Report NEP-ECM-2019-03-11

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:

• Adam M. Rosen & Takuya Ura, 2019. "Finite Sample Inference for the Maximum Score Estimand," Papers 1903.01511, arXiv.org, revised May 2020.
• Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo MM & Taylor, AM Robert, 2019. "Testing for Episodic Predictability in Stock Returns," Essex Finance Centre Working Papers 24137, University of Essex, Essex Business School.
• Shengfang Tang & Zongwu Cai & Ying Fang & Ming Lin, 2019. "Testing Unconfoundedness Assumption Using Auxiliary Variables," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201905, University of Kansas, Department of Economics, revised Mar 2019.
• Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
• Sebastian Kripfganz & Daniel C. Schneider, 2019. "Response surface regressions for critical value bounds and approximate p-values in equilibrium correction models," Discussion Papers 1901, University of Exeter, Department of Economics.
• Ayala, Astrid & Blazsek, Szabolcs, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
• Jiun-Hua Su, 2019. "Model Selection in Utility-Maximizing Binary Prediction," Papers 1903.00716, arXiv.org, revised Jul 2020.
• Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.
• Denis Kojevnikov & Vadim Marmer & Kyungchul Song, 2019. "Limit Theorems for Network Dependent Random Variables," Papers 1903.01059, arXiv.org, revised Feb 2021.
• Ashesh Rambachan & Neil Shephard, 2019. "Econometric analysis of potential outcomes time series: instruments, shocks, linearity and the causal response function," Papers 1903.01637, arXiv.org, revised Feb 2020.
• Reza Hajargasht, 2019. "Approximation Properties of Variational Bayes for Vector Autoregressions," Papers 1903.00617, arXiv.org.
• Zeqin Liu & Zongwu Cai & Ying Fang & Ming Lin, 2019. "Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201904, University of Kansas, Department of Economics, revised Mar 2019.
• Sergio Correia & Paulo Guimar~aes & Thomas Zylkin, 2019. "Verifying the existence of maximum likelihood estimates for generalized linear models," Papers 1903.01633, arXiv.org, revised Jun 2021.
• Kapetanios, George & Papailias, Fotis & Taylor, AM Robert, 2019. "A Generalised Fractional Differencing Bootstrap for Long Memory Processes," Essex Finance Centre Working Papers 24136, University of Essex, Essex Business School.
• L'aszl'o Csat'o & D'ora Gr'eta Petr'oczy, 2019. "On the monotonicity of the eigenvector method," Papers 1902.10790, arXiv.org, revised Oct 2020.
• Nikkil Sudharsanan & Maarten J. Bijlsma, 2019. "A generalized counterfactual approach to decomposing differences between populations," MPIDR Working Papers WP-2019-004, Max Planck Institute for Demographic Research, Rostock, Germany.
• Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
• Christopher F. Baum & Arthur Lewbel, 2018. "Advice on using heteroscedasticity based identification," Boston College Working Papers in Economics 975, Boston College Department of Economics, revised 17 Jun 2019.
• Jonas Rothfuss & Fabio Ferreira & Simon Walther & Maxim Ulrich, 2019. "Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks," Papers 1903.00954, arXiv.org, revised Apr 2019.
• Sariev, Eduard & Germano, Guido, 2018. "An innovative feature selection method for support vector machines and its test on the estimation of the credit risk of default," LSE Research Online Documents on Economics 100211, London School of Economics and Political Science, LSE Library.
• Stelios Arvanitis & Alexandros Louka, 2017. "Limits for the Gaussian QMLE in the Non-Stationary GARCH(1,1) Mod," Working Papers 201705, Athens University Of Economics and Business, Department of Economics.