Christophe Bellégo , David Benatia , Vincent Dortet-Bernadet
{"title":"The chained difference-in-differences","authors":"Christophe Bellégo , David Benatia , Vincent Dortet-Bernadet","doi":"10.1016/j.jeconom.2024.105783","DOIUrl":"10.1016/j.jeconom.2024.105783","url":null,"abstract":"<div><div>This paper studies the identification, estimation, and inference of long-term (binary) treatment effect parameters when balanced panel data is not available, or consists of only a subset of the available data. We develop a new estimator: the chained difference-in-differences, which leverages the overlapping structure of many unbalanced panel data sets. This approach consists in aggregating a collection of short-term treatment effects estimated on multiple incomplete panels. Our estimator accommodates (1) multiple time periods, (2) variation in treatment timing, (3) treatment effect heterogeneity, (4) general missing data patterns, and (5) sample selection on observables. We establish the asymptotic properties of the proposed estimator and discuss identification and efficiency gains in comparison to existing methods. Finally, we illustrate its relevance through (i) numerical simulations, and (ii) an application about the effects of an innovation policy in France.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105783"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526861","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":"The term structure of macroeconomic risks at the effective lower bound","authors":"Guillaume Roussellet","doi":"10.1016/j.jeconom.2023.01.005","DOIUrl":"10.1016/j.jeconom.2023.01.005","url":null,"abstract":"<div><div>This paper proposes a new macro-finance model that solves the tension between tractability, flexibility in macroeconomic<span><span><span> dynamics, and consistency of the term structures of treasury yields with the effective lower bound (ELB). I use the term structures of U.S. nominal and real treasury yields from 1990 to explore the interdependence between </span>inflation expectations, volatility, and </span>monetary policy<span> at the ELB. The estimation reveals that real yields stay elevated during the ELB due to large premia and deflation fears, produced by a persistent shift in inflation<span> dynamics, with low average inflation and heightened inflation volatility.</span></span></span></div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105383"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45139733","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":"Regularizing stock return covariance matrices via multiple testing of correlations","authors":"Richard Luger","doi":"10.1016/j.jeconom.2024.105753","DOIUrl":"10.1016/j.jeconom.2024.105753","url":null,"abstract":"<div><div>This paper develops a large-scale inference approach for the regularization of stock return covariance matrices. The framework allows for the presence of heavy tails and multivariate GARCH-type effects of unknown form among the stock returns. The approach involves simultaneous testing of all pairwise correlations, followed by setting non-statistically significant elements to zero. This adaptive thresholding is achieved through sign-based Monte Carlo resampling within multiple testing procedures, controlling either the traditional familywise error rate, a generalized familywise error rate, or the false discovery proportion. Subsequent shrinkage ensures that the final covariance matrix estimate is positive definite and well-conditioned while preserving the achieved sparsity. Compared to alternative estimators, this new regularization method demonstrates strong performance in simulation experiments and real portfolio optimization.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105753"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141056593","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":"Simulation-based estimation with many auxiliary statistics applied to long-run dynamic analysis","authors":"Bertille Antoine , Wenqian Sun","doi":"10.1016/j.jeconom.2024.105814","DOIUrl":"10.1016/j.jeconom.2024.105814","url":null,"abstract":"<div><div>The existing asymptotic theory for estimators obtained by simulated minimum distance does not cover situations in which the number of components of the auxiliary statistics (or number of matched “moments”) is large — typically larger than the sample size. We establish the consistency of the simulated minimum distance estimator in this situation and derive its asymptotic distribution.</div><div>Our estimator is easy to implement and allows us to exploit all the informational content of a large number of auxiliary statistics without having to, (i) know these functions explicitly, or (ii) choose <em>a priori</em> which functions are the most informative. As a result, we are able to exploit, among other things, long-run information. We illustrate the implementation of the proposed method through Monte-Carlo simulation experiments based on small- and medium-scale New Keynesian models. These examples highlight how to conveniently exploit valuable information from matching a large number of impulse responses including at long-run horizons.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105814"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141845397","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}
Yacine Aït-Sahalia , Felix Matthys , Emilio Osambela , Ronnie Sircar
{"title":"When uncertainty and volatility are disconnected: Implications for asset pricing and portfolio performance","authors":"Yacine Aït-Sahalia , Felix Matthys , Emilio Osambela , Ronnie Sircar","doi":"10.1016/j.jeconom.2023.105654","DOIUrl":"10.1016/j.jeconom.2023.105654","url":null,"abstract":"<div><div>We analyze an environment where the uncertainty in the equity market return and its volatility are both stochastic and may be potentially disconnected. We solve a representative investor’s optimal asset allocation and derive the resulting conditional equity premium and risk-free rate in equilibrium. Our empirical analysis shows that the equity premium appears to be earned for facing uncertainty, especially high uncertainty that is disconnected from lower volatility, rather than for facing volatility as traditionally assumed. Incorporating the possibility of a disconnect between volatility and uncertainty significantly improves portfolio performance, over and above the performance obtained by conditioning on volatility only.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105654"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139951483","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":"Reprint of: Finite underidentification","authors":"Enrique Sentana","doi":"10.1016/j.jeconom.2025.105947","DOIUrl":"10.1016/j.jeconom.2025.105947","url":null,"abstract":"<div><div>I adapt the Generalised Method of Moments to deal with nonlinear models in which a finite number of isolated parameter values satisfy the moment conditions. I also study the closely related class of first-order underidentified models, whose expected Jacobian is rank deficient but not necessarily zero. In both cases, my proposed procedures exploit the underidentification structure to yield parameter estimators and underidentification tests within a standard asymptotically normal GMM framework. I study nonlinear models with and without separation of data and parameters. I also illustrate my proposed inference procedures with applications to production function estimation and dynamic panel data models.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105947"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526831","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}
David T. Frazier , Eric Renault , Lina Zhang , Xueyan Zhao
{"title":"Weak identification in discrete choice models","authors":"David T. Frazier , Eric Renault , Lina Zhang , Xueyan Zhao","doi":"10.1016/j.jeconom.2024.105866","DOIUrl":"10.1016/j.jeconom.2024.105866","url":null,"abstract":"<div><div>We study the impact of weak identification in discrete choice models, and provide insights into the determinants of identification strength in these models. Using these insights, we propose a novel test that can consistently detect weak identification in commonly applied discrete choice models, such as probit, logit, and many of their extensions. Furthermore, we demonstrate that when the null hypothesis of weak identification is rejected, Wald-based inference can be carried out using standard formulas and critical values. A Monte Carlo study compares our proposed testing approach against commonly applied weak identification tests. The results simultaneously demonstrate the good performance of our approach and the fundamental failure of using conventional weak identification tests for linear models in the discrete choice model context. Lastly, we apply our approach in two empirical examples: married women labor force participation, and US food aid and civil conflicts.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105866"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526832","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}
Veronika Czellar , René Garcia , François Le Grand
{"title":"Uncovering asset market participation from household consumption and income","authors":"Veronika Czellar , René Garcia , François Le Grand","doi":"10.1016/j.jeconom.2024.105867","DOIUrl":"10.1016/j.jeconom.2024.105867","url":null,"abstract":"<div><div>We propose an asset pricing model featuring time-varying limited participation in both bond and stock markets and household heterogeneity. Households participate in financial markets with a certain probability that depends on their individual income and on asset market conditions. We use indirect inference to uncover individual asset market participation from individual consumption data and asset prices. Our model very accurately reproduces the proportions of stockholders in the Survey of Consumer Finances over three-year intervals, provides a reasonable estimate of stock market participation costs, and is able to price characteristic-based stock portfolios with the top decile of households identified as stockholders.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105867"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526837","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}
Marie-Claude Beaulieu , Jean-Marie Dufour , Lynda Khalaf
{"title":"Identification-robust and simultaneous inference in multifactor asset pricing models","authors":"Marie-Claude Beaulieu , Jean-Marie Dufour , Lynda Khalaf","doi":"10.1016/j.jeconom.2024.105915","DOIUrl":"10.1016/j.jeconom.2024.105915","url":null,"abstract":"<div><div>This paper proposes exact identification-robust confidence sets for the zero-beta rate and ex-post factor prices in asset pricing models. Exploiting the information from the cross-sectional intercept allows us to impose or formally test model-consistent restrictions, including those resulting from traded factors in excess of the zero beta-rate or from return spreads. Analytical projection-based solutions for confidence set outcomes are developed. The proposed procedures are extended to the case of missing factors. Empirical and simulation results with traded and non-traded factors show that model-consistent restrictions and elusive factors can materially affect model fit, identification, inference and temporal constancy of pricing influence.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105915"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526836","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}