Regime-switching models and panel data: from nonlinearity to heterogeneity.

Summary Over the last twenty years, panel data econometrics has undergone a profound renewal linked to the emergence of major time series issues, such as non-stationarity, cointegration and causality. However, it is clear that there is still very little work on taking into account non-linearity and more specifically the change of panel regimes. In this context, the general problem of this thesis consists in highlighting the interest of modeling regime shifts on panel data. Panel regime-switching models are a direct extension of the threshold models proposed for time series. However, the introduction of the individual dimension fundamentally enriches their economic interpretation. In this thesis, we study more specifically three specifications: threshold models with abrupt transition (PTR), threshold models with smooth transition (PSTR), autoregressive models with smooth transition (PSTAR). We propose three applications of these models successively on the threshold effects in Okun's law, the Feldstein Horioka (1980) paradox and the non-linear relationship between power consumption and temperature. These applications highlight various advantages of using threshold modeling in panel data. In particular, these models provide a simple parametric solution to account for both the nonlinearity and the individual heterogeneity of the parameters. The slope coefficients are also allowed to change over time. Furthermore, we show that the increase in the information set allows us to identify threshold effects that would not have been possible to identify in time series.