Volume 25, Issue 3 (Autumn 2020)
JPBUD 2020, 25(3): 95-116 |
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Shahabadi A, Heydarkhani F. (2020). The Effect of Knowledge-Based Economy Components on Misery Index in Selected Countries. JPBUD. 25(3), 95-116. doi:10.52547/jpbud.25.3.95
URL: http://jpbud.ir/article-1-1947-en.html
URL: http://jpbud.ir/article-1-1947-en.html
1- Professor, Department of Economics, Faculty of Economics and Social Sciences, Alzahra University, Tehran, Iran. , shahabadi@alzahra.ac.ir
2- M.A. in Economics, Department of Economics, Alzahra University, Tehran, Iran.
2- M.A. in Economics, Department of Economics, Alzahra University, Tehran, Iran.
Abstract: (5530 Views)
The sum of inflation and unemployment rates is called the misery index, and its escalation can be associated with many social and economic costs such as increased crime, reduced social security, and harm to the mental health of the society. The present study investigates the effect of knowledge-based economy components on the misery index in two groups of selected countries via the approach of panel data and generalized moment method at the level of pre-innovation-driven stage and innovation-driven stage for the period 2008-2018. The results showed the effect of all components of the knowledge-based economy (including economic incentives and institutional regime, innovation system, training and development of human resources and ICT infrastructure) with different estimated coefficients and at different levels of confidence was negative and significant on economic misery in both groups of selected countries. In addition, the effect of control variables, including population and abundance of natural resources, on the misery index in the pre-innovation-driven stage in the selected countries is positive and significant; yet it is not significant in the innovation-driven stage. Also, the effect of economic openness on the misery index in both groups of selected countries was negative and significant.
Keywords: Misery Index, Inflation Rate, Unemployment Rate, Knowledge Based Economy, Economic Openness, Innovation System, Training and Development of Human Resources.
Type of Study: Research |
Subject:
Macroeconomics
Received: Nov 14 2020 | Accepted: Mar 07 2021 | ePublished: Mar 19 2021
Received: Nov 14 2020 | Accepted: Mar 07 2021 | ePublished: Mar 19 2021
References
1. Al-Manaseer, D. S., & Al-Qudah, A. M. (2018). The Impact of Higher Education Output on Unemployment Rates in Jordan. International Journal of Academic Research in Accounting, Finance and Management Sciences, 8(2), 65-72.
2. Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. The Review of Economic Studies, 58(2), 277-297. [DOI]
3. Barkhordari, S., Fattahi, M., & Azimi, N. A. (2019). The Impact of Knowledge-Based Economy on Growth Performance: Evidence from MENA Countries. Journal of the Knowledge Economy, 10(3), 1168-1182. [DOI]
4. Burke, A., & Fraser, S. (2012). Self-Employment: The Role of Intellectual Property Right Laws. Small Business Economics, 39(4), 819-833. [DOI]
5. Cohen, I. K., Ferretti, F., & McIntosh, B. (2014). Decomposing the Misery Index: A Dynamic Approach. Cogent Economics & Finance, 2(1), 991089. [DOI]
6. Dutta, N., Kar, S., & Roy, S. (2013). Corruption and Persistent Informality: An Empirical Investigation for India. International Review of Economics & Finance, 27(1), 357-373. [DOI]
7. Hayashi, F. (2000). Econometrics: Princeton University Press.
8. Levin, A., Lin, C.-F., & Chu, C.-S. J. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108(1), 1-24. [DOI]
9. Matuzeviciute, K., Butkus, M., & Karaliute, A. (2017). Do Technological Innovations Affect Unemployment? Some Empirical Evidence from European Countries. Economies, 5(4), 48-67. [DOI]
10. Mefteh, H., Bouhajeb, M., & Smaoui, F. (2016). Higher Education, Graduate Unemployment, Poverty and Economic Growth in Tunisia, 1990-2013. Atlantic Review of Economics: Revista Atlántica de Economía, 1(1), 1-22.
11. Pogoy, A. M., Balo, V. T., Plaisent, M., & Bernard, P. (2016). Global Implication of Fractals on Misery Index across Countries. International Journal of Global Business, 9(1), 30-38.
12. Romer, D. (2012). Advanced Macroeconomics: Mcgraw-Hill.
13. Ruprah, I. J., & Luengas, P. (2011). Monetary Policy and Happiness: Preferences over Inflation and Unemployment in Latin America. The Journal of Socio-Economics, 40(1), 59-66. [DOI]
14. Selim, M., & Hassan, M. K. (2019). Interest-Free Monetary Policy and Its Impact on Inflation and Unemployment Rates. ISRA International Journal of Islamic Finance, 11(1), 46-61. [DOI]
15. Shahabadi, A., Kheshtmal Nasrani, M., & Moradi, A. (2020). The Effect of Knowledge Components on the Inequality of Global Wealth Distribution. The Journal of Planning and Budgeting, 24(4), 75-96. [Article]
16. Smith, K. (2002). What is the'Knowledge Economy'? Knowledge Intensity and Distributed Knowledge Bases. United Nations University, Institute for New Technologies, Discussion Papers ISSN 1564-8370.
17. Tule, K. M., Egbuna, E. N., Dada, E., & Ebuh, G. U. (2017). A Dynamic Fragmentation of the Misery Index in Nigeria. Cogent Economics & Finance, 5(1), 1336295. [DOI]
18. Vinnychuk, O., Skrashchuk, L., & Vinnychuk, I. (2014). Research of Economic Growth in the Context of Knowledge Economy. Intellectual Economics, 8(1), 116-127. [DOI]
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