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Working Papers

Working Papers

  • WP 18-11 | A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification


    Mark Bognanni

    Abstract

    This paper develops a new class of structural vector autoregressions (SVARs) with time-varying parameters, which I call a drifting SVAR (DSVAR). The DSVAR is the first structural time-varying parameter model to allow for internally consistent probabilistic inference under exact—or set—identification, nesting the widely used SVAR framework as a special case. I prove that the DSVAR implies a reduced-form representation, from which structural inference can proceed similarly to the widely used two-step approach for SVARs: beginning with estimation of a reduced form and then choosing among observationally equivalent candidate structural parameters via the imposition of identifying restrictions. In a special case, the implied reduced form is a tractable known model for which I provide the first algorithm for Bayesian estimation of all free parameters. I demonstrate the framework in the context of Baumeister and Peersman’s (2013b) work on time variation in the elasticity of oil demand.   Read More

  • WP 16-35R | Goods-Market Frictions and International Trade


    Pawel Krolikowski Andrew McCallum

    Original Paper: WP 16-35

    Abstract

    We add goods-market frictions to a general equilibrium dynamic model with heterogeneous exporting producers and identical importing retailers. Our tractable framework leads to endogenously unmatched producers, which attenuate welfare responses to foreign shocks but increase the trade elasticity relative to a model without search costs. Search frictions are quantitatively important in our calibration, attenuating welfare responses to tariffs by 40 percent and increasing the trade elasticity by 50 percent. Eliminating search costs raises welfare by 1 percent and increasing them by only a few dollars has the same effects on welfare and trade flows as a 10 percent tariff.   Read More

  • 16-10R | Rival Growth Prospects and Equity Prices: Evidence from Mass Layoff Announcements


    Adam Bordeman Bharadwaj Kannan Roberto Pinheiro

    Original Paper: WP 16-10

    Abstract

    We investigate the impact of mass layoff announcements on the equity value of industry rivals. When a layoff announcement conveys good (bad) news for the announcer, rivals on average witness a 0.44 percent increase (0.60 percent decrease) in cumulative abnormal stock returns. This effect is concentrated on rivals with high growth opportunities. Consistent with this finding, we also show that our results are strongest in technology industries, where growth opportunities matter the most. Our results suggest that investors perceive layoff announcements as news about industry prospects rather than just the announcer.   Read More

  • WP 18-10 | Liquidity Requirements and the Interbank Loan Market: An Experimental Investigation


    Douglas Davis Oleg Korenok John Lightle Edward S. Prescott

    Abstract

    We develop a stylized interbank market environment and use it to evaluate with experimental methods the effects of liquidity requirements. Baseline and liquidity-regulated regimes are analyzed in a simple shock environment, which features a single idiosyncratic shock, and in a compound shock environment, in which the idiosyncratic shock is followed by a randomly occurring second-stage shock. Interbank trading of the illiquid asset follows each shock. In the simple shock environment, we find that liquidity regulations reduce the incidence of bankruptcies, but at a large loss of investment efficiency. In the compound shock environment, liquidity regulations not only impose a loss of investment efficiency but also fail to reduce bankruptcies.   Read More

  • 16-13r | Information Production, Misconduct Effort, and the Duration of Financial Misrepresentation


    Jonathan Black Mattias Nilsson Roberto Pinheiro Maximiliano da Silva

    Original Paper: WP 16-13

    Abstract

    We examine the link between information produced by auditors and analysts and fraud duration. Using a hazard model, we analyze misstatement periods related to SEC accounting and auditing enforcement releases (AAERs) between 1982 and 2012. Results suggest that misconduct is more likely to end just after firms announce an auditor switch or issue audited financial statements, particularly when the audit report contains explanatory language. Analyst following increases the fraud termination hazard. However, increases (decreases) in analyst coverage have a negative (positive) marginal impact on the termination hazard, suggesting that analysts signal whistleblowers with their choice to add or drop coverage. Finally, our results suggest that misconduct lasts longer when it is well planned, more complex, or involves more accrual manipulation. Taken together, our findings are consistent with auditors and analysts playing a key informational role in fraud detection, while managerial effort to conceal misconduct significantly extends its duration.   Read More

  • WP 18-09 | Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy


    Ellis W. Tallman Saeed Zaman

    Abstract

    This paper constructs hybrid forecasts that combine both short- and long-term conditioning information from external surveys with forecasts from a standard fixed-coefficient vector autoregression (VAR) model. Specifically, we use relative entropy to tilt one-step ahead and long-horizon VAR forecasts to match the nowcast and long-horizon forecast from the Survey of Professional Forecasters. The results indicate meaningful gains in multi-horizon forecast accuracy relative to model forecasts that do not incorporate long-term survey conditions. The accuracy gains are achieved for a range of variables, including those that are not directly tilted but are affected through spillover effects from tilted variables. The forecast accuracy gains for inflation are substantial, statistically significant, and are competitive with the forecast accuracy from both time-varying VARs and univariate benchmarks. We view our proposal as an indirect approach to accommodating structural change and moving end points.   Read More

  • WP 18-08 | Can Wealth Explain Neighborhood Sorting by Race and Income?


    Dionissi Aliprantis Daniel R. Carroll Eric Young

    Abstract

    Why do high-income blacks live in neighborhoods with characteristics similar to those of low-income whites? One plausible explanation is wealth, since homeownership requires some wealth, and black households hold less wealth than white households at all levels of income. We present evidence against this hypothesis by showing that wealth does not predict sorting into neighborhood quality once race and income are taken into account. An alternative explanation is that the scarcity of high-quality black neighborhoods increases the cost of living in a high-quality neighborhood for black households with even weak race preferences. We present evidence in favor of this hypothesis by showing that sorting into neighborhood racial composition is similar across wealth levels conditional on race and income.   Read More

  • WP 18-07 | Opioids and the Labor Market


    Dionissi Aliprantis Mark E. Schweitzer

    Abstract

    This paper finds evidence that opioid availability decreases labor force participation while a large labor market shock does not influence the share of opioid abusers. We first identify the effect of availability on participation using the geographic variation in opioid prescription rates. We use a combination of the American Community Survey (ACS) and Centers for Disease Control and Prevention (CDC) county-level prescription data to examine labor market patterns across both rural and metropolitan areas of the United States from 2007 to 2016. Individuals in areas with higher prescription rates are less likely to participate after accounting for standard demographic factors and regional controls. This relationship remains significant for important demographic groups when increasingly strong panel data controls, including a full set of geographic fixed effects and measures of local labor market conditions in 2000, are introduced to the regressions. We also investigate the possibility of reverse causality, using the Great Recession as an instrument to identify the effect of weak labor demand on opioid abuse. The share abusing opioids did not increase after the onset of the Great Recession. The evidence on the frequency of abuse is more ambiguous since the identified increases could be the continuation of a pre-trend.   Read More

  • WP 18-06 | The Impact of the Tax Cuts and Jobs Act on Local Home Values


    Hal Martin

    Abstract

    This paper simulates changes to neighborhood home prices resulting from reforms to tax preferences in the recently passed Tax Cuts and Jobs Act (TCJA). The simulation uses federal tax data summarized at a fine geography to impute homeowner rents at the zip code level across six income classes. Employing a user cost framework, I model rents as a function of prices under the old tax law and under the TCJA. While the average price impact of the TCJA is found to be −5.7 percent, local effects range from 0 to −23 percent across zip codes. Variation across income class is also large. Simulations by income class suggest that the most severe declines in price occur for upper middle-income households ($100,000–$200,000). The paper also simulates partial versions of the TCJA that omit different features of the law that affect housing preference. I find that the higher standard deductions in the new law are the largest driver of price declines.   Read More

  • WP 17-15R | Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors


    Todd E. Clark Michael McCracken Elmar Mertens

    Original Paper: WP 17-15

    Abstract

    We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to constant variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts. Our method can also be applied to other surveys like the Blue Chip Consensus, or the Federal Open Market Committee’s Summary of Economic Projections.   Read More