Semiparametric efficient estimation of AR(1) panel data models.

By Byeong U. Park, Robin C. Sickles, Léopold Simar. 2003

74 citations recorded by the source corpus.

Subfields: Demography, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/4d63edce9b9cee0dfb7f1ded6e204fa397e8202e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Demography

1. Alois Kneip
2. Wonho Song
3. Robin C. Sickles

In Economics and Econometrics

1. Mika Kortelainen
2. Timo Kuosmanen
3. Alois Kneip
4. Wonho Song
5. Robin C. Sickles
6. Peng Zhou
7. Léopold Simar
8. Timo Sipiläinen

Citations in the corpus

• Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints (2012, background): “Other semi/nonparametric panel data approaches include Park et al. (1998, 2003, 2006) and Henderson and Simar (2005), among others.”
• Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings (2005, methodology): “Here we illustrate the various estimators and their temporal patterns using a subset of 50 unit banks from the U. S. banking data analyzed elsewhere by Adams et al. (1999), Park et al. (2003a), and Fernández et al. (2004).”
• A NEW PANEL DATA TREATMENT FOR HETEROGENEITY IN TIME TRENDS (2012, methodology): “In each Monte Carlo sample, the regressors are generated according to a bivariate vector autoregression (VAR) model as in Park et al. (2003, 2007): Xit = RXi,t−1 +ηi t , where ηi t ∼N(0, I2), R = ( 0.4 0.05 0.05 0.4 ) .”