UC Berkeley

This dissertation contains two chapters. In Chapter 1, I combine randomized controlled trials with transaction-level data and survey data, I show that credit-limit extensions significantly increase consumer expectations about their future income without increasing realized income. A one-dollar higher qualified credit limit raises consumer income expectations over the nextsix months by 40 cents and total consumption by 34 cents. The expectation changes explain around 35% of the total spending responses to credit limit extensions. The results show that consumers infer information about their future income from credit supply, and this learning behavior impacts their economic decision-making greatly.

In the second chapter, I structurally estimate a life-cycle model incorporating the income-inference channel to study how shocks to banks’ beliefs affect their credit extensions and consumers’ subsequent spending behaviors. I find that, When the precision of bank signal about consumer future income increases by 25%, equilibrium credit supply and spending for the median consumer respectively increase by 14.11% and 4.11%. As suggested by the counter-factual analysis, when the advancement of information technology enables banks to extract more precise signals about household future income, credit supply, and spending tend to increase. The elasticity of spending with respect to bank-signal precision is around 0.16.