The model simulates the evolution of the labor market in the context of the PNRR (National Recovery and Resilience Plan). It tracks how two types of agents (angajati and neangajati) develop their professional competencies to match the requirements of seven distinct job categories.
The simulation focuses on the gap between current skill levels and market demands, specifically modeling how a sudden “Market Shift” (the introduction of a 13th competency) impacts the workforce’s readiness.

This model is a market game for evaluating the effectiveness of the UK government’s 2008-2010 policy on promoting smart metering in the UK retail electricity market. We break down the policy into four

This model simulates the emergence of a dual market structure from firm-level interaction. Firms are profit-seeking, and demand is represented by a unimodal distribution of consumers along a set of taste positions.

This model test the efficiency of the market economy in comparison with a hunter/gatherer economy. It also compares the model outcomes between a market economy when using eternal agents with one using mortal agents.

Building upon the distance-based Hotelling’s differentiation idea, we describe the behavioral experience of several prototypes of consumers, who walk a hypothetical cognitive path in an attempt to maximize their satisfaction.

A simple model is constructed using C# in order to to capture key features of market dynamics, while also producing reasonable results for the individual insurers. A replication of Taylor’s model is also constructed in order to compare results with the new premium setting mechanism. To enable the comparison of the two premium mechanisms, the rest of the model set-up is maintained as in the Taylor model. As in the Taylor example, homogeneous customers represented as a total market exposure which is allocated amongst the insurers.

In each time period, the model undergoes the following steps:
1. Insurers set competitive premiums per exposure unit
2. Losses are generated based on each insurer’s share of the market exposure
3. Accounting results are calculated for each insurer
…

This model simulates the motion picture industry and tests how social influences affect market shares. It is empirically validated at the micro level by a cross-cultural survey.

This model explores the effects of agent interaction, information feedback, and adaptive learning in repeated auctions for farmland. It gathers information for three types of sealed-bid auctions, and one English auction and compares the auctions on the basis of several measures, including efficiency, price information revelation, and ability to handle repeated bidding and agent learning.

A very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)