the legal definition, which overlaps with the definition of the benefits category, and −0.51 for the productive definition.

Principal-component analysis further shows that the JQM using four dimensions captures four distinct components and cannot easily be reduced to fewer dimensions (annex table A7). Using the full set of wage workers in 40 countries with over 1.1 million observations, the four components account for 41.2 percent, 24.4 percent, 21.0 percent, and 13.4 percent of the variation in job quality.

# **5. Conclusions**

The vast majority of policy research work on labor markets across developing countries focuses on job creation, while less attention has been devoted to the quality of employment beyond a single dimension, such as formality or labor earnings. However, because not all jobs have the same implications for worker well-being, understanding the multiple characteristics that contribute to worker welfare, especially those that allow individuals to move out of poverty and into the middle class in a sustained way, is a crucial issue in designing and implementing policies to achieve inclusive growth across developing countries.

This paper proposes an index of the quality of wage employment across developing countries that combines four dimensions—widely discussed in the literature—that characterize a good job: sufficient earnings to move a family out of poverty, access to employment benefits, job stability, and acceptable working conditions. To develop this global JQM, the analysis harmonizes a common set of indicators available for each dimension in recent labor force and household surveys across 40 developing countries. A JQM that scores several important characteristics of employment as opposed to a single indicator, such as wages or formality (widely used in the previous literature), adds value to both empirical research and policy analysis. A globally harmonized comprehensive dataset also allows the quality of jobs to be analyzed across various countries, regions, industries, and sociodemographic groups, such as women and youth.

The results show a strong positive correlation between the JQM and the share of the wage employed in total employment across developing countries, indicating that countries with more opportunities for workers to find paid employment perform better in terms of the availability of good jobs than countries with large self-employed or informal worker populations. Also, there is substantial variation not only in the composite job quality index across countries, but in all its dimensions, with greater differences observed in benefits and stability.

Sectors with the highest JQM include public administration, financial and business services, and utilities, while low-skill sectors, such as agriculture and construction, have the lowest JQMs. The analysis finds that the JQM is, on average, similar between men and women despite differences in individual dimensions. For example, the JQM decomposition reveals that women fare especially well in the working conditions dimension, while men perform better in terms of income. However, the job quality is much lower among other disadvantaged groups, such as rural residents and youth, relative to urban residents and older wage employees. The starkest difference is observed between different educational attainment groups, indicating that the strongest predictors of JQM within countries is educational attainment.

Despite these insightful results, large gaps in the data limit the scope and country coverage of job quality analysis. First, most country surveys lack information on certain dimensions of job quality, which have been discussed in the literature as the desirable characteristics of good jobs, particularly those related to 26