Essays on Household Consumption and Spending

This dissertation studies household consumption and spending, using household-level microdata in the Consumer Expenditure Survey.

The first chapter studies consumption smoothing of households between monthly payments of mortgage or rent. My focus on regular payments contrasts with most of this literature that finds excess sensitivity to regular receipt of income. Using the Consumer Expenditure Survey (CEX) Diary survey from 1998 to 2011, I find that spending on non-durable goods is $3.34 or 9.0% higher per day during the two weeks following the day when a housing payment occurs, compared to the two weeks prior to that day, inconsistent with the consumption smoothing predicted by the life cycle/permanent income hypothesis. My finding is robust to the coincident timing of households' regular housing payments and their regular income arrivals, and suggests that findings in the previous literature of excess sensitivity of consumption to regular income arrivals may in part reflect excess sensitivity to the timing of making regular payments. The increase in bi-weekly average spending following a housing payment day is larger for households in which the household head has lower educational attainment, larger for households with lower income, and has a U-shaped profile in age of household head. My finding is not fully consistent with existing theories that aim to explain departures from consumption smoothing between regular payments, including liquidity constraints and uncertainty about bank account balances.

In the second chapter, I provide the first nationwide study that empirically estimates the effect of casinos on the non-gambling economy. Using household spending data from the Consumer Expenditure Survey from 1996 to 2013, and a restricted access file containing the county codes of the CEX households, I find a positive effect of casinos on household spending on non-gambling goods. When casinos appear within 100 miles, households increase their quarterly non-gambling spending by up to 2.6%. The positive effect suggests that casinos can have a complementary effect on the non-gambling economy. The positive effect does not always significantly accumulate when more casinos are built in nearby areas. A comparison among income groups shows that the complementary effect of casinos on non-gambling sectors is largely driven by the spending changes of lower-income households. The complementary effect persists in the long run.

The third chapter studies the relationship between lottery jackpots and household spending. Large lottery jackpots that accumulate over time until winners appear generate massive ticket sales. To investigate how household spending changes when lottery jackpots increase, I focus on Powerball and Mega Millions, two multi-state lotto games that produce the highest jackpots among all the lotteries in the U.S. I find that spending on non-gambling goods is $4.28 per day or 3.4% lower when either lottery has a jackpot above $100 million, compared to when it is below $50 million. This difference is larger for households in the lowest income tercile, at $4.81 per day or 5.7%. The changes in spending on subcategories suggest that most of the spending decrease of lower-income households during the periods when jackpots are high is driven by postponed housing payments.