Report NEP-ECM-2021-12-06

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.

Other reports in NEP-ECM

The following items were announced in this report:

• Donggyu Kim, 2021. "Exponential GARCH-Ito Volatility Models," Papers 2111.04267, arXiv.org.
• Heng Chen & Mototsugu Shintani, 2021. "Inference of Jumps Using Wavelet Variance," CARF F-Series CARF-F-527, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
• Kaveh Salehzadeh Nobari, 2021. "Pair copula constructions of point-optimal sign-based tests for predictive linear and nonlinear regressions," Papers 2111.04919, arXiv.org.
• Rahul Singh, 2021. "Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection," Papers 2111.05277, arXiv.org.
• Sokbae Lee & Martin Weidner, 2021. "Bounding Treatment Effects by Pooling Limited Information across Observations," Papers 2111.05243, arXiv.org, revised Dec 2023.
• Rahul Singh & Liyuan Xu & Arthur Gretton, 2021. "Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves," Papers 2111.03950, arXiv.org, revised Jul 2023.
• Yuheng Ling, 2021. "A tale of two “AR” models: a spatial analysis of Corsican second home incidence," Working Papers 022, Laboratoire Lieux, Identités, eSpaces et Activités (LISA).
• Gianluca Cubadda & Alain Hecq, 2021. "Reduced Rank Regression Models in Economics and Finance," CEIS Research Paper 525, Tor Vergata University, CEIS, revised 08 Nov 2021.
• Carlos A. Abanto-Valle & Gabriel Rodríguez & Luis M. Castro Cepero & Hernán B. Garrafa-Aragón, 2021. "Approximate Bayesian Estimation of Stochastic Volatility in Mean Models using Hidden Markov Models: Empirical Evidence from Stock Latin American Markets," Documentos de Trabajo / Working Papers 2021-502, Departamento de Economía - Pontificia Universidad Católica del Perú.
• Michael P. Leung, 2021. "Rate-Optimal Cluster-Randomized Designs for Spatial Interference," Papers 2111.04219, arXiv.org, revised Sep 2022.
• Jeronymo Marcondes Pinto & Jennifer L. Castle, 2021. "A machine learning dynamic switching approach to forecasting when there are structural breaks," Economics Series Working Papers 950 JEL classification: C, University of Oxford, Department of Economics.
• Jiarui Tian, 2021. "A Replication of “The effect of the conservation reserve program on rural economies: Deriving a statistical verdict from a null finding” (American Journal of Agricultural Economics, 2019)," Working Papers in Economics 21/12, University of Canterbury, Department of Economics and Finance.
• Gaurab Aryal & Hanna Charankevich & Seungwon Jeong & Dong-Hyuk Kim, 2021. "Procurements with Bidder Asymmetry in Cost and Risk-Aversion," Papers 2111.04626, arXiv.org, revised Jul 2022.
• Florian Eckert & Nina Mühlebach, 2021. "Global and Local Components of Output Gaps," KOF Working papers 21-497, KOF Swiss Economic Institute, ETH Zurich.
• Sayani Gupta & Rob J Hyndman & Dianne Cook, 2021. "Detecting Distributional Differences between Temporal Granularities for Exploratory Time Series Analysis," Monash Econometrics and Business Statistics Working Papers 20/21, Monash University, Department of Econometrics and Business Statistics.
• Brandon Buell & Reda Cherif & Carissa Chen & Karl Walentin & Jiawen Tang & Nils Wendt, 2021. "Impact of COVID-19: Nowcasting and Big Data to Track Economic Activity in Sub-Saharan Africa," IMF Working Papers 2021/124, International Monetary Fund.