Printed from https://ideas.repec.org/n/nep-ecm/2023-10-16.html
Report NEP-ECM-2023-10-16
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:
- Jacob Dorn & Luther Yap, 2023, "Sensitivity Analysis for Linear Estimators," Papers, arXiv.org, number 2309.06305, Sep, revised Apr 2024.
- Christis Katsouris, 2023, "Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models," Papers, arXiv.org, number 2308.13915, Aug.
- Hao Hao & Tae-Hwy Lee, 2023, "Boosting GMM with Many Instruments When Some Are Invalid or Irrelevant," Working Papers, University of California at Riverside, Department of Economics, number 202309, Sep.
- S. Yaser Samadi & Wiranthe B. Herath, 2023, "Reduced-rank Envelope Vector Autoregressive Models," Papers, arXiv.org, number 2309.12902, Sep.
- Chaudhuri, Saraswata & Renault, Eric, 2023, "Efficient estimation of regression models with user-specified parametric model for heteroskedasticty," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1473.
- Tae-Hwy Lee & Tao Wang, 2023, "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers, University of California at Riverside, Department of Economics, number 202307, Sep.
- Zhou, Yunzhe & Qi, Zhengling & Shi, Chengchun & Li, Lexin, 2023, "Optimizing pessimism in dynamic treatment regimes: a Bayesian learning approach," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 118233, Dec.
- Mikihito Nishi, 2023, "Testing for Stationary or Persistent Coefficient Randomness in Predictive Regressions," Papers, arXiv.org, number 2309.04926, Sep, revised May 2024.
- Deborah Gefang & Stephen G. Hall & George S. Tavlas, 2023, "Identifying spatial interdependence in panel data with large N and small T," Papers, arXiv.org, number 2309.03740, Sep.
- John M. Abowd & Kevin L. McKinney, 2023, "Mixed-Effects Methods for Search and Matching Research," Papers, arXiv.org, number 2308.15445, Aug.
- Wojciech Victor Fulmyk, 2023, "Nonlinear Granger Causality using Kernel Ridge Regression," Papers, arXiv.org, number 2309.05107, Sep.
- Philippe Andrade & Filippo Ferroni & Leonardo Melosi, 2023, "Identification Using Higher-Order Moments Restrictions," Working Paper Series, Federal Reserve Bank of Chicago, number WP 2023-28, Aug, DOI: 10.21033/wp-2023-28.
- Liang Chen & Yao Luo, 2023, "Empirical Analysis of Network Effects in Nonlinear Pricing Data," Working Papers, University of Toronto, Department of Economics, number tecipa-758, Sep.
- Xiyuan Ren & Joseph Y. J. Chow & Prateek Bansal, 2023, "Nonparametric mixed logit model with market-level parameters estimated from market share data," Papers, arXiv.org, number 2309.13159, Sep, revised Apr 2025.
- Vod Vilfort & Whitney Zhang, 2023, "Interpreting TSLS Estimators in Information Provision Experiments," Papers, arXiv.org, number 2309.04793, Sep, revised Jun 2024.
- Tingxuan Han & Luxi Zhang & Xinshu Zhao & Ke Deng, 2023, "Total-effect Test May Erroneously Reject So-called "Full" or "Complete" Mediation," Papers, arXiv.org, number 2309.08910, Sep, revised Sep 2023.
- Daniel J. Benjamin & Kristen Cooper & Ori Heffetz & Miles S. Kimball & Jiannan Zhou, 2023, "Adjusting for Scale-Use Heterogeneity in Self-Reported Well-Being," NBER Working Papers, National Bureau of Economic Research, Inc, number 31728, Sep.