Agents variables. The Rational Expectation Hypothesis (REH), firstly

Agents make their everyday choices based on their expectations.

As suggested in Assenza et al. (2014), we should think of an economy as an expectation feedback mechanism in which expectations influence individual decisions and these choices determine the realization of the main macro or financial variables.The Rational Expectation Hypothesis (REH), firstly introduced by Muth (1961) and then analyzed in detail by Lucas and Prescott (1971), is the mainstream approach applied today. According to this hypothesis, agents make no systematic errors in forecasting, taking into account the entire set of available information. Recent studies, based on both simulation and experimental evidence, show that this approach is often unrealistic, that is agents do not have sufficient capabilities to make rational predictions (see: for example, (Sargent, 1993), Evans and Honkapohja (2001) and Branch (2004)).An alternative hypothesis is that agents form their expectations based on an adaptive rule, namely that the forecast is a function of both past expectations and past realization (Colasante Et.

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al 2017). This is known as the theory of adaptive expectations. It was the prevalent theory before the REH. The 1973 oil crisis in the USA was a test for the theory of adaptive expectations; however it failed to predict the crisis (Mikolajec 2014). In his famous paper “The Lucas critique”, Lucas (1976) announced that previous models could not predict the 1973 oil crisis, because they were based on an incorrect assumption about expectations (namely, that individual agents are passive and react post factum). Lucas (1976) thus proposed the REH basing on the earlier work of Muth (1961) (Mikolajec 2014). Lucas (1976) proposed that when making forecasts of future states agents use their economic knowledge as well as information available at the moment of creating expectations.It should be emphasized, however, that the current theory of rational expectations describes reasonable rather than rational expectations (Mikolajec 2014).

Under conditions of real uncertainty rational construction of expectations is not possible, because each agent has access to different and only partial knowledge (Mikolajec 2014). However, it is worth noting that the current version of the REH includes also the learning process of market players, which may justify its relevance (Mikolajec 2014).One key criticism of the rational expectations hypothesis is that it doesn’t address the cost of acquiring and processing information for the purpose of forecasting and forming expectations (Mucha 2009).

2.2.2 Behavioral theories of expectations formationBehavioral economics attempts to combine insights from psychology with economics to better understand economic behavior (Coyne 2011). Important foundations for the influence of behavioral and psychological factors in economic behavior were laid down in the Keynes (1936) General theory of Employment, Interest and Money. The General Theory, Keynes states that the formation of entrepreneurial long-term expectations on investments under genuine uncertainty is not supported solely by cold calculation. Rather, in his opinion, decision making concerning future courses of actions is affected by “animal spirits” – spontaneous optimism or urge to action – and by ‘not rational’ motives – ‘habit, instinct, preference, desire, will, etc.

‘ and ‘passions’- that supplement and even substitute the probabilistic computation of benefits. Akerlof and Shiller (2009) reinforce this claim that macroeconomics can indeed be based on behavioral foundations, proposing a behaviorally informed “Keynesianism”. This view has not encountered much favor among economists, after Keynes. On the one hand, irrational and psychological motives have been sensed as falling beyond the object of economic science. Dequech (1999) shows how animal spirits influence both expectations and confidence, demonstrating that animal spirits are interrelated with cognition. He offers an overarching definition of the meaning of animal spirits as ‘the optimistic disposition to face uncertainty’ (Dequech 1999). The importance of behavioral sentiments in predicting future out comes was well tested by economic psychologist George Katona. Katona devised a survey after World War II to show how people viewed the country’s prospects and their own, asking them about their plans for purchases and general attitudes towards the economy.

It assumed that expectations are inherently uncertain, and that they reflected the knowledge and attitudes of people, as well as their behavior in preparing for events in advance. It basically asked questions on intentions to buy a car, a house, and household appliances using representative samples of American adults, as well as questions on attitudes towards general economic trends, like “Do you think that a year from now you will be better off financially, or worse off, or just about the same as now?” Despite its simplicity and directness, this survey was more successful than any other instrument used at that time to forecast and explain macroeconomic data, leading to the birth of the Index of Consumer Sentiment and the Indexes of Producer Sentiment and Intentions. Specifically, about 6-9 months following the observation of a downturn in the Index of Consumer Sentiment, a recession set in (Katona, 1979).Recent work in behavioral research illustrates that a critical element of expectation management is how outcomes relate to expectations.

For instance, Diener (1984) and Frank (1989, 1997) conclude from their work that individuals assess their current state of affairs relative to their expectations. The central issue is the “frame of reference,” the benchmark against which an individual compares his or her current situation, which is a critical determinant of ultimate satisfaction or disappointment. This observation is illustrated by Toews (2015), who found that households in Kazakhstan’s oil rich region were dissatisfied with their already high incomes due to the rise in oil prices, even though they had higher incomes compared to other regions. A related literature emphasizes the importance of “anchoring” (see Tversky and Kahneman 1974). Anchoring is the tendency for people to establish one piece of information—the anchor—as a baseline when deciding (Coyne 2011). Given limited brain processing capability, people cannot compare all relevant alternatives.

As such, they pick an anchor to serve as a benchmark for comparison. The anchor, in turn, is based on past experiences and the context within which the chooser acts.


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