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- 저자 : Donggyu Sul (검색결과 2 건)
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Uniform Asymptotic Normality in Stationary and Unit Root Autoregression
Chirok Han,Peter C. B. Phillips,Donggyu Sul 한국계량경제학회 2009 한국계량경제학회 학술대회 논문집 Vol.2009 No.2
While differencing transformations can eliminate nonstationarity, they typically reduce signal strength and correspondingly reduce rates of convergence in unit root autoregressions. The present paper shows that aggregating moment conditions that are formulated in differences provides an orderly mechanism for preserving information and signal strength in autoregressions with some very desirable properties. In rst order autoregression, a partially aggregated estimator based on moment conditions in differences is shown to have a limiting normal distribution which holds uniformly in the autoregressive coef cient including stationary and unit root cases. The rate of convergence is p n when j j < 1 and the limit distribution is the same as the Gaussian maximum likelihood estimator (MLE), but when = 1 the rate of convergence to the normal distribution is within a slowly varying factor of n: A fully aggregated estimator is shown to have the same limit behavior in the stationary case and to have nonstandard limit distributions in unit root and near integrated cases which reduce both the bias and the variance of the MLE in the vicinity of unity. This result shows that it is possible to improve on the asymptotic behavior of the MLE without using an arti cial shrinkage technique or otherwise accelerating convergence at unity at the cost of performance in the neighborhood of unity.
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Standardization and Estimation of Factor Numbers for Panel Data
Ryan Greenaway-McGrevy,Chirok Han,Donggyu Sul 한국계량경제학회 2012 JOURNAL OF ECONOMIC THEORY AND ECONOMETRICS Vol.23 No.2
Practitioners often standardize panel data before estimating a factor model. In this paper we show an example that the standardization leads to inconsistent estimation of the factor number. When the common component exhibits strong heteroskedasticity, the conventional eigenvalue-based decompositions are consistent but standardization does not necessarily result in consistent estimation. To overcome this issue, we recommend using a “minimum-rule” whereby the minimum factor-number estimated from both the conventional and standardized panel is used. Monte Carlo studies and an empirical application are provided.
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