Federal Reserve Bank of Cleveland

We make substantial progress on understanding the Phillips curve, yielding important monetary policy implications. Inflation responds differently to persistent versus moderately persistent (or transient) fluctuations in the unemployment gap. This persistence‐dependent relationship aligns with business‐cycle stages, and is consistent with existing theory. Previous work fails to model this dependence, thereby finding the numerous “inflation puzzles”—for example, missing inflation/disinflation—noted in the literature. Our specification eliminates these puzzles; for example, the Phillips curve has not weakened; inflation's post‐2012 slow upward trudge was predictable. The model's coefficients are stable, and it provides accurate out‐of‐sample conditional recursive forecasts through the Great Recession and recovery.

We evaluate alternative public debt management policies in light of constraints imposed by the effective lower bound on interest rates. Replacing the current limit on gross debt issued by the fiscal authority with a limit on consolidated debt of the government can ensure that output always reaches its potential, but it may permit excess government spending when the economy is away from the effective lower bound. The welfare-maximizing policy sets the gross debt limit to the level implied by Samuelson (1954), while the central bank finances government spending with money when the economy is at the effective lower bound.

In this article, I study the optimality of differential asset taxation in an environment with entrepreneurs and workers in which output is stochastic and entrepreneurs can misreport profits and abscond with capital. I show that a stationary efficient allocation may be implemented as an equilibrium with endogenous collateral constraints, transfers to newborns, and linear taxes on profits, investment, and interest. Furthermore, these taxes differ from one another and serve distinct purposes. The profits tax shares risk and depends solely on the severity of the misreporting friction, whereas the remaining instruments determine the efficient mean and variance of entrepreneurs' consumption growth.

Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks. This paper examines various choices in the specification of quantile regressions for macro applications, including how and to what extent to include shrinkage and whether to apply shrinkage in a classical or Bayesian framework. We focus on forecasting accuracy, measured with quantile scores and quantile‐weighted continuous ranked probability scores at a range of quantiles from the left to right tail. Across applications, we find that shrinkage is generally helpful to quantile forecast accuracy, with Bayesian quantile regression dominating frequentist quantile regression. JEL Classification: C53, E17, E37, F47

This paper studies decentralized trade in networked markets with intermediaries using a stochastic model of multilateral bargaining in which players compete on different routes through the network. The paper characterizes stationary equilibrium payoffs as the fixed point of a set of intuitive value function equations and studies efficiency and the impact of network structure on payoffs. In equilibrium players will never pass on an efficient trade opportunity, but they may trade in situations where delay would be efficient. With homogeneous surplus, the payoffs for players who are not essential to a trade opportunity go to zero if there is at least one essential player as trade frictions vanish.

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.

The scale of wildfire impacts to the built environment is growing and will likely continue under rising average global temperatures. We investigate whether and at what destruction threshold wildfires have influenced human mobility patterns by examining the migration effects of the most destructive wildfires in the contiguous U.S. between 1999 and 2020. We find that only the most extreme wildfires (258+ structures destroyed) influenced migration patterns. In contrast, the majority of wildfires examined were less destructive and did not cause significant changes to out- or in-migration. These findings suggest that, for the past two decades, the influence of wildfire on population mobility was rare and operated primarily through destruction of the built environment.

There is substantial asymmetry in effective corporate income tax rates across firms. While tax asymmetries would reduce productivity in frictionless economies, they can improve efficiency in a distorted economy if taxes alleviate other economic frictions. We develop a framework to estimate to what extent tax asymmetries affect productivity in distorted economies. Using US firm-level balance sheet data alongside measures of effective marginal tax rates, we find a positive correlation between tax rates and factor productivity, suggesting that tax asymmetry exacerbates the distortions from other economic frictions. Eliminating tax rate asymmetries would raise aggregate productivity by 3 to 4 percent if taxes distort capital costs alone. Models where taxes also distort the marginal cost of labor predict potential gains as high as 9 percent.

Rent measurement determines 32 percent of the CPI. Accurate rent measurement is therefore essential for accurate inflation measurement, but the CPI rent index often differs from alternative rent inflation measures. Using repeat-rent inflation measures created from CPI microdata, we show that this discrepancy is largely explained by differences in rent growth for new tenants relative to all tenants. New-tenant rent inflation provides information about future all-tenant rent inflation, but the use of new-tenant rents is contraindicated in a cost-of-living index such as the CPI. Nevertheless, policy-makers should integrate new-tenant inflation into inflation forecasts and monetary policy decisions. (JEL E31, E37, E52, R31)

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 U.S. 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.

A recent literature within quantitative macroeconomics has advocated the use of continuous-time methods for dynamic programming problems. In this paper we explore the relative merits of continuous-time and discrete-time methods within the context of stationary and nonstationary income fluctuation problems. For stationary problems in two dimensions, the continuous-time approach is both more stable and typically faster than the discrete-time approach for any given level of accuracy. In contrast, for concave lifecycle problems (in which age or time enters explicitly), simply iterating backwards from the terminal date in discrete time is superior to any continuous-time algorithm. However, we also show that the continuous-time framework can easily incorporate nonconvexities and multiple controls—complications that often require either problem-specific ingenuity or nonlinear root-finding in the discrete-time context. In general, neither approach unequivocally dominates the other, making the choice of one over the other an art, rather than an exact science.

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 United States 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.

We use natural language processing methods to quantify the sentiment expressed in the Federal Reserve's anecdotal summaries of current economic conditions in the national and 12 Federal Reserve District-level economies as published eight times per year in the Beige Book since 1970. We document that both national and District-level economic sentiment tend to rise and fall with the US business cycle. But economic sentiment is extremely heterogeneous across Districts, and we find that national economic sentiment is not always the simple aggregation of District-level sentiment. We show that the heterogeneity in District-level economic sentiment can be used, over and above the information contained in national economic sentiment, to better forecast US recessions.

We use microdata on the phases of commercial construction projects to document three facts regarding time-to-plan lags: (1) plan times are long—about 1.5 years on average—and highly variable, (2) roughly one-third of projects are abandoned in planning, (3) property price appreciation reduces the likelihood of abandonment. We construct a model with endogenous planning starts and abandonment that matches these facts. Endogenous abandonment makes short-term building supply more elastic, as price shocks immediately affect the exercise of construction options rather than just planning starts. The model has the testable implicationthat supply is more elastic when there are more “shovel ready” projects available to advance to construction. We use local projections to validate that this prediction holds in the cross-section for U.S. cities.

Following the Global Financial Crisis of 2007-2008, the capital standards for banks operating in the United States were tightened as US banking regulators implemented the Basel III framework. This Economic Commentary briefly presents the key elements of Basel III relevant to bank capital and analyzes the timing of the evolution of regulatory capital ratios for US bank holding companies during that time. It shows that, on average, banks’ capital ratios increased notably between 2009 and 2012, plateauing before the new rules came into force. While larger and better-capitalized banks increased capital ratios soon after the financial crisis, it took smaller and less-well-capitalized banks longer on average to start that process.

This Economic Commentary describes the collapse and subsequent bailout of the Detroit-headquartered Bank of the Commonwealth in 1972. Commonwealth failed because it invested heavily in long-duration, fixed-rate municipal securities in the mid-1960s in a bet that interest rates would decline. Instead, with the beginning of the Great Inflation of 1965–1980, rates rose. Liquidity problems then ensued, and the bank approached failure. Unable to find an acquirer because of Michigan’s banking restrictions, regulators instead bailed out the bank because of fears of contagion. This article also compares the collapse of Commonwealth with the spring 2023 failures of Silicon Valley Bank and First Republic. In particular, I discuss structural changes in banking that impacted the speed of the runs and the pools of potential acquirers.

We study the large labor force increases since 2020 among disabled workers and among foreign-born workers in the United States. We show that the increase in the disabled labor force largely reflects a change in self-reported disability status among those already in the labor force rather than an actual increase in labor supply. We conjecture that immigration will likely contribute more to labor supply in 2024 than it did before the pandemic, but less than in 2020-2023.

In this Economic Commentary, we compare characteristics of the 2000-2006 house-price boom that preceded the Great Recession to the house-price boom that began in 2020 during the COVID-19 pandemic. These two episodes of high house-price growth have important differences, including the behavior of rental rates, the dynamics of housing supply and demand, and the state of the mortgage market. The absence of changes in fundamentals during the 2000s is consistent with the literature emphasizing house-price beliefs during this prior episode. In contrast to during the 2000s boom, changes in fundamentals (including rent and demand growth) played a more dominant role in the 2020s house-price boom.

We implement a novel nonlinear structural model featuring an empirically successful frequency‐dependent and asymmetric Phillips curve; unemployment frequency components interact with three components of core personal consumption expenditures (PCE)—core goods, housing, and core services ex‐housing—and a variable capturing supply shocks. Forecast tests verify accuracy in its unemployment–inflation trade‐offs, crucial for monetary policy. Using this model, we assess the plausibility of the December 2022 Summary of Economic Projections (SEP). By 2025Q4, the SEP projects 2.1% inflation; however, conditional on the SEP unemployment path, we project 2.9%. A fairly deep recession delivers the SEP inflation path, but a simple welfare analysis rejects this outcome.