the benefit may have the expected effect despite its small amount. Men are working less in manufacturing, while women are moving out of the primary sector and are working less on agricultural land. Labor income is declining, though mostly this effect is not statistically significant, and the same is true for the number of hours worked. However, the decline in labor income is smaller than the amount of the benefit.

**Table 17: Results of Labor Force Participation among Other Adults Living in a Household with a Potential Beneficiary**

|_Variable_|_(1)_<br>_OLS_<br>_All_|_(2)_<br>_OLS_<br>_All_|_(3)_<br>_OLS_<br>_Males_|_(4)_<br>_OLS_<br>_Females_|_(5)_<br>_IV_<br>_All_|_(6)_<br>_IV_<br>_All_|_(7)_<br>_IV_<br>_Males_|_(8)_<br>_IV_<br>_Females_|
|---|---|---|---|---|---|---|---|---|
|Colombia Mayor|0.029***<br>(0.008)|0.035***<br>(0.007)|0.019***<br>(0.007)|0.052***<br>(0.014)|0.017<br>(0.020)|0.032<br>(0.026)|0.007<br>(0.024)|0.094*<br>(0.055)|
|Ddt ibl b|0.705***|0.570***|0.276***|0.812***|0.714***|0.575***|0.301***|0.806***|
|epenen varae y year|(0.028)<br>|(0.031)<br>|(0.040)<br>|(0.055)<br>|(0.029)<br>|(0.032)<br>|(0.041)<br>|(0.058)<br>|
|Dependent variable by area|0.769***<br>(0.024)|0.653***<br>(0.027)|0.322***<br>(0.040)|0.925***<br>(0.059)|0.767***<br>(0.024)|0.650***<br>(0.028)|0.310***<br>(0.042)|0.926***<br>(0.062)|
|Observations|16,563|15,145|7,898|7,233|16,171|14,707|7,502|6,771|
|R-squared|0.188|0.327|0.384|0.172|0.187|0.326|0.381|0.167|
|Municipalities, number|292|292|283|284|264|262|237|243|
|F|343.5|478.7|1549|152.0|335.3|459.5|1456|138.2|
|Partial R-squared|||||0.0595|0.0670|0.0753|0.0599|
|Kleinbergen-Paap statistic|||||431.3|467.7|342.3|247.1|
|OIR test|||||0.996|0.996|0.0281|0.0330|
|Endogeneity test|||||0.557|0.919|0.597|0.440|
|_First stage_|||||||||
|Ddt ibl b|||||0.005|0.005|0.008|−0.002|
|epenen varae y year|||||(0.049)|(0.048)|(0.064)|(0.062)|
|Deendent variable b area|||||0.003|−0.004|−0.011|0.006|
|p y|||||(0.047)|(0.047)|(0.071)|(0.060)|
|Instrument from probit|||||0.961***<br>(0.046)|0.990***<br>(0.046)|1.007***<br>(0.054)|0.967***<br>(0.062)|

_Note:_ The table illustrates a linear probability model on a dependent variable indicating participation in the labor force. The IV specification uses a three-stage procedure for binary treatment variables. Only the OIR test is derived from a twostep procedure. Columns (1) and (5) do not include additional control variables. Standard errors are shown in parenthesis.

It is also of interest to take a quick look at the situation among other household members. Table 17 shows the results for other adult household members. The potential for the endogeneity of treatment here is far smaller because we are not looking at the actual beneficiary, but at someone else. Yet, it cannot be completely ruled out that unobserved household-level characteristics act as omitted variables. The effect is positive and statistically significant for all four OLS estimations. The inclusion of the additional control variables has only a marginal effect on our estimates. While statistically insignificant, the point estimates on the full sample are only slightly lower under the IV estimation. The lack of statistical significance can be explained by larger standard errors. However, there is some concern about instrument validity, as shown by the OIR test, once the sample is divided according to 34