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Business owners in the United States are disproportionately represented among the wealthy and are exposed to substantial idiosyncratic risk. Further, recent evidence indicates that business income primarily reflects returns to the human capital of the owner. Motivated by these facts, this paper characterizes stationary efficient allocations and optimal linear taxes on income and wealth when business income depends on innate ability, luck, and the past effort of the owner. I first show that in stationary efficient allocations, more productive entrepreneurs typically bear more risk and the distributions of consumption and firm size are approximately Pareto, with the tail of the latter typically thicker than that of the former. I then characterize optimal linear taxes when owners may save in a riskfree bond and trade shares in their businesses. The optimal utilitarian policy calls for separate taxes on firm profits, capital income, and wealth, serving distinct purposes. The tax on profits plays a redistributive role, the tax on capital income affects the incentives to retain equity and exert effort, and the tax on wealth affects the degree of consumption smoothing over time. [ABSTRACT FROM AUTHOR]

An increasing share of corporate loans, a critical source of firm credit, are sold off banks' balance sheets and actively traded in a secondary over-the-counter market. We develop a microfounded equilibrium search-theoretic model with labor, credit, and financial markets to explore how this secondary loan market affects the real economy, highlighting a trade-off: while the market reduces the steady-state level of unemployment by 0.6pp, it amplifies its response to a 1% productivity drop from 3.6% to 4.3%. Secondary market frictions matter significantly: eliminating them would not only reduce unemployment by 1.2pp, but also dampen its volatility down to 2.7%. [ABSTRACT FROM AUTHOR]

Following Manzan (2021), this paper examines how professional forecasters revise their fixed-event uncertainty (variance) forecasts and tests the Bayesian learning prediction that variance forecasts should decrease as the horizon shortens. We show that Manzan’s (2021) use of first moment “efficiency” tests are not applicable to studying revisions of variance forecasts. Instead, we employ monotonicity tests developed by Patton and Timmermann (2012) in the first application of these tests to second moments of survey expectations. We find strong evidence that the variance forecasts are consistent with the Bayesian learning prediction of declining monotonicity. [ABSTRACT FROM AUTHOR]

We use high-frequency interbank payments data to trace deposit flows in March 2023 and identify twenty-two banks that suffered a run, significantly more than the two that failed but fewer than the number that experienced large negative stock returns. The runs were driven by a small number of large depositors and were related to weak fundamentals. However, we find evidence for the importance of coordination because run bankswere disproportionately publicly traded and many banks with similarly bad fundamentals did not suffer a run. Banks survived the run by borrowing new funds and raising deposit rates, not by selling securities. [ABSTRACT FROM AUTHOR]

The article discusses the activities of the Texas-based Globalization and Monetary Policy Institute in 2012. The major activities of the institute include informing Federal Reserve Bank of Dallas president Richard Fisher and other senior bank officials of global economic developments and their impact on U.S. monetary policy. The institute also circulated 134 working papers including "Core Import Price Inflation in the U.S.," and organized two conferences.

The article discusses the rising interest of the banking disintermediation shocks emanating from and propagating through the banking system, in the macroeconomics literature due to fixed deposit rate ceilings. Topics discussed include nonlinear impact on monetary policy on bank level credit growth, identifying credit supply shifts in the empirical literature, and bank capitalization.

This paper studies the impacts of state appropriations on staffing and salaries at public higher education institutions in the United States using employment and revenue data from the Integrated Postsecondary Education Data System, along with an instrumental variables strategy borrowed from Deming and Walters (2018) and Chakrabarti, Gorton, and Lovenheim (2020). The instrument sidesteps the potential endogeneity of state appropriations for a given institution in a given year by interacting an institution's historical reliance on state appropriations with total state appropriations for all higher education institutions in a given year. The results suggest that higher state appropriations are associated with an increase in tenure-track assistant professors at four-year institutions. They are also associated with an increase in part-time instructional staff at both four-year and two-year institutions. However, they are not associated with a change in the number of tenured faculty. Appropriations are also positively related to salaries for a variety of employee groups, although notably not for instructional staff who are instructors, lecturers, or without an academic rank. Overall, the results show that public higher education institutions use state appropriations in a variety of ways, but I do not find evidence that they replace contingent faculty with tenured or tenure-track faculty when appropriations rise. [ABSTRACT FROM AUTHOR]

It is common in applied work to estimate responses of macroeconomic aggregates to news shocks derived from surprise changes in daily futures prices around the date of policy announcements. This requires mapping the daily surprises into a monthly shock that may be used as an external instrument in a monthly VAR model or local projection. The standard approach has been to sum these daily surprises over the course of a given month when constructing the monthly proxy variable, ignoring the accounting relationship between daily and average monthly price data. In this paper, I provide a new approach to constructing monthly proxies from daily surprises that takes account of this link and revisit the question of how to use OPEC announcements to identify news shocks in VAR models of the global oil market. The proposed approach calls into question the interpretation of the identified shock as oil supply news and implies quantitatively and qualitatively different estimates of the macroeconomic impact of OPEC announcements. [ABSTRACT FROM AUTHOR]

In this paper we study neural networks and their approximating power in panel data models. We provide asymptotic guarantees on deep feed-forward neural network estimation of the conditional mean, building on the work of Farrell et al. (2021), and explore latent patterns in the cross-section. We use the proposed estimators to forecast the progression of new COVID-19 cases across the G7 countries during the pandemic. We find significant forecasting gains over both linear panel and nonlinear time-series models. Containment or lockdown policies, as instigated at the national level by governments, are found to have out-of-sample predictive power for new COVID-19 cases. We illustrate how the use of partial derivatives can help open the "black box" of neural networks and facilitate semi-structural analysis: school and workplace closures are found to have been effective policies at restricting the progression of the pandemic across the G7 countries. But our methods illustrate significant heterogeneity and time variation in the effectiveness of specific containment policies. [ABSTRACT FROM AUTHOR]

The past 15 years have been eventful. The Global Financial Crisis (GFC) reminded us of the importance of a stable financial system to a well-functioning economy, one with low and stable inflation and maximum employment. Given the recent banking stress, we ponder this issue again. The pandemic was a huge shock surrounded by much uncertainty, making precise forecasts within traditional models difficult. And more recently, there has been continuous talk of a soft landing and recession risks. In this paper, I focus on some of the lessons we have learned over the years: (i) uncertainty and tail risk have cyclical variation; (ii) financial shocks can have a significant effect on macroeconomic outcomes; (iii) the impact of shocks is stronger in periods of high volatility. These lessons have important implications for policymakers in today's environment. [ABSTRACT FROM AUTHOR]

This paper outlines the dynamic stochastic general equilibrium (DSGE) model developed at the Federal Reserve Bank of Cleveland as part of the suite of models used for forecasting and policy analysis by Cleveland Fed researchers, which we have nicknamed Clementine (CLeveland Equilibrium ModEl iNcluding Trend INformation and the Effective lower bound). This document adopts a practitioner’s guide approach, detailing the construction of the model and offering practical guidance on its use as a policy tool designed to support decision-making through forecasting exercises and policy counterfactuals. [ABSTRACT FROM AUTHOR]

This paper examines the forecasting efficacy and implications of the recently popular breakdown of core inflation into three components: goods excluding food and energy, services excluding energy and housing, and housing. A comprehensive historical evaluation of the accuracy of point and density forecasts from a range of models and approaches shows that a BVAR with stochastic volatility in aggregate core inflation, its three components, and wage growth is an effective tool for forecasting inflation’s components as well as aggregate core inflation. Looking ahead, the model’s baseline projection puts core inflation at 2.6 percent in 2026, well below its 2023 level but still elevated relative to the Federal Reserve’s 2 percent objective. The probability that core inflation will return to 2 percent or less is much higher when conditioning on goods or non-housing services inflation slowing to pre-pandemic levels than when conditioning on these components remaining above the same thresholds. Scenario analysis indicates that slower wage growth will likely be associated with reduced inflation in all three components, especially goods and non-housing services, helping to return core inflation to near the 2 percent target by 2026. [ABSTRACT FROM AUTHOR]

This paper provides a narrative analysis of postwar federal appropriations for the research and development (R&D) activities of the Department of Defense, Department of Energy, National Aeronautics and Space Administration, National Institutes of Health, and National Science Foundation--five agencies that consistently account for the vast majority of federal outlays for all types of R&D. We build a novel dataset quantifying the enacted fullyear appropriations for all budgetary accounts funding R&D activities at these five agencies over fiscal years 1947-2019. We use this dataset to isolate a subset of 218 "significant" changes in real appropriations for each agency, and we analyze numerous primary and secondary sources to understand the context and motivation. Based on these sources, we classify each significant change in federal R&D appropriations as either "endogenous" or "exogenous" to short-run macroeconomic developments. The exogenous changes in R&D appropriations are intended as instrumental variables for studying the causal effects of government R&D in appropriately specified empirical models. [ABSTRACT FROM AUTHOR]

After the events in March 2020, it became clear to policymakers that the 2014 reform of the money market funds (MMFs) industry had not successfully addressed all associated stability concerns related to surges in withdrawals. In December 2021, the SEC proposed a new set of rules governing how money market funds can operate. A fundamental problem behind the instability of (some) money market funds is the expectation that backstop liquidity support will be provided by the government in the event of financial distress, along with the government's inability to credibly commit to not provide such support. This expectation dampens funds' incentives to take steps ahead of time to mitigate the risk of sudden withdrawals. The newly proposed reforms aim to address this problem by constraining withdrawals or penalizing them with "swing pricing." We argue that if the commitment problem is the fundamental issue, it would be more useful to reduce expectations of ex post support by requiring MMFs to have contractual commitments in place, ex ante, for liquidity support from private parties. [ABSTRACT FROM AUTHOR]

Interest in regional economic issues coupled with advances in administrative data is driving the creation of new regional economic data. Many of these data series could be useful for nowcasting regional economic activity, but they suffer from a short (albeit constantly expanding) time series which makes incorporating them into nowcasting models problematic. Regional nowcasting is already challenging because the release delay on regional data tends to be greater than that at the national level, and “short” data imply a “ragged edge” at both the beginning and the end of regional data sets, which adds a further complication. In this paper, via an application to the UK, we develop methods to include a wide range of short data into a regional mixed-frequency VAR model. These short data include hitherto unexploited regional VAT turnover data. We address the problem of the ragged edge at both the beginning and end of our sample by estimating regional factors using different missing data algorithms that we then incorporate into our mixed-frequency VAR model. We find that nowcasts of regional output growth are generally improved when we condition them on the factors, but only when the regional nowcasts are produced before the national (UK-wide) output growth data are published. [ABSTRACT FROM AUTHOR]

In this paper, we revisit the scope for macroprudential policy in production economies with pecuniary externalities and collateral constraints. We study competitive equilibria and constrained-efficient equilibria and examine the extent to which the gap between the two depends on the production structure and the policy instruments available to the planner. We argue that macroprudential policy is desirable regardless of whether the competitive equilibrium features more or less borrowing than the constrained-efficient equilibrium. In our quantitative analysis, macroprudential taxes on borrowing turn out to be larger when the government has access to ex-post stabilization policies. [ABSTRACT FROM AUTHOR]

Quantile regression methods are increasingly used to forecast tail risks and uncertainties in macroeconomic outcomes. This paper reconsiders how to construct predictive densities from quantile regressions. We compare a popular two-step approach that fits a specific parametric density to the quantile forecasts with a nonparametric alternative that lets the "data speak." Simulation evidence and an application revisiting GDP growth uncertainties in the US demonstrate the flexibility of the nonparametric approach when constructing density forecasts from both frequentist and Bayesian quantile regressions. They identify its ability to unmask deviations from symmetrical and unimodal densities. The dominant macroeconomic narrative becomes one of the evolution, over the business cycle, of multimodalities rather than asymmetries in the predictive distribution of GDP growth when conditioned on financial conditions. [ABSTRACT FROM AUTHOR]

Recent decades have seen advances in using econometric methods to produce more timely and higher-frequency estimates of economic activity at the national level, enabling better tracking of the economy in real time. These advances have not generally been replicated at the sub-national level, likely because of the empirical challenges that nowcasting at a regional level presents, notably, the short time series of available data, changes in data frequency over time, and the hierarchical structure of the data. This paper develops a mixed-frequency Bayesian VAR model to address common features of the regional nowcasting context, using an application to regional productivity in the UK. We evaluate the contribution that different features of our model provide to the accuracy of point and density nowcasts, in particular the role of hierarchical aggregation constraints. We show that these aggregation constraints, imposed in stochastic form, play a key role in delivering improved regional nowcasts; they prove to be more important than adding region-specific predictors when the equivalent national data are known, but not when this aggregate is unknown. [ABSTRACT FROM AUTHOR]

We study the optimal one-shot tax reform in the standard incomplete markets model where households differ in their wealth, earnings, permanent labor skill, and age. The government can provide transfers by raising tax revenue and has several tax instruments at its disposal: a flat capital income tax, a flat consumption tax, and a non-linear labor income tax. We compute the equilibrium and transitional dynamics for 3888 different tax combinations and find that the optimal fiscal policy funds a transfer that is above 60 percent of GDP through a combination of very high taxes on consumption and capital income. The labor tax schedule has a high average rate and more progressivity than the current US system. We explore the role of transitional dynamics, debt issuance, intergenerational disagreement, and fiscal spending rules in shaping the optimal policy. Policy is broadly similar if it is determined through majority voting rather than by a utilitarian planner. [ABSTRACT FROM AUTHOR]

How does competition affect banks’ adaptation to emergent risks for which there is limited supervisory oversight? The analysis matches detailed supervisory data on home equity lines of credit with high resolution flood projections to identify climate risks. Following Hurricane Harvey, banks updated their internal risk models to better reflect flood risk projections, even in areas unaffected by the disaster. These updates are only detected in banks with exposures to the disaster, indicating heterogeneous bank learning. We use this heterogeneity to identify how bank adaptation is affected by competition. Exposed banks reduce lending to areas with higher flood risks, but only in less competitive markets, suggesting that competition fosters risk-taking over risk mitigation. Additionally, banks are less likely to adapt in markets where competitors are also less likely to do so, suggesting a strategic complementarity in bank adaptation. More broadly, our paper sheds light on the role of competitive forces in how banks manage emerging risks and relevant supervisory challenges. [ABSTRACT FROM AUTHOR]

We study climate policy in an economy with heterogeneous households, two types of goods (clean and dirty), and a climate externality from the dirty good. Using household expenditure and emissions data, we document that low-income households have higher emissions per dollar spent than high-income households, making a carbon tax regressive. We build a model that captures this fact and study climate policies that are neutral with respect to the income distribution. A central feature of these policies is that resource transfers across consumers are ruled out. We show that the constrained optimal carbon tax in a heterogeneous economy is heterogeneous: Higher-income households face a higher rate. Our main result shows that when the planner is limited to a uniform carbon tax, the tax follows the Pigouvian rule but is lower than the unconstrained carbon tax. Finally, we embed this model into a standard incomplete markets framework to quantify the policy effects on the economy, climate, and welfare, and we find a Pareto-improving result. The climate policy is welfare-improving for every consumer. [ABSTRACT FROM AUTHOR]

A significant share of commercial real estate (CRE) investment properties--about half by our estimates--are purchased without a mortgage. Using comprehensive microdata on transactions in the US CRE market, we analyze which types of properties are purchased without a mortgage, highlighting the important role of renovation or redevelopment options. We show that mortgage-financed properties are less likely to be subsequently redeveloped, and that owners anticipate these redevelopment frictions and avoid mortgage financing for properties with greater redevelopment options. These effects were even stronger during the COVID-19 pandemic, when uncertainty increased redevelopment option values. [ABSTRACT FROM AUTHOR]

Repeatedly solving the Aiyagari (1994) model with random parameters, we construct hundreds of examples with multiple stationary equilibria. We never find multiplicity with risk aversion less than ≈ 1.49, depreciation less than ≈ 0.19, or income persistence less than ≈ 0.47, and multiplicity requires a disaster state for income. In cases with multiplicity, the lowest rental rate occurs near depreciation times the capital share. It is possible for the economy, without a change in fundamentals, to transition rationally from a higher-rate equilibrium to one with a lower rental rate, lower inequality, and lower welfare (for most agents). We also construct the first Krusell and Smith (1998) examples with multiple recursive competitive equilibria. [ABSTRACT FROM AUTHOR]

We show that inflation expectations are heterogeneous and depend on past individual experiences. We propose a diagnostic expectations-augmented Kalman filter to represent consumers' heterogeneous inflation expectations-formation process, where heterogeneity comes from an anchoring-to-the-past mechanism. We estimate the diagnosticity parameter that governs the inflation expectations-formation process and show that the model can replicate systematic differences in inflation expectations across cohorts in the US. We introduce this mechanism into a New Keynesian model and find that heterogeneous expectations anchor aggregate responses to the agents' memory, making shocks more persistent. Central banks should be more active to prevent agents from remembering current shocks far into the future. [ABSTRACT FROM AUTHOR]

This paper offers a solution to the international co-movement puzzle found in open-economy macroeconomic models. We develop a small open-economy (SOE) dynamic stochastic general equilibrium (DSGE) model describing three endogenous channels that capture spillovers from the world to a commodity exporter: a world commodity price channel, a domestic commodity supply channel, and a financial channel. We estimate our model with Bayesian methods on two commodity-exporting SOEs, namely Canada and South Africa. In addition to explaining international business cycle synchronization, the new model attributes an important fraction of business cycle fluctuations to foreign shocks in the SOEs. [ABSTRACT FROM AUTHOR]

The paper considers a New Keynesian framework in which agents form expectations based on a combination of mis-specified forecasts and myopia. The proposed expectations formation process is found to be consistent with all three empirical facts on consensus inflation forecasts, namely, that forecasters under-react to ex-ante forecast revisions, that forecasters over-react to recent events, and that the response of forecast errors to a shock initially under-shoots but then over-shoots. The paper then derives the general equilibrium solution consistent with the proposed expectations formation process and estimates the model with likelihood-based Bayesian methods, yielding three novel results: (i) The data strongly prefer the combination of autoregressive mis-specified forecasting rules and myopia over other alternatives; (ii) The best fitting expectations formation process for both households and firms is characterized by high degrees of myopia and simple AR(1) forecasting rules; (iii) Frictions such as habit in consumption, which are typically necessary for models with Full-information Rational Expectations, are significantly less important, because the proposed expectations generate substantial internal persistence and amplification to exogenous shocks. Simulated inflation expectations data from the estimated general equilibrium model reflect the three empirical facts on forecasting data. [ABSTRACT FROM AUTHOR]

Bayesian predictive synthesis (BPS) provides a method for combining multiple predictive distributions based on agent/expert opinion analysis theory and encompasses a range of existing density forecast pooling methods. The key ingredient in BPS is a "synthesis" function. This is typically specified parametrically as a dynamic linear regression. In this paper, we develop a nonparametric treatment of the synthesis function using regression trees. We show the advantages of our tree-based approach in two macroeconomic forecasting applications. The first uses density forecasts for GDP growth from the euro area's Survey of Professional Forecasters. The second combines density forecasts of US inflation produced by many regression models involving different predictors. Both applications demonstrate the benefits - in terms of improved forecast accuracy and interpretability - of modeling the synthesis function nonparametrically. [ABSTRACT FROM AUTHOR]

Congressional districts are political entities with heterogeneous trade policy preferences due to their diverse economic structures. Representation of these interests in Congress is a crucial aspect of trade policymaking that is missing in canonical political economy models of trade. In this paper, we underscore the influence of districts by developing a political economy model of trade with region-specific factors. Using 2002 data from U.S. Congressional Districts, we first characterize the unobserved district-level demand for protection. Extending the model beyond the small country assumption to account for export interests as a force countering protection, we develop a model of national tariff-setting. The model predictions are used to estimate the welfare weights implied by tariff and non-tariff measures enacted nationally. Our supply-side explanation for trade policy, while complementing Grossman and Helpman (1994), reveals district and industry-level patterns of winners and losers, central to understanding the political consequences of trade and the backlash against globalization. [ABSTRACT FROM AUTHOR]

Unemployment insurance (UI) acts both as a disincentive for labor supply and as a demand stimulus which may explain why empirical studies often find limited effects of UI on employment. This paper provides independent estimates of the disincentive effects arising from the largest expansion of UI in U.S. history, the pandemic unemployment benefits. Using high-frequency data on small restaurants and retailers from Homebase, we control for local demand effects by comparing neighboring businesses that largely share the positive impact of UI stimulus. We find that employment in low-wage businesses recovered more slowly than employment in high-wage businesses in labor markets with larger differences in the relative generosity of pandemic UI benefits. According to a labor search model that replicates the estimated employment differences between low- and high-wage businesses, the disincentive effects from the pandemic UI programs held back the aggregate employment recovery by 4.7 percentage points between April and December 2020. [ABSTRACT FROM AUTHOR]

This paper documents a novel finding indicating that re-employment wages are elastic to the level of unemployment insurance (i.e., a binding reservation wage) and adapts the IV estimator for duration dependence in Schmieder et al. (2016) to account for this fact. Using administrative data from Spain, we find that unemployed workers lower their re-employment wages by 3 percent immediately after the exhaustion of unemployment insurance (UI) benefits. Workers’ characteristics and permanent unobserved heterogeneity cannot explain this. To estimate duration dependence, we extend the IV framework proposed by Schmieder et al. (2016), whose estimator of duration dependence is proportional to the response of wages to an extension of the potential duration of UI, to account for the response of reservation wages. We find that while extending the potential duration of UI has an insignificant effect on re-employment wages, duration dependence is strongly negative. We estimate that the degree of duration dependence in Spain is approximately 0.8 percent per month in daily wages. Workers’ inability to find full-time jobs as the duration of non-employment increases is an important mechanism behind this effect, since the duration dependence of hourly wages is 0.25 percent per month. Failing to account for the fact that reservation wages are binding would underestimate the magnitude of duration dependence by 15 to 20 percent. [ABSTRACT FROM AUTHOR]

A large number of companies operating in the EV and battery supply chain have listed on a major U.S. stock exchange in recent years. This paper investigates 1) how these companies' stock returns are related to systematic risk factors that can explain movements in the stock market and 2) how these companies' idiosyncratic returns are related to one another. To do so, I compile a unique data set of intradaily stock returns that spans the supply chain, including companies focused on the mining of battery and EV-related critical minerals, advanced battery technology, lithium-ion battery production, EV original equipment manufacturers (EV OEMs) and EV charging companies. The returns are decomposed into a systematic and idiosyncratic component, with the systematic component given by latent factors extracted from a large panel of stock returns using highfrequency principal components. A key feature of the returns of interest is that they can be explained not only by a market factor but also by a second factor that loads on tech and consumer discretionary stocks. There is evidence for cross-sectional dependence in the idiosyncratic returns but correlations are generally low, except for some specific groups, e.g., lithium mining companies. The first principal component of the idiosyncratic returns, which can be viewed as an "EV" factor, explains only about 13 percent of their variation. [ABSTRACT FROM AUTHOR]

This paper develops Mean Group Distributed Lag (MGDL) estimation of impulse responses in large panels with one or two cross-section dimensions. Sufficient conditions for asymptotic consistency and asymptotic normality are derived, and satisfactory small sample performance is documented using Monte Carlo experiments. MGDL estimators are used to estimate the effects of crude oil price increases on US city- and product-level retail prices. [ABSTRACT FROM AUTHOR]

When firms decide to post a vacancy they can hire from the pool of unemployed workers or they can poach a worker from another firm. In this paper we show that if there are two different matching processes, one for unemployed workers and another one for job-to-job transitions, then implications for the Beveridge curve are potentially very different, influencing the effects of monetary policy on unemployment. We show that over the years the hiring process and how job postings are used as an input into this process have changed dramatically. [ABSTRACT FROM AUTHOR]

This paper is about the nonparametric regression of a choice variable on a nonlinear budget set when there is general heterogeneity, i.e., in the random utility model (RUM). We show that utility maximization makes this a three-dimensional regression with piecewise linear, convex budget sets with a more parsimonious specification than previously derived. We show that the regression allows for measurement and/or optimization errors in the outcome variable. We characterize all of the restrictions of utility maximization on the budget set regression and show how to check these restrictions. We formulate nonlinear budget set effects that can be identified by this regression and give automatic debiased machine learners of these effects. We find that in practice nonconvexities in the budget set have little effect on these estimates. We use control variables to allow for endogeneity of budget sets and adjust for productivity growth in taxable income. We apply the results to estimate .52 as the elasticity of an overall tax rate change in Sweden. We also find that the restrictions of utility maximization are satisfied at the choices made by nearly all individuals in the data. [ABSTRACT FROM AUTHOR]