# **Table OA10: Displacement and elite capture**

||Gives inputs to<br>others|Used<br>inorganic<br>fertilizers in<br>2009/10|Used improved<br>seeds in<br>2009/10|Related to<br>government<br>officials and<br>influentials|Socializes with<br>government officials<br>and influentials|Paid to become<br>beneficiary in<br>2010/11|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Beneficiary|-0.0418|0.242*|-0.008|-0.146*|-0.125|0.008|
||_0.659_|_0.053_|_0.929_|_0.082_|_0.142_|_0.720_|
|Meeting & Lottery village|-0.104|0.236*|0.171*|-0.063|-0.079|0.017|
||_0.209_|_0.090_|_0.058_|_0.455_|_0.373_|_0.321_|
|Lottery village|-0.140*|0.188|0.089|-0.078|-0.057|0.008|
||_0.082_|_0.142_|_0.429_|_0.362_|_0.515_|_0.635_|
|Meeting village|-0.0737|0.152|0.022|-0.149*|-0.148*|-0.000|
||_0.376_|_0.303_|_0.848_|_0.060_|_0.068_|_0.956_|
|Beneficiary x M&L|0.0953|-0.381***|-0.011|0.183|0.165|-0.011|
||_0.316_|_0.005_|_0.936_|_0.108_|_0.152_|_0.673_|
|Beneficiary x Lottery|0.169|-0.375**|0.005|0.188|0.149|0.008|
||_0.101_|_0.015_|_0.970_|_0.111_|_0.210_|_0.714_|
|Beneficiary x Meeting|0.0331|-0.232|0.094|0.218**|0.217*|-0.008|
||_0.730_|_0.103_|_0.464_|_0.039_|_0.057_|_0.769_|
|Number of contacts|523||||||
|Number of households|294|427|427|427|427|920|
|R-squared|0.025|0.028|0.016|0.019|0.017|0.004|
|Mean of DepVar in Control|0.140|0.401|0.554|0.134|0.115|0.018|
|_P-val of B = Non-B in..._|||||||
|Meeting & Lottery village|_0.180_|_0.007_|_0.756_|_0.034_|_0.062_|_0.927_|
|Lottery village|_0.068_|_0.199_|_0.980_|_0.629_|_0.763_|_0.224_|
|Meetingvillage|_0.796_|_0.923_|_0.337_|_0.302_|_0.231_|_0.801_|

Note: In Column 1, we report the estimation of the following specification: _y ijk = α ijk + β 1 Beneficiary ij + β 2 ML j + β 3 L j + β 4 M j + β 5 Beneficiary ij *ML j + β 6 Beneficiary ij *L j + β 7 Beneficiary ij *M j + ε ijk_ , where _i_ indexes the individual (household), _j_ indexes the village and _k_ indexes another individual reported to be in the respondent's network. Columns 2-6 report the estimation of the following specification _y ij_ = _α ij_ + _β 1 Beneficiary ij_ + _β 2 ML j_ + _β 3 L j_ + _β 4 M j_ + _β 5 Beneficiary ij_ * _ML j_ + _β 6 Beneficiary ij_ * _L j_ + _β 7 Beneficiary ij *M j_ + _ε ij_ , where _i_ indexes the individual (household) and _j_ indexes the village. _Beneficiary ij_ is a dummy that takes value of 1 if the individual _i_ in village _j_ is a beneficiary of the NAIVS voucher program in 2010/11. Variables _ML j , L j_ and _M j_ are dummies that take value of 1 if village _j_ is under both interventions, only second intervention and only first intervention, respectively. The models presented here represent an intention to treat analysis and are not adjusted for any baseline covariates. The dependent variable in Column 1 is a dummy variable that takes a value 1 if the respondent reported giving agricultural inputs to a nonbeneficiary friend. The dependent variables in Column 2 and 3 are dummy variables that take value of 1 if the respondent reports using improved seeds and inorganic fertilizers in 2009/10, respectively, using household survey data collected at baseline. In Columns 4 and 5, the dependent variables are dummies that takes value of 1 if respondent reports holding the position of or being related to and having regular social interaction with DALDO, WEO, VEO, VVC member, or Village or Hamlet Chair. The dependent variable in Column 6 is a dummy variable that takes value of 1 if respondent reports at follow-up household survey having paid to become a voucher beneficiary in 2010/11. Data for the Columns 1 and 6 were collected using household survey at follow-up while data in Columns 2-6 come from household survey at baseline. P-values are computed using the t-asymptotic wild cluster bootstrap procedure described in Cameron et al. (2008) and reported below the coefficients. Clustering was done at the village level. ***,**,* denote statistical significance at the 1, 5 and 10 percent level, respectively. See Appendix Table 1 for definition of variables.