9,271 research outputs found

    Optimal Growth with Heterogeneous Agents and the Twisted Turnpike: An Example

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    The dynamics of a welfare maximizing, heterogeneous agent, one sector optimal Ramsey model is analyzed assuming two agents, each with a distinct discount factor and log utility. Production is Cobb-Douglas. Explicit time varying policy functions are derived, one for each period. A Twisted Turnpike Property and eventually monotone dynamics are demonstrated to govern the evolution of the economy’s aggregate capital stock.

    Discretion, rules and volatility - commentary

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    Business cycles

    Efficient Ramsey Equilibria

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    Ramsey equilibrium models with heterogeneous agents and borrowing constraints are shown to yield efficient equilibrium sequences of aggregate capital and consumption. The proof of this result is based on verifying that equilibrium sequences of prices satisfy the Malinvaud criterion for efficiency.

    Radio Observations of 4079 Quasars

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    Using the NVSS radio catalog, we have searched for radio emission from 4079 quasars taken from the 1996 version of the Veron-Cetty and Veron (1996) quasar catalog. The comparison resulted in the positive detection of radio emission from 799 quasars. Of these, 168 are new radio detections. Examination of the radio luminosities shows a dramatic increase in the fraction of radio-loud quasars from the current epoch to z=0.5 and a gradual decline beyond z=1.0. Inspection of the radio-loud fraction as a function of M_B shows little dependence fainter than M_B=-29.5.Comment: 25 pages, including 9 figures and 1 tabl

    Selected Issues in the Rise of Income Inequality

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    macroeconomics, Income Inequality

    A Cholesky-MIDAS model for predicting stock portfolio volatility

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    This paper presents a simple forecasting technique for variance covariance matrices. It relies significantly on the contribution of Chiriac and Voev (2010) who propose to forecast elements of the Cholesky decomposition which recombine to form a positive definite forecast for the variance covariance matrix. The method proposed here combines this methodology with advances made in the MIDAS literature to produce a forecasting methodology that is flexible, scales easily with the size of the portfolio and produces superior forecasts in simulation experiments and an empirical application.Cholesky, Midas, volatility forecasts
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