Journal of Applied Econometrics最新文献

{"title":"Fast Likelihood-Free Parameter Estimation for Lévy Processes","authors":"Nicolas Coloma,&nbsp;William Kleiber","doi":"10.1002/jae.70075","DOIUrl":"https://doi.org/10.1002/jae.70075","url":null,"abstract":"<div>\u0000 \u0000 <p>Lévy processes are widely used in financial modeling due to their ability to capture discontinuities and heavy tails, which are common in high-frequency asset return data. However, parameter estimation remains a challenge when associated likelihoods are unavailable or costly to compute. We propose a fast and accurate method for Lévy parameter estimation using the neural Bayes estimation (NBE) framework—a simulation-based, likelihood-free approach that leverages permutation-invariant neural networks to approximate Bayes estimators. We contribute new theoretical results, showing that NBE results in consistent estimators whose risk converges to that of the Bayes estimator under mild conditions. Moreover, through extensive simulations across several Lévy models, we show that NBE outperforms traditional methods in both accuracy and runtime, while also enabling two complementary approaches to uncertainty quantification. We illustrate our approach on a challenging high-frequency cryptocurrency return dataset, where the method captures evolving parameter dynamics and delivers reliable and interpretable inference at a fraction of the computational cost of traditional methods. We investigate nearly a decade of high-frequency Bitcoin returns, requiring less than one minute to estimate parameters under the proposed approach.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"862-876"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099433","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":"Multivariate Trend Inflation in the United States and the Euro Area","authors":"Max-Sebastian Dovì","doi":"10.1002/jae.70064","DOIUrl":"https://doi.org/10.1002/jae.70064","url":null,"abstract":"<div>\u0000 \u0000 <p>I provide a precision-sampler-based replication of the multivariate unobserved component stochastic volatility outlier-adjusted model of Stock and Watson (2016) applied to inflation in the United States and the Euro Area (EA). I find a substantial post-2020 increase in trend inflation for both the United States and the EA, and estimate end-2024 trend inflation at 2.3 and 2.0 percent, respectively.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"894-899"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099695","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":"Estimation of Heterogeneous Panel Data Models With Mixed Sampling Frequencies","authors":"Haoran Li,&nbsp;Haoyang Li,&nbsp;Naifu Xiao,&nbsp;Yimin Yang","doi":"10.1002/jae.70067","DOIUrl":"https://doi.org/10.1002/jae.70067","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper studies heterogeneous mixed-frequency panel data models, focusing on linear specifications that allow heterogeneity in both aggregation weights and slope coefficients. To address potential correlations between the heterogeneity and the covariates, we first show that, under additional normalization conditions, the mean-group estimator delivers consistent and asymptotically normal slope estimates but biased weights estimators. As an alternative, we propose a correlated random effects estimator using a generalized Mundlak specification. We further discuss the implementation of these two estimators when covariates are observed at substantially higher sampling frequencies. Monte Carlo simulations are conducted to assess their finite-sample properties. As an empirical illustration, we revisit the impact of temperature fluctuations on economic growth using the proposed framework.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"731-744"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149100594","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":"Conditional Randomization Tests for the Specification of Interference Structure","authors":"Tadao Hoshino,&nbsp;Takahide Yanagi","doi":"10.1002/jae.70076","DOIUrl":"https://doi.org/10.1002/jae.70076","url":null,"abstract":"<p>This study proposes specification tests for interference structure in causal inference with spillovers. We focus on experimental settings in which the treatment assignment mechanism is known. To test whether a given exposure mapping adequately summarizes the true interference structure, we develop conditional randomization tests by utilizing the hierarchical relationship between the null and alternative exposure mappings. When there are multiple candidate exposure mappings of interest, we propose a sequential specification testing procedure that controls the false discovery rate. Through extensive simulation exercises, we demonstrate that our tests have desirable size properties and satisfactory power. To illustrate the proposed methods, we revisit two existing social network experiments: One on farmers' insurance adoption and another on anti-conflict education programs.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"791-805"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.70076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149100394","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":"Labor Market Institutions, Fiscal Multipliers, and Macroeconomic Volatility","authors":"Maximilian Boeck,&nbsp;Jesús Crespo Cuaresma,&nbsp;Christian Glocker","doi":"10.1002/jae.70078","DOIUrl":"https://doi.org/10.1002/jae.70078","url":null,"abstract":"<p>How do labor market institutions shape the transmission of government spending shocks and macroeconomic volatility? We develop a theoretical model in which labor market institutions affect fiscal transmission through their effect on wage rigidity, job separation, and matching frictions. We estimate an interacted panel vector autoregressive model for 16 OECD economies and study how macroeconomic responses to government spending shocks vary with institutional labor market characteristics. In line with our theoretical predictions, we show that institutions that stabilize employment and wages tend to reduce output volatility and attenuate the response of output and employment to government spending shocks.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"806-820"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.70078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149100497","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":"Triply Robust Panel Estimators","authors":"Susan Athey,&nbsp;Guido Imbens,&nbsp;Zhaonan Qu,&nbsp;Davide Viviano","doi":"10.1002/jae.70061","DOIUrl":"https://doi.org/10.1002/jae.70061","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper studies estimation of causal effects in a panel data setting. We introduce a new estimator, the Triply Robust Panel (TROP) estimator, that combines <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mi>i</mi>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation>$$ (i) $$</annotation>\u0000 </semantics></math> a flexible model for the potential outcomes based on a low-rank factor structure on top of a two-way-fixed effect specification, with <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mi>i</mi>\u0000 <mi>i</mi>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation>$$ (ii) $$</annotation>\u0000 </semantics></math> unit weights intended to upweight units similar to the treated units and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mi>i</mi>\u0000 <mi>i</mi>\u0000 <mi>i</mi>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation>$$ (iii) $$</annotation>\u0000 </semantics></math> time weights intended to upweight time periods close to the treated time periods. We study the performance of the estimator in a set of simulations designed to closely match several commonly studied real data sets. We find that there is substantial variation in the performance of the estimators across the settings considered. The proposed estimator outperforms Two-Way-Fixed-Effect (TWFE) or Difference-In-Differences (DID), Synthetic Control (SC), Matrix Completion (MC) and Synthetic-Difference-In-Differences (SDID) estimators. We investigate what features of the data generating process lead to this superior performance and assess the relative importance of the three components of the proposed estimator. We have two recommendations. Our preferred strategy is that researchers use simulations closely matched to the data they are interested in, along the lines discussed in this paper, to investigate which estimators work well in their particular setting. A simpler approach is to use more robust estimators such as SDID or the new TROP estimator, which we find to substantially outperform TWFE/DID estimators in many empirically relevant settings.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"745-760"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149100733","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":"Regularization of Synthetic Controls for Policy Evaluation","authors":"Yi-Ting Chen","doi":"10.1002/jae.70071","DOIUrl":"https://doi.org/10.1002/jae.70071","url":null,"abstract":"<div>\u0000 \u0000 <p>We propose a unified framework for interpreting and comparing a broad class of synthetic control (SC) methods. Our framework is built on an analysis of a mean-squared prediction error (MSPE) bound for the counterfactual predicted by a generic SC method, without imposing a specific outcome model. Using this framework, we develop a generalized SC method that provides a more comprehensive regularization of the MSPE bound than several existing SC methods. Through simulation studies and placebo analyses, we demonstrate the effectiveness of the proposed approach in predicting the counterfactual.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"761-775"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149100734","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":"Opportunistic Upskilling in European Labour Markets—Evidence From a Wide Replication","authors":"Anil Yadav,&nbsp;John McHale,&nbsp;Jefferson R. B. Galetti","doi":"10.1002/jae.70072","DOIUrl":"https://doi.org/10.1002/jae.70072","url":null,"abstract":"<div>\u0000 \u0000 <p>We build on Modestino et al., who analysed “opportunistic upskilling” during the 2007 recession in the US, by extending their approach to European labour markets following recent economic shocks. Using a comprehensive dataset of online job postings (2019–2023) and an instrumental variable approach leveraging Ukrainian refugee inflows, we find that increases in labour supply have a significant positive effect on both education and experience requirements. Our findings reinforce the idea that employers opportunistically upskill labour demand in different but challenging macroeconomic contexts. The identification of such patterns, however, depends on the presence of a plausibly exogenous shock to labour markets.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"900-906"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149100177","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":"Housing Supply Elasticities: A Structural Vector Autoregression Approach","authors":"Wesley A. Miller,&nbsp;Anthony W. Orlando,&nbsp;Christian L. Redfearn","doi":"10.1002/jae.70073","DOIUrl":"https://doi.org/10.1002/jae.70073","url":null,"abstract":"<div>\u0000 \u0000 <p>We estimate the first time-varying, county-level index of housing supply elasticities across the United States, using a structural vector autoregression model with sign restrictions to identify the effect of a positive demand shock. This index reveals four features of the supply curve in different local housing markets. First, supply elasticities are low, on average, generating faster price growth than housing unit growth for most of the country. Second, there is significant variation in elasticities across counties, both urban and rural. Third, elasticities have declined in more counties than they have risen over time, particularly in large urban markets. Fourth, these new estimates predict housing quantity growth better than previous models in the literature.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"840-861"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099431","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":"Identifying Peer Effects in Networks with Unobserved Effort and Isolated Students","authors":"Aristide Houndetoungan,&nbsp;Cristelle Kouame,&nbsp;Michael Vlassopoulos","doi":"10.1002/jae.70069","DOIUrl":"https://doi.org/10.1002/jae.70069","url":null,"abstract":"<p>Peer influence on effort devoted to some activity is often studied when effort is unobserved, and the researcher instead observes an outcome that combines effort with other shocks. For instance, in education, achievement measures such as GPA reflect both effort and idiosyncratic GPA shocks. We propose an alternative approach that circumvents this approximation. Our framework distinguishes unobserved shocks to GPA that do not affect effort from preference shocks that do affect effort levels. We show that peer effects estimates obtained using our approach can differ significantly from classical estimates (where effort is approximated) if the network includes isolated students. Applying our approach to data on high school students in the United States, we find that peer effect estimates relying on GPA as a proxy for effort are 40% lower than those obtained using our approach.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"41 6","pages":"877-893"},"PeriodicalIF":2.5,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099434","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}