Empirical analysis of household consumption behavior
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[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The dissertation is an empirical analysis of consumer behavior using household-level data. The dissertation consists of two essays. The first essay conducts split sample test on whether household consumption responds to anticipated changes in income. The second essay explores heterogeneity in a dynamic panel setting. The first essay is "The Excess Sensitivity in Consumption without Liquidity Constraint: Evidence from Monthly Household Data". The monthly salaries and allowances of Korean government employees are known in advance but vary greatly throughout the year. Using a large Korean monthly panel data set from 1994 to 2003, we examine how nondurable consumption expenditure in households headed by government employees responds to predictable income changes. We find excess sensitivity in consumption during the pre-Asian financial crisis era in households headed by young government employees with low liquid assets or low income. These household features are commonly associated with liquidity constraints. Further analysis shows that despite the apparent association, liquidity constraint is not the most convincing explanation for the excess sensitivity. Instead, the empirical finding is consistent with the theory that certain households deviate from consumption smoothing when the effort involved exceeds the welfare gained. The second essay is "A Dynamic Panel Analysis on the Heterogeneity in Excess Sensitivity Household Consumption." The existing empirical models of household consumption assume parameters are constant across households, implying homogenous responses by households to changes in environment. Using a large Korean monthly panel data set, we explore heterogeneity in response of household consumption expenditure to predictable income changes. We find excess sensitivity in about 4% of the households in the sample. The connection between household characteristics and estimated household excess sensitivity sheds new light in the cause of excess sensitivity: excess sensitivity is likely due to low cost of failure in consumption smoothing rather than liquidity constraint. We also find that these small number of households are the main cause for excess sensitivity found in the pooled regression and time series regression of aggregated data. We conduct finite sample inference on household heterogeneity in a Bayesian framework.
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