{"title":"Revisiting the effects of conventional and unconventional monetary policies","authors":"Eul Noh","doi":"10.1002/jae.3052","DOIUrl":"10.1002/jae.3052","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper extends the discussion on the effects of the two distinctive monetary surprises in the literature. First, we show that the proxy of conventional monetary shock Granger causes the endogenous variables in the vector autoregressive model. Second, we provide evidence that the existing model can be exposed to a weak instrument problem. With our alternative model mitigating these concerns, the second monetary shock can be interpreted as unconventional monetary news in general. The estimation results show contractionary effect of the unconventional policy. We find increases in output after a positive conventional monetary surprise, suggesting an important Fed's information effect.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification and forecasting of bull and bear markets using multivariate returns","authors":"Jia Liu, John M. Maheu, Yong Song","doi":"10.1002/jae.3048","DOIUrl":"10.1002/jae.3048","url":null,"abstract":"<div>\u0000 \u0000 <p>Bull and bear market identification generally focuses on a broad index of returns through a univariate analysis. This paper proposes a new approach to identify and forecast bull and bear markets through multivariate returns. The model assumes that all assets are directed by a common discrete state variable from a hierarchical Markov switching model. The hierarchical specification allows the cross-section of state-specific means and variances to differ over bull and bear markets. We investigate several empirically realistic specifications that permit feasible estimation even with 100 assets. Our results show that the multivariate framework provides competitive bull and bear regime identification and improves portfolio performance and density prediction compared with several benchmark models including univariate Markov switching models.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring skill distribution tails through stochastic dominance","authors":"Petra Besenhard","doi":"10.1002/jae.3043","DOIUrl":"10.1002/jae.3043","url":null,"abstract":"<div>\u0000 \u0000 <p>Location choices of differently skilled workers are analyzed in previous work on labor mobility, which proposes a model that suggests thicker tails in the skill distributions of large cities. This paper replicates the empirical findings of this work by using quantile regression and density plots as employed in the existing study, while also suggesting an alternative testing method for thick tails in the form of an initial stochastic dominance test. The test reveals clear evidence of a thicker lower tail, but the results are less clear for the upper tail, which raises some questions on how to best handle extreme upper tails of skill distributions.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Re-examining the relationship between patience, risk-taking, and human capital investment across countries*","authors":"Alexandra de Gendre, Jan Feld, Nicolás Salamanca","doi":"10.1002/jae.3045","DOIUrl":"10.1002/jae.3045","url":null,"abstract":"<p>Hanushek et al. (2022) show that students in countries in which people are more patient and less risk-taking perform better in the Programme for International Student Assessment (PISA) test. In this paper, we probe the robustness of this study. Our narrow replication shows that most of the results are robust to alternative model specifications. Our broad replication shows that the main results are robust to measuring student performance with data from the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS) instead of PISA.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimating the price elasticity of gasoline demand in correlated random coefficient models with endogeneity","authors":"Michael Bates, Seolah Kim","doi":"10.1002/jae.3042","DOIUrl":"10.1002/jae.3042","url":null,"abstract":"<div>\u0000 \u0000 <p>We propose a per-cluster instrumental variable (PCIV) approach for estimating linear correlated random coefficient models in the presence of contemporaneous endogeneity and two-way fixed effects. This approach estimates heterogeneous effects and aggregates them to population averages. We demonstrate consistency, showing robustness over standard estimators, and provide analytic standard errors for robust inference. In Monte Carlo simulation, PCIV performs relatively well in finite samples in either dimension. We apply PCIV in estimating the price elasticity of gasoline demand using state fuel taxes as instrumental variables. We find significant elasticity heterogeneity and more elastic gasoline demand on average than with standard estimators.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140368966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Iván Fernández-Val, Aico van Vuuren, Francis Vella, Franco Peracchi
{"title":"Hours worked and the US distribution of real annual earnings 1976–2019","authors":"Iván Fernández-Val, Aico van Vuuren, Francis Vella, Franco Peracchi","doi":"10.1002/jae.3039","DOIUrl":"10.1002/jae.3039","url":null,"abstract":"<div>\u0000 \u0000 <p>We examine the impact of annual hours worked on annual earnings by decomposing changes in the real annual earnings distribution into composition, structural, and hours effects. We do so via a nonseparable simultaneous model of hours, wages, and earnings. Using the Current Population Survey for the survey years 1976–2019, we find that changes in the female distribution of annual hours of work are important in explaining movements in inequality in female annual earnings. This captures the substantial changes in their employment behavior over this period. Movements in the male hours' distribution only affect the lower part of their earnings distribution and reflect the sensitivity of these workers' annual hours of work to cyclical factors.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140300086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties","authors":"Fei Jin, Lung-fei Lee, Kai Yang","doi":"10.1002/jae.3046","DOIUrl":"10.1002/jae.3046","url":null,"abstract":"<div>\u0000 \u0000 <p>We provide a novel analytic procedure to construct best linear and quadratic moments of the generalized method of moments estimation for a large class of cross-sectional network and spatial econometric models. These moments generate an estimator that is asymptotically more efficient than the quasi-maximum likelihood estimator when the disturbances follow a non-normal and unknown distribution. We apply this procedure to a high-order spatial autoregressive model with spatial errors, where the disturbances are heteroskedastic. Two normality tests of disturbances are developed. We apply the model to employment data in US counties, which demonstrates spatial interdependence patterns of regional employment growth.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Statistical identification in panel structural vector autoregressive models based on independence criteria","authors":"Helmut Herwartz, Shu Wang","doi":"10.1002/jae.3044","DOIUrl":"10.1002/jae.3044","url":null,"abstract":"<p>This paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural innovations at the pooled level. We demonstrate robustness of the method under cross-sectional correlation and heterogeneity through simulation experiments. In an empirical application on monetary policy transmission in the Euro area, we find that bond spreads rise significantly after an unexpected monetary tightening. Furthermore, the central bank responds to offset effects of adverse financial shocks. Additionally, we document sizable heterogeneity in country-specific output responses.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayesian collapsed Gibbs sampling for a stochastic volatility model with a Dirichlet process mixture","authors":"Frank C. Z. Wu","doi":"10.1002/jae.3040","DOIUrl":"10.1002/jae.3040","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper replicates the results of the stochastic volatility–Dirichlet process mixture (SV-DPM) models proposed in Jensen and Maheu (2010) in both a narrow and a wide sense. By using a normal-Wishart prior and the collapsed Gibbs sampling method, our algorithm can be applied for more general settings, and it is more efficient for sampling the Dirichlet process mixture. For the stochastic volatility component, we adopt the method in Chan (2017) to further increase the overall efficiency of our algorithm. Using the same dataset, we obtain mixed results. Some of the results have significant differences. If we use recent time period dataset, which includes the COVID-19 pandemic period, the log market portfolio volatility seems to increase in terms of the number of clusters and size of magnitude.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140099306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"US fiscal policy shocks: Proxy-SVAR overidentification via GMM","authors":"Allan W. Gregory, James McNeil, Gregor W. Smith","doi":"10.1002/jae.3038","DOIUrl":"10.1002/jae.3038","url":null,"abstract":"<div>\u0000 \u0000 <p>Using external instruments, one can recover the effects of individual shocks without fully identifying a vector autoregression (VAR). We show that fully or almost fully instrumenting a VAR—that is, using an instrument for each shock—allows one to overidentify the model by incorporating the condition that the structural shocks are uncorrelated, via the generalized method of moments (GMM). We apply our approach to a fiscal VAR for the United States over 1948–2019, where the overidentifying restrictions are not rejected. The overidentified structural vector autoregression (SVAR) yields (a) greater precision in estimating impulse response functions and multipliers and (b) measures of the effects of nonfiscal shocks even when there is no instrument for them.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}