We use regularized machine learning models to forecast Brazilian power electricity
consumption for short and medium terms. We compare our models to benchmark …

We show that high-dimensional econometric models, such as shrinkage and complete
subset regression, perform very well in the real-time forecasting of inflation in data-rich …

The purpose of this paper is to explore machine learning techniques to forecast the oil price.
In the era of big data, we investigate whether new automated tools can improve over …

In this paper, we explore machine learning (ML) methods to improve inflation forecasting in
Brazil. An extensive out-of-sample forecasting exercise is designed with multiple horizons, a …

Purpose The main purpose of this study is to forecast inflation rates in the case of the Turkish
economy with shrinkage methods of machine learning algorithms. Design/methodology …

Este artigo analisa o desempenho de modelos fatoriais de alta dimensão para prever quatro
variáveis macroeconômicas brasileiras: duas variáveis reais, taxa de desemprego eo índice …

This paper evaluates the inflation forecasting models of a small open economy. We compare
forecasts of Brazilian inflation (consumer price index—IPCA) based on the generalized …

Economic Journal of Emerging Markets Page 1 Economic Journal of Emerging Markets, 14(1)
2022, 55-71 Econ.J.Emerg.Mark. Economic Journal of Emerging Markets Available at https://journal.uii.ac.id/jep …

Modern problems in Economics have tremendously benefited from the ever increasing
amount of available information. Hence, most of the recent econometric approaches have …

We investigate the predictive ability of machine learning methods to produce weekly inflation
nowcasts using high-frequency macro-financial indicators and a survey of professional …