ECONOMETRIC ANALYSIS OF FACTORS AFFECTING THE DEVELOPMENT OF THE LABOR MARKET IN THE FIELD OF DIGITAL TECHNOLOGIES IN THE REGIONS OF UZBEKISTAN
Abstract
At the current stage of modern economic development, the assessment of factors influencing the development of the labor market in the field of digital technologies, based on various research methods, is the basis for determining the correct strategic directions in the digital economy in the country.
It is acknowledged that one of the main indicators assessing the demand for labor resources in the labor market is the salary of specialists. Consequently, the purpose of our study is to carry out an econometric analysis of the factors affecting the wages of specialists in the field of digital technologies in the regions of Uzbekistan, and develop appropriate conclusions and proposals based on the obtained econometric models.
Keywords:
digital technology labor market econometric equations Pooled OLS estimator (POLSE) model Fixed effects estimator (FEE) model Random effects estimator (REE) modelReferences
Bell A., Fairbrother M., Jones K. Fixed and random effects models: making an informed choice //Quality & quantity. – 2019. – Т. 53. – P. 1051-1074.
Brynjolfsson E., Rock D., Syverson C. (2018) Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics //The economics of artificial intelligence: An agenda. – University of Chicago Press, – P. 23-57.
Castells M. (2016) A sociology of power: My intellectual journey //Annual Review of Sociology. –. – Т. 42. – P. 1-19.
Clark J., Bailey D. (2018) Labour, work and regional resilience //Regional Studies. – Т. 52. – №. 6. – P. 741-744.
Clark T. S., Linzer D. A. Should I use fixed or random effects? //Political science research and methods. – 2015. – Т. 3. – №. 2. – P. 399-408.
Cowhey P.F., Aronson J.D. (2012) Transforming global information and communication markets: The political economy of innovation. – MIT Press.
European Vacancy Monitor (EVM), 2023. Электрон манба: https://www.eurofound.europa.eu/observatories/emcc/european-jobs-monitor
Frees E. W. et al. Longitudinal and panel data: analysis and applications in the social sciences. – Cambridge University Press, 2004.
Gunasekara F. I. et al. Fixed effects analysis of repeated measures data //International journal of epidemiology. – 2014. – Т. 43. – №. 1. – P. 264-269.
ICT Skills Demand and Supply Monitor Report, 2021. Электрон манба: https://digital-skills-jobs.europa.eu/en/inspiration/research/ict-skills-demand-and-supply-monitor-report-2021
Kang S.J., Lee H. (2011) Foreign direct investment and de‐industrialisation //The World Economy. – Т. 34. – №. 2. – P. 313-329.
Kenney M., Breznitz D., Murphree M. (2013) Coming back home after the sun rises: Returnee entrepreneurs and growth of high tech industries //Research Policy. – Т. 42. – №. 2. – P. 391-407.
Kerr W. R. (2008) Ethnic scientific communities and international technology diffusion //The Review of Economics and Statistics. – Т. 90. – №. 3. – P. 518-537
Mark N., Sul D. When Are Pooled Panel‐Data Regression Forecasts of Exchange Rates More Accurate than the Time‐Series Regression Forecasts? //Handbook of exchange rates. – 2012. – P. 265-281.
Plümper T., Troeger V. E. Not so harmless after all: The fixed-effects model //Political Analysis. – 2019. – Т. 27. – №. 1. – P. 21-45.
Venturini F. (2015) The modern drivers of productivity //Research Policy. –– Т. 44. – №. 2. – P. 357-369.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
