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Abstract
In the first chapter of this dissertation, I find that an increase in the likelihood of extreme temperatures leads to a decline in the availability of credit in a region. I also document that for certain loan types, such as a revolving line of credit, the price of credit is increasing in the likelihood of extreme temperatures. Lastly, I find that temperature shocks may propagate from one region to other regions via a bank lending channel. Such indirect exposure, to temperature shocks elsewhere, adversely affects firm-level outcomes.
The second chapter of this dissertation focuses on the implications of temperature extremes for small businesses in a region. I find that an increase in the likelihood of extreme temperature leads to an adverse impact on the availability of credit in a region. I find that the average adverse effect of extreme temperatures on credit availability is present for all bank types based on size. The adversity of extreme temperature effect, on credit availability in a region, increases with bank size.
In the third chapter of this dissertation, I propose a new heterogeneous-agent stochastic discount factor (SDF) that equals the previous period investment weighted average of agents' SDFs. I implement this SDF on the consumption growth of cohorts of households in the Consumer Expenditure Survey dataset from the U.S. Bureau of Labor Statistics. I use factor analysis to reduce the impact of measurement error present in consumption data. For quarterly data observed at a monthly frequency, the investment weighted SDF reconciles the historical equity premium for relative risk aversion of 7. The proposed SDF fares well when tested using classical asset pricing tests like Hansen-Jagannathan volatility bounds and JT test. The weighting methodology is the primary driver of my results.