MPC Heterogeneity and Household Balance Sheets

Abstract

Using Norwegian administrative data, we study how sizable lottery prizes affect household expenditure and savings. Expenditure responses (MPCs) spike in the year of winning, with a mean estimate of 0.35, and thereafter fall markedly. Controlling for all items on the household balance sheet and characteristics such as education and age, MPCs vary with the amount won and liquid assets only. Shock size matters: The MPC among the 25 percent winning least is twice as high as among the 25 percent winning most. Many households are wealthy, illiquid and have high MPCs, consistent with 2-asset models of consumer choice.

Sticky Expectations and Consumption Dynamics

“…One of our objectives is to faithfully match microeconomic data. In such data there is incontrovertible evidence-most recently from millions of datapoints from the Norwegian population registry examined by Fagereng, Holm, and Natvik (2017)-that the consumption function is not linear. It is concave, as the general theory suggests (Carroll and Kimball (1996)), and this concavity matters greatly for matching the main micro facts.…”

“…It is simply not plausible to assume that consumers are not aware their income has permanently changed when they take a new job or are fired from an existing one. Furthermore, there are at least some shocks whose transitory nature is impossible to misperceive; the best example is lottery winnings in Norway, see again Fagereng, Holm, and Natvik (2017). The consumption responses to those shocks resemble the responses measured in the previous literature to shocks that economists presumed (contra Pischke) that consumers knew Granting our choice to assume that consumers correctly perceive the events that are idiosyncratic to them (job changes, lottery winnings, etc), there is still a potential role for application of the MLP framework: Instead of assuming sticky expectations, we could instead have assumed that consumers perform a signal extraction exercise on only the aggregate component of their income, because they cannot perceive the transitory/permanent split for the (tiny) part of their income change that reflects aggregate macroeconomic developments.…”

What Would You Do With $500? Spending Responses to Gains, Losses, News, and Loans

“…Johnson et al, 2006), but more recent work that uses larger samples and richer data routinely finds a significant correlation (see e.g. Fagereng et al, 2016;Baker, 2017;Aydin, 2018). However the R-squared measures remain very low.…”

“…These data come either from household surveys or financial datasets-e.g. Consumer Expenditure Survey (Johnson et al, 2006), Kilts-Nielsen Consumer Panel (Parker, 2017), or banks and other financial service providers (Gelman et al, 2014;Baker, 2017;Ganong and Noel, 2017;Aydin, 2018) -or by backing out expenditures from administrative data on income and wealth (Fagereng et al, 2016). The revealed preference approach uses these data to estimate MPCs either by cleverly exploiting natural experiments that mimic unexpected changes in household budgets-e.g.…”

“…The revealed preference approach uses these data to estimate MPCs either by cleverly exploiting natural experiments that mimic unexpected changes in household budgets-e.g. fiscal stimulus payments (Parker et al, 2013), lottery winnings (Fagereng et al, 2016), or mortgage modifications (Ganong and Noel, 2017)-or by extracting the transitory component of stochastic income fluctuations (Blundell et al, 2008). Another set of studies uses what Parker and Souleles (2017) label the "reported preference" approach, in which individuals are asked how their spending would respond in hypothetical or actual scenarios.…”