Всего статей в данном разделе : 242
A Comparative Study of Tests for Homogeneity of Variance, with Applications to the Outer Continental Shelf Bidding Data [статья]
Опубликовано на портале: 24-06-2004William Jay Conover, Mark E. Johnson, Myrle M. Johnson Technometrics. 1981. Vol. 23. No. 4. P. 351-361.
Many of the existing parametric and nonparametric tests for homogeneity of variances, and some variations of these tests, are examined in this paper. Comparisons are made under the null hypothesis (for robustness) and under the alternative (for power). Monte Carlo simulations of various symmetric and asymmetric distributions, for various sample sizes, reveal a few tests that are robust and have good power. These tests are further compared using data from outer continental shelf bidding on oil and gas leases.
Опубликовано на портале: 01-07-2004William A. Brock, Blake LeBaron Review of Economics and Statistics. 1996. Vol. 78. No. 1. P. 94-122.
An examination is made of an adaptive beliefs model that is able to roughly reproduce the following features seen in the data: 1. The autocorrelation functions of the volatility of returns and trading volume are positive with slowly decaying tails. 2. The cross-correlation function of volatility is approximately zero for squared returns with past and future volumes and is positive for squared returns with current volumes. 3. Abrupt changes in prices and returns occur that are hard to attach to "news." The last feature is obtained because the Law of Large Numbers can fail in the large economy limit.
Опубликовано на портале: 07-04-2004Blake LeBaron Studies in Nonlinear Dynamics and Econometrics. 1997. Vol. 2. No. 2. P. 53-59.
The BDS statistic has proved to be one of several useful nonlinear diagnostics. It has been shown to have good power against many nonlinear alternatives, and its asymptotic properties as a residual diagnostic are well understood. Furthermore, extensive Monte Carlo results have proved it useful in relatively small samples. However, the BDS test is not trivial to calculate, and is even more difficult to deal with if one wants the speed necessary to make bootstrap resampling feasible. This short paper presents a fast algorithm for the BDS statistic, and outlines how these speed improvements are achieved. Source code in the C programming language is included.
A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity [статья]
Опубликовано на портале: 06-04-2004Halbert L. White Econometrica. 1980. Vol. 48. No. 4. P. 817-838.
This paper presents a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic. This estimator does not depend on a formal model of the structure of the heteroskedasticity. By comparing the elements of the new estimator to those of the usual covariance estimator, one obtains a direct test for heteroskedasticity, since in the absence of heteroskedasticity, the two estimators will be approximately equal, but will generally diverge otherwise. The test has an appealing least squares interpretation.
Опубликовано на портале: 24-12-2007Elena Schneider, Pu Chen, Joachim Frohn Economics Discussion Papers. 2007. No. 2007-47.
The objective of this paper is to apply the method developed in Garratt, Lee, Pesaran, and Shin (2000) to build a structural model for Germany with a transparent and theoretically coherent foundation. The modelling strategy consists of a set of long-run structural relationships suggested by economic theory and an otherwise unrestricted VAR model. It turns out that we can rebuild the structure of the model in Garratt, Lee, Pesaran, and Shin (2003b) for German data. Five long run relations : PPP, UIP, production function, trade balance, and real money balance characterize the equilibrium state of Germany as an open economy in our structural model.
Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models [статья]
Опубликовано на портале: 06-04-2004Robert F. Engle, Mark W. Watson Journal of Econometrics. 1983. Vol. 23. No. 3. P. 385-400.
This paper provides a general approach to the formulation and estimation of dynamic unobserved component models. After introducing the general model, two methods for estimating the unknown parameters are presented. Both are algorithms for maximizing the likelihood function. The first is based on the method of Scoring. The second is the EM algorithm, a derivative-free method. Each iteration of EM requires a Kalman filter and smoother followed by straightforward regression calculations. The paper suggests using the EM methods to quickly locate a neighborhood of the maximum. Scoring can then be used to pinpoint the maximum and calculate the information matrix.
Опубликовано на портале: 06-10-2004Robert A. Jarrow, David Lando, Stuart M. Turnbull Review of Financial Studies. 1997. Vol. 10. No. 2. P. 481-523.
This article provides a Markov model for the term structure of credit risk spreads. The model is based on Jarrow and Turnbull (1995), with the bankruptcy process following a discrete state space Markov chain in credit ratings. The parameters of this process are easily estimated using observable data. This model is useful for pricing and hedging corporate debt with imbedded options, for pricing and hedging OTC derivatives with counterparty risk, for pricing and hedging (foreign) government bonds subject to default risk (e.g., municipal bonds), for pricing and hedging credit derivatives, and for risk management.
Опубликовано на портале: 24-06-2004Gerard E. Dallal, Leland Wilkinson American Statistician. 1986. Vol. 40. No. 4. P. 294-296.
Table 1 corrects the critical values for testing normality reported by Lilliefors (1967). The corrected table allows us to derive a simple analytic approximation to the upper tail probabilities of his test statistic for probabilities less than 0.10. With few exceptions, the approximation is more accurate than Lilliefors's original table.
An Efficient Filtering Approach to Likelihood Approximation for State-Space Representations [статья]
Опубликовано на портале: 26-11-2007David N. DeJong, Hariharan Dharmarajan, Roman Liesenfeld, Jean-Francois Richard Economics Working Papers of Department of Economics and Business, Universitat Pompeu Fabra. 2007. No. 2007-25.
We develop a numerical filtering procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-gaussian state-space models. The procedure approximates necessary integrals using continuous or piecewise-continuous approximations of target densities. Construction is achieved via efficient importance sampling, and approximating densities are adapted to fully incorporate current information.
Опубликовано на портале: 07-04-2004Harry H. Kelejian Journal of Econometrics. 1982. Vol. 20. No. 2. P. 325-333.
The Glejser (1969) test for heteroskedasticity concerning the disturbance terms of a regression model is widely referenced - see, e.g., Goldfeld and Quandt (1972), Johnston (1972), Theil (1971) and Maddala (1978) among others. As originally proposed, Glejser suggested estimating the model’s disturbance terms via least squares, and then regressing their absolute values on certain known functions of the regressors; the suggested test for heteroskedasticity then relates to the significance of the ‘slope’ coefficients. Obvious modifications of this procedure, such as using squared estimated disturbance terms, have been suggested - see Goldfeld and Quandt (1972), and Kelejian and Oates (1974); still others have suggested modifications of the procedure which involve iterations - see Maddala (1978). Glejser noted that there may be shortcomings in the procedure which arise due to the use of the estimated disturbances in the second-stage regression. Goldfeld and Quandt (1972), among others, also noted shortcomings in the procedure but recognized that conditions may exist under which these shortcomings are of no consequence in the relevant asymptotic distribution; they went on to note, however, that at the time, a demonstration of such conditions was not available. In recent papers Amemiya (1977) and White (1980) gave results which justify the large sample version of the Glejser test based on squared estimated disturbances. However, their results assumed the absence of lagged dependent variables, and were given in the single-equation context. The purpose of this paper is to extend the Amemiya (1977) and White (1980) results to the case of a simultaneous equation framework, which may or may not contain lagged endogenous variables. We consider two cases. The first is the one in which the researcher suspects that heteroskedasticity may exist in only one of the system’s equations. This extension is not trivial due to, among other things, feedbacks involving the endogenous regressors. Nevertheless, it turns out that if the least-squares procedure in the first stage is replaced by virtually any consistent procedure, such as two-stage least- squares - henceforth 2SLS, no additional complexities arise. The importance of this result is that under typical modelling specifications, a computationally simple large sample test for heteroskedasticity, which is associated with one equation of a system, can be carried out in the context of that system. This test should be especially useful in those cases in which the exact specification of the ‘suspected’ heteroskedasticity is not known1 The second case we consider is the one in which the researcher suspects that heteroskedasticity may be associated with more than one equation of the system. As expected, the resulting test is computationally more ‘demanding’. The model is specified in section 2, and the basic results are given in section 3. Suggestions for further work are given in section 4; technical details are relegated to the appendix.
Опубликовано на портале: 13-04-2004Donald Wilfrid Kao Andrews, J. Christopher Monahan Econometrica. 1992. Vol. 60. No. 4. P. 953-966.
This paper considers a new class of heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimators. The estimators considered are prewhitened kernel estimators with vector autoregressions employed in the prewhitening stage. The paper establishes consistency, rate of convergence, and asymptotic truncated mean squared error (MSE) results for the estimators when a fixed or automatic bandwidth procedure is employed. Conditions are obtained under which prewhitening improves asymptotic truncated MSE. Monte Carlo results show that prewhitening is very effective in reducing bias, improving confidence interval coverage probabilities, and rescuing over-rejection of t-statistics constructed using kernel-HAC estimators. On the other hand, prewhitening is found to inflate variance and MSE of the kernel estimators. Since confidence interval coverage probabilities and over-rejection of t-statistics are usually of primary concern, prewhitened kernel estimators provide a significant improvement over the standard non-prewhitened kernel estimators.
A Note on Model Selection in (Time Series) Regression Models - General-to-Specific or Specific-to-General? [статья]
Опубликовано на портале: 26-11-2007Helmut Herwartz Economics Working Papers of Department of Economics and Business, Universitat Pompeu Fabra. 2007. No. 2007-09.
The paper provides Monte Carlo evidence on the performance of general-to-specific and specific-to-general selection of explanatory variables in linear (auto)regressions. In small samples the former is markedly inefficient in terms of ex-ante forecasting performance.
A Note on the Coefficient of Determination in Regression Models with Infinite-Variance Variables [статья]
Опубликовано на портале: 03-12-2007Jeong-Ryeol Kurz-Kim, Michael Stanislaus Loretan Discussion Paper Series 1: Economic Studies. 2007. No. 10/2007.
Since Mandelbrot's seminal work (1963), alpha-stable distributions with infinite variance have been regarded as a more realistic distributional assumption than the normal distribution for some economic variables, especially financial data. After providing a brief survey of theoretical results on estimation and hypothesis testing in regression models with infinite-variance variables, we examine the statistical properties of the coefficient of determination in regression models with infinite-variance variables. These properties differ in several important aspects from those in the well-known finite variance case. In the infinite-variance case when the regressor and error term share the same index of stability, the coefficient of determination has a nondegenerate asymptotic distribution on the entire [0,1] interval, and the probability density function of this distribution is unbounded at 0 and 1. We provide closedform expressions for the cumulative distribution function and probability density function of this limit random variable. In an empirical application, we revisit the Fama-MacBeth two-stage regression and show that in the infinite variance case the coefficient of determination of the second-stage regression converges to zero asymptotically.
Опубликовано на портале: 06-04-2004Svend Hylleberg, Grayham E. Mizon Economics Letters. 1989. Vol. 29. No. 3. P. 225-230.
It is shown that the application of the result that the Dickey-Fuller `T' obtained from a regression with an intercept is asymptotically normal if the DGP is a random walk with drift may be of little use in small samples unless the drift is enormous. In fact the Dickey-Fuller distribution may give a better approximation in many case.
Опубликовано на портале: 06-04-2004Jeffrey M. Wooldridge Economics Letters. 1990. Vol. 34. No. 2. P. 151-155.
The asymptotic properties of a regression-based Lagrange multiplier test for omitted variables in the context of two stage least squares is discussed, and an F-statistic for 2SLS regressions is proposed. The choice of instruments under the null and alternative models is explicitly considered, thereby clearing up some unresolved issues in the literature