Neumark and Munguía Corella's meta-analysis of 229 preferred employment elasticities from 61 developing-country studies found that estimates are more often negative and statistically significant when the minimum wage is binding, covers the formal sector, is strongly enforced in law, and targets vulnerable workers — the four features under which the competitive labor-market model predicts job loss. Yet a minority of estimates with these features are positive, and the paper could not test the leading noncompetitive explanation: employer monopsony power, which predicts that a moderate binding minimum wage raises employment. The open problem is, for developing countries, to determine whether measured monopsony power (local employer concentration and worker mobility, or firm-level labor-supply elasticities) explains the positive employment estimates. The paper separately notes that its enforcement variable captures legislated penalties rather than de facto (actual) enforcement intensity, and that enforcement may be endogenous. Later work provides a US and German template, structural monopsony estimates for Peru, China, and India, and one Indian sector-level test consistent with monopsony, but no systematic developing-country evidence.

Background

A minimum wage sets a legal wage floor. In the perfectly competitive labor-market model, a binding floor (one that raises wages above the market-clearing level) lowers employment of low-skilled workers; the size of the change is often summarized as an employment elasticity, the percentage change in employment for a one-percent change in the minimum wage. Under monopsony — a labor-market structure in which a single or few employers face an upward-sloping labor supply to the firm, so they set wages below marginal productivity (a wage markdown) — a moderate minimum wage can raise both wages and employment by pushing the wage toward the competitive level. Monopsony power is commonly proxied by labor-market concentration, e.g. the Herfindahl–Hirschman index (HHI), the sum of squared employment shares of employers in a local labor market, and by low worker mobility across employers.

Empirical evidence on minimum wages in developing countries is famously mixed: many studies estimate negative elasticities, but a substantial number report positive or statistically insignificant ones. Neumark and Munguía Corella (2021) systematized this evidence by classifying each of 229 authors' preferred estimates from 61 studies by four features that predict negative effects under the competitive model and standard institutional reasoning: (i) bindingness (evidence the minimum wage raised average wages or produced a spike in the wage distribution at the minimum), (ii) formal-sector coverage (as opposed to the informal sector, where firms and workers operate outside labor-law enforcement), (iii) strong legal enforcement of the wage floor, and (iv) focus on vulnerable workers (young, female, or unskilled). Their linear-probability meta-regressions — regressions of estimate signs on study features across the pooled estimates — show that estimates with more of these features are substantially more likely to be negative and statistically significant.

Two measurement limitations qualify this conclusion and motivate the open problem. First, the enforcement variable captures legislated penalties (de jure enforcement), not actual enforcement intensity on the ground (de facto enforcement, such as inspection activity), and enforcement choices may be endogenous to labor-market conditions. Second, and central here, the study-level data cannot support any test of the monopsony explanation for the minority of positive estimates that occur even in studies whose features predict negative effects: such a test requires disaggregated, sub-national measures of local labor-market concentration and worker mobility joined to minimum-wage variation, which the meta-analytic design cannot use. The authors note that recent US work by Azar et al. (2024) and Munguía Corella (2020) begins to implement this design using disaggregated, sub-national variation in labor-market concentration and worker mobility, and that later work by Popp (2021) applies the same design to Germany; these studies find minimum-wage employment effects that are less negative, or positive, in more concentrated labor markets. They state that exploring whether monopsony power sometimes generates positive employment effects of minimum wages in developing countries would be useful. Monopsony is not the only candidate: the standard two-sector competitive model predicts positive employment effects in the informal sector, and local aggregate-demand effects are another channel, so a credible test must separate these. Concurrently, Soundararajan (2019) studied India's construction-sector minimum wages across enforcement regimes, finding employment effects that move from negative or null under weak enforcement to positive or null under stricter enforcement — a pattern consistent with imperfectly enforced minimum wages in monopsonistic labor markets — using state-year inspection intensity as a de facto enforcement measure.

Problem Statement

For developing countries, determine whether employer monopsony power explains the subset of estimated minimum-wage employment effects that are positive — in particular those observed in studies whose features (binding wage floors, formal-sector coverage, strong enforcement, vulnerable workers) predict negative effects under the competitive model. Concretely: estimate how the employment effect of minimum wages varies across local labor markets with independently measured monopsony power, using disaggregated proxies such as employer concentration (e.g. employment-share HHI within local labor markets), worker mobility, or firm-level labor-supply elasticities joined to minimum-wage variation in one or more developing countries, and separate the monopsony channel from competing explanations of positive estimates (notably the two-sector competitive model's prediction of positive informal-sector employment effects and local aggregate-demand effects). The monopsony explanation is taken to be supported if the estimated employment effect is significantly less negative, or positive, in local labor markets with higher independently measured monopsony power, once those competing channels are netted out — the meta-analytic positive estimates motivate this test but need not each be individually re-explained by it.

References

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