A fiscal and statistical governance loop for decent work in digital employment: a methodological approach for Uzbekistan

Cover Page

Cite item

Full Text

Abstract

Abstract: Problem. The expansion of platform employment, self-employment, and other forms of digital employment increases the accessibility of work activities but weakens the connection between the registration of economic activity, social protection, fiscal incentives, and statistical assessment of job quality. As a result, there is no reproducible procedure for converting identified risk into targeted management decisions. Aim. To develop a methodological fiscal and statistical governance loop for decent work that connects the diagnosis of digital employment risks with the selection of support in-struments, verification of results, and policy adjustment. Methods. The research applies institutional-functional analysis of the literature, structural-dynamic interpretation of aggregated employment indicators for 2019–2024, logical modeling, scenario verification of internal consistency, and sensitivity analysis of parameters. Results. It is shown that the growth in the share of formal employment to 52.4 % in 2024 was combined with the persistence of informal employment at 37.1 % and an increase in self-employment to 7.7 %. A six-stage loop of “data – risk – instrument – implementation – verification – ad-justment” was proposed, along with the principle of conditional support across four result groups and a panel of seven op-erational indicators. Sensitivity analysis demonstrated that thresholds for income volatility, platform dependence, and em-ployment retention duration should be considered adjustable parameters rather than universal norms. Scenario verification established the internal traceability of the “risk – instrument – result” link without claiming to assess the actual causal ef-fect. Conclusions. For piloting targeted support for digital and non-standard employment in Uzbekistan, it is recommend-ed to apply a six-stage loop with a multidimensional risk passport, while calibrating indicator thresholds on panel and ad-ministrative data before scaling up measures.

About the authors

Dilshadbek Nabizhanovich Nurmatov

Andijan State University

Author for correspondence.
Email: DNN220371@gmail.com
ORCID iD: 0009-0007-1592-6120

PhD (Economics), Professor, Professor of the Department of Economics and Finance

Uzbekistan, 170100, Andijan, Uzbekistan, University Street, 129.

References

  1. North D.C. Institutions, Institutional Change and Economic Performance. Cambridge, Cambridge University Press Publ., 1990. 159 p. doi: 10.1017/CBO9780511808678.
  2. Anker R., Chernyshev I., Egger P., Mehran F., Ritter J.A. Measuring decent work with statistical indicators. International Labour Review, 2003, vol. 142, no. 2, pp. 147–178. doi: 10.1111/j.1564-913X.2003.tb00257.x.
  3. Muñoz de Bustillo R., Fernández-Macías E., Esteve F., Antón J.-I. E pluribus unum? A critical survey of job quality indicators. Socio-Economic Review, 2011, vol. 9, no. 3, pp. 447–475. doi: 10.1093/ser/mwr005.
  4. Nurmatov D.N. Decent work methodology: evolution, indicators and adaptation in the age of digitalization. Journal of wellbeing technologies, 2025, vol. 53, no. 4, pp. 300–307. doi: 10.18799/26584956/2025/4/2043.
  5. Nurmatov D.N. Structural changes in employment and adaptation of decent work indicators amid digitalization: the experience of Uzbekistan. Russian Journal of Labour Economics, 2026, vol. 13, no. 5, pp. 667–682. doi: 10.18334/et.13.5.125967.
  6. Nurmatov D.N. Assessment of the status and trends of decent work in the republic of Uzbekistan. Standard of Living of the Population of Russian Regions, 2026, vol. 22, no. 1, pp. 74–86. doi: 10.52180/1999-9836_2026_22_1_5_74_86.
  7. Nurmatov D.N. Employment, wages and social-labor indicators in Uzbekistan's industry: a statistical assessment. π-Economy, 2026, vol. 19, no. 3, pp. 53–67. doi: 10.18721/JE.19304.
  8. Card D., Kluve J., Weber A. What works? A meta-analysis of recent active labor market program evaluations. Journal of the European Economic Association, 2018, vol. 16, no. 3, pp. 894–931. doi: 10.1093/jeea/jvx028.
  9. McKenzie D. How effective are active labor market policies in developing countries? A critical review of recent evidence. The World Bank Research Observer, 2017, vol. 32, no. 2, pp. 127–154. doi: 10.1093/wbro/lkx001.
  10. Brown A.J.G., Koettl J. Active labor market programs – employment gain or fiscal drain? IZA Journal of Labor Economics, 2015, vol. 4, article number 12. doi: 10.1186/s40172-015-0025-5.
  11. Graham M., Hjorth I., Lehdonvirta V. Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods. Transfer: European Review of Labour and Research, 2017, vol. 23, no. 2, pp. 135–162. doi: 10.1177/1024258916687250.
  12. Wood A.J., Graham M., Lehdonvirta V., Hjorth I. Good gig, bad gig: autonomy and algorithmic control in the global gig economy. Work, Employment and Society, 2019, vol. 33, no. 1, pp. 56–75. doi: 10.1177/0950017018785616.
  13. Behrendt C., Quynh Anh Nguyen, Rani U. Social protection systems and the future of work: ensuring social security for digital platform workers. International Social Security Review, 2019, vol. 72, no. 3, pp. 17–41. doi: 10.1111/issr.12212.
  14. Vallistu J. Digital social security accounts for platform workers: the case of Estonia’s entrepreneur account. International Social Security Review, 2023, vol. 76, no. 3, pp. 3–24. doi: 10.1111/issr.12337.
  15. Kellogg K.C., Valentine M.A., Christin A. Algorithms at work: the new contested terrain of control. Academy of Management Annals, 2020, vol. 14, no. 1, pp. 366–410. doi: 10.5465/annals.2018.0174.
  16. Duggan J., Sherman U., Carbery R., McDonnell A. Algorithmic management and app-work in the gig economy: a research agenda for employment relations and HRM. Human Resource Management Journal, 2020, vol. 30, no. 1, pp. 114–132. doi: 10.1111/1748-8583.12258.
  17. Parent-Rocheleau X., Parker S.K. Algorithms as work designers: how algorithmic management influences the design of jobs. Human Resource Management Review, 2022, vol. 32, no. 3, article number 100838. doi: 10.1016/j.hrmr.2021.100838.
  18. Koutsimpogiorgos N., van Slageren J., Herrmann A.M., Frenken K. Conceptualizing the gig economy and its regulatory problems. Policy & Internet, 2020, vol. 12, no. 4, pp. 525–545. doi: 10.1002/poi3.237.
  19. Rani U., Furrer M. Digital labour platforms and new forms of flexible work in developing countries: algorithmic management of work and workers. Competition & Change, 2021, vol. 25, no. 2, pp. 212–236. doi: 10.1177/1024529420905187.
  20. Chernykh E.A., Zolotina O.A. Quality of employment on digital labor platforms: approaches to measurement and assessments for BRICS countries. Standard of Living of the Population of Russian Regions, 2024, vol. 20, no. 2, pp. 211–227. doi: 10.52180/1999-9836_2024_20_2_6_211_227.
  21. Yanchenko E.V. Decent work in the context of digitalization of the economy and society. Russian Journal of Labour Economics, 2024, vol. 11, no. 6, pp. 799–818. doi: 10.18334/et.11.6.121197.
  22. Ogunde F. Algorithmic management of platform workers: an examination of the Canadian and European approaches to regulation. European Labour Law Journal, 2024, vol. 15, no. 4, pp. 803–821. doi: 10.1177/20319525241239632.
  23. Antonucci L. The lived experiences of the welfare state of platform workers: the barriers to accessing social protection in Italy, Sweden and the United Kingdom. International Journal of Social Welfare, 2025, vol. 34, no. 1, article number e12708. doi: 10.1111/ijsw.12708.
  24. Keegan A., Meijerink J. Algorithmic Management in Organizations? From Edge Case to Center Stage. Annual Review of Organizational Psychology and Organizational Behavior, 2025, vol. 12, pp. 395–422. doi: 10.1146/annurev-orgpsych-110622-070928.
  25. Rosin A., Parviainen H. Improving the transparency of algorithmic management in platform work: The role of the Platform Work Directive. European Labour Law Journal, 2025, vol. 16, no. 4, pp. 472–493. doi: 10.1177/20319525251375023.
  26. Liping Liu, Yu Wang, Ting Xiao, Chunyu Zhang. Platform gig work conditions and workers’ perceptions of decent work: a configurational and necessity perspective. Humanities and Social Sciences Communications, 2026, vol. 13, article number 359. doi: 10.1057/s41599-026-06702-5.

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Copyright (c) 2026 Nurmatov D.N.

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