2,701 research outputs found

    CONFIDENCE INTERVALS FOR VARIANCE COMPONENTS USING NON-NORMAL DISTRIBUTIONS

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    Simulation studies are conducted to evaluate the performance of confidence intervals for variance components under non-normal distribution assumptions. Confidence intervals based on the pivotal quantity (PQ) method and the large-sample properties of the restricted maximum likelihood (REML) estimator are considered. Of particular interest is the actual coverage value of nominal 95% confidence intervals for a ratio of variance components. In the context of unbalanced one-way random effects models, simulation results and an empirical example involving arsenic concentrations in oyster tissue suggest that the REML-based confidence interval is preferred

    Evaluating the Precision of Estimators of Quantile-Based Risk Measures

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    This paper examines the intra-day seasonality of transacted limit and market orders in the DEM/USD foreign exchange market. Empirical analysis of completed transactions data based on the Dealing 2000-2 electronic inter-dealer broking system indicates significant evidence of intraday seasonality in returns and return volatilities under usual market conditions. Moreover, analysis of realised tail outcomes supports seasonality for extraordinary market conditions across the trading day.Value at Risk, Expected Shortfall, Spectral Risk Measures, Moments, Precision.

    Assessing heterogeneity in meta-analysis: Q statistic or I2 index?

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    In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I² index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the Q test and the confidence interval around the I² index are compared by means of a Monte Carlo simulation. The results show the utility of the I² index as a complement to the Q test, although it has the same problems of power with a small number of studies

    A New Right Tailed Test of the Ratio of Variances

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    It is important to be able to compare variances efficiently and accurately regardless of the parent populations. This study proposes a new right tailed test for the ratio of two variances using the Edgeworth’s expansion. To study the Type I error rate and Power performance, simulation was performed on the new test with various combinations of symmetric and skewed distributions. It is found to have more controlled Type I error rates than the existing tests. Additionally, it also has sufficient power. Therefore, the newly derived test provides a good robust alternative to the already existing methods

    Vol. 13, No. 1 (Full Issue)

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    Efficient Inflation Estimation

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    This paper investigates the use of trimmed means as high-frequency estimators of" inflation. The known characteristics of price change distributions, specifically the observation" that they generally exhibit high levels of kurtosis, imply that simple averages of price data are" unlikely to produce efficient estimates of inflation. Trimmed means produce superior estimates" of core inflation,' which we define as a long-run centered moving average of CPI and PPI" inflation. We find that trimming 9% from each tail of the CPI price-change distribution from the tails of the PPI price-change distribution, yields an efficient estimator of core inflation" for these two series, although lesser trims also produce substantial efficiency gains. Historically the optimal trimmed estimators are found to be nearly 23% more efficient (in terms of root-mean-square error) than the standard mean CPI Moreover, the efficient estimators are robust to sample period and to the definition of the" presumed underlying long-run trend in inflation.
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