At the bottom of the table, we also present results for monthly labor income and hours worked. These are estimated by a simple linear regression with values equal to zero for individuals not in the labor force. Although we admit that a Tobit or Heckman selection model may be more appropriate, as with the multinomial models, no IV techniques exist for these methods. Also, as mentioned above, for hours worked, no information is available from the 2012 round, reducing the sample by more than 25 percent. With these caveats in mind, we still believe that these result have important implications.

**Table 16: Results for the Treatment Effect of Program Receipt on Various Labor Force**

|||**O**<br>|**utcomes**||||
|---|---|---|---|---|---|---|
|||_< 70 years_|||_> 70 years_||
|_Variable_|_All_|<br>_Males_|_Females_|_All_|<br>_Males_|_Females_|
|_Size of business_|||||||
|k l|0.038|0.138**|−0.017|0.023|0.080**|−0.007|
|Wors aone|(0.030)|(0.056)|(0.039)|(0.023)|(0.040)|(0.028)|
|_Place of work_|||||||
||0.020|0.025|−0.007|0.001|−0.027|0.018|
|Home or street|(0.022)|(0.042)|(0.034)|(0.016)|(0.032)|(0.024)|
|Othr hm|−0.002|−0.009|0.010|−0.008|−0.010|−0.009|
|e oes|(0.011)|(0.019)|(0.016)|(0.007)|(0.011)|(0.011)|
||<br>0.042*|<br>0.093*|<br>0.029|<br>−0.003|<br>0.071*|<br>−0.031**|
|Land, river, or sea|(0.023)|(0.048)|(0.026)|(0.019)|(0.038)|(0.015)|
|_Type of occupation_|||||||
|<br>Pi l|0.027**|0.014|0.040***|−0.001|−0.006|−0.000|
|rvate empoyee|(0.010)|(0.023)|(0.013)|(0.008)|(0.015)|(0.006)|
|Pbli l|0.006|0.000|0.009|0.002|0.003|0.000|
|uc empoyee|(0.007)|(0.009)|(0.010)|(0.002)|(0.004)|(0.001)|
||<br>0.060**|<br>0.147**|<br>−0.025|<br>0.019|<br>0.067|<br>−0.020|
|Independent worker|(0.029)|(0.059)|(0.039)|(0.023)|(0.046)|(0.026)|
||<br>−0.002|<br>0.065**|<br>−0.020|<br>0.007|<br>0.020|<br>0.011|
|Own land|(0.015)|(0.033)|(0.016)|(0.013)|(0.030)|(0.010)|
|Uid|0.012|0.000|0.017|0.001|0.003|−0.003|
|npa|(0.008)|(0.015)|(0.011)|(0.006)|(0.011)|(0.008)|
|_Sector of work_|||||||
|<br>|0.038|0.057|0.039|−0.009|0.060|−0.029*|
|Agriculture & related|(0.024)|(0.049)|(0.027)|(0.020)|(0.038)|(0.017)|
|Mfi|<br>0.029**|<br>0.017|<br>0.034*|<br>−0.010|<br>−0.029**|<br>−0.001|
|anuacturng|(0.012)|(0.018)|(0.018)|(0.010)|(0.014)|(0.013)|
||0.004|0.032|−0.046*|0.021*|0.037*|0.004|
|Trade & commerce|(0.018)|(0.033)|(0.025)|(0.012)|(0.022)|(0.017)|
||<br>0.031*|<br>0.045|<br>0.024|<br>0.003|<br>0.007|<br>−0.004|
|Service & tourism|(0.016)|(0.029)|(0.026)|(0.010)|(0.018)|(0.016)|
|_Other outcomes_|||||||
||137,327.628***|152,043.474**|89,104.746**|−28,262.658|−31,913.834|−20,480.467*|
|Labor income|(38,036.743)|(61,568.069)|(42,852.815)|<br>(18,488.245)|<br>(32,228.232)|<br>(10,770.416)|
|H kd|4.474***|7.416***|1.029|−0.943|−0.957|−0.618|
|ours wore|(1.416)|(2.369)|(1.682)|(0.858)|(1.764)|(0.861)|

_Note:_ Only parameters on treatment variable shown. Linear probability model with three-stage procedure for binary treatment variables on respective dependent variable. Only the OIR test is derived from two-step procedure. For “Other Outcomes” dependent variables are continuous. All specifications include complete set of control variables and full set of fixed effects. Standard error in parenthesis.

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