Report NEP-ECM-2023-11-20

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.

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Other reports in NEP-ECM

The following items were announced in this report:

• Brice Romuald Gueyap Kounga, 2023. "Nonparametric Regression with Dyadic Data," Papers 2310.12825, arXiv.org.
• Donald S. Poskitt & Xueyan Zhao, 2023. "Bootstrap Hausdorff Confidence Regions for Average Treatment Effect Identified Sets," Monash Econometrics and Business Statistics Working Papers 9/23, Monash University, Department of Econometrics and Business Statistics.
• Denis Chetverikov & Daniel Wilhelm, 2023. "Inference for Rank-Rank Regressions," Papers 2310.15512, arXiv.org, revised Jul 2024.
• Pan Zhao & Yifan Cui, 2023. "A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learning," Papers 2310.09545, arXiv.org.
• Maciej Berk{e}sewicz, 2023. "Survey calibration for causal inference: a simple method to balance covariate distributions," Papers 2310.11969, arXiv.org, revised Mar 2024.
• B. Cooper Boniece & Jos'e E. Figueroa-L'opez & Yuchen Han, 2023. "Data-driven fixed-point tuning for truncated realized variations," Papers 2311.00905, arXiv.org, revised Oct 2024.
• Sid Kankanala, 2023. "On Gaussian Process Priors in Conditional Moment Restriction Models," Papers 2311.00662, arXiv.org, revised Nov 2023.
• Martin Magris & Alexandros Iosifidis, 2023. "Variational Inference for GARCH-family Models," Papers 2310.03435, arXiv.org.
• Yuta Okamoto, 2023. "Robustify and Tighten the Lee Bounds: A Sample Selection Model under Stochastic Monotonicity and Symmetry Assumptions," Papers 2311.00439, arXiv.org, revised Jan 2025.
• Isaiah Andrews & Nano Barahona & Matthew Gentzkow & Ashesh Rambachan & Jesse M. Shapiro, 2023. "Structural Estimation Under Misspecification: Theory and Implications for Practice," NBER Working Papers 31799, National Bureau of Economic Research, Inc.
• Ghislain Geniaux, 2023. "Functional gradient descent boosting for additive non‐linear spatial autoregressive model (gaussian and probit)," Post-Print hal-04229868, HAL.
• Holger Dette & Martin Schumann, 2023. "Testing for equivalence of pre-trends in Difference-in-Differences estimation," Papers 2310.15796, arXiv.org.
• Donggyu Kim & Minseog Oh, 2023. "Dynamic Realized Minimum Variance Portfolio Models," Papers 2310.13511, arXiv.org.
• Dimitris Christopoulos & Peter McAdam & Elias Tzavalis, 2023. "Threshold Endogeneity in Threshold VARs: An Application to Monetary State Dependence," Research Working Paper RWP 23-09, Federal Reserve Bank of Kansas City.
• Julia Hatamyar & Noemi Kreif & Rudi Rocha & Martin Huber, 2023. "Machine Learning for Staggered Difference-in-Differences and Dynamic Treatment Effect Heterogeneity," Papers 2310.11962, arXiv.org.
• Xin Du & Kai Moriyama & Kumiko Tanaka-Ishii, 2023. "Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation," Papers 2310.14536, arXiv.org.
• Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023. "Causal clustering: design of cluster experiments under network interference," Papers 2310.14983, arXiv.org, revised Jan 2024.
• Julio Gálvez, 2023. "Household portfolio choices under (non-)linear income risk: an empirical framework," Working Papers 2327, Banco de España.
• HONDA, Toshio & 本田, 敏雄, 2023. "Sparse quantile regression via ℓ０-penalty," Discussion Papers 2023-03, Graduate School of Economics, Hitotsubashi University.
• Puwasala Gamakumara & Edgar Santos-Fernandez & Priyanga Dilini Talagala & Rob J Hyndman & Kerrie Mengersen & Catherine Leigh, 2023. "Conditional Normalization in Time Series Analysis," Monash Econometrics and Business Statistics Working Papers 10/23, Monash University, Department of Econometrics and Business Statistics.
• Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
• Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
• John Mullahy, 2023. "Analyzing Bounded Count Data," NBER Working Papers 31814, National Bureau of Economic Research, Inc.
• Patrick Rehill & Nicholas Biddle, 2023. "Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability," Papers 2310.13240, arXiv.org, revised Mar 2024.
• Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
• Minglian Lin & Indranil SenGupta & William Wilson, 2023. "Estimation of VaR with jump process: application in corn and soybean markets," Papers 2311.00832, arXiv.org, revised Jun 2024.
• Joshua Rosaler & Dhruv Desai & Bhaskarjit Sarmah & Dimitrios Vamvourellis & Deran Onay & Dhagash Mehta & Stefano Pasquali, 2023. "Enhanced Local Explainability and Trust Scores with Random Forest Proximities," Papers 2310.12428, arXiv.org, revised Aug 2024.