We have Yoonseok Lee from Yale as a job candidate Wendesday 1 February. The seminar will *not* be in the usual room, but instead in Savery 110 C. The time remains the same: 2.00 - 3.30. The title of his paper is "Nonparametric Estimation of Dynamic Panel Models". Abstract: This paper develops nonparametric estimation of dynamic panel models using series approximations. We extend the standard linear dynamic panel model to a nonparametric form that maintains additive fixed effects, where the fixed effects are eliminated by the within transformation. This approach generalizes earlier work on cross sectional series estimation by Newey (1997). Nonlinear homogenous Markov process is properly conditioned to be a stationary β-mixing. Convergence rates and the asymptotic distribution of the series estimator are derived when both the cross section sample size and the length of the time series are large and of comparable sizes. Just as for pooled estimation in linear dynamic panels, an asymptotic bias is present, which reduces the mean square convergence rate compared with the cross section case. To tackle this problem, bias correction is developed using a heteroskedasticity and autocorrelation consistent (HAC) type estimator. Some extensions of this framework are also considered under exogenous variables and partial linear models. The limit theory and bias correction formulae follow by extending the main results. Finally, an empirical study on nonlinearities in cross-country growth regressions is presented to illustrate the use of the nonparametric dynamic panel models with fixed effects. After bias correction, the convergence hypothesis is true only for countries in the upper income range and for OECD countries.