specific large correlation between being treated and moving to a big city for any of the groups. We note that the results for the new households are robust to controlling for the new household being itself a PROSPERA recipient.

Table 7: Effects on durable good’s accumulation. New households.

||(1)<br>Transport|(2)<br>Entert eq|(3)<br>Kitchen sup|(4)<br>Basic serv|(5)<br>IT items|(6)<br>IT serv|(7)<br>ln(impcons)|
|---|---|---|---|---|---|---|---|
|**_Panel A: Cross-sectio_**|**_n_**|||||||
|Treatment|-0.001|0.092**|0.158**|0.067|0.035|0.059*|0.036**|
||(0.024)|(0.045)|(0.062)|(0.042)|(0.034)|(0.035)|(0.014)|
|Constant|0.223***|1.529***|1.847***|2.456***|0.779***|0.337***|8.826***|
||(0.080)|(0.153)|(0.170)|(0.109)|(0.093)|(0.114)|(0.037)|
|Observations|2,265|2,265|2,265|2,265|2,265|2,265|2,152|
|**_Panel B: DiD 1997-2_**|**_017_**|||||||
|Treatment X 2017|0.014|0.194***|0.244***|0.025|0.197*|0.217*|0.054***|
||(0.028)|(0.067)|(0.070)|(0.087)|(0.118)|(0.125)|(0.014)|
|Treatment|-0.011<br>(0.014)|-0.115**<br>(0.052)|-0.080<br>(0.052)|0.032<br>(0.069)|-0.186*<br>(0.102)|-0.184*<br>(0.102)|-0.017<br>(0.011)|
|2017|0.170***|0.312***|1.338***|1.232***|-0.735***|-1.166***|0.208***|
||(0.023)|(0.051)|(0.052)|(0.063)|(0.090)|(0.099)|(0.009)|
|Constant|0.016|1.013***|0.422***|1.345***|1.318***|1.313***|8.644***|
||(0.043)|(0.125)|(0.123)|(0.104)|(0.143)|(0.146)|(0.027)|
|Observations|4,530|4,530|4,530|4,530|4,530|4,530|4,407|
|**_Panel C: ANCOVA_**||||||||
|Treatment|0.001|0.096**|0.173***|0.066|0.045|0.060*|0.042***|
||(0.024)|(0.045)|(0.060)|(0.041)|(0.034)|(0.035)|(0.013)|
|Y(97)|0.195**<br>(0.081)|0.035<br>(0.027)|0.209***<br>(0.034)|0.039**<br>(0.018)|0.047***<br>(0.010)|0.006<br>(0.014)|0.310***<br>(0.045)|
|Constant|0.227***|1.501***|1.776***|2.399***|0.726***|0.330***|6.139***|
||(0.080)|(0.155)|(0.168)|(0.111)|(0.095)|(0.117)|(0.398)|
|Observations|2,265|2,265|2,265|2,265|2,265|2,265|2,149|
|Mean T 2017|0.208|1.450|1.992|2.605|0.840|0.428|9.241|
|Mean C 2017|0.200|1.354|1.793|2.522|0.793|0.361|9.203|

This table shows the long-term effects of the program on a set of variables that result from aggregating groups of durable assets and household characteristics. Observations are restricted to newly formed households in 2017 (new households) that were identified by searching for members no longer present in their original 1997 households. The outcomes constructed are: (1) _Transportation_ , which adds the number of cars and vans; (2) _Entertainment equipment_ , which gathers under entertainment equipment number of TV, radio and sound equipment; (3) _Kitchen supplies_ , which sums the following appliances: blender, refrigerator, electric grill, gas stove or microwave oven; (4) _Basic services_ , which consists of the availability of the following services: firm floor, electricity, drainage and water access in the property; (5) _IT items_ , which refer to the number of computers and cellphones; and (6) _IT services_ , which sums the home phone, internet and pay-TV; (7) _ln(imp cons)_ , is the imputed measure of non-durable expenditure on food personal products, and clothing. Data employed comes from 1997 ENCASEH and 2017-18 ENCEL. Panel A shows the result from a cross-section estimate which only uses data from 2017. Treatment is a dummy variable that identifies if the observation belongs to one of the 320 original Progresa RCT treatment localities. Panel B does a DiD estimation with 1997 and 2017 as the two periods considered. Panel C estimates an ANCOVA, which controls for the pre-existing level of the dependent variable (denoted as Y(97)). Controls include (from ENCASEH 1997): HH head age, education, speaking a dialect, HH size, % members under 15, dummies for home, productive land and draft animals ownership, and locality marginalization index. Standard errors clustered at the locality level. Asterisks indicate significance at the ***1%, **5%, and *10% level.

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