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Working Papers

Working Papers

  • WP 19-17R | On the Optimality of Differential Asset Taxation


    Tom Phelan

    Original Paper: WP 19-17

    Abstract

    How should a government balance risk-sharing and redistributive concerns with the need to provide incentives for investment? Should they tax firm profits or individual savings, or simply levy lump-sum transfers? I address these questions in an environment with entrepreneurs and workers in which output is subject to privately observed shocks and firm owners can both misreport profits and abscond with a fraction of assets. When frictions in financial markets restrict private risk-sharing, the stationary efficient allocation may be implemented in a competitive equilibrium with collateral constraints using (occupation-specific) linear taxes on savings and profits and lump-sum transfers to newborns. Further, the two taxes serve distinct roles and in general differ from one another. The savings tax affects consumption smoothing and may be positive or negative depending on the strength of general equilibrium effects, while the profits tax shares risk between the government and entrepreneurs, is unambiguously positive, and depends solely on the degree of frictions in financial markets.   Read More

  • WP 22-25 | Specification Choices in Quantile Regression for Empirical Macroeconomics


    Andrea Carriero Todd E. Clark Massimiliano Marcellino

    Abstract

    Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks to macroeconomic indicators. In this paper we examine various choices in the specification of quantile regressions for macro applications, for example, choices related to how and to what extent to include shrinkage, and whether to apply shrinkage in a classical or Bayesian framework. We focus on forecasting accuracy, using for evaluation both quantile scores and quantile-weighted continuous ranked probability scores at a range of quantiles spanning from the left to right tail. We find that shrinkage is generally helpful to tail forecast accuracy, with gains that are particularly large for GDP applications featuring large sets of predictors and unemployment and inflation applications, and with gains that increase with the forecast horizon.   Read More

  • WP 21-12R | Censored Density Forecasts: Production and Evaluation


    James Mitchell Martin Weale

    Original Paper: WP 21-12

    Abstract

    This paper develops methods for the production and evaluation of censored density forecasts. The focus is on censored density forecasts that quantify forecast risks in a middle region of the density covering a specified probability, and ignore the magnitude but not the frequency of outlying observations. We propose a fixed-point algorithm that fits a potentially skewed and fat-tailed density to the inner observations, acknowledging that the outlying observations may be drawn from a different but unknown distribution. We also introduce a new test for calibration of censored density forecasts. An application using historical forecast errors from the Federal Reserve Board and the Monetary Policy Committee (MPC) at the Bank of England suggests that the use of censored density functions to represent the pattern of forecast errors results in much greater parameter stability than do uncensored densities. We illustrate the utility of censored density forecasts when quantifying forecast risks after shocks such as the global financial crisis and the COVID-19 pandemic and find that these outperform the official forecasts produced by the MPC.   Read More

  • WP 22-17R | Labor Supply Shocks, Labor Force Entry, and Monetary Policy


    Takushi Kurozumi Willem Van Zandweghe

    Original Paper: WP 22-17

    Abstract

    Should monetary policy offset the effects of labor supply shocks on inflation and the output gap? Canonical New Keynesian models answer yes. Motivated by weak labor force participation during the pandemic, we reexamine the question by introducing labor force entry and exit in an otherwise canonical model with sticky prices and wages. The entry decision generates an employment channel of monetary policy, by which a decline in employment raises wage growth. Consequently, a labor supply shock to the value of nonparticipation in the labor market induces a policy trade-off between stabilization of the employment gap and wage growth. For an adverse labor supply shock, optimal policy dampens the decline in employment to rein in wage growth, which entails a period of higher inflation and a positive output gap. A welfare analysis of policy rules shows that monetary policy should not lean against the employment gap.   Read More

  • WP 21-23R | A Unified Framework to Estimate Macroeconomic Stars


    Saeed Zaman

    Original Paper: WP 21-23

    Abstract

    We develop a flexible semi-structural time-series model to estimate jointly several macroeconomic "stars" -- i.e., unobserved long-run equilibrium levels of output (and growth rate of output), the unemployment rate, the real rate of interest, productivity growth, price inflation, and wage inflation. The ingredients of the model are in part motivated by economic theory and in part by the empirical features necessitated by the changing economic environment. Following the recent literature on inflation and interest rate modeling, we explicitly model the links between long-run survey expectations and stars to improve the stars' econometric estimation. Our approach permits time variation in the relationships between various components, including time variation in error variances. To tractably estimate the large multivariate model, we use a recently developed precision sampler that relies on Bayesian methods. The by-products of this approach are the time-varying estimates of the wage and price Phillips curves, and the pass-through between prices and wages, both of which provide new insights into these empirical relationships' instability in US data. Generally, the contours of the stars echo those documented elsewhere in the literature -- estimated using smaller models -- but at times the estimates of stars are different, and these differences can matter for policy. Furthermore, our estimates of the stars are among the most precise. Last, we document the competitive real-time forecasting properties of the model and, separately, the usefulness of stars' estimates as steady-state values in external models.   Read More

  • WP 22-24 | The Effect of Minimum Wages on Consumer Bankruptcy


    Diego Legal Eric Young

    Abstract

    We use cross-state differences in minimum wage (MW) levels and county-level consumer bankruptcy rates from 1991-2017 to estimate the effect of changes in minimum wages on consumer bankruptcy by exploiting policy discontinuities at state borders. We find that Chapter 7 bankruptcy rates are significantly lower in counties belonging to states with higher MW compared to neighboring counties in the lower MW state: a 10 percent increase in MW decreases the bankruptcy rate by around 4 percent. Before the 2005 bankruptcy reform, this effect was almost twice as large as for the entire sample. Theoretically, we cannot sign the effect of MW on bankruptcy and credit utilization; we use a stylized consumption/saving model with default to illustrate the dependence on particular parameters and to provide intuition on how to interpret our results.   Read More

  • WP 22-23 | Improving Inflation Forecasts Using Robust Measures


    Randal J. Verbrugge Saeed Zaman

    Abstract

    Both theory and extant empirical evidence suggest that the cross-sectional asymmetry across disaggregated price indexes might be useful in the forecasting of aggregate inflation. Trimmed-mean inflation estimators have been shown to be useful devices for forecasting headline PCE inflation. But does this stem from their ability to signal the underlying trend, or does it mainly come from their implicit signaling of asymmetry (when included alongside headline PCE)? We address this question by augmenting a “hard to beat” benchmark inflation forecasting model of headline PCE price inflation with robust measures of trimmed-mean estimators of inflation (median PCE and trimmed-mean PCE) and robust measures of the cross-sectional asymmetry (Bowley skewness; Kelly skewness) computed using the 180+ components of the PCE price index. We also construct new trimmed-mean measures of goods and services PCE inflation and their accompanying robust skewness. Our results indicate significant gains in the point and density accuracy of PCE inflation forecasts over medium- and longer-term horizons, up through and including the COVID-19 pandemic. We find that improvements in accuracy stem mainly from the trend information implicit in trimmed-mean estimators, but that skewness is also useful. Median PCE slightly outperforms trimmed-mean PCE; both outperform core PCE. For point forecasts, Kelly skewness is preferred; but for estimating stochastic volatility, Bowley skewness is preferred. An examination of goods and services PCE inflation provides similar inference.   Read More

  • WP 22-22 | Heterogeneity and the Effects of Aggregation on Wage Growth


    Robert Rich Joseph Tracy

    Abstract

    This paper focuses on the implications of alternative methods of aggregating individual wage data for the behavior of economy-wide wage growth. The analysis is motivated by evidence of significant heterogeneity in individual wage growth and its cyclicality. Because of this heterogeneity, the choice of aggregation will affect the properties of economy-wide wage growth measures. To assess the importance of this consideration, we provide a decomposition of wage growth into aggregation effects and composition effects and use the decomposition to compare growth in an average wage—specifically average hourly earnings—to a measure of average wage growth from the Survey of Income and Program Participation. We find that aggregation effects largely account for average hourly earnings growth being persistently lower and less cyclical than average wage growth over the period 1990-2015, with these effects reflecting a disproportionate weighting of high-earning workers. The analysis also indicates that composition effects now play a more limited role in the cyclicality of wage growth compared to results reported in previous studies for earlier time periods.   Read More

  • WP 18-07R3 | Opioids and the Labor Market


    Dionissi Aliprantis Kyle Fee Mark E. Schweitzer

    Original Paper: WP 18-07R | Revisions: WP 18-07R2

    Abstract

    This paper quantifies the relationship between local opioid prescription rates and labor market outcomes in the United States between 2006 and 2016. To understand this relationship at the national level, we assemble a data set that allows us both to include rural areas and to estimate the relationship at a disaggregated level. We control for geographic variation in both short-term and long-term economic conditions. In our preferred specification, a 10 percent higher local prescription rate is associated with a lower prime-age labor force participation rate of 0.53 percentage points for men and 0.10 percentage points for women. We focus on measuring the impact of opioid prescriptions on labor markets, so we evaluate the robustness of our estimates to an alternative causal path, unobserved selection, and an instrumental variable from the literature.   Read More

  • WP 21-28R | Communicating Data Uncertainty: Multi-Wave Experimental Evidence for UK GDP


    Ana Galvão James Mitchell

    Original Paper: WP 21-28

    Abstract

    Economic statistics are commonly published without estimates of their uncertainty. We conduct two waves of a randomized controlled online experiment to assess if and how the UK public understands data uncertainty. A control group observes only the point estimate of GDP. Treatment groups are presented with alternative qualitative and quantitative communications of GDP data uncertainty. We find that most of the public understands that GDP numbers are uncertain. Quantitative communications of data uncertainty help align the public’s subjective probabilistic expectations of data uncertainty with objective estimates, but do not decrease trust in the statistical office.   Read More