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Dmitry - EconWPA - 2005

PROBLEM SOLVING OF FORECASTING ON SHORT PERIODS IN THE CASE OF TRANSITIONAL STRUCTURE-CHANGING CHARACTER OF DEVELOPMENT …

Persistent link: https://www.econbiz.de/10005407982

Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity

Ishida, Isao; Kvedaras, Virmantas - In: Econometrics 3 (2015) 1, pp. 2-54

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

Persistent link: https://www.econbiz.de/10011123002

Assessing Forecast Performance in a VEC Model: An Empirical Examination

Zacharias, Bragoudakis - EconWPA - 2005

, Forecasting, Simulation Analysis, Vector error- correction models JEL Classifications: C15, C32, C53, E0, E6 Working Paper Series …This paper is an exercise in applied macroeconomic forecasting. We examine the forecasting power of a vector error … expenditure as suggested by the economic theory. We compare the estimated forecasting values of the endogenous variables to the …

Persistent link: https://www.econbiz.de/10005119198

‘‘MOVING MEDIAN’’ A NEW METHOD OF FORECASTING

Giovanis, Eleftherios - EconWPA - 2005

For hundred years the future was occupying the persons. The ancient Greeks, the Romans, the Egyptians, the Indians, the Chinese and other great ancient cultures, but also the modern, as the English, Germans and the Americans and with the help of the development of technology and computers they...

Persistent link: https://www.econbiz.de/10005119209

STOCHASTIC VOLATILITY: LIKELIHOOD INFERENCE AND COMPARISON WITH ARCH MODELS

Kim, Sangjoon; Shephard, Neil; Chib, Siddhartha - EconWPA - 1996

. This approach is compared with several alternative methods using real data. The paper also develops simulation- based …

Persistent link: https://www.econbiz.de/10005556396

Data-driven jump detection thresholds for application in jump regressions

Davies, Robert; Tauchen, George - In: Econometrics 6 (2018) 2, pp. 1-25

This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

Persistent link: https://www.econbiz.de/10011995217

Two-Part Models for Fractional Responses Defined as Ratios of Integers

Oberhofer, Harald; Pfaffermayr, Michael - In: Econometrics 2 (2014) 3, pp. 123-144

This paper discusses two alternative two-part models for fractional response variables that are defined as ratios of integers. The first two-part model assumes a Binomial distribution and known group size. It nests the one-part fractional response model proposed by Papke and Wooldridge (1996)...

Persistent link: https://www.econbiz.de/10010945729

Information Recovery in a Dynamic Statistical Markov Model

Miller, Douglas J.; Judge, George - In: Econometrics 3 (2015) 2, pp. 187-198

Although economic processes and systems are in general simple in nature, the underlying dynamics are complicated and seldom understood. Recognizing this, in this paper we use a nonstationary-conditional Markov process model of observed aggregate data to learn about and recover causal influence...

Persistent link: https://www.econbiz.de/10011211017

Plug-in Bandwidth Selection for Kernel Density Estimation with Discrete Data

Chu, Chi-Yang; Henderson, Daniel J.; Parmeter, … - In: Econometrics 3 (2015) 2, pp. 199-214

mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross …

Persistent link: https://www.econbiz.de/10011220361

The SAR Model for Very Large Datasets: A Reduced Rank Approach

Burden, Sandy; Cressie, Noel; Steel, David G. - In: Econometrics 3 (2015) 2, pp. 317-338

The SAR model is widely used in spatial econometrics to model Gaussian processes on a discrete spatial lattice, but for large datasets, fitting it becomes computationally prohibitive, and hence, its usefulness can be limited. A computationally-efficient spatial model is the spatial random...

Persistent link: https://www.econbiz.de/10011276475

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