Session 19: Macroeconomics in the Sequence Space

We survey 6,000 U.S. individuals and find that most do not account for the future tax implications of government transfers in their spending plans. To explain this behavior, we develop a theory of bounded rationality in which consumers have limited foresight about future taxes and embed this theory into a Heterogeneous-Agent New Keynesian (HANK) model. We calibrate the model using data from our survey. Our quantitative results indicate that this form of bounded rationality substantially amplifies the effects of fiscal transfers and government spending on output, relative to a model in which individuals have full information and rational expectations.

As the economy emerges from a crisis, macroeconomic policy confronts a dilemma: a protracted stimulus can foster a more inclusive labor market recovery, yet risks igniting inflation that ultimately undermines workers’ welfare. This tension amplifies in the presence of the ZLB and aggregate capacity constraints. We develop a quantitative model to examine how U.S. monetary and fiscal policies managed this trade-off in the wake of the pandemic, and use the model to contrast observed outcomes with those under counterfactual policy scenarios. Our experiments highlight four main findings. First, navigating this trade-off was especially challenging in this episode, because policy was squeezed between these two constraints. Second, inflationary pressures in the recovery stemmed from the joint deployment of monetary and fiscal stimulus; each policy in isolation would have generated milder price dynamics. Third, the Federal Reserve’s new framework was successful in delivering a more inclusive labor market recovery compared to the previous regime, even accounting for the higher inflation it fueled. Fourth, while additional fiscal support boosted short-run employment, it dampened real wages (via inflation) and participation (via wealth effects) later on — suggesting that the monetary response alone, without any further fiscal intervention after 2020, could have achieved a more balanced medium-run outcome.

This paper studies monetary and fiscal policy transmission in a multi-sector heterogeneous-agent NewKeynesian model with an input-output network (“HANK-IO”). We document systematic household-sector linkages in micro data and calibrate our model to match them. To identify when these linkages have implications for policy transmission, we analytically characterize an as-if benchmark that features a strict decoupling between household and sectoral heterogeneity. Away from this benchmark, novel earnings and expenditure heterogeneity channels emerge that govern the propagation of demand and supply shocks. We develop a new decomposition that allows us to isolate and compute the contributions of distinct dimensions of heterogeneity to overall policy transmission. The contribution of earnings and expenditure heterogeneity channels in the transmission to aggregates is small, confirming the quantitative relevance of our as-if benchmark. In the cross section, we characterize the distributional consequences of monetary and fiscal policy across households and sectors.

We study the aggregate and distributional effects of monetary policy in a heterogeneous agent New Keynesian model that explicitly represents the life cycle of households. The model matches the age patterns in the level and dispersion of labor income and financial wealth in the U.S. despite the absence of preference heterogeneity and portfolio adjustment costs. Monetary policy affects the consumption of young households mainly through labor income and the consumption of old households mainly through asset returns. More than half of the aggregate consumption response to an expansionary monetary policy shock comes from those below the age of 40. The shock redistributes welfare from the wealthiest old to the poorest young and increases average welfare of most cohorts.

We develop a heterogeneous agent New Keynesian model featuring a frictional labor market with on-the-job search to quantitatively study the positive and normative implications of employer-to-employer (EE) transitions for macroeconomic outcomes and monetary policy. We find that EE dynamics played an important role in shaping inflation dynamics during the Great Recession and COVID-19 recoveries, with the former exhibiting subdued EE transitions and inflation despite both episodes sharing similar unemployment dynamics. Optimal monetary policy prescribes a strong positive response to EE fluctuations, which implies that central banks should distinguish between episodes with similar unemployment but different EE dynamics. We also show that accounting for market incompleteness significantly alters macroeconomic outcomes and optimal monetary policy prescriptions in response to changes in EE transitions.

How do long-term relationships between banks and firms shape loan pricing and capital allocation? Using administrative data from Mexico’s credit registry, I provide stark evidence for an insurance view of relationship lending. When firms repeatedly borrow from the same bank, the pass-through of changes in their default risk to loan rates is nearly zero, and past risk assessments persistently influence credit terms. In contrast, switching to a new bank results in full risk pass-through, consistent with competitive market predictions. I rationalize this evidence in a structural model where banks compete for borrowers by offering optimal long-term contracts. Switching costs sustain commitment to banking relationships, enabling insurance. The estimated model replicates the observed pricing patterns and generates new predictions, which I validate in the data, regarding when firms receive cheap funding and when they are tempted to switch. At the macro level, switching costs enhance capital allocation by strengthen- ing relationships, recovering over 10 percent of welfare losses from financial frictions. However, when embedded in a New Keynesian framework, relationships dampen monetary and fiscal policy pass-through, as banks optimally absorb part of these policy shocks.

Westudy the optimal allocation of population and consumption in a dynamic spatial general equilibrium model with frictional migration, where households’ idiosyncratic location preference shocks are private information. We derive a recursive formula for the constrainedefficient allocation, capturing the trade-off between consumption smoothing and efficient migration. In a quantitative model calibrated to the US economy featuring both cross-state migration and risk-free savings, we find that the constrained-efficient allocation features lower population but higher average consumption in less productive states than the status quo, achieving efficiency and spatial redistribution simultaneously through dynamic incentives. In response to local negative productivity shocks, the constrained-efficient allocation features more front-loaded consumption profiles than the status quo, with systematic heterogeneity linked to the location’s pre-shock fundamentals.

We characterize optimal monetary policy under state-dependent pricing. The framework gives rise to nonlinear inflation dynamics: The flexibility of the price level increases after large shocks due to an endogenous rise in the frequency of price changes. In response to large cost-push shocks, optimal policy leverages the lower sacrifice ratio to curb inflation. When faced with total factor productivity shocks, an efficient disturbance, the optimal policy commits to strict price stability. The optimal long-run inflation rate is just above zero.

We study the optimal allocation of population and consumption in a dynamic spatial general equilibrium model with frictional migration, where households’ idiosyncratic location preference shocks are private information. We derive a recursive formula for the constrained efficient allocation, capturing the trade-off between consumption smoothing and efficient migration. In a quantitative model calibrated to the US economy featuring both cross-state migration and risk-free savings, we find that the constrained-efficient allocation features lower population but higher average consumption in less productive states than the status quo, achieving efficiency and spatial redistribution simultaneously through dynamic incentives. In response to local negative productivity shocks, the constrained-efficient allocation features more front-loaded consumption profiles than the status quo, with systematic heterogeneity linked to the location’s pre-shock fundamentals.

The classic tariff formula states that the optimal unilateral tariff equals the inverse of the foreign export supply elasticity. We generalize this result and show that an intertemporal tariff formula characterizes the efficient tariff in a large class of dynamic heterogeneous agent (HA) economies with multiple goods. Intertemporal export supply elasticities and relative tariff revenue weights are sufficient statistics for the optimal tariff that decentralizes the efficient allocation. We also develop a general theory of second-best optimal tariffs. In dynamic HA incomplete markets economies, Ramsey optimal tariffs trade off intertemporal terms of trade manipulation against production efficiency, risk-sharing, and redistribution. Intertemporal export supply elasticities and relative tariff revenue weights remain sufficient statistics for the intertemporal terms of trade manipulation motive of second-best optimal tariffs. We apply our results to a quantitative heterogeneous agent New Keynesian (HANK) model with trade.

Given a loss function and a set of policy objectives, how should we evaluate and compare the performances of policy institutions? In this work, we show that it is possible to evaluate policy makers with minimal assumptions on the underlying economic model. The Distance to Minimum Loss —the component of the loss that a policy institution can be held accountable for—, can be computed from well known and estimable suff icient statistics: the impulse responses to policy and non-policy shocks. We use our methodology to evaluate US monetary policy since 1879. We find no material improvement in performance over the first 100 years, and it is only in the last 30 years that we estimate large and uniform improvements in the conduct of monetary policy.

This paper develops a unified framework for globally solving dynamic stochastic general equilibrium models with high accuracy and computational efficiency in sequence space. The method efficiently handles rich heterogeneity, nonlinearities such as occasionally binding constraints, and non-trivial market clearing conditions — without assuming perfect foresight. Building on this, I introduce the generalized transition function (GTF), defined as a sub-path of the recursive competitive equilibrium. The GTF nests generalized impulse responses and stochastic growth paths, enabling global analysis of state-dependent dynamics and the interaction between growth and uncertainty. Applications to heterogeneous-agent models with occasionally binding constraints and portfolio choice reveal rich equilibrium predictions driven by the cross-sectional heterogeneity — including uncertainty-driven dampened growth, endogenous disasters, state-dependent fiscal multipliers, heterogeneous portfolio adjustments over the business cycle, and state-dependent risk premium dynamics.