Travis Baseler is a PhD Student in the Department of Economics at Stanford University. Prior to attending Stanford, he received a BA from Columbia University, where he studied economics and mathematics. His research focuses on internal migration in developing countries. Baseler’s most recent work studies information barriers to migration using a field experiment in rural Kenya.
The large income gap between urban and rural parts of many poor countries invites the question of why migration does not arbitrage this gap away. Using a sample of households in rural Kenya, Baseler shows that individuals on average underestimate urban wages considerably. Randomly providing households with city-level labor market information induces seven percent of households to send a migrant to Nairobi, increasing household income. Baseler proposes that downward-biased beliefs persist because of strategic income misreporting by migrants, and uses matched survey data to show that information flows from migrants to origin households are consistent with hidden income incentives.
Rural individuals require reasonably accurate information about destination labor market conditions to compute expected migration returns. Gathering such information can be costly, and in-network migrants face incentives to understate income to reduce remittance demands. In an ongoing experiment in Western Kenya, I randomly expose rural households to information on urban labor markets. Treated households are 9 percentage points more likely (on a base of 12%) to send a migrant to Nairobi and earn 30% more income. Origin households underestimate total earnings of migrants from their own households by 49%, suggesting that income misreporting may be behind the persistently low beliefs.