I develop a highly tractable general equilibrium model in which heterogeneous producers face collateral constraints, and study the effect of financial frictions on capital misallocation and aggregate productivity. My economy is isomorphic to a Solow model but with time-varying TFP. I argue that the persistence of idiosyncratic productivity shocks determines both the size of steady-state productivity losses and the speed of transitions: if shocks are persistent, steady-state losses are small but transitions are slow. Even if financial frictions are unimportant in the long run, they tend to matter in the short run and analyzing steady states only can be misleading. (JEL E21, E22, E23, G32, L26, O16)

We analyze a model economy with many agents, each with a different productivity level. Agents divide their time between two activities: producing goods with the production-related knowledge they already have and interacting with others in search of new, productivity-increasing ideas. These choices jointly determine the economy’s current production level and its rate of learning and real growth. We construct the balanced growth path for this economy. We also study the allocation chosen by an idealized planner who takes into account and internalizes the external benefits of search. Finally, we provide three examples of alternative learning technologies and show that the properties of equilibrium allocations are quite sensitive to two of these variations.

Abstract We study the effect of monetary and fiscal policy in a heterogeneous-agent model where households have present-biased time preferences and naive beliefs. The model features a liquid asset and illiquid home equity, which households can use as collateral for borrowing. Because present bias substantially increases households’ marginal propensity to consume (MPC), present bias increases the effect of fiscal policy. Present bias also amplifies the effect of monetary policy, but at the same time, slows down the speed of monetary transmission. Interest rate cuts incentivize households to conduct cash-out refinances, which become targeted liquidity injections to high-MPC households. Present bias also introduces a motive for households to procrastinate refinancing their mortgages, which slows down the speed with which this monetary channel operates.

The benefits of new technologies accrue not only to high‐skilled labor but also to owners of capital in the form of higher capital incomes. This increases inequality. To make this argument, we develop a tractable theory that links technology to the distribution of income and wealth—and not just that of wages—and use it to study the distributional effects of automation. We isolate a new theoretical mechanism: automation increases inequality by raising returns to wealth. The flip side of such return movements is that automation can lead to stagnant wages and, therefore, stagnant incomes at the bottom of the distribution. We use a multiasset model extension to confront differing empirical trends in returns to productive and safe assets and show that the relevant return measures have increased over time. Automation can account for part of the observed trends in income and wealth inequality.

We revisit the transmission mechanism from monetary policy to household consumption in a Heterogeneous Agent New Keynesian (HANK) model. The model yields empirically realistic distributions of wealth and marginal propensities to consume because of two features: uninsurable income shocks and multiple assets with different degrees of liquidity and different returns. In this environment, the indirect effects of an unexpected cut in interest rates, which operate through a general equilibrium increase in labor demand, far outweigh direct effects such as intertemporal substitution. This finding is in stark contrast to small- and medium-scale Representative Agent New Keynesian (RANK) economies, where the substitution channel drives virtually all of the transmission from interest rates to consumption. Failure of Ricardian equivalence implies that, in HANK models, the fiscal reaction to the monetary expansion is a key determinant of the overall size of the macroeconomic response. (JEL D31, E12, E21, E24, E43, E52, E62)

Is there a role for governments in emerging countries to accelerate economic development by intervening in product and factor markets? To address this question, we study optimal dynamic Ramsey policies in a standard growth model with financial frictions. The optimal policy intervention involves pro-business policies like suppressed wages in early stages of the transition, resulting in higher entrepreneurial profits and faster wealth accumulation. This, in turn, relaxes borrowing constraints in the future, leading to higher labor productivity and wages. In the long run, optimal policy reverses sign and becomes pro-worker. In a multi-sector extension, optimal policy subsidizes sectors with a latent comparative advantage and, under certain circumstances, involves a depreciated real exchange rate. Our results provide an efficiency rationale, but also identify caveats, for many of the development policies actively pursued by dynamic emerging economies.

The past forty years have seen a rapid rise in top income inequality in the United States. While there is a large number of existing theories of the Pareto tail of the long-run income distributions, almost none of these address the fast rise in top inequality observed in the data. We show that standard theories, which build on a random growth mechanism, generate transition dynamics that are too slow relative to those observed in the data. We then suggest two parsimonious deviations from the canonical model that can explain such changes: “scale dependence” that may arise from changes in skill prices, and “type dependence,” that is, the presence of some “high-growth types.” These deviations are consistent with theories in which the increase in top income inequality is driven by the rise of “superstar” entrepreneurs or managers.

Abstract We recast the Aiyagari–Bewley–Huggett model of income and wealth distribution in continuous time. This workhorse model—as well as heterogeneous agent models more generally—then boils down to a system of partial differential equations, a fact we take advantage of to make two types of contributions. First, a number of new theoretical results: (1) an analytic characterization of the consumption and saving behaviour of the poor, particularly their marginal propensities to consume; (2) a closed-form solution for the wealth distribution in a special case with two income types; (3) a proof that there is a unique stationary equilibrium if the intertemporal elasticity of substitution is weakly greater than one. Second, we develop a simple, efficient and portable algorithm for numerically solving for equilibria in a wide class of heterogeneous agent models, including—but not limited to—the Aiyagari–Bewley–Huggett model.

This paper documents how life cycle wage growth varies across countries. We harmonize repeated cross-sectional surveys from a set of countries of all income levels and then measure how wages rise with potential experience. Our main finding is that experience-wage profiles are on average twice as steep in rich countries as in poor countries. In addition, more educated workers have steeper profiles than the less educated; this accounts for around one-third of cross-country differences in aggregate profiles. Our findings are consistent with theories in which workers in poor countries accumulate less human capital or face greater search frictions over the life cycle.

Over the last several decades, there has been a large increase in asset valuations across many asset classes. These rising valuations had important effects on the distribution of wealth. However, little is known regarding their effect on the distribution of welfare. To make progress on this question, we derive a sufficient statistic for the (money metric) welfare effect of a change in asset valuations, which depends on the present value of an individual’s net asset sales: rising asset prices benefit prospective sellers and harm prospective buyers. We estimate this quantity using panel microdata covering the universe of financial transactions in Norway from 1994 to 2019. We find that rising asset valuations had large redistributive effects: they redistributed from the young towards the old and from the poor towards the wealthy