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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.

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The savings-inflation puzzle

TL;DR: The authors found that inflation does not unanimously decrease savings in the US during the postwar period, and this result is puzzling as it contradicts the implications of most monetary general equilibria models.
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What Defines "News" in Foreign Exchange Markets?

TL;DR: This paper examined the intra-daily influence of a broad set of news reports, including variables which are not typically considered "fundamentals" in the context of standard models of exchange rate determination, and ask whether they too help predict exchange rate behavior.
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FDI and Growth: What Cross-Country Industry Data Say

TL;DR: In this article, the authors provide evidence that FDI has a positive and statistically significant growth effect in recipient countries, using a panel of 14 manufacturing sectors for (a sample of) developed and developing countries over the period 1992 -2004.
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The ACD Model: Predictability of the Time Between Consecutive Trades

TL;DR: In this article, the authors compared the performance of several parameterizations of ACD models compared to benchmark linear autoregressions for inter-trade durations and proposed a new constructive test based on the series of probability integral transforms.
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Forecasting Stock Returns through An Efficient Aggregation of Mutual Fund Holdings

TL;DR: This paper developed a stock return-predictive measure based on an efficient aggregation of the portfolio holdings of all actively managed U.S. domestic equity mutual funds, and used this model to study the source of fund managers' stock selection abilities.
References
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Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data

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.
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