distribution within the sample (Taylor et al. 2003). The authors used a retrospective report of the village migration network size from seven years earlier to control for migrant selection at the household, but do not control for village fixed effects, such as proximity to cities (and markets) and other factors affecting the local economy, which will lead to biased estimates of the effect of migration on earnings. In another study examining earnings across the earnings distribution, the authors estimate models in first-differences and identify migration through the one-year lag in size of the village migrant network, finding that households with migrants have per capita incomes 8.5 to 13.1 percent higher than those without migrants (Du et al. 2005). First-differences control for many unobserved factors that might be introducing bias through migrant selection, though even lags in size of the village migrant network may be correlated with past shocks to the local economy. If there are persistent effects of shocks, or mean reversion after a negative shock driving earlier migration, there could yet be bias in these estimates. That said, these estimates are considerably more credible than those found by Taylor et al. (2003).<sup>15</sup>

# **4.2 Consumption and Investment**

Given the earning gains from migration, studying the consumption and investment patterns affected by migration would allow us to comprehend the specific budget constraints households can overcome with migration. de Brauw and Giles (2018) highlight the positive effect of migration on annual changes in consumption in a panel of households and villages between 1988 and 2002: out-migration contributes to a 2% to 2.9% annual increase in consumption per capita, or between 65% and 93% of the annual consumption growth recorded in the RCRE sample villages between 1988 and 2002.<sup>16</sup> During the period with rapid expansion in migration, from 1995 to 2002, a one-percentage point increase in out-migration from the villages is associated with consumption per capita increases of 10% and 7% percent for households in the low and middle terciles of initial consumption distributions, respectively. More affluent households in the village also experienced consumption growth of 4% though this increase appears attributable to the accumulation of durable goods and housing.<sup>17</sup>

> 15 Recent debates on the returns of rural-to-urban migration on income and consumption in developing countries focus on the income and consumption of migrants themselves and their households in the cities (Hamory et al., 2021; Lagakos et al., 2020). The estimated impact of migration on household consumption for migrants in urban China is 23%.

> 16 To identify the migrant impact, the authors use differences in the timing of availability of new ID cards (which were important for legal temporary migration) across counties of rural China. The authors show that timing is exogenous to local shocks and preferences for migration (de Brauw and Giles, 2018, 2017).

> 17 These findings are consistent with an earlier study suggesting that income from work outside the village (by both migrants and commuters) contributes to reducing inequality (Benjamin et al. 2005).

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