Institution
Federal Reserve Bank of Dallas
Other•Dallas, Texas, United States•
About: Federal Reserve Bank of Dallas is a other organization based out in Dallas, Texas, United States. It is known for research contribution in the topics: Monetary policy & Inflation. The organization has 196 authors who have published 994 publications receiving 35508 citations.
Papers published on a yearly basis
Papers
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TL;DR: Baumeister and Hamilton as discussed by the authors argue that every critique of their work on oil markets by Kilian and Zhou (2019a) is without merit and make the case that key aspects of the economic and econometric analysis in the widely used oil market model of Kilian, Murphy and its precursors are incorrect.
Abstract: Baumeister and Hamilton (2019a) assert that every critique of their work on oil markets by Kilian and Zhou (2019a) is without merit. In addition, they make the case that key aspects of the economic and econometric analysis in the widely used oil market model of Kilian and Murphy (2014) and its precursors are incorrect. Their critiques are also directed at other researchers who have worked in this area and, more generally, extend to research using structural VAR models outside of energy economics. The purpose of this paper is to help the reader understand what the real issues are in this debate. The focus is not only on correcting important misunderstandings in the recent literature, but on the substantive and methodological insights generated by this exchange, which are of broader interest to applied researchers.
7 citations
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TL;DR: In this paper, the authors study the impact of the COVID-19 pandemic on the location demand for housing and find that the pandemic has led to a shift in housing demand away from neighborhoods with high population density.
Abstract: We study the impact of the COVID-19 pandemic on the location demand for housing. We find that the pandemic has led to a shift in housing demand away from neighborhoods with high population density. The reduced demand for density is driven partially by the diminished need for living close to telework-compatible jobs and the declining value of access to consumption amenities. Neighborhoods with high pre-COVID-19 home values also see a greater drop in housing demand. We also find significant shift in housing demand away from large cities, though the magnitude is smaller.
7 citations
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TL;DR: In this article, the authors extend a standard New Keynesian model by introducing anticipated shocks to inflation, output, and interest rates, and by incorporating forward-looking, forecast-targeting Taylor rules, parsimoniously modeled through the presence of an expected future interest rate term in the Taylor rule.
Abstract: This paper extends a standard New Keynesian model by introducing anticipated shocks to inflation, output, and interest rates, and by incorporating forward-looking, forecast-targeting Taylor rules. The latter aspect is parsimoniously modeled through the presence of an expected future interest rate term in the Taylor rule that recent literature has found to be economically and statistically important in a variety of settings without anticipated shocks. Using Bayesian econometric methods, we find that the presence of anticipated shocks improves the model's fit to the U.S. data but substantially decreases the weight on future macroeconomic variables in the forward-looking Taylor rule. Our results suggest that, although communicating its intentions regarding future monetary policy conduct, as modeled by anticipated monetary shocks, plays an important role for the Fed, responding to its expectations of future macroeconomic conditions does not. Furthermore, we conduct extensive robustness checks with respect to modeling the forward-looking specification of the Taylor rule that confirm our baseline results.
7 citations
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TL;DR: The authors argue that technological change and globalization mean there is less need to admit immigrant workers, but such arguments fail to account for both recent data and historical experience. But they do not consider the costs of immigration, which are disproportionately borne by the least educated.
Abstract: U.S. GDP growth is anticipated to remain sluggish over the next decade, and slow labor force growth is a key underlying reason. Admitting more immigrants is one way U.S. policymakers can bolster growth in the workforce and the economy. A larger role for immigrant workers also can help mitigate other symptoms of the economy’s long-run malaise, such as low productivity growth, declining domestic geographic mobility, and falling entrepreneurship, as well as help address the looming mismatch between the skills U.S. employers want and the skills U.S. workers have. While some might argue that technological change and globalization mean there is less need to admit immigrant workers, such arguments fail to account for both recent data and historical experience. Of course, immigration—like anything else—is not without costs, which are disproportionately borne by the least educated. A plan to increase employment-based immigration as a way to spur economic growth could be paired with new programs to help low-skilled U.S. natives and earlier immigrants so that the benefits of immigration are shared more equitably.
7 citations
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TL;DR: In this article, a simple stock-flow matching model with fully informed market participants is considered, where prices are assumed to be set ex-ante and the unique equilibrium is characterized by price dispersion due to the idiosyncratic match payoffs in a marketplace with full information.
7 citations
Authors
Showing all 202 results
Name | H-index | Papers | Citations |
---|---|---|---|
Lutz Kilian | 81 | 251 | 39552 |
Peter Egger | 72 | 457 | 17654 |
Francis E. Warnock | 41 | 125 | 8657 |
Rebel A. Cole | 41 | 149 | 9092 |
Finn E. Kydland | 38 | 123 | 21288 |
Daniel L. Millimet | 38 | 159 | 5196 |
Joseph Tracy | 35 | 90 | 4286 |
Marc P. Giannoni | 33 | 85 | 5131 |
Ping Wang | 33 | 241 | 4263 |
W. Scott Frame | 32 | 85 | 4616 |
Kei-Mu Yi | 30 | 81 | 7481 |
John V. Duca | 29 | 145 | 3535 |
Stephen P. A. Brown | 28 | 118 | 3455 |
Kathy J. Hayes | 27 | 85 | 3075 |
Alexander Chudik | 26 | 103 | 3907 |