The Tax Cuts and Jobs Act (TCJA) of 2017 is the most extensive overhaul of the U.S. income tax code since the Tax Reform Act of 1986. Existing estimates of TCJA’s economic impact are based on economic projections using pre-TCJA estimates of tax effects. I exploit plausibly exogenous state-level variation in tax changes from TCJA and find that an income tax cut equaling 1 percent of GDP led to a 1.2-percentage-point faster job growth and nearly 1.5 percentage points higher GDP growth over two years following the law change. While the estimates are imprecise, the overall pattern suggests that the TCJA stimulated economic growth. The estimates imply a two-year tax cut multiplier of 1.5 and a cost per job of $105,000. The estimated growth effect was driven by a nearly 1.3-percentage-point increase in the labor force participation rate.
{"title":"Did the Tax Cuts and Jobs Act Create Jobs and Stimulate Growth?","authors":"Anil Kumar","doi":"10.24149/wp2001r1","DOIUrl":"https://doi.org/10.24149/wp2001r1","url":null,"abstract":"The Tax Cuts and Jobs Act (TCJA) of 2017 is the most extensive overhaul of the U.S. income tax code since the Tax Reform Act of 1986. Existing estimates of TCJA’s economic impact are based on economic projections using pre-TCJA estimates of tax effects. I exploit plausibly exogenous state-level variation in tax changes from TCJA and find that an income tax cut equaling 1 percent of GDP led to a 1.2-percentage-point faster job growth and nearly 1.5 percentage points higher GDP growth over two years following the law change. While the estimates are imprecise, the overall pattern suggests that the TCJA stimulated economic growth. The estimates imply a two-year tax cut multiplier of 1.5 and a cost per job of $105,000. The estimated growth effect was driven by a nearly 1.3-percentage-point increase in the labor force participation rate.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116797723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic Identification Using System Projections and Instrumental Variables","authors":"Daniel J. Lewis, Karel Mertens","doi":"10.24149/wp2204","DOIUrl":"https://doi.org/10.24149/wp2204","url":null,"abstract":",","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134266564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Bernstein, A. W. Richter, Nathaniel A. Throckmorton
The Cobb‐Douglas matching function is ubiquitous in labor search and matching models, even though it imposes a constant matching elasticity that is unlikely to hold empirically. To examine the implications of this discrepancy, this paper uses a general constant returns to scale matching function to derive conditions that show how the cyclicality of the matching elasticity affects the shape of the job finding rate as a function of productivity and amplifies or dampens nonlinear labor market dynamics. It then shows that modest variation in the matching elasticity, consistent with recent estimates, significantly affects higher order moments and optimal policy. This motivates research that can provide greater clarity on the matching function specification.
{"title":"The Matching Function and Nonlinear Business Cycles","authors":"J. Bernstein, A. W. Richter, Nathaniel A. Throckmorton","doi":"10.24149/wp2201","DOIUrl":"https://doi.org/10.24149/wp2201","url":null,"abstract":"The Cobb‐Douglas matching function is ubiquitous in labor search and matching models, even though it imposes a constant matching elasticity that is unlikely to hold empirically. To examine the implications of this discrepancy, this paper uses a general constant returns to scale matching function to derive conditions that show how the cyclicality of the matching elasticity affects the shape of the job finding rate as a function of productivity and amplifies or dampens nonlinear labor market dynamics. It then shows that modest variation in the matching elasticity, consistent with recent estimates, significantly affects higher order moments and optimal policy. This motivates research that can provide greater clarity on the matching function specification.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130965701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pallavi Basu, Luella Fu, Alessio Saretto, Wenguang Sun
In sparse large-scale testing problems where the false discovery proportion (FDP) is highly variable, the false discovery exceedance (FDX) provides a valuable alternative to the widely used false discovery rate (FDR). We develop an empirical Bayes approach to controlling the FDX. We show that for independent hypotheses from a two-group model and dependent hypotheses from a Gaussian model fulfilling the exchangeability condition, an oracle decision rule based on ranking and thresholding the local false discovery rate (lfdr) is optimal in the sense that the power is maximized subject to FDX constraint. We propose a data-driven FDX procedure that emulates the oracle via carefully designed computational shortcuts. We investigate the empirical performance of the proposed method using simulations and illustrate the merits of FDX control through an application for identifying abnormal stock trading strategies.
{"title":"Empirical Bayes Control of the False Discovery Exceedance","authors":"Pallavi Basu, Luella Fu, Alessio Saretto, Wenguang Sun","doi":"10.24149/wp2115","DOIUrl":"https://doi.org/10.24149/wp2115","url":null,"abstract":"In sparse large-scale testing problems where the false discovery proportion (FDP) is highly variable, the false discovery exceedance (FDX) provides a valuable alternative to the widely used false discovery rate (FDR). We develop an empirical Bayes approach to controlling the FDX. We show that for independent hypotheses from a two-group model and dependent hypotheses from a Gaussian model fulfilling the exchangeability condition, an oracle decision rule based on ranking and thresholding the local false discovery rate (lfdr) is optimal in the sense that the power is maximized subject to FDX constraint. We propose a data-driven FDX procedure that emulates the oracle via carefully designed computational shortcuts. We investigate the empirical performance of the proposed method using simulations and illustrate the merits of FDX control through an application for identifying abnormal stock trading strategies.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121192894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Predictions of oil prices reaching $100 per barrel during the winter of 2021/22 have raised fears of persistently high inflation and rising inflation expectations for years to come. We show that these concerns have been overstated. A $100 oil scenario of the type discussed by many observers, would only briefly raise monthly headline inflation, before fading rather quickly. However, the short-run effects on headline inflation would be sizable. For example, on a year-over-year basis, headline PCE inflation would increase by 1.8 percentage points at the end of 2021 under this scenario, but only by 0.4 percentage points at the end of 2022. In contrast, the impact on measures of core inflation such as trimmed mean PCE inflation is only 0.4 and 0.3 percentage points in 2021 and 2022, respectively. These estimates already account for any increases in inflation expectations under the scenario. The peak response of the 1-year household inflation expectation would be 1.2 percentage points, while that of the 5-year expectation would be 0.2 percentage points.
{"title":"The Impact of Rising Oil Prices on U.S. Inflation and Inflation Expectations in 2020-23","authors":"L. Kilian, Xiaoqing Zhou","doi":"10.24149/wp2116","DOIUrl":"https://doi.org/10.24149/wp2116","url":null,"abstract":"Predictions of oil prices reaching $100 per barrel during the winter of 2021/22 have raised fears of persistently high inflation and rising inflation expectations for years to come. We show that these concerns have been overstated. A $100 oil scenario of the type discussed by many observers, would only briefly raise monthly headline inflation, before fading rather quickly. However, the short-run effects on headline inflation would be sizable. For example, on a year-over-year basis, headline PCE inflation would increase by 1.8 percentage points at the end of 2021 under this scenario, but only by 0.4 percentage points at the end of 2022. In contrast, the impact on measures of core inflation such as trimmed mean PCE inflation is only 0.4 and 0.3 percentage points in 2021 and 2022, respectively. These estimates already account for any increases in inflation expectations under the scenario. The peak response of the 1-year household inflation expectation would be 1.2 percentage points, while that of the 5-year expectation would be 0.2 percentage points.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127799328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When setting initial compensation some firms set a fixed non-negotiable wage while others bargain. In this paper we propose a parsimonious search and matching model with two sided heterogeneity, where search intensity and the degree of randomness in matching are endogenous, and firms decide whether to bargain or post wages. We study the implications of heterogeneous search costs and market tightness on the choice of the wage setting mechanism, as well as the relationship between bargaining prevalence and wage level, residual wage dispersion, and labor market tightness. We find that bargaining prevalence is positively correlated with wages, residual wage dispersion, and labor market tightness, both in the model and in the data.
{"title":"Wage Setting Under Targeted Search","authors":"Paulina Restrepo-Echavarria, Anton Cheremukhin","doi":"10.20955/wp.2020.041","DOIUrl":"https://doi.org/10.20955/wp.2020.041","url":null,"abstract":"When setting initial compensation some firms set a fixed non-negotiable wage while others bargain. In this paper we propose a parsimonious search and matching model with two sided heterogeneity, where search intensity and the degree of randomness in matching are endogenous, and firms decide whether to bargain or post wages. We study the implications of heterogeneous search costs and market tightness on the choice of the wage setting mechanism, as well as the relationship between bargaining prevalence and wage level, residual wage dispersion, and labor market tightness. We find that bargaining prevalence is positively correlated with wages, residual wage dispersion, and labor market tightness, both in the model and in the data.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132195461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Bernstein, A. W. Richter, Nathaniel A. Throckmorton
Competing explanations for the sources of nonlinearity in search and matching models indicate that they are not fully understood. This paper derives an analytical solution to a textbook model that highlights the mechanisms that generate nonlinearity and quantifies their contributions. Procyclical variation in the matching elasticity creates nonlinearity in the job finding rate, which interacts with the law of motion for unemployment. These results show the matching function choice is not innocuous. Quantitatively, the Den Haan et al. (2000) matching function more than doubles the skewness of unemployment and welfare cost of business cycles, compared to the Cobb-Douglas specification.
{"title":"Nonlinear Search and Matching Explained","authors":"J. Bernstein, A. W. Richter, Nathaniel A. Throckmorton","doi":"10.24149/WP2106","DOIUrl":"https://doi.org/10.24149/WP2106","url":null,"abstract":"Competing explanations for the sources of nonlinearity in search and matching models indicate that they are not fully understood. This paper derives an analytical solution to a textbook model that highlights the mechanisms that generate nonlinearity and quantifies their contributions. Procyclical variation in the matching elasticity creates nonlinearity in the job finding rate, which interacts with the law of motion for unemployment. These results show the matching function choice is not innocuous. Quantitatively, the Den Haan et al. (2000) matching function more than doubles the skewness of unemployment and welfare cost of business cycles, compared to the Cobb-Douglas specification.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115764868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper uses U.S. county-level data to study the determinants and effects of the Paycheck Protection Program (PPP). The paper first overviews the timeline and institutional aspects of the PPP, implemented in the second quarter of 2020 and worth about $669 billion in forgivable small business loans guaranteed by the Small Business Administration (SBA). It then studies the determinants of the county-level ratios of PPP loans per job lost during the original unemployment surge associated with the onset of the COVID-19 pandemic in late March 2020 and finds that it does not appear to be a major driver of the PPP loan concentration; instead, it was primarily driven by the local banking conditions and demographic factors. The second part of this paper uses the method of local projections to determine whether the participation in the PPP program improved economic conditions following its implementation. Impulse responses in the standard linear framework are positive and statistically significant, albeit economically negligible, suggesting that the PPP was entirely ineffective in stabilizing labor market conditions. Extending the framework to state-dependent local projections reverses this result: PPP lending had a significant effect on reducing unemployment on average and especially in counties with strong banking liquidity and an educated labor force.
{"title":"Paycheck Protection Program: County-Level Determinants and Effect on Unemployment","authors":"P. Kapinos","doi":"10.24149/WP2105","DOIUrl":"https://doi.org/10.24149/WP2105","url":null,"abstract":"This paper uses U.S. county-level data to study the determinants and effects of the Paycheck Protection Program (PPP). The paper first overviews the timeline and institutional aspects of the PPP, implemented in the second quarter of 2020 and worth about $669 billion in forgivable small business loans guaranteed by the Small Business Administration (SBA). It then studies the determinants of the county-level ratios of PPP loans per job lost during the original unemployment surge associated with the onset of the COVID-19 pandemic in late March 2020 and finds that it does not appear to be a major driver of the PPP loan concentration; instead, it was primarily driven by the local banking conditions and demographic factors. The second part of this paper uses the method of local projections to determine whether the participation in the PPP program improved economic conditions following its implementation. Impulse responses in the standard linear framework are positive and statistically significant, albeit economically negligible, suggesting that the PPP was entirely ineffective in stabilizing labor market conditions. Extending the framework to state-dependent local projections reverses this result: PPP lending had a significant effect on reducing unemployment on average and especially in counties with strong banking liquidity and an educated labor force.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117304281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An emerging literature documents a link between central bank quantitative easing (QE) and financial institution credit risk-taking. This paper tests the complementary hypothesis that QE may also affect financial risk-taking. We study Agency MREITs – levered shadow banks that invest in guaranteed U.S. Agency mortgage-backed securities (MBS) and that are principally funded with repo debt. We first show that Agency MREIT asset growth is inversely related to the Federal Reserve’s Agency MBS purchases, reflecting investor portfolio rebalancing. We then document that Agency MREITs increased financial leverage during the later stages of QE, consistent with “reaching for yield” behavior. However, Agency MREITs countered the heightened solvency risk by extending repo maturity and increased hedging of their funding costs to reduce liquidity and interest rate risk. The findings suggest that research linking QE to increased credit risk-taking should account for contemporaneous changes in financing choices and risk management.
{"title":"Quantitative Easing and Agency MBS Investment and Financing Choices by Mortgage REITs","authors":"W. Frame, Eva Steiner","doi":"10.1111/1540-6229.12355","DOIUrl":"https://doi.org/10.1111/1540-6229.12355","url":null,"abstract":"An emerging literature documents a link between central bank quantitative easing (QE) and financial institution credit risk-taking. This paper tests the complementary hypothesis that QE may also affect financial risk-taking. We study Agency MREITs – levered shadow banks that invest in guaranteed U.S. Agency mortgage-backed securities (MBS) and that are principally funded with repo debt. We first show that Agency MREIT asset growth is inversely related to the Federal Reserve’s Agency MBS purchases, reflecting investor portfolio rebalancing. We then document that Agency MREITs increased financial leverage during the later stages of QE, consistent with “reaching for yield” behavior. However, Agency MREITs countered the heightened solvency risk by extending repo maturity and increased hedging of their funding costs to reduce liquidity and interest rate risk. The findings suggest that research linking QE to increased credit risk-taking should account for contemporaneous changes in financing choices and risk management.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123116528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We provide evidence on the dynamic effects of fuel price shocks, shipping demand shocks, and shipping supply shocks on real dry bulk freight rates in the long run. We first analyze a new and large dataset on dry bulk freight rates for the period from 1850 to 2020, finding that they followed a downward but undulating path with a cumulative decline of 79%. Next, we turn to understanding the drivers of booms and busts in the dry bulk shipping industry, finding that shipping demand shocks strongly dominate all others as drivers of real dry bulk freight rates in the long run. Furthermore, while shipping demand shocks have increased in importance over time, shipping supply shocks in particular have become less relevant.
{"title":"Dry Bulk Shipping and the Evolution of Maritime Transport Costs, 1850-2020","authors":"D. Jacks, M. Stuermer","doi":"10.24149/WP2102","DOIUrl":"https://doi.org/10.24149/WP2102","url":null,"abstract":"We provide evidence on the dynamic effects of fuel price shocks, shipping demand shocks, and shipping supply shocks on real dry bulk freight rates in the long run. We first analyze a new and large dataset on dry bulk freight rates for the period from 1850 to 2020, finding that they followed a downward but undulating path with a cumulative decline of 79%. Next, we turn to understanding the drivers of booms and busts in the dry bulk shipping industry, finding that shipping demand shocks strongly dominate all others as drivers of real dry bulk freight rates in the long run. Furthermore, while shipping demand shocks have increased in importance over time, shipping supply shocks in particular have become less relevant.","PeriodicalId":322311,"journal":{"name":"Federal Reserve Bank of Dallas, Working Papers","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127279476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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