nep-ets New Economics Papers
on Econometric Time Series
Issue of 2012‒04‒03
seven papers chosen by
Yong Yin
SUNY at Buffalo

  1. Identification, Estimation and Specification in a Class of Semiparametic Time Series Models By Jiti Gao
  2. Robustness of Power Properties of Non-linearity Tests By Marian Vavra
  3. Testing Non-linearity Using a Modified Q Test By Marian Vavra
  4. A Note on the Finite Sample Properties of the CLS Method of TAR Models By Marian Vavra
  5. Testing Weak Cross-Sectional Dependence in Large Panels By Pesaran, Hashem
  6. Heavy-Tail Distribution from Correlation of Discrete Stochastic Process By Jongwook Kim; Teppei Okumura
  7. Backward and forward closed solutions of multivariate ARMA models. By Ludlow-Wiechers, Jorge

  1. By: Jiti Gao
    Abstract: In this paper, we consider some identification, estimation and specification problems in a class of semiparametric time series models. Existing studies for the stationary time series case have been reviewed and discussed. We also consider the case where new studies for the integrated nonstationary case are established. In the meantime, we propose some new estimation methods and establish some new results for a new class of semiparametric autoregressive models. In addition, we discuss certain directions for further research.
    Keywords: Asymptotic theory, departure function, kernel method, nonlinearity, nonstationarity, semiparametric model, stationarity, time series
    JEL: C13 C14 C22
    Date: 2012–03
  2. By: Marian Vavra (Department of Economics, Mathematics & Statistics, Birkbeck)
    Abstract: The paper examines the robustness of the size and power properties of the standard non-linearity tests under different conditions such as moment failure and asymmetry of innovations. Our results reveal the following. First, there seems not to be a direct link between moment condition failure and the power variation of non-linearity tests. Second, the power of the tests is very sensitive to asymmetry of innovations compared to moment condition failure. Third, although we evaluate 9 non-linear time series models using 8 standard non-linearity tests, some non-linear models remain completely undetected.
    Keywords: non-linearity testing, Monte Carlo experiments
    JEL: C15 C22
    Date: 2012–03
  3. By: Marian Vavra (Department of Economics, Mathematics & Statistics, Birkbeck)
    Abstract: A new version of the Q test, based on generalized residual correlations (i.e. auto-correlations and cross-correlations), is developed in this paper. The Q test fixes two main shortcomings of the Mcleod and Li Q (MLQ) test often used in the literature: (i) the test is capable to capture some interesting non-linear models, for which the original MLQ test completely fails (e.g. a non-linear moving average model). Additionally, the Q test also significantly improves the power for some other non-linear models (e.g. a threshold moving average model), for which the original MLQ test does not work very well; (ii) the new Q test can be used for discrimination between simple and more complicated (non-linear/asymmetric) GARCH models as well.
    Keywords: non-linearity testing, portmanteau Q test, auto-correlation, cross-correlation
    JEL: C12 C15 C32 C46
    Date: 2012–03
  4. By: Marian Vavra (Department of Economics, Mathematics & Statistics, Birkbeck)
    Abstract: In this paper we focus on the finite sample properties of the conditional least squares (CLS) method of threshold autoregressive (TAR) parameters under the following conditions: (a) non-Gaussian model innovations; (b) two types of asymmetry (i.e. deepness and steepness) captured by TAR models. It is clearly demonstrated that the finite sample properties of the CLS method of TAR parameters significantly differ depending on the type of asymmetry. The behavior of steepness-based models is very good compared to that obtained from deepness-based models. Therefore, extreme caution must be excercised to preliminary modelling steps, such as testing the type of asymmetry before estimating TAR models in practice. A mistake in this phase of modelling can, in turn, give rise to very problematic results.
    Keywords: threshold autoregressive model, Monte Carlo method, bias, asymmetry
    JEL: C15 C22 C46
    Date: 2012–03
  5. By: Pesaran, Hashem (University of Cambridge)
    Abstract: This paper considers testing the hypothesis that errors in a panel data model are weakly cross sectionally dependent, using the exponent of cross-sectional dependence α, introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the CD test depends on the relative expansion rates of N and T. When T=O(N^ϵ), for some 0 < ϵ ≤ 1, then the implicit null of the CD test is given by 0 ≤ α < (2–ϵ)/4, which gives 0 ≤ α < 1/4, when N and T tend to infinity at the same rate such that T/N → к, with к ; with being a finite positive constant. It is argued that in the case of large N panels, the null of weak dependence is more appropriate than the null of independence which could be quite restrictive for large panels. Using Monte Carlo experiments, it is shown that the CD test has the correct size for values of α in the range [0, 1/4], for all combinations of N and T, and irrespective of whether the panel contains lagged values of the dependent variables, so long as there are no major asymmetries in the error distribution.
    Keywords: exponent of cross-sectional dependence, diagnostic tests, panel data models, dynamic heterogenous panels
    JEL: C12 C13 C33
    Date: 2012–03
  6. By: Jongwook Kim; Teppei Okumura
    Abstract: We propose a stochastic process driven by the memory effect with novel distributions which include both exponential and leptokurtic heavy-tailed distributions. A class of the distributions is analytically derived from the continuum limit of the discrete binary process with the renormalized auto-correlation. The moment generating function with a closed form is obtained, thus the cumulants are calculated and shown to be convergent. The other class of the distributions is numerically investigated. The combination of the two stochastic processes of memory with different signs under regime switching mechanism does result in behaviors of power-law decay. Therefore we claim that memory is the alternative origin of heavy-tail.
    Date: 2012–03
  7. By: Ludlow-Wiechers, Jorge
    Abstract: Some of the most widely used models in economics are based on variables not yet observed, and their specification depends on future observations; the theory that underpins these delivers the backward/ forward solution. We present a newly unified construction, starting with a more general specification of an ARMA model, yet is capable of delivering in closed form, in both the backward and forward cases, leading to an alternative presentation of causal/non-causal and invertible/non-invertible cases.
    Keywords: Causal models; non-causal models; invertible models; non-invertible models; backward solution; forward solution
    JEL: C32 C50 C22 C01
    Date: 2012–03–25

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