The idea that the happiness of an individual depends upon the consumption of others is widely viewed as an important feature of our shared social existence. Recent research in finance has used this idea, through consumption externalities, to explore asset-pricing anomalies. Consumption externalities potentially break the link between Pareto optimality and competitive equilibria and open the door for beneficial government intervention (e.g., Lars Ljungqvist and Harald Uhlig, 2000). In this paper, we delineate two effects that a consumption externality may have. An increase in aggregate consumption may: (a) raise the marginal utility of individual consumption relative to leisure, and/or (b) lower an individual’s utility level. We refer to (a) as “keeping up with the Joneses” (henceforth, KUJ), following Jordi Gali (1994), and we refer to (b) as jealousy. Jealousy is a distinct concept from KUJ. Under KUJ, an individual derives greater utility from additional own consumption relative to leisure when others consume more. At the same time, higher per capita consumption holding fixed individual consumption can trigger either jealousy, so that individual utility falls, or admiration, so that individual utility rises. In Section I of this paper, we show that jealousy implies that the laissez-faire equilibrium consumption level is greater than the optimal level. Whether preferences exhibit KUJ is not necessary for this main result. Intuitively, in the presence of jealousy, consumption is similar to pollution. Overpollution exists because individuals do not take into account the cost of polluting on others, not because an increase in economywide pollution makes the return to individual polluting higher. Similarly, overconsumption exists because individuals do not take into account the negative effect of own consumption on jealous others. Things go in the opposite direction when individuals are admiring. In Section II, we consider a functional form that encompasses several existing models. We show that jealousy determines the optimal tax to correct overconsumption and that KUJ is mainly important for asset pricing.

We use regional variation in the American Recovery and Reinvestment Act (2009–12) to analyse the effect of government spending on consumer spending. Our consumption data come from household-level retail purchases in the Nielsen scanner data and auto purchases from Equifax credit balances. We estimate that a $1 increase in county-level government spending increases local non-durable consumer spending by $0.29 and local auto spending by $0.09. We translate the regional consumption responses to an aggregate fiscal multiplier using a multi-region, new Keynesian model with heterogeneous agents, incomplete markets, and trade linkages. Our model is consistent with the estimated positive local multiplier, a result that distinguishes our incomplete markets model from models with complete markets. At the zero lower bound, the aggregate consumption multiplier is twice as large as the local multiplier because trade linkages propagate the effect of government spending across regions.

A number of researchers and market observers hold that the dramatic increase during the 1990's and subsequent decline in U.S. stock prices were due to non-fundamental factors, such as irrational expectations or bubbles. If this view is correct, policymakers may be concerned with the real macroeconomic consequences of the stock market run-up. These might include overconsumption due to a perceived wealth effect or too much physical investment due to a lower financing cost of capital. Following this reasoning, the Federal Reserve could raise the Fed Funds target rate to offset perceived non-fundamental stock price increases. This policy stance may seem particularly appealing if the Fed's primary target, low and stable inflation, is already being achieved. This paper studies how Federal Reserve interestrate policy, from 1979:4 onward, responds to an aggregate measure of stock-market activity under high versus low inflation. Most existing research makes no distinction between policy across the highand low-inflation times of the past 24 years. Two conventional findings of this existing research are that the Federal Reserve: (i) raises the short-term real interest rate in response to inflation and (ii) does not change policy in response to equity price movements.1

Understanding the relationship between nominal and real variables, most notably inflation and cyclical output, is one of the fundamental questions of economics. Toward this understanding, we develop a model that integrates sticky prices and sticky information—a dual-stickiness model. We find that both rigidities are present in U.S. data. We also show that the dual-stickiness model's closest competitor is the hybrid New Keynesian model. For both models, current inflation depends in part on last period's inflation. The former model achieves this dependence endogenously through the interaction of the two rigidities rather than through backward-looking behavior. U.S. data support the dual-stickiness model over the hybrid model because lagged expectations terms appear in the former's inflation Euler equation. Finally, we show that it is quantitatively important to distinguish between the two by simulating a dynamic equilibrium model under each of the two inflation equations.

This paper presents a spatial econometric method for characterizing productivity comovement across sectors of the U.S. economy. Input‐output relations provide an economic distance measure that is used to characterize interactions between sectors, as well as conduct estimation and inference. We construct two different economic distance measures. One metric implies that two sectors are close to one another if they use inputs of other industrial sectors in nearly the same proportion, and the other metric implies that sectors are close if their outputs are used by the same sectors. Our model holds that covariance in productivity growth across sectors is a function of economic distance. We find that (1) positive cross‐sector covariance of productivity growth generates a substantial fraction of the variance in aggregate productivity, (2) cross‐sector productivity covariance tends to be greatest between sectors with similar input relations, and (3) there are constant to modest increasing returns to scale. We test and reject the hypothesis that these correlations are due to a common shock.