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 time-varying coefficients in panel data regressions, which is based on penalized regression techniques. To illustrate the usefulness of...

We develop a non-dynamic panel smooth transition regression model with fixed individual effects. The model is useful for describing heterogenous panels, with regression coefficients that vary across individuals and over time. Heterogeneity is allowed for by assuming that these coefficients are...

Most research questions in agricultural and applied economics are of a causal nature, i.e., how one or more variables (e.g., policies, prices, the weather) affect one or more other variables (e.g., the welfare of individuals or the society, the demanded or produced quantity, pollution). Only a...

In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including...

Identification of equations explaining a continuous variable, e.g., the length of sickness absence spells, by age, cohort and time (ACT), subject to their definitional identity is reconsidered. Various extensions of a linear equation to polynomials are explored. If no interactions between the...

In this paper we deal with the measurement of technical efficiency (or X-efficiency) of institutions whose operations might be significantly affected by macroeconomic, environmental and non-controllable factors. For this purpose we introduce a four-stage DEA methodology based on the approach...

This paper proposes a network regression model to account for peer contextual effects on the outcome variable. In contrast to the literature, we estimate the interaction matrix that defines the network structure. Spill-over effects are modelled as a functional coefficient that is approximated...

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...