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It is possible to see effective use of Artificial Intelligence-based systems in many fields because it easily outperforms traditional solutions or provides solutions for the problems not previously solved. Prediction applications are a widely used mechanism in research because they allow for forecasting of future states. Logical inference mechanisms in the field of Artificial Intelligence allow for faster and more accurate and powerful computation. Machine Learning, which is a sub-field of Artificial Intelligence, has been used as a tool for creating effective solutions for prediction problems.

In this chapter the authors will focus on employing Machine Learning techniques for predicting data for future states of economic using techniques which include Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference System, Dynamic Boltzmann Machine, Support Vector Machine, Hidden Markov Model, Bayesian Learning on Gaussian process model, Autoregressive Integrated Moving Average, Autoregressive Model (Poggi, Muselli, Notton, Cristofari, & Louche, 2003), and K-Nearest Neighbor Algorithm. Findings revealed positive results in terms of predicting economic data.

Previous studies have shown that the effectiveness of monetary policy depends, to a large extent, on the market expectations of its future actions. This paper proposes an econometric framework to address the effect of the current state of the economy on monetary policy expectations. Specifically, we study the effect of contractionary (or expansionary) demand (or supply) shocks hitting the euro area countries on the expectations of the ECB's monetary policy in two stages. In the first stage, we construct indexes of real activity and inflation dynamics for each country, based on soft and hard indicators. In the second stage, we use those indexes to provide assessments on the type of aggregate shock hitting each country and assess its effect on monetary policy expectations at different horizons. Our results indicate that expectations are responsive to aggregate contractionary shocks, but not to expansionary shocks. Particularly, contractionary demand shocks have a negative effect on short-term monetary policy expectations, while contractionary supply shocks have negative effect on medium- and long-term expectations. Moreover, shocks to different economies do not have significantly different effects on expectations, although some differences across countries arise.

Organizational researchers live in two worlds. The first demands and rewards speculations about how to improve performance. The second demands and rewards adherence to rigorous standards of scholarship (March & Sutton, 1997, p. 698).Those of us who study organizations and are professors of management work on the front lines, so to speak, where the beliefs we have about how to improve managerial performance get passed directly on to practitioners. The question is, What right do we have to put our beliefs in a privileged position? Beliefs, by definition, are supposed to be true. According to Webster’s (1996) a belief is a conviction about the truth of some statement and/or reality of some phenomenon, especially when based on examination of evidence. Are all of our lectures based on consensually agreed upon evidentiary standards? What are these standards and who should maintain them?