Project No. 33). Retrieved from http://collected.jcu.edu/honorspapers/33
  41. Ünal, U. (2015). The unemployment effects of fiscal policy in Netherlands. The Journal of Faculty of Economics and Administrative Sciences, 20(1), 143–153.
  42. World Bank. (2011). World development indicators. Washington, D. C.
  43. World Bank. (2014). Maldives: Country snapshot. Washington, D. C.: World Bank. Retrieved from https://www.worldbank.org/en/country/maldives/overview
  44. Zyra, J. (2013). Econometric models and data processing framework for monitoring of youth labor market in Poland. Information Systems in Management, 2(4), 323–334.
No Related Submission Found