Bias Reduction by Recursive Mean Adjustment in Dynamic Panel Data Models
2004/07/20
研討會日期 : 2004-07-20
時間 : 15:00
主講人 : Prof. Chi-Young Choi
地點 : B棟110室
演講者簡介 : Prof. Chi-Young Choi為Ph.D. in Economics，The Ohio State University (2000)。
現為Assistant Professor, Department of Economics, University of New Hampshire。
其主要研究領域為International Macroeconomics and Finance、Time Series Econometrics、Regional Growth and Policy Issues、 Money and Macro Economics及Financial Economics。
演講摘要 : Accurate estimation of the dominant root of a stationary but persistent time series are required to determine the speed at which economic time series, such as real exchange rates or interest rates, adjust towards their mean values. In practice, accuracy is hampered by downward small-sample bias. Recursive mean adjustment has been found to be a useful bias reduction strategy in the regression context. In this paper, we study recursive mean adjustment in dynamic panel data models. When there exists cross-sectional heterogeneity in the dominant root, the recursive mean adjusted SUR estimator is appropriate. When homogeneity restrictions can be imposed, a pooled recursive mean adjusted GLS estimator with fixed effects is the desired estimator. Application of these techniques to a small panel of five eurocurrency rates finds that these interest rates are unit root non-stationary as the bias-corrected autoregressive coefficient exceeds 1.
