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Sökning: LAR1:lu > Jönköping University > (2005-2009) > Tidskriftsartikel > Hacker R Scott

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1.
  • Hacker, R Scott, et al. (författare)
  • A Test for Multivariate ARCH Effects
  • 2005
  • Ingår i: Applied Economics Letters. - : Informa UK Limited. - 1350-4851 .- 1466-4291. ; 12:7, s. 411-417
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper extends Engle's LM test for ARCH affects to multivariate cases. The size and power properties of this multivariate test for ARCH effects in VAR models are investigated based on asymptotic and bootstrap distributions. Using the asymptotic distribution, deviations of actual size from nominal size do not appear to be very excessive. Nevertheless, there is a tendency for the actual size to overreject the null hypothesis when the nominal size is 1% and underreject the null when the nominal size is 5% or 10%. It is found that using a bootstrap distribution for the multivariate LM test is generally superior in achieving the appropriate size to using the asymptotic distribution when (1) the nominal size is 5%; (2) the sample size is small (40 observations) and/or the VAR system is stable. With a small sample, the power of the test using the bootstrap distribution also appears better at the 5% nominal size.
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2.
  • Hacker, R Scott, et al. (författare)
  • Tests for Causality between Integrated Variables Using Asymptotic and Bootstrap Distributions : Theory and Application
  • 2006
  • Ingår i: Applied Economics. - : Informa UK Limited. - 0003-6846 .- 1466-4283. ; 38:13, s. 1489-1500
  • Tidskriftsartikel (refereegranskat)abstract
    • Causality tests in the Granger's sense are increasingly applied in empirical research. Since the unit root revolution in time-series analysis, several modifications of tests for causality have been introduced in the literature. One of the recent developments is the Toda-Yamamoto modified Wald (MWALD) test, which is attractive due to its simple application, its absence of pre-testing distortions, and its basis on a standard asymptotical distribution irrespective of the number of unit roots and the cointegrating properties of the data. This study investigates the size properties of the MWALD test and finds that in small sample sizes this test performs poorly on those properties when using its asymptotical distribution, the chi-square. It is suggested that use be made of a leveraged bootstrap distribution to lower the size distortions. Monte Carlo simulation results show that an MWALD test based on a bootstrap distribution has much smaller size distortions than corresponding cases when the asymptotic distribution is used. These results hold for different sample sizes, integration orders, and error term processes (homoscedastic or ARCH). This new method is applied to the testing of the efficient market hypothesis
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3.
  • Hatemi-J, Abdulnasser, et al. (författare)
  • Can the LR Test Be Helpful in Choosing the Otpimal Lag Order in the VAR Model When Information Criteria Suggest Different Lag Orders?
  • 2009
  • Ingår i: Applied Economics. - : Informa UK Limited. - 0003-6846 .- 1466-4283. ; 41:9, s. 1121-1125
  • Tidskriftsartikel (refereegranskat)abstract
    • The objective of this simulation study is to investigate whether the likelihood ratio (LR) test can pick the optimal lag order in the vector autoregressive model when the most applied information criteria (i.e. vector Schwarz--Bayesian, SBC and vector Hannan-Quinn, HQC) suggest two different lag orders. This lag-choosing procedure has been suggested by Hatemi-J (1999). The results based on the Monte Carlo simulations show that combining the LR test with SBC and HQC causes a substantial increase in the success rate of choosing the optimal lag order compared to cases when only SBC or HQC are used. This appears to be the case irrespective of homoscedasticity or conditional heteroscedasticity properties of the error-term in small sample sizes. This improvement in choosing the right lag order also tends to improve the forecasting capability of the underlying model.
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