Hungary launched its first Technology Foresight Programme (TEP) in 1997. This was a holistic foresight programme, based on panel activities and a large-scale Delphi survey, with a strong emphasis on socio-economic needs. The paper discusses why a foresight exercise is relevant to a transition...

Marketing expenditures in the form of pricing, product development, promotion and channel development are made to maximize return on investment. A challenge in evaluating the effectiveness of these expenditures is that decisions such as whether to lower prices or run promotions are made based on...

There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches...

The aim of this article is to prove the key role of the structure of the research sample used for accuracy determining on the accuracy of bankruptcy models. The creators of these models report the accuracy usually in the range of 60 to 90%. The authors of this article claim that these values are...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

The adaptive learning approach has been fruitfully employed to model the formation of aggregate expectations at the macroeconomic level, as an alternative to rational expectations. This paper uses adaptive learning to understand, instead, the formation of expectations at the micro-level, by...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

Recent empirical studies have shown that the chaotic behaviour and excess volatility of financial series are the result of interactions between heterogeneous investors. In our article, we propose verifying this hypothesis. Thus, we use the Chen, Lux, and Marchesi (2000) model to show that the...

We build a game-theoretic model to examine how better demand forecasting due to algorithms, machine learning and artificial intelligence affects the sustainability of collusion in an industry. We find that while better forecasting allows colluding firms to better tailor prices to demand...

This study examines the forecasting power of confidence indicators for the Russian economy. ARX models are fitted to the six confidence or composite indicators, which were then compared to a simple benchmark AR-model. The study used the output of the five main branches as the reference series....