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Report NEP-ECM-2023-10-02
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:
- Lorenzo Tedesco & Jad Beyhum & Ingrid Van Keilegom, 2023, "Instrumental variable estimation of the proportional hazards model by presmoothing," Papers, arXiv.org, number 2309.02183, Sep.
- Harold D. Chiang & Yuya Sasaki & Yulong Wang, 2023, "Genuinely Robust Inference for Clustered Data," Papers, arXiv.org, number 2308.10138, Aug, revised Oct 2025.
- Hoffmann, Nathan Isaac, 2023, "Double Robust, Flexible Adjustment Methods for Causal Inference: An Overview and an Evaluation," SocArXiv, Center for Open Science, number dzayg, Aug, DOI: 10.31219/osf.io/dzayg.
- Mertens, Elmar, 2023, "Precision-based sampling for state space models that have no measurement error," Discussion Papers, Deutsche Bundesbank, number 25/2023.
- Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023, "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers, University of California at Riverside, Department of Economics, number 202306, Aug.
- Kaicheng Chen & Robert S. Martin & Jeffrey M. Wooldridge, 2023, "Another Look at the Linear Probability Model and Nonlinear Index Models," Papers, arXiv.org, number 2308.15338, Aug, revised Oct 2023.
- Neville Francis & Michael T. Owyang & Daniel Soques, 2023, "Impulse Response Functions for Self-Exciting Nonlinear Models," Working Papers, Federal Reserve Bank of St. Louis, number 2023-021, Aug, revised 29 Aug 2023, DOI: 10.20955/wp.2023.021.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023, "Econometrics of Machine Learning Methods in Economic Forecasting," Papers, arXiv.org, number 2308.10993, Aug.
- Hanwen Xuan & Luca Maestrini & Feng Chen & Clara Grazian, 2023, "Stochastic Variational Inference for GARCH Models," Papers, arXiv.org, number 2308.14952, Aug.
- Christopher Conlon & Jeff Gortmaker, 2023, "Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP," NBER Working Papers, National Bureau of Economic Research, Inc, number 31605, Aug.
- Brunori, Paolo & Hufe, Paul & Mahler, Daniel, 2023, "The roots of inequality: estimating inequality of opportunity from regression trees and forests," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 118220, Oct.
- Aleksy Leeuwenkamp & Wentao Hu, 2023, "New general dependence measures: construction, estimation and application to high-frequency stock returns," Papers, arXiv.org, number 2309.00025, Aug.
- Elliot Beck & Damian Kozbur & Michael Wolf, 2023, "Hedging Forecast Combinations With an Application to the Random Forest," Papers, arXiv.org, number 2308.15384, Aug, revised Aug 2023.
- Simon Bensnes & Ingrid Huitfeldt & Edwin Leuven, 2023, "Reconciling estimates of the long-term earnings effect of fertility," Discussion Papers, Statistics Norway, Research Department, number 1004, Aug.
- Webel, Karsten & Smyk, Anna, 2023, "Towards seasonal adjustment of infra-monthly time series with JDemetra+," Discussion Papers, Deutsche Bundesbank, number 24/2023.
- Jared Amani Greathouse & Mani Bayani & Jason Coupet, 2023, "Splash! Robustifying Donor Pools for Policy Studies," Papers, arXiv.org, number 2308.13688, Aug.