We propose two robust bootstrap-based simultaneous inference methods for time series models featuring time-varying coefficients and conduct an extensive simulation study to assess their performance. Our exploration covers a wide range of scenarios, encompassing serially correlated,...

Preface -- Chapter 1 Introduction -- Chapter 2 Big Data Analysis of Energy Economics in Oil Market -- Chapter 2 Big Data Analysis of Energy Economics in Oil Market -- Chapter 3 Big Data Analysis of Energy Economics in Coal Market -- Chapter 4 Big Data Analysis of Energy Economics in Wind Power...

In the past decade, the popularity of realized measures and various linear models for volatility forecasting has attracted attention in the literature on the price variability of energy markets. However, results that would guide practitioners to a specific estimator and model when aiming for the...

We test for the presence of time-varying parameters (TVP) in the long-run dynamics of energy prices for oil, natural gas and coal, within a standard class of mean-reverting models. We also propose residual-based diagnostic tests and examine out-of-sample forecasts. In-sample LR tests support the...

We use a Bayesian Threshold Vector Autoregression model identified through sign and narrative restrictions to uncover non-linearities in the propagation of energy supply shocks. We find that the transmission of energy supply shocks on consumer prices is stronger in high-inflation regimes,...