Papers on Economic Agent-Based simulation
Agent-Based Computational Economics: A Constructive Approach to Economic Theory
- Uses Walrasian Auctioneer pricing mechanism: simultaneous auction where each agent calculates its demand for the good at every possible price and submits this to auctioneer.
- Difference between ACE and other models: Events are driven by agent interactions after initial conditions; goes TOWARDS equilibrium rather than starting with one.
- Disadvantages: validating ACE model outcomes against empirical data. An empirically observed outcome might be a low-probability event lying in a relatively small peak of the outcome of distribution for this true data-generating process, or in a thin tail of this distribution.
- States that ACE models are still just a complement, not a substitute, for analytical and statistical modeling approaches.
The ACE Trading World: Technical Details
- 0 to T periods, finite number of profit seeking hash and bean firms, finite number of consumers
- Each firm has positive amount of money and production capacity
- Each total cost function has amortized fixed costs proportional to capacity.
- Known to the companies: # of hash firms, bean firms, and # of consumers, and that hash and beans are both perishable.
- Unknown: income levels and utility functions of consumers or cost functions/capacities of other firms
- Collusion is prohibited
- Each consumer has a lifetime money endowment profile and utility function measuring preferences and subsistence
- Income is determined partly by money endowment, savings from previous periods and dividends
How Things Work
Firms use supply offer and learning method. Consumers can acquire complete info about the supply offers when they are posted at the beginning of the period. Price discovery process: Person who can’t meet subsistence needs at lowest prices will exit the process. Remaining people determine demands conditional on remaining income, unmet needs, and lowest prices. They submit demands to firms that posted low prices, then the firms try to satisfy demands with rationing method. Consumers rationed with less than needs adjust their demand downward for remaining goods to preserve income. Trades happen, then firms with surplus/consumers with unspent income continue into the next round. End of rounds: firms stocked out or when there is no more income. Consumers who exit or finish with needs still-> die at end of period and their unspent money holdings are lost to the economy but stock shares are redistributed.
SUMMARY OF TECHNICAL PORTION: ACE trading world is a deterministhic Markov process where X(T+1) is determined as a function of X(T), where profiles and metrics are initialized. It is supposedly being implemented, as detailed in COOK AND TESFATSION (2006) as a computational lab with graphical interface.
There is an appendix detailing the mathematical models and classes.
Other Relevant Materials
Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents
Blake LeBaron and Leigh Tesfatsion
This article just gives an overview about ACE: what ACE is about and used for. It is not as useful in giving any technical specifics. It states problems of ACE, such as degrees of freedom, the fact that modeling tools may be too rich to fit to data, and that the properties of ACE are not understood well enough to model human behavior. It also lists some things that ACE can model (National economy, financial sector, etc.). Policy makers and how they can use ACE is stated on page 9.
The article's three criteria for ACE are: 1. Model must include appropriate empirically-based taxonomy of agents 2. Scale of model must be suitable for particular purpose 3. Model specifications must be subject to empirical validation
You can access this paper here.