New PDF release: Macroeconometrics: Developments, Tensions, and Prospects

Nonfiction 10

By Kevin D. Hoover (auth.), Kevin D. Hoover (eds.)

ISBN-10: 9401042934

ISBN-13: 9789401042932

ISBN-10: 940110669X

ISBN-13: 9789401106696

Each bankruptcy of Macroeconometrics is written through revered econometricians which will offer worthwhile details and views if you desire to practice econometrics in macroeconomics. The chapters are all written with transparent methodological views, making the virtues and obstacles of specific econometric methods obtainable to a common readership conversant in utilized macroeconomics. the genuine tensions in macroeconometrics are printed through the severe reviews from diversified econometricians, having an alternate standpoint, which stick with each one chapter.

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Download e-book for iPad: Macroeconometrics: Developments, Tensions, and Prospects by Kevin D. Hoover (auth.), Kevin D. Hoover (eds.)

Every one bankruptcy of Macroeconometrics is written via revered econometricians to be able to supply worthy details and views if you happen to desire to practice econometrics in macroeconomics. The chapters are all written with transparent methodological views, making the virtues and obstacles of specific econometric techniques obtainable to a normal readership acquainted with utilized macroeconomics.

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Extra info for Macroeconometrics: Developments, Tensions, and Prospects

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Several authors have attempted to ground calibration on a finner statistical footing. Gregory and Smith (1989,1991) and Christiano and Eichenbaum (1992) treat calibration as a method-of-moments estimator. S. data. Since real depreciation is not constant across different types of capital, the average rate of depreciation (the sample first moment) would be used to estimate 0. Then uncertainty about the calibrated value of 0 arises from sampling error in estimating the mean rate of depreciation across different types of capital.

They propose that models be augmented by additional shocks, until the number of shocks in the model equals the number of observed variables in the data set. In the example, suppose that 8 were random. Then the solution to the model is essentially the same: = (1 - {3)(1 - 8, + A,)k'_I' k, = f3(1 - 8, + A,)k'_I' c, Now the equation that ties consumption to output and lagged consumption is c, = f3y, + (1 - f3)(1 - 8,)c t _ l· Unless we have restricted {8" t = I, ... , T} a priori, for any f3, we can always find a sequence for depreciation such that the previous equation holds.

Judd (1991) presents a critique of this method, to which Marcet (1993) responds. 9. There is no reason to backsolve a linear model; I use this eumple for pedagogic purposes. 10. J[c, ~t A,)' = O. 11. The exceptions of which I am aware are Altug (1989), McGrattan (1994), and Leeper and Sims (1994). 12. If the available data was the capital stock instead of the consumption series, we could use the same steps to derive an equality involving k, and EM' 13. However, if a researcher is planning to perfonn a policy experiment in which the model is simulated, or if the researcher is going to examine the statistical properties of the series in the model, this fonn will need to be specified.

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Macroeconometrics: Developments, Tensions, and Prospects by Kevin D. Hoover (auth.), Kevin D. Hoover (eds.)


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