The first chapter examines the performance of various forecasting models on US electricity prices. This study is, in essence, a “meta-analysis,” employing nearly 20 different forecasting models. Our model selection acts as a retrospective on the many different generation forecasting. We largely generalize them into two groups: Old School (OS) and New School (NS) models. This distinction was initially noted in Enders et al. (2009). They suggest that the Old School forecasting methods utilize standard linear models or various smoothing functions. The New School models involve threshold models, structural change models, regime-switching, and other modern approaches. We add some new forecasting models to them. For performance assessment, we focus on out-of-sample forecasting errors. The second chapter examines how international comovements of energy consumption create global and regional effects on nations’ energy consumption. The existing literature links the energy consumption behaviors of countries to country-specific components and examines the comovement of certain variables with the energy consumption of some specific countries. However, this study presents detailed empirical evidence of exogenous factors on energy consumption. We employ the time-varying Bayesian Dynamic Factor model with loadings and stochastic volatility, which permits us to estimate the global, regional, and country-specific factors affecting the energy consumption of the 52 countries divided by six different regions. We find that the magnitude of the effects is time-dependent, the global factor is generally a more dominant driving source of energy consumption than regional and idiosyncratic components, and there is a significant regional factor effect in the European region. Moreover, we find clear evidence of international shocks linked to real-world events such as the 1973 OPEC crisis, the 1979 Iranian revolution, the 1997 Asian Financial crisis, the 2008 Great Recession, and renewable energy agreements between Nordic countries. We emulated the approach of the literature by comparing variables labeled as driving factors to our factor model and found that GDP and urbanization variables have pronounced effects on the international comovement of energy consumption