Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation

Andrews, Donald W.K.

doi:10.2307/2938229

Cited by 3,437 publications

(3,035 citation statements)

References 25 publications

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“…To make full use of the data, we generate the average spreads with overlapping sample periods. We estimate equation (1) using the generalized method of moments, with the weighting matrix computed according to Newey and West (1987) and the lags chosen optimally according to Andrews (1991) based on an VAR(1) specification. Table 1 reports the estimates and the absolute magnitudes of the t-statistics (in parentheses) of the panel regressions.…”

Section: Data and Evidencementioning

confidence: 99%

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Chen

Cheng

2005

SSRN Journal

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Using a large data set on credit default swaps, we study how default risk interacts with interest-rate risk and liquidity risk to jointly determine the term structure of credit spreads. We classify the reference companies into two broad industry sectors, two broad credit rating classes, and two liquidity groups. We develop a class of dynamic term structure models that include (i) two benchmark interest-rate factors to capture the libor and swap rates term structure, (ii) two credit-risk factors to capture the credit swap spreads of high-liquidity group of each industry and rating class, and (iii) both an additional credit-risk factor and a liquidity-risk factor to capture the difference between the high-and low-liquidity groups.Estimation shows that companies in different industry and credit rating classes have different credit-risk dynamics. Nevertheless, in all cases, credit risks exhibit intricate dynamic interactions with the interestrate factors. Interest-rate factors both affect credit spreads simultaneously, and impact subsequent moves in the credit-risk factors. Within each industry and credit rating class, we also find that the average credit default swap spreads for the high-liquidity group are significantly higher than for the low-liquidity group. Estimation shows that the difference is driven by both credit risk and liquidity differences. The low-liquidity group has a lower default arrival rate and also a much heavier discounting induced by the liquidity risk.JEL CLASSIFICATION CODES: E43, G12, G13, C51.KEY WORDS: Credit default swap; credit risk; credit premium; term structure; interest rate risk; liquidity risk; liquidity premium; maximum likelihood estimation. Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap SpreadsIt is important to understand how credit risk interacts with interest-rate risk and liquidity risk in determining the term structure of credit spreads on different reference entities. Nevertheless, limited data availability has severely hindered the understanding. Since defaults are rare events that often lead to termination or restructuring of the underlying reference entity, researchers need to rely heavily on cross-sectional averages of different entities over a long history to obtain any reasonable estimates of statistical default probabilities.Although corporate bond prices contain useful information on the default probability and the price of credit risk, the information is often mingled with the pricing of the underlying interest-rate risk and other factors such as liquidity and tax. 1 The recent development in credit derivatives provides us with an excellent opportunity to better understand the pricing of credit risk, its interactions with interest-rate risk and liquidity, and the impacts on the term structure of credit spreads. The most widely traded credit derivative is in the form of credit default swap (CDS), written on a reference entity such as a sovereign country or a cor...

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Section: Data and Evidencementioning

confidence: 99%

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Chen

Cheng

2005

SSRN Journal

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“…Les tests sont quelquefois sensibles au choix du paramètre k (quoique la pratique suggère une moindre sensibilité que dans l'approche de Dickey et Fuller). Il peut être désirable de sélectionner k selon une méthode basée sur la nature des données (telle que celle suggérée par Andrews, 1991), mais aucune étude traitant des propriétés de ces statistiques dans un tel contexte n'est disponible à l'heure actuelle.…”

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Racines unitaires en macroéconomie : le cas d’une variable

Perron

2009

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“…For comparison purposes, we include in our experiments two popular LRV estimators that are consistent in the usual asymptotic thought experiment: the quadratic spectral estimator Ω QA with an automatic bandwidth selection using an AR(1) model for the bandwidth determination as suggested by Andrews (1991), and an AR(1) prewhitened LRV estimatorΩ P W with a second stage automatic bandwidth quadratic spectral kernel estimator as described in Andrews and Monahan (1992). The (asymptotically justified) critical values of thet and F -tests (4) based onΩ QA andΩ P W are accordingly those from standard normal and χ 2 distributions.…”

Section: Quantitative Evaluationmentioning

confidence: 99%

“…The following Theorem provides the answer in the class of quadratic LRV estimators, along with the form of the LRV estimators that optimally trade off robustness against efficiency. Comparable to Andrews (1991), the variance of the LRV estimators is used as a proxy for their inefficiency when employed in the tests (4).…”

Section: It Corresponds Tomentioning

confidence: 99%

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A theory of robust long-run variance estimation

Müller

2007

Journal of Econometrics

101

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The paper studies the robustness of long-run variance estimators employed for conducting Wald-type tests in standard time series models. It is shown that all long-run variance estimators that are consistent for the variance of Gaussian White Noise lack robustness in the sense that they yield arbitrary results for some underlying process that satisfies a Functional Central Limit Theorem. An analytical measure of robustness of long-run variance estimators is suggested that captures the degree of this fragility.A family of inconsistent long-run variance estimators is derived that optimally trade off this measure of robustness against efficiency. A minor modification of these optimal estimators lead to asymptotically F-distributed test statistics under the null hypothesis, so that robust large sample inference can be conducted very similarly to well-understood small sample Gaussian inference.JEL Classification: C13, C12, C32

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Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation

Cited by 3,437 publications

References 25 publications

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Racines unitaires en macroéconomie : le cas d’une variable

A theory of robust long-run variance estimation

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