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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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Fiscal convergence in the european union before the crisis
TL;DR: In this article, the authors focus on the convergence of the tax burden and the tax structure for the EU-15 member states over the period 1965-2004, observing limited convergence of fiscal pressure.
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Estimating the Marginal Law of a Time Series With Applications to Heavy-Tailed Distributions
TL;DR: In this article, an estimator obtained by maximization of the "quasi-marginal" likelihood, which is a likelihood written as if the observations were independent, was used to estimate parametric marginal densities of stationary time series.
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Congress and the Political Expansion of the U.S. Districts Courts
TL;DR: In this paper, the authors examine empirically the relative importance of caseload pressure and political motives for Congress to expand the number of federal district judgeships and demonstrate that politics dominates the timing of judgeship expansion in the U.S. District Courts.
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Asymptotic F and t Tests in an Efficient GMM Setting
TL;DR: In this paper, a simple and easy-to-implement modification to the trinity of test statistics in the two-step efficient GMM setting was proposed and the modified test statistics are all asymptotically F distributed under the so-called fixed-smoothing asmptotics.
Generalized Forecast Errors, A Change of Measure, and Forecast Optimality
TL;DR: In this article, the authors established properties of optimal forecasts under general loss functions, extending existing results obtained under speci c functional forms and data generating processes, and proposed a new method that changes the probability measure under which the well-known properties of optimality under mean squared error loss can be recovered.
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.