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This paper discusses theoretical aspects and evidences related to designing labor market institutions in emerging market and developing economies. This note reviews the state of theory and evidence on the design of labor market institutions in a developing economy context and then reviews its consistency with actual labor market advice in a selected set of emerging and developing economies. The focus is mainly on three broad sets of institutions that matter for both workers’ protection and labor market efficiency: employment protection, unemployment insurance and social assistance, minimum wages and collective bargaining. Text mining techniques are used to identify IMF recommendations in these areas in Article IV Reports for 30 emerging and frontier economies over 2005–2016. This note has provided a critical review of the literature on the design of labor market institutions in emerging and developing market economies, and benchmarked the advice featured in IMF recommendations for 30 emerging market and frontier economies against the tentative conclusions from the literature.
I use three decades of county-level data to estimate the effects of federal unemployment benefit extensions on economic activity. To overcome the reverse causality coming from the fact that benefit extensions are a function of state unemployment rates, I only use the within-state variation in outcomes to identify treatment effects. Identification rests on a differences-in-differences approach which exploits heterogeneity in county exposure to policy changes. To distinguish demand and supply-side channels, I estimate the model separately for tradable and non-tradable sectors. Finally I use benefit extensions as an instrument to estimate local fiscal multipliers of unemployment benefit transfers. I find (i) that the overall impact of benefit extensions on activity is positive, pointing to strong demand effects; (ii) that, even in tradable sectors, there are no negative supply-side effects from work disincentives; and (iii) a fiscal multiplier estimate of 1.92, similar to estimates in the literature for other types of spending.