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643
Dynamic Panel Estimation and Homogeneity Testing under CrossSection Dependence, Cowles Foundation Discussion Paper n.1362
, 2002
"... Least squares bias in autoregression and dynamic panel regression is shown to be exacerbated in case of cross section dependence. The bias is substantial and is shown to have serious effects in applications like HAC estimation and dynamic halflife response estimation. To address the bias problem, t ..."
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Cited by 80 (4 self)
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Least squares bias in autoregression and dynamic panel regression is shown to be exacerbated in case of cross section dependence. The bias is substantial and is shown to have serious effects in applications like HAC estimation and dynamic halflife response estimation. To address the bias problem, this paper develops a panel approach to median unbiased estimation that takes into account cross section dependence. The new estimators given here considerably reduce the effects of bias and gain precision from estimating cross section error correlation. The paper also develops an asymptotic theory for tests of coefficient homogeneity under cross section dependence, and proposes a modiÞed Hausman test to test for the presence of homogeneous unit roots. An orthogonalization procedure is developed to remove cross section dependence and permit the use of conventional and meta unit root tests with panel data. Some simulations investigating the Þnite sample performance of the estimation and test procedures are reported.
The bootstrap
 In Handbook of Econometrics
, 2001
"... The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data. It amounts to treating the data as if they were the population for the purpose of evaluating the distribution of interest. Under mild regularity conditions, the bootstrap yields an a ..."
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Cited by 78 (1 self)
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The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data. It amounts to treating the data as if they were the population for the purpose of evaluating the distribution of interest. Under mild regularity conditions, the bootstrap yields an approximation to the distribution of an estimator or test statistic that is at least as accurate as the
Herding among investment newsletters: Theory and evidence
 Journal of Finance
, 1999
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at ..."
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Cited by 72 (0 self)
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Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
Learning and Forgetting: The Dynamics of Aircraft Production
 American Economic Review
, 2000
"... this paper studies commercial aircraft production, with an emphasis on the dynamics of production technology. Because commercial production is subject to many uncertainties not present in military production, the data presented here allows consideration of a richer set of hypotheses than was previou ..."
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Cited by 71 (0 self)
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this paper studies commercial aircraft production, with an emphasis on the dynamics of production technology. Because commercial production is subject to many uncertainties not present in military production, the data presented here allows consideration of a richer set of hypotheses than was previously possible. In addition to learning, support is found for organizational forgetting, the hypothesis that the rm's production experience depreciates over time, and incomplete spillovers of production expertise from one generation of an aircraft to the next.
Measuring Market Inefficiencies in California's Restructured Wholesale Electricity Market
, 2002
"... We present a method for decomposing wholesale electricity payments into production costs, inframarginal competitive rents, and payments resulting from the exercise of market power. The method also parses actual variable costs into the minimum variable costs necessary to meet demand and increased pro ..."
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Cited by 71 (10 self)
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We present a method for decomposing wholesale electricity payments into production costs, inframarginal competitive rents, and payments resulting from the exercise of market power. The method also parses actual variable costs into the minimum variable costs necessary to meet demand and increased production costs caused by market power and other market ineciencies. Using data from June 1998 to October 2000 in California, we nd signicant departures from competitive pricing, particularly during the highdemand summer months. Electricity expenditures in the state's restructured wholesale market rose from $2.04 billion in summer 1999 to $8.98 billion in summer 2000. We nd that 21% of this increase was due to increased production costs, 20% was due to increased competitive rents, and the remaining 59% was attributable to increased market power.
Using OutofSample Mean Squared Prediction Errors to Test the Martingale Difference Hypothesis,” 2004. Working paper, Federal Reserve Bank of Kansas City
"... We consider using outofsample mean squared prediction errors (MSPEs) to evaluate the null that a given series follows a zero mean martingale difference against the alternative that it is linearly predictable. Under the null of no predictability, the population MSPE of the null “no change ” model e ..."
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Cited by 70 (14 self)
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We consider using outofsample mean squared prediction errors (MSPEs) to evaluate the null that a given series follows a zero mean martingale difference against the alternative that it is linearly predictable. Under the null of no predictability, the population MSPE of the null “no change ” model equals that of the linear alternative. We show analytically and via simulations that despite this equality, the alternative model’s sample MSPE is expected to be greater than the null’s. For rolling regression estimators of the alternative model’s parameters, we propose and evaluate an asymptotically normal test that properly accounts for the upward shift of the sample MSPE of the alternative model. Our simulations indicate that our proposed procedure works well.
Confidence intervals for diffusion index forecasts and inference for factoraugmented regressions
, 2003
"... We consider the situation when there is a large number of series, N,eachwithTob servations, and each series has some predictive ability for some variable of interest. A methodology of growing interest is first to estimate common factors from the panel of data by the method of principal components an ..."
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Cited by 59 (10 self)
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We consider the situation when there is a large number of series, N,eachwithTob servations, and each series has some predictive ability for some variable of interest. A methodology of growing interest is first to estimate common factors from the panel of data by the method of principal components and then to augment an otherwise standard regression with the estimated factors. In this paper, we show that the least squares estimates obtained from these factoraugmented regressions are √ T consistent and asymptotically normal if √ T/N → 0. The conditional mean predicted by the estimated factors is min [ √ T � √ N] consistent and asymptotically normal. Except when T/N goes to zero, inference should take into account the effect of “estimated regressors ” on the estimated conditional mean. We present analytical formulas for prediction intervals that are valid regardless of the magnitude of N/T and that can also be used when the factors are nonstationary.
Diversification, Integration, and Emerging Market ClosedEnd Funds
 Journal of Finance
, 1996
"... We are grateful to Lewis Aaron at S.G. Warburg for generously providing data and many helpful ..."
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Cited by 56 (4 self)
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We are grateful to Lewis Aaron at S.G. Warburg for generously providing data and many helpful
Does the TimeConsistency Problem Explain the Behavior of Inflation in the United States?
 JOURNAL OF MONETARY ECONOMICS
, 1999
"... This paper derives the restrictions imposed by Barro and Gordon's theory of timeconsistent monetary policy on a bivariate timeseries model for inflation and unemployment and tests those restrictions using quarterly US data from 1960 through 1997. The results show that the data are consistent ..."
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Cited by 56 (1 self)
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This paper derives the restrictions imposed by Barro and Gordon's theory of timeconsistent monetary policy on a bivariate timeseries model for inflation and unemployment and tests those restrictions using quarterly US data from 1960 through 1997. The results show that the data are consistent with the theory's implications for the longrun behavior of the two variables, indicating that the theory can explain inflation's initial rise and subsequent fall over the past four decades. The results also suggest that the theory must be extended to account more fully for the shortrun dynamics that appear in the data.