Report NEP-ECM-2022-02-21

This is the archive for NEP-ECM, a report on new working papers in the area of Econometrics. Sune Karlsson issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-ECM

The following items were announced in this report:

• Jinyong Hahn & Hyungsik Roger Moon & Ruoyao Shi, 2022, "Test of Neglected Heterogeneity in Dyadic Models," Working Papers, University of California at Riverside, Department of Economics, number 202206, Feb.
• Kenichi Shimizu, 2022, "Asymptotic properties of Bayesian inference in linear regression with a structural break," Working Papers, Business School - Economics, University of Glasgow, number 2022_05, Feb.
• Andriy Norets & Kenichi Shimizu, 2022, "Semiparametric Bayesian Estimation of Dynamic Discrete Choice Models," Working Papers, Business School - Economics, University of Glasgow, number 2022_06, Feb.
• Ke-Li Xu & Junjie Guo, 2021, "A New Test for Multiple Predictive Regression," CAEPR Working Papers, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington, number 2022-001 Classification-C, Dec.
• Chen, Yunxiao & Li, Xiaoou, 2022, "Determining the number of factors in high-dimensional generalized latent factor models," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 111574, Sep.
• Ron Mittelhammer & George Judge & Miguel Henry, 2022, "An Entropy-Based Approach for Nonparametrically Testing Simple Probability Distribution Hypotheses," Papers, arXiv.org, number 2201.06647, Jan.
• Debasis Kundu, 2021, "Stationary GE-Process and its Application in Analyzing Gold Price Data," Papers, arXiv.org, number 2201.02568, Oct.
• Xiaohong Chen & Zhengling Qi, 2022, "On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation," Papers, arXiv.org, number 2201.06169, Jan, revised Jun 2022.
• Ando, Tomohiro & Bai, Jushan, 2021, "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper, University Library of Munich, Germany, number 111431, Dec.
• Simon Jurkatis, 2022, "Why you should not use the LSV herding measure," Bank of England working papers, Bank of England, number 959, Jan.
• George Planiteros, 2022, "Reverse matching for ex-ante policy evaluation," DEOS Working Papers, Athens University of Economics and Business, number 2206, Jan.
• Nathan Kallus, 2022, "Treatment Effect Risk: Bounds and Inference," Papers, arXiv.org, number 2201.05893, Jan, revised Jul 2022.
• Vembye, Mikkel Helding & Pustejovsky, James E & Pigott, Terri, 2022, "Power Approximations for Meta-Analysis of Dependent Effect Sizes," MetaArXiv, Center for Open Science, number 6tp9y, Jan, DOI: 10.31219/osf.io/6tp9y.
• Li, Xiaoou & Chen, Yunxiao & Chen, Xi & Liu, Jingchen & Ying, Zhiliang, 2021, "Optimal stopping and worker selection in crowdsourcing: an adaptive sequential probability ratio test framework," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 100873, Jan.
• Kristoffer Pons Bertelsen, 2022, "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2022-05, Jan.
• Joshi, Megha & Pustejovsky, James E & Beretvas, S. Natasha, 2021, "Cluster Wild Bootstrapping to Handle Dependent Effect Sizes in Meta-Analysis with a Small Number of Studies," MetaArXiv, Center for Open Science, number x6uhk, Sep, DOI: 10.31219/osf.io/x6uhk.
• Yuen, Christine & Fryzlewicz, Piotr, 2022, "Exploiting disagreement between high-dimensional variable selectors for uncertainty visualization," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 112480, Apr.
• Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2022, "Bayesian Estimation of Multivariate Panel Probits with Higher-order Network Interdependence and an Application to Firms' Global Market Participation in Guangdong," Center for Policy Research Working Papers, Center for Policy Research, Maxwell School, Syracuse University, number 247, Feb.
• Margherita Fort & Andrea Ichino & Enrico Rettore & Giulio Zanella, 2022, "Multi-cutoff RD designs with observations located at each cutoff: problems and solutions," "Marco Fanno" Working Papers, Dipartimento di Scienze Economiche "Marco Fanno", number 0278, Jan.
• Thomas R. Cook & Zach Modig & Nathan M. Palmer, 2021, "Explaining Machine Learning by Bootstrapping Partial Marginal Effects and Shapley Values," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 21-12, Nov, revised 06 Aug 2024, DOI: 10.18651/RWP2021-12.
• Chen, Yudong & Wang, Tengyao & Samworth, Richard J., 2022, "High-dimensional, multiscale online changepoint detection," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 113665, Feb.
• Yasumasa Matsuda & Xin Yuan, 2022, "Convolutional regression for big spatial data," DSSR Discussion Papers, Graduate School of Economics and Management, Tohoku University, number 124, Feb.
• Robin Braun, 2021, "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers, Bank of England, number 957, Dec.
• Banker, Rajiv & Park, Han-Up & Sahoo, Biresh, 2022, "A statistical foundation for the measurement of managerial ability," MPRA Paper, University Library of Munich, Germany, number 111832, Jan.
• Luke De Clerk & Sergey Savl'ev, 2022, "A machine learning search for optimal GARCH parameters," Papers, arXiv.org, number 2201.03286, Jan.

Report NEP-ECM-2022-02-21

This is the archive for NEP-ECM, a report on new working papers in the area of Econometrics. Sune Karlsson issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-ECM

The following items were announced in this report: