Asymptotic Expansions of the Information Matrix Test Statistic

Chesher, Andrew; Spady, Richard H.

doi:10.2307/2938228

Cited by 88 publications

(49 citation statements)

References 15 publications

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“…Testing Gamma or reciprocal Gamma against GIG are examples of this situation. Other examples of interest are conjugate families of non-negative random variables without moments generating function, testing exponentiality against singly truncated normal distribution (Castillo and Puig, 1999-a) and several situations in reliability theory and survival analysis, see Castillo and Puig (1999-b Taylor (1987), Orme (1990), Chesher and Spady (1991), Davidson and MacKinnon (1992), and Horowitz (1994. Several approaches have been proposed to overcome this problem.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The Use of Score Tests for Inference on Variance Components

Verbeke¹,

Molenberghs²

2003

Biometrics

203

144

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Summary Whenever inference for variance components is required, the choice between one‐sided and two‐sided tests is crucial. This choice is usually driven by whether or not negative variance components are permitted. For two‐sided tests, classical inferential procedures can be followed, based on likelihood ratios, score statistics, or Wald statistics. For one‐sided tests, however, one‐sided test statistics need to be developed, and their null distribution derived. While this has received considerable attention in the context of the likelihood ratio test, there appears to be much confusion about the related problem for the score test. The aim of this paper is to illustrate that classical (two‐sided) score test statistics, frequently advocated in practice, cannot be used in this context, but that well‐chosen one‐sided counterparts could be used instead. The relation with likelihood ratio tests will be established, and all results are illustrated in an analysis of continuous longitudinal data using linear mixed models.

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Section: Resultsmentioning

confidence: 99%

“…Several approaches have been proposed to overcome this problem. Chesher and Spady (1991) derive, for specific models, critical values for the IM test statistic that are based on a higher order Edgeworth expansion. Davidson and MacKinnon (1992) propose a variant of the IM test based on double-length artificial regressions.…”

Section: Resultsmentioning

confidence: 99%

The Use of Score Tests for Inference on Variance Components

Verbeke¹,

Molenberghs²

2003

Biometrics

203

144

View full text Add to dashboard Cite

show abstract

“…In contrast, not much work has been done on the finite sample properties of the nonlinear statistics, although see Roberston and Fryer (1970), Amemiya (1980), Chesher and Spady (1989), Cordeiro and McCullagh (1991), Koenker et al (1992), and Newy and Smith (2001). However, most of these works are for some specific estimators and there is little with the dependent observations for nonlinear cases, although see Cordeiro and Klein (1994) and Linton (1997).…”

Section: Introductionmentioning

confidence: 99%

The second-order bias and mean squared error of estimators in time-series models

Bao

Ullah

2007

Journal of Econometrics

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We develop the analytical results on the second-order bias and mean squared error (MSE) of estimators in time series. These results provide a unified approach to developing the properties of a large class of estimators in the linear and nonlinear time series models and they are valid for both the normal and non-normal sample of observations, and where the regressors are stochastic. The estimators included are the generalized method of moments, maximum likelihood, least squares, and other extremum estimators. Our general results are applied to a wide variety of econometric models. Numerical results for some of these models are presented.

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“…To test the null hypothesis that the durations are exponentially distributed, we use a test statistic based on the equality between the mean and the standard deviation (see, e.g. Chesher and Spady, 1991;Chesher et al, 1999), and a Bootstrap procedure to account for finite sample level distortions. We consider models with absolute variation sizes a ranging from 0.25% to 5%.…”

Section: Ibm Transaction Datamentioning

confidence: 99%

Option pricing with discrete rebalancing

Prigent

Renault²,

Scaillet³

2004

Journal of Empirical Finance

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We consider option pricing when dynamic portfolios are discretely rebalanced. The portfolio adjustments only occur after fixed relative changes in the stock price. The stock price follows a marked point process (MPP) and the market is incomplete. We first characterise the equivalent martingale measures. An explicit pricing formula based on the minimal martingale measure (MMM) is then provided together with the hedging strategy underlying portfolio adjustments. Two examples illustrate our pricing framework: a jump process driven by a latent geometric Brownian motion and a marked Poisson process. We establish the convergence to the Black -Scholes model when the triggering price increment shrinks to zero. For the empirical application, we use IBM, France Telecom (FT) and CAC 40 intraday transaction data, and compare option prices given by the marked Poisson model, the Black -Scholes model and observed option prices. D

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Asymptotic Expansions of the Information Matrix Test Statistic

Cited by 88 publications

References 15 publications

The Use of Score Tests for Inference on Variance Components

The Use of Score Tests for Inference on Variance Components

The second-order bias and mean squared error of estimators in time-series models

Option pricing with discrete rebalancing

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