6,809 research outputs found

    Asymptotic normality of extreme value estimators on C[0,1]C[0,1]

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    Consider nn i.i.d. random elements on C[0,1]C[0,1]. We show that, under an appropriate strengthening of the domain of attraction condition, natural estimators of the extreme-value index, which is now a continuous function, and the normalizing functions have a Gaussian process as limiting distribution. A key tool is the weak convergence of a weighted tail empirical process, which makes it possible to obtain the results uniformly on [0,1][0,1]. Detailed examples are also presented.Comment: Published at http://dx.doi.org/10.1214/009053605000000831 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Regulation and the neo-Wicksellian approach to monetary policy

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    Laubach and Williams (2003) employ a Kalman filter approach to jointly estimate the neutral real federal funds rate and trend output growth using an IS relationship and an output gap based inflation equation. They find a positive link between these two variables, but also much error surrounding neutral real rate estimates. We modify their approach by including variables for regulations on deposit interest rates and on wages and prices. These variables are statistically significant and notably affect estimates of two policy relevant coefficients: the sensitivity of output to the real interest rate and that of inflation to the output gap.Monetary policy ; Federal funds rate
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