Similar Search Results

Modelling, Simulation and Inference for Multivariate Time Series of Counts Using Trawl Processes

Veraart, Almut - 2018

This article presents a new continuous-time modelling framework for multivariate time series of counts which have an infinitely divisible marginal distribution. The model is based on a mixed moving average process driven by Levy noise - called a trawl process - where the serial correlation and...

Persistent link: https://www.econbiz.de/10012930587

Estimating causal effects in the presence of partial interference using multivariate bayesian structural time series models

Menchetti, Fiammetta; Bojinov, Iavor - 2020

Researchers regularly use synthetic control methods for estimating causal effects when a sub-set of units receive a single persistent treatment, and the rest are unaffected by the change. In many applications, however, units not assigned to treatment are nevertheless impacted by the intervention...

Persistent link: https://www.econbiz.de/10012511332

Indirect inference for locally stationary models

Frazier, David T.; Koo, Bonsoo - In: Journal of econometrics 223 (2021) 1, pp. 1-27

Persistent link: https://www.econbiz.de/10012619956

Continuous record Laplace-based inference about the break date in structural change models

Casini, Alessandro; Perron, Pierre - In: Journal of econometrics 224 (2021) 1, pp. 3-21

Persistent link: https://www.econbiz.de/10013275376

Policy choice in time series by empirical welfare maximization

Kitagawa, Toru; Wang, Weining; Xu, Mengshan - 2022

This paper develops a novel method for policy choice in a dynamic setting where the available data is a multi-variate time-series. Building on the statistical treatment choice framework, we propose Time-series Empirical Welfare Maximization (T-EWM) methods to estimate an optimal policy rule for...

Persistent link: https://www.econbiz.de/10013198871

Handbook of applied economic statistics

Ullah, Aman (ed.); Giles, David E. A. (contributor) - 1998

Persistent link: https://www.econbiz.de/10013282228

Causality in structural vector autoregressions : science or sorcery?

Ghanem, Dalia; Smith, Aaron D. - In: American journal of agricultural economics 104 (2022) 3, pp. 881-904

Persistent link: https://www.econbiz.de/10013193363

A Class of Non-Gaussian State Space Models with Exact Likelihood Inference

Creal, Drew - 2014

The likelihood function for general non-linear, non-Gaussian state space models is a high- dimensional integral with no closed-form solution. In this paper, I show how to calculate the likelihood function exactly for a large class of non-Gaussian state space models that includes stochastic...

Persistent link: https://www.econbiz.de/10013063258

Variable Selection and Inference for Multi-Period Forecasting Problems

Pesaran, M. Hashem - 2011

This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...

Persistent link: https://www.econbiz.de/10012756285

Fixed-k inference for volatility

Bollerslev, Tim; Li, Jia; Liao, Zhipeng - In: Quantitative economics : QE ; journal of the … 12 (2021) 4, pp. 1053-1084

We present a new theory for the conduct of nonparametric inference about the latent spot volatility of a semimartingale … in local estimation blocks, our theory treats the estimation block size k as fixed. While the resulting spot volatility … estimator is no longer consistent, the new theory permits the construction of asymptotically valid and easy …

Persistent link: https://www.econbiz.de/10012795628