{"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":"39 4","pages":"620-639"},"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":"39 4","pages":"697-704"},"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":"39 4","pages":"607-619"},"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}
{"title":"Should we trust cross-sectional multiplier estimates?","authors":"Fabio Canova","doi":"10.1002/jae.3041","DOIUrl":"10.1002/jae.3041","url":null,"abstract":"<div>\u0000 \u0000 <p>I examine the properties of cross-sectional estimators of multipliers, elasticities, or pass-throughs when a conventional spatial macroeconomic specification generates the data. A number of important biases plague standard estimates; the most relevant one occurs when the units display heterogeneous dynamics. Methods that work well in this situation are suggested. An experimental setting shows the magnitude of the biases cross-sectional estimators display. Average estimates of local fiscal multipliers in the US states are compared and contrasted.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 4","pages":"589-606"},"PeriodicalIF":2.1,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055223","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":"A flexible stochastic production frontier model with panel data","authors":"Taining Wang, Feng Yao, Subal C. Kumbhakar","doi":"10.1002/jae.3033","DOIUrl":"10.1002/jae.3033","url":null,"abstract":"<div>\u0000 \u0000 <p>We propose a flexible stochastic production frontier model with fixed effects for the panel data in which the semiparametric frontier is additive with bivariate interactions. To avoid potential misspecification and/or “wrong skew problem” due to distributional assumptions, we model the conditional mean of the inefficiency to depend on environmental variables and to be known up to a vector of parameters. We propose a difference-based estimator for parameters characterizing the conditional mean of the inefficiency term, a profile series estimator, and a kernel-based one-step backfitting estimator for the frontier to facilitate inference. We establish their asymptotic properties and show that each component in the frontier estimated by the kernel-based backfitting has the same asymptotic distribution as the one estimated with the true knowledge on the other components in the frontier (i.e., the oracle property). Through a Monte Carlo study, we demonstrate that the proposed estimators perform well in finite samples. Utilizing a panel of Chinese firm-level data in 2000–2006, we apply our method to estimate the frontier and efficiency scores and conclude that export plays a significant role in reducing the efficiency of firms.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 4","pages":"564-588"},"PeriodicalIF":2.1,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140090084","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}
Guido Ascari, Qazi Haque, Leandro M. Magnusson, Sophocles Mavroeidis
{"title":"Empirical evidence on the Euler equation for investment in the US","authors":"Guido Ascari, Qazi Haque, Leandro M. Magnusson, Sophocles Mavroeidis","doi":"10.1002/jae.3037","DOIUrl":"10.1002/jae.3037","url":null,"abstract":"<p>Is the typical specification of the Euler equation for investment employed in dynamic stochastic general equilibrium (DSGE) models consistent with aggregate macro data? The answer is yes using state-of-the-art econometric methods that are robust to weak instruments and exploit information in possible structural changes. Unfortunately, however, there is very little information about the values of the parameters in aggregate data because investment is unresponsive to changes in capital utilization and the real interest rate. Bayesian estimation using fully specified DSGE models is more accurate due to both informative priors and cross-equation restrictions.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 4","pages":"543-563"},"PeriodicalIF":2.1,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140019576","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":"Peer desirability and academic achievement","authors":"Adrian Mehic","doi":"10.1002/jae.3036","DOIUrl":"10.1002/jae.3036","url":null,"abstract":"<p>Using the random assignment of university engineering students to peer groups during introductory freshmen weeks, this paper studies how a student's parental income and facial attractiveness affect the grade outcomes of peers. The results show that exposure to highly desirable peers with respect to socioeconomic background and beauty improves grades. The results operate chiefly through a direct spillover channel and also through an indirect marriage market channel, through which exposure to high-desirability peers improves well-being. A field experiment suggests that the marriage market mechanism is likely to be limited to students not currently in a romantic relationship.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 4","pages":"525-542"},"PeriodicalIF":2.1,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140003996","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":"How does the dramatic rise of nonresponse in the Current Population Survey impact labor market indicators?","authors":"Robert Bernhardt, David Munro, Erin L. Wolcott","doi":"10.1002/jae.3035","DOIUrl":"10.1002/jae.3035","url":null,"abstract":"<div>\u0000 \u0000 <p>Within a decade, the share of households refusing to participate in the Current Population Survey (CPS) tripled. We show households that refuse 1 month but respond in an adjacent month account for an important part of the rise. Leveraging the labor force status of survey participants in the months surrounding their nonresponse, we find that rising refusals suppressed the measured labor force participation rate and employment–population ratio but had little effect on the unemployment rate. Notably, nonresponse bias accounts for at least 10% of the reported decline in the labor force participation rate from 2000 to 2020.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 3","pages":"498-512"},"PeriodicalIF":2.1,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139968505","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":"A high-dimensional multinomial logit model","authors":"Didier Nibbering","doi":"10.1002/jae.3034","DOIUrl":"10.1002/jae.3034","url":null,"abstract":"<p>The number of parameters in a standard multinomial logit model increases linearly with the number of choice alternatives and number of explanatory variables. Because many modern applications involve large choice sets with categorical explanatory variables, which enter the model as large sets of binary dummies, the number of parameters in a multinomial logit model is often large. This paper proposes a new method for data-driven two-way parameter clustering over outcome categories and explanatory dummy categories in a multinomial logit model. A Bayesian Dirichlet process mixture model encourages parameters to cluster over the categories, which reduces the number of unique model parameters and provides interpretable clusters of categories. In an empirical application, we estimate the holiday preferences of 11 household types over 49 holiday destinations and identify a small number of household segments with different preferences across clusters of holiday destinations.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 3","pages":"481-497"},"PeriodicalIF":2.1,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139919502","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":"Advance layoff notices and aggregate job loss","authors":"Pawel M. Krolikowski, Kurt G. Lunsford","doi":"10.1002/jae.3032","DOIUrl":"10.1002/jae.3032","url":null,"abstract":"<div>\u0000 \u0000 <p>We collect data from Worker Adjustment and Retraining Notification (WARN) Act notices and establish their usefulness as an indicator of aggregate job loss. The number of workers affected by WARN notices (“WARN layoffs”) leads state-level initial unemployment insurance claims and unemployment rate (UR) and private employment changes. WARN layoffs comove with aggregate layoffs from Mass Layoff Statistics and the Job Openings and Labor Turnover Survey but are timelier and cover a longer sample. In a vector autoregression, changes in WARN layoffs lead UR changes and job separations. Finally, they improve pseudo real-time forecasts of the UR and private employment changes.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 3","pages":"462-480"},"PeriodicalIF":2.1,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139919559","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}