# 5. Results

## _Sample characteristics_

The selection of roads for RTP3 interventions was carried out at the start of the program and was strictly based on criteria linked to the development objective of the program: to _improve year-round access to markets, economic opportunities, and social services for rural populations_ . The criteria included the number of poor and total population affected by the road, defined as the population living within 2 km of the road, and whether or not the commune previously had an all-weather road. Our study sample differs from the broader VARHS 2008 sample, which was constructed to be representative of the rural population in the provinces it covered, because we restricted our study to the communes that were selected to receive RTP3 interventions.

A comparison of households from the two sets of communes suggests that the program achieved its targeting objectives:<sup>15</sup> our study sample is poorer than the full VARHS sample and this difference is quite large in some measures. There are few statistically significant differences in terms of household size and household head characteristics (Table A.3), but there are significant differences in income, consumption, and indicators of wealth like assets and quality of housing. For instance, households in RTP3 communes are less likely to have a brick wall or a cement floor. Total incomes among the RTP3 sample are approximately 40 percent lower than in the full VARHS sample. The differences appear to come from wages, agriculture, and income from non-farm sources, all of which are suggestive of lower levels of economic opportunity in these villages. Indeed, considering land ownership, we see little difference in the size of land owned, but significant differences in the amount of land cultivated, and perhaps unsurprisingly, in the value of land (Table A.3).

## _Male- versus female-headed households_

A second relevant comparison to make at the outset is between gender differences at baseline: mainly differences between male- and female-headed households since most of our regressions are at the household level. Anecdotal evidence suggests that the default head of household is a man, with the implication that female-headed households are likely those where women are widowed, separated, or divorced. In contrast, a very small percentage of male-headed households are unmarried. Therefore, it is likely that female-headed households have one working-age adult less on average, compared to maleheaded households. This indeed appears to be the case in our sample. As Table A.4a shows, there appear to be only small differences between male- and female-headed households in VARHS 2008 in the education or literacy levels of the household heads, but statistically significant differences in the size of the household. Male-headed households are larger on average than female-headed households by close to one adult per household.

> 15 Another reason these samples could differ is that the sampling unit that we draw data from is the commune whereas VARHS is intended to be representative at the province level. However, nothing in the sampling strategy of VARHS (described in Section 2) gives us a reason why we should expect the systematic differences we observe in Table A.3 based on the fact that the data are not representative at the commune level. Therefore, we interpret this largely as a result of RTP3 targeting.

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