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Analyzing account-level data from an account aggregator, we find that households increase consumption when they receive expected tax refunds, as if they face liquidity constraints. However, these same households smooth consumption when making payments in other years, primarily by transferring funds among liquid accounts. Even households carrying credit card debt smooth consumption when making payments, and even highly liquid households spend out of refunds. This behavior is inconsistent with pure liquidity constraints or hand-to-mouth behavior and is most consistent with a mental accounting life-cycle model. (JEL D12, E21, G51, H24, H31)

© 2019 The Ohio State University Using variation in minimum wages across cities and controlling for differences in business-cycle factors and long-run local economic trends, we find that following minimum wage increases, both, prices and nominal spending rise modestly. These gains are larger for certain subcategories of goods such as food away from home and in locations where low-wage workers account for a larger share of employment. Further, minimum wage increases are associated with reduced total debt among households with low credit scores, higher auto debt, and increased access to credit.

Using detailed transaction-level data from financial accounts, this paper shows that the revenues of small businesses and the consumption spending of their owners both decline by roughly 40% following the declaration of the national emergency in March 2020. However, through May 2020, the vast majority of this average decline in revenues is due to national factors rather than to variation in local infection rates or policies. Further, there is only a modest propensity for business owners to cut consumption in response to their individual business losses: Comparing owners in the same county but whose businesses operate in industries differentially impacted by local infections and state-level policies, we show that each dollar of revenue loss leads to a 1.6 cent decline in the consumption of the owner at this early stage of the pandemic. This limited passthrough appears to be explained by three factors: (1) the liquidity of households and businesses entering the crisis – consumption is twice as responsive for small business owners who operate with low liquidity; (2) emergency Federal programs – median account balances in both business and checking accounts decline in March but rebound in April and May when the transfer programs begin; (3) pandemic induced declines in the ability to spend on consumption – spending on travel, restaurants or personal services dropped dramatically.

This paper evaluates theoretical explanations for the propensity of households to increase spending in response to the arrival of predictable, lump-sum payments, using households in the Nielsen Consumer Panel who received $25 million in randomly distributed stimulus payments. The pattern of spending is inconsistent with models in which identical households cycle rapidly through high and low- response states as they manage liquidity, but is instead highly predictable by income years before the payment. Spending responses are unrelated to expectation errors, almost unrelated to crude measures of procrastination and self-control, significantly related to sophistication and planning, and highly related to impatience. (JEL D12, D14, D91, E21, H23)

We evaluate the consistency of two methods for estimating the effect of an economic policy: i) asking people how the policy caused them to change their behavior (reported effects); ii) inferring this change using data on behavior and differences in treatment across people (revealed-preference estimates). Both methods are widely used to measure spending caused by increases in liquidity. Using Federal stimulus payments disbursed quasi-randomly in 2008, we find larger revealed-preference estimates of spending propensities for households who report greater spending responses, and the methods produce similar average propensities. But evidence is mixed on the relationship between spending propensities and liquidity.

Households in the Nielsen Consumer Panel were surveyed about their 2008 Economic Stimulus Payment. In estimates identified by the randomized timing of disbursement, the average household׳s spending rose by 10 percent the week it received a Payment and remained high cumulating to 1.5–3.8 percent of spending over three months. These estimates imply partial-equilibrium increases in aggregate demand of 1.3 percent of consumption in the second quarter of 2008 and 0.6 percent in the third. Spending is concentrated among households with low wealth or low past income; a household׳s spending did not increase significantly when it learned about its Payment., Sloan School of Management, Northwestern University (Evanston, Ill.). Kellogg School of Management, University of Chicago. Initiative for Global Markets, Northwestern University (Evanston, Ill.). Kellogg School of Management. Zell Center for Risk Research, Harvard University. Laboratory for Applied Economics and Policy

Under the Economic Growth and Tax Relief Reconciliation Act of 2001, most U.S. taxpayers received a tax rebate between July and September, 2001. The week in which the rebate was mailed was based on the second-to-last digit of the taxpayer's Social Security number, a digit that is effectively randomly assigned. Using special questions about the rebates added to the Consumer Expenditure Survey, we exploit this historically unique experiment to measure the change in consumption expenditures caused by receipt of the rebate and to test the Permanent Income Hypothesis and related models. We find that households spent about 20-40 percent of their rebates on non-durable goods during the three-month period in which their rebates were received, and roughly another third of their rebates during the subsequent three-month period. The implied effects on aggregate consumption demand are significant. The estimated responses are largest for households with relatively low liquid wealth and low income, consistent with liquidity constraints.

This paper uses the consumption Euler equation to derive a decomposition of consumption growth into four sources. These four sources are new information, and three sources of predictable consumption growth: intertemporal substitution, changes in the preferences for consumption, and incomplete markets for consumption insurance. Using household-level data, we implement this decomposition for the average growth rate of consumption expenditures on nondurable goods in the United States from 1982 to 1997. The economic importance of precautionary saving rivals that of the real interest rate, but the relative importance of each source of movement in the volatility of consumption is not precisely measured.

This paper employs a synthetic cohort technique and Consumer Expenditure Survey data to construct average age-profiles of consumption and income over the working lives of typical households across different education and occupation groups. Using these profiles, we estimate a structural model of optimal life-cycle consumption expenditures in the presence of realistic labor income uncertainty. The model fits the profiles quite well. In addition to providing tight estimates of the discount rate and risk aversion, we find that consumer behavior changes strikingly over the life-cycle. Young consumers behave as buffer-stock agents. Around age 40, the typical household starts accumulating liquid assets for retirement, and its behavior mimics more closely that of a certainty equivalent consumer. This change in behavior is mostly driven by the life-cycle profile of expected income. Our methodology provides a natural decomposition of saving into its precautionary and retirement components.

The key implication of rational expectations and the basic life-cycle/permanent-income hypothesis: that predictable changes in income have no effect on the growth rate of consumption expenditures, is examined. This implication is important for understanding the effectiveness and optimal timing of fiscal policy, the causes and propagation of business cycles, and the effects of income fluctuations on the growth rate of the economy. Using household-level consumption data from the Consumer Expenditure Survey, whether expenditures on nondurable goods increase contemporaneously with predictable changes in Social Security tax withholding is tested. It is found that households do change their consumption expenditures in response to the predictable fluctuations in income induced by the Social Security tax system.

We explore household consumption surrounding federal tax returns filings and refunds receipt to test various theories of consumption. Because uncertainty regarding the refund is resolved at filing, precautionary savings theory predicts an increase in consumption at this date. Contrary to this prediction, we find that households generally do not increase consumption at filing. Following the receipt of the refunds, consumption of both durables and nondurables increases dramatically and then decays quickly. Our results show that households, on average, are financially constrained, exhibit myopic behavior, and do not respond to precautionary savings motives.

The consumption of high-consumption households is more exposed to fluctuations in aggregate consumption and income than that of low-consumption households in the Consumer Expenditure (CEX) Survey. The exposure to aggregate consumption growth of households in the top 10 percent of the consumption distribution in the CEX is about five times that of households in the bottom 80 percent. Given real aggregate per capita consumption growth about 3 percentage points less than its historical mean during the past year, these figures predict that the ratio of consumption of the top 10 percent to the bottom 80 percent has fallen by about 15 percentage points (relative to trend). Using income data from Piketty and Saez (2003), we show that the income (especially the wage income) of rich households is more exposed to aggregate fluctuations, so their higher income exposure is a likely contributor to their higher consumption exposure. Finally, we find a striking change in the exposure of the incomes of high-income households: prior to the early 1980's, the incomes of high-income households were not more exposed to aggregate fluctuations. Thus, while high-income households currently bear an inordinately large share of aggregate fluctuations, this is a recent occurrence.

Human beings want to believe that good outcomes in the future are more likely, but also want to make good decisions that increase average outcomes in the future. We consider a general equilibrium model with complete markets and show that when investors hold beliefs that optimally balance these two incentives, portfolio holdings and asset prices match six observed patterns: (i) because the cost of biased beliefs are typically second-order, investors typically hold biased assessments of probabilities and so are not perfectly diversified according to objective metrics; (ii) because the costs of biased beliefs temper these biases, the utility costs of the lack of diversification are limited; (iii) because there is a complementarity between believing a state more likely and purchasing more of the asset that pays off in that state, investors over-invest in only one Arrow-Debreu security and smooth their consumption well across the remaining states; (iv) because different households can settle on different states to be optimistic about, optimal portfolios of ex ante identical investors can be heterogeneous; (v) because low-price and low-probability states are the cheapest states to buy consumption in, overoptimism about these states distorts consumption the least in the rest of the states, so that investors tend to overinvest in the most skewed securities; (vi) finally, because investors with optimal expectations have higher demand for more skewed assets, ceteris paribus, more skewed asset can have lower average returns.

This paper evaluates the central insight of the consumption capital asset pricing model that an asset’s expected return is determined by its equilibrium risk to consumption. Rather than measure risk by the contemporaneous covariance of an asset’s return and consumption growth, we measure risk by the covariance of an asset’s return and consumption growth cumulated over many quarters following the return. While contemporaneous consumption risk explains little of the variation in average returns across the 25 Fama‐French portfolios, our measure of ultimate consumption risk at a horizon of three years explains a large fraction of this variation.

Under the Economic Growth and Tax Relief Reconciliation Act of 2001, most U.S. taxpayers received a tax rebate between July and September, 2001. The week in which the rebate was mailed was based on the second-to-last digit of the taxpayer's Social Security number, a digit that is effectively randomly assigned. Using special questions about the rebates added to the Consumer Expenditure Survey, we exploit this historically unique experiment to measure the change in consumption expenditures caused by receipt of the rebate and to test the Permanent Income Hypothesis and related models. We find that households spent about 20-40 percent of their rebates on non-durable goods during the three-month period in which their rebates were received, and roughly another third of their rebates during the subsequent three-month period. The implied effects on aggregate consumption demand are significant. The estimated responses are largest for households with relatively low liquid wealth and low income, consistent with liquidity constraints.

This paper evaluates the central insight of the Consumption Capital Asset Pricing Model (CCAPM) that an asset's expected return is determined by its equilibrium risk to consumption. Rather than measure the risk of a portfolio by the contemporaneous covariance of its return and consumption growth - as done in the previous literature on the CCAPM and the pattern of crosssectional returns - we measure the risk of a portfolio by its ultimate consumption risk defined as the covariance of its return and consumption growth over the quarter of the return and many following quarters. While contemporaneous consumption risk explains little of the variation in observed average returns across the Fama and French 25 portfolios, ultimate consumption risk at a horizon of three years explains a large fraction of this variation.

This paper uses the consumption Euler equation to derive a decomposition of consumption growth into four sources. These are new information and three sources of predictable consumption growth: intertemporal substitution, changes in the preferences for consumption, and incomplete markets for consumption insurance. Using data on the expenditures of households, we implement the decomposition for the average growth rate of consumption expenditures on nondurable goods in the U.S. from the beginning of 1982 to the end of 1997. Incomplete markets for trading consumption in future states lead to statistically significant and countercyclical movements in expected consumption growth: consumption growth is expected to be higher when the unemployment rate is high. The economic importance of precautionary saving rivals that of the real interest rate, but the relative importance of each source of movement in the volatility of consumption is not precisely measured.

This paper evaluates the central insight of the Consumption Capital Asset Pricing Model (C-CAPM) that an asset's expected return is determined by its equilibrium risk to consumption. Rather that measure the risk of a portfolio by the contemporaneous covariance of its return and consumption growth -- as done in the previous literature on the C-CAPM and the pattern of cross-sectional returns -- we measure the risk of a portfolio by its ultimate consumption risk defined as the covariance of its return and consumption growth over the quarter of the return and many following quarters. While contemporaneous consumption risk has little predictive power for explaining the pattern of average returns across the Fama and French (25) portfolios, ultimate consumption risk is highly statistically significant in explaining average returns and explains a large fraction of the variation in average returns. Aditionally, estimates of the average risk-free real rate of interest and the coefficient of relative risk aversion of the representative household based on ultimate consumption risk are more reasonable than those obtained using contemporaneous consumption risk.

This paper evaluates the equity premium using novel data on the consumption of luxury goods. Specifying utility as a nonhomothetic function of both luxury and basic consumption goods, we derive pricing equations and evaluate the risk of holding equity. Household survey and national accounts data mostly reflect basic consumption and therefore overstate the risk aversion necessary to match the observed equity premium. The risk aversion implied by the consumption of luxury goods is more than an order of magnitude less than that implied by national accounts data. For the very rich, the equity premium is much less of a puzzle.

This paper evaluates the equity premium using novel data on the consumption of luxury goods. Specifying utility as a nonhomothetic function of both luxury and basic consumption goods, we derive pricing equations and evaluate the risk of holding equity. Household survey and national accounts data mostly reflect basic consumption, and therefore overstate the risk aversion necessary to match the observed equity premium. The risk aversion implied by the consumption of luxury goods is more than an order of magnitude less than that implied by national accounts data. For the very rich, the equity premium is much less of a puzzle. AS DEMONSTRATED BY GROSSMAN AND SHILLER (1981), SHILLER (1982), Mehra and Prescott (1985), and the extensive literature that follows, the risk of the stock market as measured by its co-movement with aggregate consumption is insufficient to justify the extent to which its average return exceeds the return on short-term government debt. We propose a partial resolution to this equity premium puzzle by distinguishing between the consumption of basic goods and that of luxury goods. Intuitively, rich households that hold most equity are almost satiated in their consumption of basic goods; wealth shocks are reflected in the consumption of luxury goods, which is much more responsive to stock returns than the consumption of basic goods. Specifically, we model utility as a function of the consumption of both a basic good, of which a certain amount is required in every period, and a luxury good, which has low marginal utility even at low consumption levels. With such preferences, households consume only basic goods at low levels of total expenditures, while the share of luxury goods in overall consumption rises with expenditures. Households display a high degree of risk aversion with respect to their consumption of basic goods, consistent with the subsistence aspect of

One of the basic motives for saving is the accumulation of wealth to insure future welfare. Both introspection and extant research on consumption insurance find that people face substantial risks that they do not fairly pool. In theory, the consumption and wealth accumulation of price-taking households in an economy with incomplete markets differs substantially from the behavior of these same households in the equivalent economy with complete-markets. The question we address in this article is whether we find this difference to be large in practice. What is the empirical importance of precautionary saving? We provide a simple decomposition that characterizes the importance of precautionary saving in the U.S. economy. We use this decomposition as an organizing framework to present four main findings: (a) the concavity of the consumption policy rule, (b) the importance of precautionary saving for life-cycle saving and wealth accumulation, (c) the contribution of changes in risk to fluctuations in aggregate consumption and (d) the significant impact of incomplete markets on aggregate fluctuations in calibrated general equilibrium models. We conclude with directions for future research.

During the past two decades, the personal saving rate in the United States has fallen from 8% to below zero, and the share of GDP that households consume rose by 6 percentage points. This increase in the share of consumption was concurrent with a reduction in the growth rate of real consumption spending per person, high real rates of return, and an increasing ratio of aggregate wealth to income. Despite this last fact, wealth changes can explain little of the boom in consumption spending: The largest increases in national wealth postdate the consumption boom, and households with differing wealth levels nevertheless had similar increases in consumption. The changing age distribution of the U.S. population does not explain the consumption boom, either: While it may be that younger, wealthier cohorts are driving this boom, the preponderance of evidence suggests rather that the rising consumption-to-income ratio is due to a common time effect. The main findings of the paper are consistent with either an incre...