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L1-regularization of high-dimensional time-series models with flexible innovations

Medeiros, Marcelo C.; Mendes, Eduardo F. - 2015

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume that both the number of covariates in the model and the number of candidate variables can increase with the sample size (polynomially or geometrically). In other...

Persistent link: https://www.econbiz.de/10010505038

Machine learning advances for time series forecasting

Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - 2020

series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to …

Persistent link: https://www.econbiz.de/10012390030

Variable selection and forecasting in high dimensional linear regressions with structural breaks

Chudik, Alexander; Pesaran, M. Hashem; Sharifvaghefi, Mahrad - 2020

This paper is concerned with problem of variable selection and forecasting in the presence of parameter instability …. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or … variable selection and forecasting stages. In this study, we investigate whether or not we should use weighted observations at …

Persistent link: https://www.econbiz.de/10012258549

Anticipating critical transitions of Chinese housing markets

Zhang, Qunzi; Sornette, Didier; Zhang, Hao - 2017

We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which we apply to the housing markets of China's major cities. Building on the Log-Periodic Power Law Singular (LPPLS) model of self-reinforcing feedback loops, we use the quantile...

Persistent link: https://www.econbiz.de/10011761282

Chapter 4 The new empirics of economic growth

Durlauf, Steven N.; Quah, Danny T. - In: Handbook of macroeconomics : volume 1, part A, (pp. 235-308). 1999

We provide an overview of recent empirical research on patterns of cross-country growth. The new empirical regularities considered differ from earlier ones, e.g., the well-known Kaldor stylized facts. The new research no longer makes production function accounting a central part of the analysis....

Persistent link: https://www.econbiz.de/10014024246

A Simple Test for Linearity Against Exponential Smooth Transition Models with Endogenous Variables

Massacci, Daniele - 2017

This paper proposes a test for linearity against exponential smooth transition models with endogenous right-hand-side variables: to the very best of our knowledge, this class of models is new to the literature. By Monte Carlo analysis the test is shown to have good finite sample properties

Persistent link: https://www.econbiz.de/10014176554

New Solution to Time Series Inference in Spurious Regression Problems

Vinod, Hrishikesh D. - 2010

Phillips (1986) provides asymptotic theory for regressions that relate nonstationary time series including those integrated of order 1, I(1). A practical implication of related literature on spurious regression is that one cannot trust the usual confidence intervals. Therefore it is recommended...

Persistent link: https://www.econbiz.de/10014197508

Forecasting with Nonlinear Time Series Models

Terasvirta, Timo; Kock, Anders Bredahl - 2010

purpose is mentioned as well. Forecasting with complex dynamic systems, albeit less frequently applied to economic forecasting …

Persistent link: https://www.econbiz.de/10014199417

(When) Should Cointegrating Regressions Be Detrended? The Case of a German Money Demand Function

Hassler, Uwe - 1999

If an economic relationship is superimposed by a linear time trend, the regression without detrending is misspecified. The estimators of such a regression do not converge to the true parameter values. First, the asymptotic limit arising from such misspecified regressions is characterized....

Persistent link: https://www.econbiz.de/10014200423

Spurious Regression, Cointegration, and Near Cointegration : A Unifying Approach

Haldrup, Niels; Jansson, Michael - 1999

This paper introduces a representation of an integrated vector time series in which the coefficient of multiple correlation computed from the long-run covariance matrix of the innovation sequences is a primitive parameter of the model. Based on this representation, a notion of near cointegration...

Persistent link: https://www.econbiz.de/10014203187