nep-ecm New Economics Papers
on Econometrics
Issue of 2005‒02‒27
four papers chosen by
Sune Karlsson
Orebro University

  1. Expectations Hypotheses Tests and Predictive Regressions at Long Horizons By Rossi, Barbara
  2. Testing for Stationarity in Panel Data when Errors are Serially Correlated. Finite-Sample Results By Jönsson , Kristian
  3. Small Concentration Asymptotics and Instrumental Variables Inference By D. S. Poskitt; C. L. Skeels
  4. Statistical Properties of a Heterogeneous Asset Price Model with Time-Varying Second Moment By Carl Chiarella; Xue-Zhong He; Duo Wang

  1. By: Rossi, Barbara
    Abstract: Many rational expectations models state that an economic variable is determined as the present value of future variables. These restrictions have traditionally been tested on VARs where variables appear either in levels (or cointegrating relationships) or first differences. Commonly used test statistics may lead to over-rejections in small samples in the presence of highly persistent variables. Similar problems occur in longhorizon predictive regressions. We propose an alternative method based on local-tounity asymptotic approximations. We apply this method to long-horizon Predictive Regressions, Uncovered Interest Rate Parity, the Term Structure, and the Permanent Income Hypothesis.
    Keywords: expectation hypotheses; present value models; long-horizon; local to unity
    JEL: F30 F40
    Date: 2005
  2. By: Jönsson , Kristian (Department of Economics, Lund University)
    Abstract: Abstract: In this paper, we study the small sample properties of the panel data stationarity test of Hadri (2000). We find that the previously suggested moments, that are to be used when standardizing the panel data stationarity test, cause size distortions when samples are small and serial correlation in the disturbance terms is allowed for. Instead, we supply standardizing moments that are to be used in a panel data stationarity test when samples are small and serial correlation in the disturbances may be an issue. We also document a serious small-sample bias in the panel data stationarity test when a linear trend is present in the data.
    Keywords: Panel Data; Stationarity; Serial Correlation; Monte Carlo Simulation
    JEL: C15 C23 C32 C33
    Date: 2005–02–18
  3. By: D. S. Poskitt; C. L. Skeels
    Abstract: Poskitt and Skeels (2003) provide a new approximation to the sampling distribution of the IV estimator in a simultaneous equations model, the approximation is appropriate when the concentration parameter associated with the reduced form model is small. A basic purpose of this paper is to provide the practitioner with easily implemented inferential tools based upon extensions to these small concentration asymptotic results. We present various approximations to the sampling distribution of functions of the IV estimator based upon small concentration asymptotics, and investigate hypothesis testing procedures and confidence region construction using these approximations. It is shown that the test statistics advanced are asymptotically pivotal and that the associated critical regions generate locally uniformly most powerful invariant tests. The confidence regions are also shown to be valid. The small-concentration asymptotic approximations lead to a non-standard application of standard distributions, facilitating numerical implementation using commonly available software.
    Keywords: IV estimator, concentration parameter, small concentration asymptotics, hypothesis testing, confidence region construction, valid inference.
    JEL: C12 C16 C30 C50
    Date: 2005–02
  4. By: Carl Chiarella (School of Finance and Economics, University of Technology, Sydney); Xue-Zhong He (School of Finance and Economics, University of Technology, Sydney); Duo Wang
    Abstract: Stability and bifurcation analysis of deterministic systems has been widely used in modeling financial markets. However, the impact of such dynamic phenomena on various statistical properties of the corresponding stochastic model, including skewness and excess kurtosis, various autocorrelation (AC) patterns of under and over reactions, and volatility clustering characterised by the long-range dependence of ACs, is not clear and has been very little studied. This paper aims to study this issue. Through a simple behavioural asset pricing model with fundamentalists and chartists, we examine the statistical properties of the model and their connection to the dynamics of the underlying deterministic model. In particular, our analysis leads to some insights into the type of mechanism that may be generating some of the stylised facts, such as fat tails, skewness, high kurtosis and long memory, observed in high frequency financial data.
    Keywords: fundamentalists; chartists, stability; bifurcation; investors' under- and over-reactions; stylized facts
    JEL: D83 D84 E21 E32 C60
    Date: 2004–11–01

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