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Table 4 Labor market intermediation on employment outcome. Labor-Market Intermediation Program, Lima 2009-2010

From: Integrating mobile phone technologies into labor-market intermediation: a multi-treatment experimental design

  Month # 1 Month # 2 Month # 3
Dep variable: employment
Overall treatment 0.066** 0.062** 0.056* 0.055* 0.003 −0.002
  (0.032) (0.027) (0.032) (0.031) (0.031) (0.033)
Type of treatment
Traditional treatment (DT1) 0.041 0.034 0.046 0.040 −0.018 −0.034
  (0.039) (0.035) (0.038) (0.036) (0.038) (0.044)
Restricted-SMS treatment (DT2) 0.081* 0.083* 0.057 0.060 0.034 0.034
  (0.046) (0.042) (0.046) (0.046) (0.045) (0.045)
Unrestricted-SMS treatment (DT3) 0.086** 0.081** 0.067* 0.069* 0.008 0.008
  (0.040) (0.032) (0.039) (0.037) (0.039) (0.035)
p-value of F-test: DT1 = DT2 = DT3 0.478 0.381 0.876 0.712 0.493 0.334
N 1118 1118 1118 1118 1118 1118
Covariates No Yes No Yes No Yes
Experimental groups FE No Yes No Yes No Yes
  1. Notes: Standard errrors in parenthesis. Estimates based on a parametric cross-sectional estimator. The treatment indicator takes the value 1 for those benefiting from labor-market intermediation, 0 otherwise. Socio-demographic covariates include age, gender, marital status, poverty index, whether individual has children, number of children, whether individual is migrant, number of years since migration, years of schooling. Labor-market covariates include whether individual had ever worked, whether individual had pension plan, health insurance, accident insurance, formal contract as well as blue-collar and white-collar worker indicators. Clustered standard errors by day are considered when including experimental groups fixed effects in columns 2, 4, and 6. ***statistically significant at 1%, **statistically significant at 5%, *statistically significant at 10%.