We consider the problem of forecasting multiple time series across multiple cross-sections based solely on the past observations of the series. We propose to use panel vector autoregressive model to capture the inter-dependencies on the past values of the multiple series. We restrict the panel vector autoregressive model to exclude the cross-sectional relationships and propose a method to learn...

Preamble These lecture notes were written for a 2nd-year Ph.D. course in econometrics of panel data and limited-dependent-variable-models. The primary goal of the course is to introduce tools necessary to understand and implement empirical studies in economics focusing on other than time-series issues. The main emphasis of the course is twofold: (i) to extend regression models in the context of...

We propose a framework to estimate earnings distributions and worker and firm unobserved heterogeneity on matched panel data. We introduce two models: a static model that allows for interaction effects between workers and firms, and a dynamic model that allows in addition for Markovian dynamics in earnings and mobility decisions. We establish identification in short panels. We develop a tractab...

When analyzing panel data using regression models, it is often reasonable to allow for time-varying covariate effects. We propose a novel approach to modelling timevarying coefficients in panel data regressions, which is based on penalized regression techniques. To illustrate the usefulness of this approach, we revisit the well-known empirical puzzle of the ‘death of distance’ in international ...

The notion of a conditional linear predictor is used as a distributionfree method for eliminating the individual-specific effects in a class of nonlinear, unobserved components panel data models. The methodology is applied to a general count model, which allows for individual dispersion in addition to an individual mean effect. As a corollary of the general results, the multinomial quasi-condit...

This paper investigates stationary β-mixing dynamics in nonlinear panel models and 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. Convergence rates and the asymptotic distribution of the series estimator are derived, in which an asymptotic bias...

We describe and analyse the portfolio structure of Dutch households using micro panel data from the CentER Savings Survey, 1993-1998. The data allows for a distinction between many types of assets. Moreover, we have information on mortgage debt, consumer debt, etc. We analyse the composition of household portfolios and the level of portfolio diversification, and its relation to age, birth cohor...

abstract soil temperature is one of the key parameters affecting most hydrologic and agricultural processes. therefore, its measurement and prediction is very crucial. so far, the statistical regression methods have been used for estimation of soil temperature for specific location encountering with lack or shortage of data. in this work, soil temperature data are estimated at six different dep...