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A Very Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
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This article is published in Research Papers in Economics.The article was published on 1991-01-01 and is currently open access. It has received 736 citations till now. The article focuses on the topics: Covariance function & Estimation of covariance matrices.read more
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International stock market efficiency: a non-Bayesian time-varying model approach
TL;DR: In this article, a non-Bayesian time-varying vector autoregressive (TV-VAR) model was used to estimate the joint degree of market efficiency in the sense of Fama (1970, 1991).
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Regional inequalities, fiscal decentralization and government quality
TL;DR: In this article, the authors apply a simultaneous equation model, which accounts for the joint determination of these three variables, to a panel of 23 Organisation for Economic Co-operation and Development (OECD) countries and find that a process of fiscal decentralization, accompanied by measures to improve the quality of government, would be an effective strategy for reducing regional inequalities.
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Robust covariance matrix estimation : HAC estimates with long memory/antipersistence correction
TL;DR: This work proposes estimates of the spectral density matrix at zero frequency which are still consistent in such circumstances, adapting automatically to memory parameters that can vary across the vector and be unknown.
Anchoring credit default swap spreads to firm fundamentals
TL;DR: In this paper, the authors examined the capability of firm fundamentals in explaining the cross-sectional variation of credit default swap (CDS) spreads and found that deviations between market quotes and the fundamental valuation predict significantly future market movements.
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Investors’ fear and herding in the stock market
TL;DR: In this article, the authors examined herding in three developed stock markets testing for the impact of investors' "fear" on herding estimations, and employed daily data of all listed stocks from all listed companies.
References
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Large sample properties of generalized method of moments estimators
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Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data
John C. Driscoll,Aart Kraay +1 more
TL;DR: The authors presented conditions under which a simple extension of common nonparametric covariance matrix estimation techniques yields standard error estimates that are robust to very general forms of spatial and temporal dependence as the time dimension becomes large.
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Assessing the Contribution of Venture Capital to Innovation
TL;DR: This paper examined the influence of venture capital on patent applications in twenty industries over three decades and found that increases in venture capital activity in an industry are associated with significantly higher patenting rates.
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Approximately Normal Tests for Equal Predictive Accuracy in Nested Models
TL;DR: In this paper, the mean squared prediction error (MSPE) from the parsimonious model is adjusted to account for the noise in the large model's model. But, the adjustment is based on the nonstandard limiting distributions derived in Clark and McCracken (2001, 2005a) to argue that use of standard normal critical values will yield actual sizes close to, but a little less than, nominal size.
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Tests of Conditional Predictive Ability
TL;DR: This paper proposed a framework for out-of-sample predictive ability testing and forecast selection designed for use in the realistic situation in which the forecasting model is possibly misspecified, due to unmodeled dynamics, unmodelled heterogeneity, incorrect functional form, or any combination of these.