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We extend the canonical epidemiology model to study the interaction between economic decisions and epidemics. Our model implies that people cut back on consumption and work to reduce the chances of being infected. These decisions reduce the severity of the epidemic but exacerbate the size of the associated recession. The competitive equilibrium is not socially optimal because infected people do not fully internalize the effect of their economic decisions on the spread of the virus. In our benchmark model, the best simple containment policy increases the severity of the recession but saves roughly half a million lives in the United States.

We argue that the vast bulk of movements in aggregate real economic activity during the Great Recession were due to financial frictions. We reach this conclusion by looking through the lens of an estimated New Keynesian model in which firms face moderate degrees of price rigidities, no nominal rigidities in wages, and a binding zero lower bound constraint on the nominal interest rate. Our model does a good job of accounting for the joint behavior of labor and goods markets, as well as inflation, during the Great Recession. According to the model the observed fall in total factor productivity and the rise in the cost of working capital played critical roles in accounting for the small drop in inflation that occurred during the Great Recession. (JEL E12, E23, E24, E31, E32, E52)

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

We develop and estimate a general equilibrium search and matching model that accounts for key business cycle properties of macroeconomic aggregates, including labor market variables. In sharp contrast to leading New Keynesian models, we do not impose wage inertia. Instead we derive wage inertia from our specification of how firms and workers negotiate wages. Our model outperforms a variant of the standard New Keynesian Calvo sticky wage model. According to our estimated model, there is a critical interaction between the degree of price stickiness, monetary policy, and the duration of an increase in unemployment benefits.

We argue that the COVID epidemic disproportionately affected the economic well-being and health of poor people. To disentangle the forces that generated this outcome, we construct a model that is consistent with the heterogeneous impact of the COVID recession on low- and high-income people. According to our model, two-thirds of the inequality in COVID deaths reflect preexisting inequality in comorbidity rates and access to quality health care. The remaining third stems from the fact that low-income people work in occupations where the risk of infection is high. Our model also implies that the rise in income inequality generated by the COVID epidemic reflects the nature of the goods that low-income people produce. Finally, we assess the health–income trade-offs associated with fiscal transfers to the poor and mandatory containment policies.

We argue that the government-spending multiplier can be much larger than one when the zero lower bound on the nominal interest rate binds. The larger the fraction of government spending that occurs while the nominal interest rate is zero, the larger the value of the multiplier. After providing intuition for these results, we investigate the size of the multiplier in a dynamic, stochastic, general equilibrium model. In this model the multiplier effect is substantially larger than one when the zero bound binds. Our model is consistent with the behavior of key macro aggregates during the recent financial crisis.

Some booms in housing prices are followed by busts. Others are not. It is generally difficult to find observable fundamentals that are useful for predicting whether a boom will turn into a bust or not. We develop a model consistent with these observations. Agents have heterogeneous expectations about long-run fundamentals but change their views because of “social dynamics.” Agents with tighter priors are more likely to convert others to their beliefs. Boom-bust episodes typically occur when skeptical agents happen to be correct. The booms that are not followed by busts typically occur when optimistic agents happen to be correct.

We study the properties of the carry trade, a currency speculation strategy in which an investor borrows low-interest-rate currencies and lends high-interest-rate currencies. This strategy generates payoffs that are on average large and uncorrelated with traditional risk factors. We argue that these payoffs reflect a peso problem. The underlying peso event features high values of the stochastic discount factor rather than very large negative payoffs.

Standard representative-agent models fail to account for the weak correlation between stock returns and measurable fundamentals, such as consumption and output growth. This failing, which underlies virtually all modern asset pricing puzzles, arises because these models load all uncertainty onto the supply side of the economy. We propose a simple theory of asset pricing in which demand shocks play a central role. These shocks give rise to valuation risk that allows the model to account for key asset pricing moments, such as the equity premium, the bond term premium, and the weak correlation between stock returns and fundamentals.

We assess the importance of nominal rigidities using a new weekly scanner dataset. We find that nominal rigidities take the form of inertia in reference prices and costs, defined as the most common prices and costs within a given quarter. Reference prices are particularly inertial and have an average duration of roughly one year, even though weekly prices change roughly once every two weeks. We document the relation between prices and costs and find sharp evidence of state dependence in prices. We use a simple model to argue that reference prices and costs are useful statistics for macroeconomic analysis.