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Assessing the Impact of Informality on Wages in Tanzania: Is There a Penalty for Women? Pablo Suárez Robles (University Paris-Est Créteil) 1.

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Presentation on theme: "Assessing the Impact of Informality on Wages in Tanzania: Is There a Penalty for Women? Pablo Suárez Robles (University Paris-Est Créteil) 1."— Presentation transcript:

1 Assessing the Impact of Informality on Wages in Tanzania: Is There a Penalty for Women? Pablo Suárez Robles (University Paris-Est Créteil) 1

2 Research Objective Assess the impact of informality on wages and determine whether, compared to men, women are more penalized by working informally. Negative vs. Positive selection to informal employment: It is wage employed workers who are most likely to select into informal employment who lose (get) the most from working informally. Exclusion vs. Exit hypotheses: Decision to work informally is less (more) linked to economic gain and more (less) the result of a constrained choice. If observed, are the negative selection and exclusion hypothesis more prevalent among women than among men? What factors could explain these phenomena? 2

3 Data Tanzanian Integrated Labour Force Survey (ILFS) 2006 -Nationally representative household survey -Collected during the four quarters of 2006 so as to capture seasonal variations -Includes a wide range of information on employment and job characteristics -Etc. 3

4 Concepts Informal employment (based on the 15 th and 17 th ICLS) -Informal sector enterprises: unregistered or which have less than 10 employees paid on a continuous basis, and which keep no written records or accounts, or keep them but without showing all the balance sheets of assets and liabilities. -Informal jobs: the employee has a casual oral work contract or is not covered with any social security scheme. Informal employment comprise all persons who are employed in an informal job, irrespective of whether it is carried out in formal sector enterprises, informal sector enterprises or households. Wages: We derive the gross cash hourly wage by dividing the gross cash monthly wage by the monthly hours of work. 4

5 Methodology We conduct treatment effect analysis of informal employment on wages, separately for men and women, making three different assumptions for the treatment effect: I.Homogeneity, II.Partial heterogeneity, III.Full heterogeneity of the population in the treatment response. 5

6 Results: Homogeneity assumption OLS regressions of log hourly wage, separately for men and women, including a dummy variable for treatment status (1 if informal job, 0 if formal job). Findings The decrease in hourly wage associated with having an informal job is, ceteris paribus, of 46.8% for men and 48% for women. Accordingly, women do not exhibit an obvious wage disadvantage relative to men from working informally. 6

7 Results: Partial heterogeneity assumption We first run propensity score Probit regression models predicting informal employment, separately for men and women in wage employment. Once the propensity score estimated, we construct balanced propensity score strata and estimate within each stratum the average treatment effect. We then test for linear trend in treatment effects using variance-weighted least squares. The treatment effect is assumed to be a constant parameter within each propensity score stratum, but not across propensity score strata. 7

8 Results: Partial heterogeneity assumption Findings Working informally is associated with a significant decreasing economic return across propensity score strata, which offer support for the assumption of negative selection into informal employment. The higher is the propensity to work informally, the higher are the constraints in terms of household responsibilities and lack of adequate infrastructure, suggesting that the exclusion hypothesis is at work. Both results are observed to a much higher extent among women. 8

9 Results: Full heterogeneity assumption We first estimate propensity score as before. We then match treated and untreated units with control units using different matching algorithms, and we plot the matched differences (treatment on the treated and treatment on the untreated) against a continuous representation of the propensity score. We finally fit nonparametric smoothed curves to obtain the pattern of treatment effect heterogeneity as a function of the propensity score. 9

10 Results: Full heterogeneity assumption Findings ATE (average treatment effects) and ATT (average treatment effects on the treated) appear to be markedly higher, in absolute value, for women than for men.  Women face a significantly higher informal employment wage penalty than men. Results imply a negative sorting gain for informal wage employed workers (ATT < ATU and ATT < ATE), which is much more acute among women. We still observe higher income-decreasing effect of informal employment as the propensity of wage employed workers, especially women, to work informally increases. However, the curves evidence that for men and, much more particularly, for women, the heterogeneity pattern of informal employment returns is not strictly linear. Accordingly, neither the assumption of homogeneity nor the assumption of partial heterogeneity of the population in the treatment response seem to hold in Tanzania. Full heterogeneity of the population => Preferred approach 10

11 Conclusion Wage employed workers have lower economic returns when working informally. Negative selection is at work, in the sense that it is wage employed workers who are most likely to select into informal employment who lose the most from working informally. The exclusion hypothesis seems to prevail since the decision to work informally appears to be less linked to economic gain and more the result of a constrained choice. Constraints such as, for instance, the burden of household responsibilities and the lack of adequate infrastructure provide strong incentives for wage employed workers to engage in informal employment. Data indicate that wage employed workers clearly differ in how they respond to a particular treatment, which is to work informally, thus supporting the full heterogeneity assumption over the strict homogeneity and partial heterogeneity hypotheses. All these phenomena affect much more women than men. 11

12 Conclusion From a policy perspective, these findings advocate explicitly for the development of infrastructure services as well as of market substitutes for domestic work in Tanzania. Progress in this direction would reduce the opportunity cost of time and other transaction costs which constitute important barriers that impede men and, above all, women to access better and more rewarding jobs in formal employment. 12


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