Hlbert White 的计量经济学论文
共10篇，全部是 英文版 ，pdf格式
1. 论文名称：A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
发表刊物名称及页码：Econometrica, Vol. 48, No. 4. (May, 1980), pp. 817-838.
发表时间：May,1980
引用网址：http://links.jstor.org/sici?sici=0012-9682%28198005%2948%3A4%3C817%3AAHCMEA%3E2.0.CO%3B2-K
论文摘要：
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.
2. 论文名称：A Reality Check for Data Snooping
发表刊物名称及页码：Econometrica, Vol. 68, No. 5. (Sep., 2000), pp. 1097-1126.
发表时间：2000年9月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28200009%2968%3A5%3C1097%3AARCFDS%3E2.0.CO%3B2-9
论文摘要：
Data snooping occurs when a given set of data is used more than once for purposes of
inference or model selection. When such data reuse occurs, there is always the possibility
that any satisfactory results obtained may simply be due to chance rather than to any
merit inherent in the method yielding the results. This problem is practically unavoidable
m the analysis of time-series data, as typically only a single history measuring a given
phenomenon of interest is available for analysis. It is widely acknowledged by empirical
researchers that data snooping is a dangerous practice to be avoided, but in fact it is
endemic. The main problem has been a lack of sufficiently simple practical methods
capable of assessing the potential dangers of data snooping in a given situation. Our
purpose here is to provide such methods by specifying a straightforward procedure for
testing the null hypothesis that the best model encountered in a specification search has
no predictive superiority over a given benchmark model. This permits data snooping to be
undertaken with some degree of confidence that one will not mistake results that could
have been generated by chance for genuinely good results.
3. 论文名称：Consistent Specification Testing Via Nonparametric Series Regression
发表刊物名称及页码：Econometrica, Vol. 63, No. 5. (Sep., 1995), pp. 1133-1159.
发表时间：1995年9月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28199509%2963%3A5%3C1133%3ACSTVNS%3E2.0.CO%3B2-1
论文摘要：
This paper proposes two consistent one-sided specification tests for parametric regression
models, one based on the sample covariance between the residual from the pararnetric
model and the discrepancy between the parametric and nonparametric fitted values;
the other based on the difference in sums of squared residuals between the parametric
and nonparametric models. We estimate the nonparametric model by series regression.
The new test statistics converge in distribution to a unit normal under correct specification
and grow to infinity faster than the parametric rate (n-'/') under misspecification,
while avoiding weighting, sample splitting, and non-nested testing procedures used elsewhere
in the literature. Asymptotically, our tests can be viewed as a test of the joint
hypothesis that the true parameters of a series regression model are zero, where the
dependent variable is the residual from the parametric model, and the series terms are
functions of the explanatory variables, chosen so as to support nonparametric estimation
of a conditional expectation. We specifically consider Fourier series and regression
splines, and present a Monte Carlo study of the finite sample performance of the new
tests in comparison to consistent tests of Bierens (19901, Eubank and Spiegelman (19901,
Jayasuriya (1990), Wooldridge (19921, and Yatchew (1992); the results show the new tests
have good power, performing quite well in some situations. We suggest a joint Bonferroni
procedure that combines a new test with those of Bierens and Wooldridge to capture the
best features of the three approaches.
4. 论文名称：Consistent Specification Testing with Nuisance Parameters Present Only under the
Alternative
发表刊物名称及页码：Econometric Theory, Vol. 14, No. 3. (Jun., 1998), pp. 295-325
发表时间：1998年6月
引用网址：http://links.jstor.org/sici?sici=0266-4666%28199806%2914%3A3%3C295%3ACSTWNP%3E2.0.CO%3B2-X
论文摘要：
The nonparametric and the nuisance parameter approaches to consistently testing
statistical models are both attempts to estimate topological measures of distance
between a parametric and a nonparametric fit, and neither dominates in experiments.
This topological unification allows us to greatly extend the nuisance parameter
approach. How and why the nuisance parameter approach works and how it can
be extended bear closely on recent developments in artificial neural networks. Statistical
content is provided by viewing specification tests with nuisance parameters
as tests of hypotheses about Banach-valued random elements and applying the Banach
central limit theorem and law of iterated logarithm, leading to simple procedures
that can be used as a guide to when computationally more elaborate procedures
may be warranted.
5. 论文名称：Determination of Estimators with Minimum Asymptotic Covariance Matrices
发表刊物名称及页码：Econometric Theory, Vol. 9, No. 4. (Dec., 1993), pp. 633-648.
发表时间：1993年12月
引用网址：http://links.jstor.org/sici?sici=0266-4666%28199312%299%3A4%3C633%3ADOEWMA%3E2.0.CO%3B2-4
论文摘要：
We give a straightforward condition sufficient for determining the minimum
asymptotic variance estimator in certain classes of estimators relevant to econometrics.
These classes are relatively broad, as they include extremum estimation
with smooth or nonsmooth objective functions; also, the rate of convergence
to the asymptotic distribution is not required to be n-'I2. We present examples
illustrating the content of our result. In particular, we apply our result to
a class of weighted Huber estimators, and obtain, among other things, analogs
of the generalized least-squares estimator for least L,-estimation, 1 I:p < m.
6. 论文名称：High Breakdown Point Conditional Dispersion Estimation with Application to S &
P 500 Daily Returns Volatility
发表刊物名称及页码：Econometrica, Vol. 66, No. 3. (May, 1998), pp. 529-567.
发表时间：1998年5月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28199805%2966%3A3%3C529%3AHBPCDE%3E2.0.CO%3B2-7
论文摘要：
We show that quasi-maximum likelihood (QML) estimators for collditional dispersion
models can be severely affected by a small number of outliers such as market crashes and
rallies. and we propose new estimation strategies (the hvo-stage Hampel estimators and
two-stage S-estimators) resistant to the effects of outliers and study the properties of
these estimators.
We apply our methods to estimate models of the collditional volatility of the daily
returns of the S&P 500 Cash Index series. I11 contrast to QML estimators. our proposed
method resists outliers, revealing an informative new picture of volatility dynamics during
"typical" daily market activity.
KEY~~ORHDigSh :br
eakdown point estimation, conditional volatility. S&P 500. quasimaximum
likelihood estimation. S-estimation.
7. 论文名称：Instrumental Variables Regression with Independent Observations
发表刊物名称及页码：Econometrica, Vol. 50, No. 2. (Mar., 1982), pp. 483-499.
发表时间：1982年3月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28198203%2950%3A2%3C483%3AIVRWIO%3E2.0.CO%3B2-L
论文摘要：
As yet. the theory of instrumental var~ables (IV) est~mation is not appl~cable to data
from a strat~fied cross section (e.g., census data) slnce the moment matrlcea need not
converge. Thls study provides general condit~ons for the consistency and asymptotic
normalit) of the I ? estlmator in this case. Homoskedastic errors are not assumed, and a
new, more general asymptotic parameter covariance matrix estimator is given which IS
consistent regardless of the presence of heteroskedasticity. A new estlmator, two-stage
~nstrumentalv ar~ables.I S proposed wh~chi s asymptotically efficient relative to two-stage
least squares. Tests for model misspecificatlon are also discussed.
8. 论文名称：Maximum Likelihood Estimation of Misspecified Models
发表刊物名称及页码：Econometrica, Vol. 50, No. 1. (Jan., 1982), pp. 1-25.
发表时间：1982年1月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28198201%2950%3A1%3C1%3AMLEOMM%3E2.0.CO%3B2-C
论文摘要：
This paper examines the consequences and detection of model misspecification when
using maximum likelihood techniques for estimation and inference. The quasi-maximum
likelihood estimator (QMLE) converges to a well defined limit, and may or may not be
consistent for particular parameters of interest. Standard tests (Wald, Lagrange Multiplier,
or Likelihood Ratio) are invalid in the presence of misspecification, but more general
statistics are given which allow inferences to be drawn robustly. The properties of the
QMLE and the information matrix are exploited to yield several useful tests for model
misspecification.
9. 论文名称：Nonlinear Regression on Cross-Section Data
发表刊物名称及页码：Econometrica, Vol. 48, No. 3. (Apr., 1980), pp. 721-746.
发表时间：1980年4月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28198004%2948%3A3%3C721%3ANROCD%3E2.0.CO%3B2-R
论文摘要：
The assumption most appropriate for nonlinear relationships estimated on stratified
cross-section data (e.g., the Current Population Surveys) is that of independent not
identically distributed (i.n.i.d.) regressors, not fixed regressors. This study provides
conditions which ensure the consistency and asymptotic normality of nonlinear weighted
least squares estimators with i.n.i.d. regressors for both the known and estimated weights
cases. A general statistic for testing hypotheses about the parameters is given, as well as a
test for model misspecification. The usual conditional parameter covariance matrix
estimator may be an inconsistent estimator of the unconditional covariance matrix, and a
consistent estimator is provided.
10. 论文名称：Nonlinear Regression with Dependent Observations
发表刊物名称及页码：Econometrica, Vol. 52, No. 1. (Jan., 1984), pp. 143-162.
发表时间：1984年1月
引用网址：http://links.jstor.org/sici?sici=0012-9682%28198401%2952%3A1%3C143%3ANRWDO%3E2.0.CO%3B2-1
论文摘要：
This paper provides general conditions which ensure consistency and asymptotic
normality for the nonlinear least squares estimator. These conditions apply to time-series,
cross-section, panel, or experimental data for single equations as well as systems of
equations. The regression errors may be serially correlated and/or heteroscedastic. For an
important special case, we propose a new covariance matrix estimator which is consistent
regardless of the presence of heteroscedasticity or serial correlation of unknown form. We
also give some new tests for model misspecification, based on the information matrix
testing principle.
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