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Report NEP-ECM-2022-08-15
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:
- Tom Boot & Gianmaria Niccodemi & Tom Wansbeek, 2022, "Unbiased estimation of the OLS covariance matrix when the errors are clustered," Papers, arXiv.org, number 2206.09644, Jun.
- Timo Dimitriadis & Yannick Hoga, 2022, "Dynamic CoVaR Modeling and Estimation," Papers, arXiv.org, number 2206.14275, Jun, revised Jan 2025.
- Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022, "On the impact of serial dependence on penalized regression methods," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number 2022/21, Jul.
- Taisuke Otsu & Mengshan Xu, 2022, "Isotonic propensity score matching," STICERD - Econometrics Paper Series, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE, number 623, Jul.
- Dimitris Korobilis, 2022, "A new algorithm for structural restrictions in Bayesian vector autoregressions," Papers, arXiv.org, number 2206.06892, Jun.
- Li, Kunpeng, 2022, "Threshold spatial autoregressive model," MPRA Paper, University Library of Munich, Germany, number 113568, Jun.
- Chen, Zezhun & Dassios, Angelos & Tzougas, George, 2022, "Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 115369, Jul.
- Helton Saulo & Roberto Vila & Shayane S. Cordeiro, 2022, "Symmetric generalized Heckman models," Papers, arXiv.org, number 2206.10054, Jun.
- Jinyong Hahn & David W. Hughes & Guido Kuersteiner & Whitney K. Newey, 2022, "Efficient Bias Correction for Cross-section and Panel Data," Papers, arXiv.org, number 2207.09943, Jul, revised Jan 2024.
- Christian Bongiorno & Damien Challet, 2022, "Statistical inference of lead-lag at various timescales between asynchronous time series from p-values of transfer entropy," Papers, arXiv.org, number 2206.10173, Jun.
- Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022, "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers, arXiv.org, number 2207.03988, Jul.
- Chang, Jinyuan & Cheng, Guanghui & Yao, Qiwei, 2022, "Testing for unit roots based on sample autocovariances," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 114620, Jun.
- Weronika Ormaniec & Marcin Pitera & Sajad Safarveisi & Thorsten Schmidt, 2022, "Estimating value at risk: LSTM vs. GARCH," Papers, arXiv.org, number 2207.10539, Jul.
- Mario P. Rothfelder & Otilia Boldea, 2022, "Testing for a Threshold in Models with Endogenous Regressors," Papers, arXiv.org, number 2207.10076, Jul.
- Danyu Lin, 2022, "Fitting the Cox proportional hazards model to interval-censored data," Biostatistics and Epidemiology Virtual Symposium 2022, Stata Users Group, number 04, Jun.
- Oliver R. Cutbill & Rami V. Tabri, 2022, "The Impossibility of Testing for Dependence Using Kendall’s Ƭ Under Missing Data of Unknown Form," Working Papers, University of Sydney, School of Economics, number 2022-03, Feb.
- Yan Liu, 2022, "Policy Learning under Endogeneity Using Instrumental Variables," Papers, arXiv.org, number 2206.09883, Jun, revised Jan 2026.
- Chiranjit Dutta & Nalini Ravishanker & Sumanta Basu, 2022, "Modeling Multivariate Positive-Valued Time Series Using R-INLA," Papers, arXiv.org, number 2206.05374, Jun, revised Jul 2022.
- Timothy G. Conley & Bill Dupor & Mahdi Ebsim, 2022, "The Sine Aggregatio Approach to Applied Macro," Working Papers, Federal Reserve Bank of St. Louis, number 2022-014, Jul, revised 11 Nov 2022, DOI: 10.20955/wp.2022.014.
- Ochoa Arellano, Maicol Jesús & Cascos Fernández, Ignacio, 2022, "Data depth and multiple output regression, the distorted M-quantiles approach," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de EstadÃstica, number 35465, Jul.
- Collin Philipps, 2022, "An Expectile Strong Law of Large Numbers," Working Papers, Department of Economics and Geosciences, US Air Force Academy, number 2022-05, Jul.
- Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022, "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports, Federal Reserve Bank of New York, number 1025, Jul.
- Di Zhang & Qiang Niu & Youzhou Zhou, 2022, "Modeling Randomly Walking Volatility with Chained Gamma Distributions," Papers, arXiv.org, number 2207.01151, Jul, revised Oct 2022.
- Anthony Coache & Sebastian Jaimungal & 'Alvaro Cartea, 2022, "Conditionally Elicitable Dynamic Risk Measures for Deep Reinforcement Learning," Papers, arXiv.org, number 2206.14666, Jun, revised May 2023.
- Andrew Y. Chen, 2022, "Most claimed statistical findings in cross-sectional return predictability are likely true," Papers, arXiv.org, number 2206.15365, Jun, revised Nov 2025.
- Bryan T. Kelly & Semyon Malamud & Kangying Zhou, 2022, "The Virtue of Complexity in Return Prediction," NBER Working Papers, National Bureau of Economic Research, Inc, number 30217, Jul.