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Econometrics, Volume 3, Issue 2

2015 June - 13 articles

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Articles (13)

  • Article
  • Open Access
12 Citations
6,762 Views
23 Pages

Bayesian Approach to Disentangling Technical and Environmental Productivity

  • Emir Malikov,
  • Subal C. Kumbhakar and
  • Efthymios G. Tsionas

This paper models the firm’s production process as a system of simultaneous technologies for desirable and undesirable outputs. Desirable outputs are produced by transforming inputs via the conventional transformation function, whereas (consistent wi...

  • Article
  • Open Access
10 Citations
6,480 Views
36 Pages

In studying the asymptotic and finite sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its compan...

  • Article
  • Open Access
1 Citations
5,787 Views
21 Pages

This paper investigates the performance of a jackknife correction to a test for cointegration rank in a vector autoregressive system. The limiting distributions of the jackknife-corrected statistics are derived and the critical values of these distri...

  • Article
  • Open Access
1 Citations
8,200 Views
16 Pages

The literature has been notably less definitive in distinguishing between finite sample studies of seasonal stationarity than in seasonal unit root tests. Although the use of seasonal stationarity and unit root tests is advised to determine correctly...

  • Article
  • Open Access
11 Citations
6,910 Views
28 Pages

A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead t...

  • Article
  • Open Access
26 Citations
9,684 Views
22 Pages

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

  • Sandy Burden,
  • Noel Cressie and
  • David G. Steel

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-effici...

  • Article
  • Open Access
116 Citations
16,038 Views
25 Pages

Detecting Location Shifts during Model Selection by Step-Indicator Saturation

  • Jennifer L. Castle,
  • Jurgen A. Doornik,
  • David F. Hendry and
  • Felix Pretis

To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of...

  • Article
  • Open Access
4 Citations
6,307 Views
24 Pages

This paper discusses nonparametric kernel regression with the regressor being a \(d\)-dimensional \(\beta\)-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence...

  • Article
  • Open Access
2 Citations
5,298 Views
7 Pages

It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance mat...

  • Article
  • Open Access
46 Citations
8,573 Views
18 Pages

Examinations of the dynamics of daily returns and volatility in stock markets of the U.S., Hong Kong and mainland China (Shanghai and Shenzhen) over 2 January 2001 to 8 February 2013 suggest: (1) evidence of unidirectional return spillovers from the...

  • Article
  • Open Access
20 Citations
8,528 Views
16 Pages

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

  • Chi-Yang Chu,
  • Daniel J. Henderson and
  • Christopher F. Parmeter

This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross-validated bandwidths, i...

  • Article
  • Open Access
12 Citations
4,927 Views
12 Pages

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...

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Econometrics - ISSN 2225-1146