fers.<sup>34</sup> Albarran and Attanasio (2002) evaluate the effects of a conditional cash transfer (CCT) program that was implemented in rural communities in Mexico (“Progresa”). that the which had an value of 250 household<sup>35</sup> They find grant, average pesos per reduced net transfers by 140 pesos per beneficiary household.<sup>36</sup> Angelucci et al. (2012) show that a CCT program implemented in urban Mexico (“Oppurtinades”) had a very limited crowding-out effect on monetary transfer received, but reduced the likelihood of in-kind transfers significantly (they don’t have data on the value of in-kind transfers). Relative to these estimates, the crowding-out effect I find is smaller. I find a fall of 13ppt in the likelihood of receiving transfers and BDT 152 decrease in the value of net informal transfers received by the average household that was eligible for the TUP program. This is low, relative to the value of assets transferred by the program (BDT 9500). It is perhaps more relevant to benchmark the crowding-out effect on informal transfers relative to the effect of the program on annual household consumption. When I estimate the effect of the program on consumption, using specification (1), I find that the program led to an increase of BDT 1136 in annual per capita consumption (p-value=0.000). The reduction in informal transfers is therefore small relative to the improvement in economic conditions of ultra-poor households caused by the program.

There are a number of possible explanations for the relatively small crowding-out effect I find on informal transfers. A key distinction between the TUP program and the programs in the aforementioned studies is the multi-faceted nature of the TUP program. As discussed in Section 3, many of these components may have opposing effects on interhousehold transfers, limiting the extent of crowding-out. Another key feature of the TUP program is that it is a one-off, big push intervention; while the transfer programs studied in previous work entail small but regular cash transfers. It is possible that access to continuing transfers are perceived differently by social networks of the beneficiaries, compared to a one-shot transfer, and therefore their crowding out effects are different. Moreover, the program I study targeted some of the poorest households in rural Bangladesh where out-migration is limited, especially for the poor (Bryan et al. (2014)). In comparison, the households studied in previous work from South Africa or Mexico had greater access to migrant networks and remittances. Furthermore, the crowding out effect of CCT programs may be different due to the fact that these programs are conditional on investments in child education and health, whereas the TUP

> 34Juarez (2009) finds a larger, almost one-to-one, crowding-out effect at the individual level. The data does not allow me to distinguish transfers received by different members of the same household, thus I cannot estimate the effects at the individual level.

> 35The amount of the transfer varied across beneficiary households, depending on the number of children in the household.

> 36Albarran and Attanasio (2003) show that the crowding-out effect was larger in villages where households’ earnings were less volatile (i.e. average variance of household income is lower), which is in line with theoretical models of risk-sharing under imperfect enforcement.

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