Economic analysis of effective policies for managing epidemics requires an integrated economic and epidemiological approach. We develop and estimate a spatial, micro-founded model of the joint evolution of economic variables and the spread of an epidemic. We empirically discipline the model using new U.S. county-level data on health, mobility, employment outcomes, and non-pharmaceutical interventions (NPIs) at a daily frequency. Absent policy or medical interventions, the model predicts an initial period of exponential growth in new cases, followed by a protracted period of roughly constant case levels and reduced economic activity. Nevertheless, if vaccine development proved impossible, and suppression cannot entirely eradicate the disease, a utilitarian policymaker cannot improve significantly over the laissez-faire equilibrium by using lockdowns. Conversely, if a vaccine will arrive within two years, NPIs can improve upon the laissez-faire outcome by dramatically decreasing the number of infectious agents and keeping infections low until vaccine arrival. Mitigation measures that reduce viral transmission (e.g., mask-wearing) both reduce the virus's spread and increase economic activity.
We propose a new method for computing equilibria in heterogeneous-agent models with aggregate uncertainty. The idea relies on an assumption that linearization offers a good approximation; we share this assumption with existing linearization methods. However, unlike those methods, the approach here does not rely on direct derivation of first-order Taylor terms. It also does not use recursive methods, whereby aggregates and prices would be expressed as linear functions of the state, usually a very high-dimensional object (such as the wealth distribution). Rather, we rely merely on solving nonlinearly for a deterministic transition path: we study the equilibrium response to a single, small “MIT shock” carefully. We then regard this impulse response path as a numerical derivative in sequence space and hence provide our linearized solution directly using this path. The method can easily be extended to the case of many shocks and computation time rises linearly in the number of shocks. We also propose a set of checks on whether linearization is a good approximation. We assert that our method is the simplest and most transparent linearization technique among currently known methods. The key numerical tool required to implement it is value-function iteration, using a very limited set of state variables.
We document systematic differences in macroeconomic expectations across U.S. households and rationalize our findings with a theory of information choice. We embed this theory into an incomplete-markets model with aggregate risk. Our model is quantitatively consistent with the pattern of expectation heterogeneity in the data. Relative to a full-information counterpart, our model implies substantially increased macroeconomic volatility and inequality. We show through the example of a wealth tax that neglecting the information channel leads to erroneous conclusions about the effects of policies. While in the model without information choice a wealth tax reduces wealth inequality, in our framework it reduces information acquired in the economy, leading to increased volatility and higher wealth inequality in equilibrium.
Solutions to macroeconomic models with wealth inequality and aggregate shocks often rely on theassumption of limited but common information among households. We show that this assumptionis inconsistent with rational information choice for plausible information costs. To do so, we embedinformation choice into the workhorse heterogeneous-agent model with aggregate risk (Krusell andSmith, 1998). First, we demonstrate that the benefits of acquiring more precise information aboutthe state of the economy depend crucially on household wealth. Second, we show that suchheterogeneous incentives to acquire information combine with the strategic substitutability ofsavings choices to imply that equilibria in which households acquire the same information do notexist for plausible information costs. Finally, we document that a representative-agent equilibriummay not exist even in the absence of exogenous sources of wealth heterogeneity.
We study the role of heterogeneity in the transmission of foreign shocks. We build a Heterogeneous-Agent New-Keynesian Small Open Model Economy (HANKSOME) that experiences a current account reversal. Households' portfolio composition and the extent of foreign currency borrowing are key determinants of the magnitude of the contraction in consumption associated with a sudden stop in capital inflows. The contraction is more severe when households are leveraged and owe debt in foreign currency. In this setting, the revaluation of foreign debt causes a larger contraction in aggregate consumption when debt and leverage are concentrated among poorer households. Closing the output gap via an exchange-rate devaluation may therefore be detrimental to household welfare due to the heterogeneous impact of the foreign debt revaluation. Our HANKSOME framework can rationalize the observed fear of floating in emerging market economies, even in the absence of contractionary devaluations.
Capital flows from equal to unequal countries. We document this empirical regularityin a large sample of advanced economies. The capital flows are largely driven by privatesavings. We propose a theory that can rationalize these findings: more unequal countriesendogenously develop deeper financial markets. Households in unequal counties, in turn,borrow more, driving the observed direction of capital flows.
We assess the power of forward guidance promises about future interest rates as a monetary tool in a liquidity trap using a quantitative incomplete-markets model. Our results suggest the effects of forward guidance are negligible. A commitment to keep future nominal interest rates low for a few quarters although macro indicators suggest otherwise has only trivial effects on current output and employment. We explain theoretically why in complete markets models forward guidance is powerful generating a forward guidance puzzle and why this puzzle disappears in our model. We also clarify theoretically ambiguous conclusions from previous research about the effectiveness of forward guidance in incomplete and complete markets models.
We measure the effect of unemployment benefit duration on employment. We exploit the variation induced by the decision of Congress in December 2013 not to reauthorize the unprecedented benefit extensions introduced during the Great Recession. Federal benefit extensions that ranged from 0 to 47 weeks across U.S. states at the beginning of December 2013 were abruptly cut to zero. To achieve identification we use the fact that this policy change was exogenous to cross-sectional differences across U.S. states and we exploit a policy discontinuity at state borders. We find that a 1% drop in benefit duration leads to a statistically significant increase of employment by 0.0161 log points. In levels, 1.8 million additional jobs were created in 2014 due to the benefit cut. Almost 1 million of these jobs were filled by workers from out of the labor force who would not have participated in the labor market had benefit extensions been reauthorized.
In an influential paper, Mian, Rao, and Sufi (2013) exploit geographic variation to measure the effect of the fall inhousing net worth on household expenditures during the Great Recession. Their widely-cited estimates arebased on proprietary house price and proprietary expenditure data and therefore not easily replicable. We usealternative data on a subset of non-durable goods and on house prices, which are more easily accessible, to replicate their study. When estimating their same specification on our data, we obtain values for the elasticity of expenditures to the housing net worth shock that are virtually indistinguishable from theirs. However, ourrobustness analyses with respect to alternative model specifications yield more nuanced conclusions about theseparate roles of house prices and initial housing exposure/leverage for the drop in expenditures. Moreover,the estimated elasticity is consistent, theoretically and quantitatively, with a simple calibrated model with wealtheffects where leverage and credit constraints play no role.
We build a model of the US economy with multiple aggregate shocks that generate fluctuations in equilibrium house prices. Through counterfactual experiments, we study the housing boom-bust around the Great Recession, with three main results. First, the main driver of movements in house prices and rents was a shift in beliefs, not a change in credit conditions. Second, the boom-bust in house prices explains half of the corresponding swings in nondurable expenditures through a wealth effect. Third, a large-scale debt forgiveness program would have done little to temper the collapse of house prices and expenditures but would have dramatically reduced foreclosures and induced a small, but persistent, increase in consumption during the recovery.
I study the implications of two major debt-relief policies in the United States: the Bankruptcy Abuse Prevention and Consumer Protection Act (BAPCPA) and the Home Affordable Refinance Program (HARP). To do so, I develop a model of housing and default that includes relevant dimensions of credit-market policy and captures rich heterogeneity in household balance sheets. The model also explains the observed cross-state variation in consumer default rates. I find that BAPCPA significantly reduced bankruptcy rates, but increased foreclosure rates when house prices fell. HARP reduced foreclosures by 1 percentage point and provided substantial welfare gains to households with high loan-to-value mortgages.
How should unemployment benefits vary in response to the economic crisis induced by the COVID-19 pandemic? We answer this question by computing the optimal unem- ployment insurance response to the COVID-induced recession. We compare the optimal policy to the provisions under the CARES Act-which substantially expanded unemployment insurance and sparked an ongoing debate over further increases-and several alternative scenarios. We find that it is optimal first to raise unemployment benefits but then to begin lowering them as the economy starts to reopen - despite unemployment remaining high. We also find that the $600 UI supplement payment implemented under CARES was close to the optimal policy. Extending this UI supplement for another six months would hamper the recovery and reduce welfare. On the other hand, a UI extension combined with a re-employment bonus would further increase welfare compared to CARES alone, with only minimal effects on unemployment.
The optimal cyclical behavior of unemployment insurance is characterized in an equilibrium search model with risk-averse workers. Contrary to the current US policy, the path of optimal unemployment benefits is pro-cyclical - positively correlated with productivity and employment. Furthermore, optimal unemployment benefits react non-monotonically to a productivity shock: in response to a fall in productivity, they rise on impact but then fall significantly below their pre-recession level during the recovery. As compared to the current US unemployment insurance policy, the optimal state-contingent unemployment benefits smooth cyclical fluctuations in unemployment and deliver substantial welfare gains.
We investigate the optimal response of unemployment insurance to economic shocks, both with and without commitment. The optimal policy with commitment follows a modified Baily-Chetty formula that accounts for job search responses to future UI benefit changes. As a result, the optimal policy with commitment tends to front-load UI, unlike the optimal discretionary policy. In response to shocks intended to mimic those that induced the COVID-19 recession, we find that a large and transitory increase in UI is optimal; and that a policy rule contingent on the change in unemployment, rather than its level, is a good approximation to the optimal policy.