Some observers have conjectured that the decline in the price of oil after June 2014 resulted from positive oil supply shocks in the second half of 2014. Others have suggested that a major shock to oil price expectations occurred when in late November 2014 OPEC announced that it would maintain...

The classical approach to long term load forecasting is often limited to the use of load and weather information occurring with monthly or annual frequency. This low resolution, infrequent data can sometimes lead to inaccurate forecasts. Load forecasters often have a hard time explaining the...

Energy forecasting is one of those areas of great importance to electric grid that gets little attention - even from power industry insiders. But you need to know how to make the best of your forecasting process. Here are 13 tips to get you started.

Electric load forecasting is a fundamental business process and well-established analytical problem in the utility industry. Due to various characteristics of electricity demand series and the business needs, electric load forecasting is a classical textbook example and popular application field...

This paper compares the forecasting performance of three structural econometric models, namely the non-parametric, ARIMAX and the Kalman filter models, in predicting stock returns in an emerging market economy using South Africa as case study. The proposed models have different functional forms....

The question of energy supply continuity is essential from the perspective of the functioning of society and the economy today. The study describes modern methods of forecasting emergency situations using Artificial Intelligence (AI) tools, especially neural networks. It examines the structure...

A tax shifting from labour income to housing taxation is generally advocated on efficiency grounds. However, most of the empirical literature focuses on the distributional implications of property tax reforms without paying much attention to potential consequences on the labour market. The aim...

Borrowing from our experience in agent-based computational economic research from `bottom-up', this paper considers economic system as multi-level dynamical system that micro-level agents' interaction leads to structural transition in meso-level, which results in macro-level market dynamics with...

This paper evaluates the ability of autoregressive models, professional forecasters, and models that leverage unemployment flows to forecast the unemployment rate. We pay particular attention to flows-based approaches—the more reduced form approach of Barnichon and Nekarda (2012) and the more...

This paper analyzes the mechanics of VAR forecast pooling and quantifies the forecast performance under varying conditions. To fill the gap between empirical and purely theoretical research we run a Monte Carlo study and simulate the data from different New Keynesian DSGE models. We find that...