Journal of Econometrics
Опубликовано на портале: 06-04-2004
Robert 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: 07-04-2004
Harry 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: 13-04-2004
Tim Bollerslev, Ray Y. Chou, Kenneth F. Kroner
Journal of Econometrics.
1992.
Vol. 52.
No. 1-2.
P. 5-59.
Although volatility clustering has a long history as a salient empirical regularity
characterizing high-frequency speculative prices, it was not until recently that
applied researchers in finance have recognized the importance of explicitly modeling
time-varying second-order moments. Instrumental in most of these empirical studies
has been the Autoregressive Conditional Heteroskedasticity (ARCH) model introduced
by Engle (1982). This paper contains an overview of some of the developments in the
formulation of ARCH models and a survey of the numerous empirical applications using
financial data. Several suggestions for future research, including the implementation
and tests of competing asset pricing theories, market microstructure models, information
transmission mechanisms, dynamic hedging strategies, and the pricing of derivative
assets, are also discussed.
Опубликовано на портале: 13-04-2004
Donald Wilfrid Kao Andrews
Journal of Econometrics.
1988.
Vol. 37.
No. 1.
P. 135-157.
The Pearson chi-square testing method is extended to nondynamic parametric econometric
models, particularly models with covariates. A chi-square test is developed that
is applicable in a variety of cross-sectional models including panel data methods.
It can be employed to test the null hypothesis that the specified parametric model
is correct, i.e., the classical goodness-of-fit hypothesis. It also can be employed
to test more specific aspects of a parametric model. The tests are applicable in
models with covariates that are discrete, continuous, or mixed. The cells may be
chosen by using the data, may have flexible shapes, and may partition the product
space of the response variable and covariate spaces. The estimator employed to calculate
the conditionally expected number of outcomes in each cell can be chosen quite generally.
Furthermore, any regular, asymptotically normal estimator can be used.
Abstract2: This paper and its sequel, Andrews, extend the Pearson chi-square
testing method to non-dynamic parametric econometric models, in particular, models
with covariates. The present paper introduced the test and discusses a wide variety
of applications. Andrews establishes the asymptotic properties of the test, by extending
recent probabilistic results for the weak convergence of empirical processes indexed
by sets. The chi-square test that is introduced can be used to test goodness-of-fit
of a parametric model, as well as to test particular aspects of the parametric model
that are of interest. In the event of rejection of the null hypothesis of correct
specification, the test provides information concerning the direction of departure
from the null. The results allow for estimation of the parameters of the model by
quite general methods. The cells used to construct the test statistic my be random
and can be specified in a general form.
Опубликовано на портале: 05-02-2007
Ronald G. Ehrenberg
Journal of Econometrics.
2004.
Vol. 121.
No. 1.
P. 19-37 .
This paper surveys the various strands of the literature on the econometrics of higher
education that have developed during the last 40 years and indicates how the papers
in the special issue of the Journal of Econometrics fit into this literature. It
discusses in turn the estimation of rates of return to higher education, studies
of the academic labor market, studies relating to institutional behavior and studies
relating to higher education as an industry. It concludes by suggesting a number
of important areas for future research.
Generalised residuals [статья]
Опубликовано на портале: 05-01-2003
Christian Gourieroux, Alain Monfort, Alain Trognon, Eric Renault
Journal of Econometrics.
1987.
Vol. 34.
No. 1-2.
P. 5-32.
This paper proposes a definition of generalised residuals for a large class of non-linear
econometric models. These residuals are shown to have properties similar to those
of the familiar residuals in the linear model and to be useful in many hypothesis
testing problems.
Опубликовано на портале: 13-04-2004
Tim Bollerslev
Journal of Econometrics.
1986.
Vol. 31.
No. 3.
P. 307-327.
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic)
process introduced in Engle (1982) to allow for past conditional variances in the
current conditional variance equation is proposed. Stationarity conditions and autocorrelation
structure for this new class of parametric models are derived. Maximum likelihood
estimation and testing are also considered. Finally an empirical example relating
to the uncertainty of the inflation rate is presented.
Опубликовано на портале: 26-09-2007
William A. Brock, Steven N. Durlauf, Kenneth D. West
Journal of Econometrics.
2007.
Vol. 136.
No. 2.
P. 629-664.
This paper explores ways to integrate model uncertainty into policy evaluation. We
first describe a general framework for the incorporation of model uncertainty into
standard econometric calculations. This framework employs Bayesian model averaging
methods that have begun to appear in a range of economic studies. Second, we illustrate
these general ideas in the context of assessment of simple monetary policy rules
for some standard New Keynesian specifications. The specifications vary in their
treatment of expectations as well as in the dynamics of output and inflation. We
conclude that the Taylor rule has good robustness properties, but may reasonably
be challenged in overall quality with respect to stabilization by alternative simple
rules that also condition on lagged interest rates, even though these rules employ
parameters that are set without accounting for model uncertainty
Опубликовано на портале: 06-04-2004
A. Colin Cameron, Pravin K. Trivedi
Journal of Econometrics.
1990.
Vol. 46.
No. 3.
P. 347-364.
A property of the Poisson regression model is mean-variance equality, conditional
on explanatory variables. "Regression-based" tests for this property are proposed
in a very general setting. Unlike classical statistical tests, these tests require
specification of only the mean-variance relationship under the alternative, rather
than the complete distribution whose choice is usually arbitrary. The optimal regression-based
test is easily computed as the t-test from an auxiliary regression. If a distribution
under the alternative hypothesis is in fact specified and is in the Katz system of
distributions or is Cox's local approximation to the Poisson, the score test for
the Poisson distribution is equivalent to the optimal regression-based test.
Опубликовано на портале: 06-04-2004
Andrew Chesher, Margaret Irish
Journal of Econometrics.
1987.
Vol. 34.
No. 1-2.
P. 33-62.
Graphical and numerical analysis of residual can be informative about model misspecification
even when data are censored or grouped. This paper provides simple procedures for
calculating diagnostic statistics to detect model misspecification when grouped or
censored data are analysed using a normal linear model. Graphs can reveal the nature
of the correlations that these statistics pick up but when grouping or censoring
is severe they can be difficult to interpret. We discuss the processing of graphs
so that they are more easily interpreted and provide examples based on artificial
data and on grouped data relating to unemployment durations.
Опубликовано на портале: 01-07-2004
Andrew Chesher
Journal of Econometrics.
1985.
Vol. 28.
No. 3.
P. 291-305.
Efficient estimation of normal linear simultaneous equations systems is frequently
easier when error covariances are zero. The score test is examined for the hypothesis
that an error covariance is zero in a 2-equation recursive normal linear simultaneous
equations system where endogenous variates may be completely observed, censored,
or grouped. The model contains the seemingly unrelated regression equation model
and its analogues for grouped and censored data as special cases. The score test
for the hypothesis explores the sample covariance of suitably defined residuals and
is closely related to the Information Matrix test calculated for the restricted model
in which the error covariance is zero. These results are obtained by viewing a non-zero
error covariance as emerging from correlated random variation in intercept parameters
that can be detected through the use of Chesher's (1984) test for neglected heterogeneity
Опубликовано на портале: 25-10-2007
Svend Hylleberg, Robert F. Engle, Clive W. J. Granger, Byung Sam Yoo
Journal of Econometrics.
1990.
Vol. 44.
No. 1.
P. 215-238.
This paper develops tests for roots in linear time series which have a modulus of
one but which correspond to seasonal frequencies. Critical values for the tests are
generated by Monte Carlo methods or are shown to be available from Dickey-Fuller
or Dickey-Hasza-Fuller critical values. Representations for multivariate processes
with combinations of seasonal and zero-frequency unit roots are developed leading
to a variety of autoregressive and error-correction representations. The techniques
are used to examine cointegration at different frequencies between consumption and
income in the U.K.
Опубликовано на портале: 06-04-2004
John Kennan
Journal of Econometrics.
1985.
Vol. 28.
No. 1.
P. 5-28.
This paper develops new evidence on the hazard function for strike duration, and
on cyclical changes in this function, using data on contract strikes in U.S. manufacturing
industries. A flexible duration model is estimated, and it is found that the hazard
rate is generally a U-shaped function of strike age. The level of industrial production
is found to have a significant positive effect on the hazard rate: strike duration
is countercyclical. A convenient parametric model of heterogeneity and duration dependence
is introduced, in which the logit of the hazard rate is a polynomial function of
strike age, up to a random individual effect drawn from a beta distribution. Estimates
of this `beta-logit' model indicate that it is difficult to detect the influence
of unobserved heterogeneity on the aggregate hazard function for strike duration.
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