Unemployment Expectations in an Agent-Based Model with Education

Abstract

Why are unemployment expectations of the man in the street markedly dierent from professional forecasts? We present an agent-based model to explain this deep disconnection using boundedly rational agents with dierent levels of education. A good t of empirical data is obtained under the assumptions that there is staggered update of information, agents update episodically their estimate and there is a fraction of households who always and stubbornly forecast that the unemployment is going to raise.The model also sheds light on the role of education and suggests that more educated agents update their information more often and less obstinately xate on the worst possible forecast.

The Equity Premium Puzzle: An Application of an Agent-Based Evolutionary Model

“…Figure 1 shows how the fractions of informed (1000), prudent (0011) and uninformed (0010) agents evolve in 10000 periods in one standard simulation run. 5 It can be seen that about 2000 periods suffice to reach a homeostatic equilibrium where the share of prudent traders hovers around 90%, informed agents are 10% and we observe the extinction of the uninformed (as well as any b other then with 1000 and 0011.…”

“…The code is available on the website of the authors 5. All simulations are initialized setting the bits in b randomly in {0, 1}.…”

Using Agent-Based Modelling for Eer Experimental Design: Preliminary Validation Based on Student Cheating Behaviours

“…4 show that the hard assignment and cheating culture fall within this range. These results also highlight the importance of assessment design, where students will be more likely to engage in cheating behaviours if assignments are not designed at the appropriate level of difficulty [10].…”

“…As Gu and Blackmore [13] note in their systematic review of agent-based models, since 2009, this interest in ABM has expanded to higher education. Specific areas of interest for higher education include (1) studies of universities as independent organizational systems (e.g., [18] and [26]), (2) university collaboration (e.g., [1] and [31]), (3) application and enrolment (e.g., [14] and [21]), (4) student performance (e.g., [5], [10], and [24]), and (5) teaching and learning (e.g., [17] and [19]). It should be noted that Gu and Blackmore's "teaching and learning" category relates to the actual teaching of ABM techniques rather than to the modelling of teaching and learning strategies.…”

Using Agent-Based Modelling for Preliminary Eer Experimental Design

“…As Gu and Blackmore [10] note in their systematic review of agent-based models, since 2009, this interest in ABM has expanded to higher education. Specific areas of interest for higher education include (1) studies of universities as independent organizational systems (e.g., [14] and [19]), (2) university collaboration (e.g., [1] and [22]), (3) application and enrolment (e.g., [11] and [16]), (4) student performance (e.g., [4], [9], and [17]), and (5) teaching and learning (e.g., [13] and [15]). It should be noted that Gu and Blackmore's "teaching and learning" category relates to the actual teaching of ABM techniques rather than to the modelling of teaching and learning strategies.…”