For over a decade, artificial life proponents have suggested that artificial life techniques will revolutionize our understanding of the way the world works. Seminal ideas, such as the notion that global regularities can arise from many local interactions, have the potential to provide theoretical underpinnings for many fields, particularly those in the social sciences.
An economic model is a set of decision-making mechanisms, organizational arrangements, and rules for allocating society's scarce resources. An economic model can be as simple as one agent on an island (a Robinson Crusoe economy), or as complex as the everyday decisions of the 5 billion people in the world, the interactions between all firms in all countries and the actions of all governments. The traditional approach to economic modeling is geared towards obtaining an equilibrium solution. This involves solving the maximization problems of all agents to yield market-clearing prices (markets clear when demand is equal to supply) for all goods and also the quantities that are exchanged at these prices. One assumption imposed for analytic tractability that rarely captures the economic phenomenon we observe is homogeneity of agents. Relaxing this assumption is not possible in a lot of economic models and, if it can be relaxed, the level of heterogeneity that can be modeled is still very restricted. Moreover, equilibrium solutions are not always very informative for policy purposes. For policy makers, the path to equilibrium is just as important as the equilibrium itself.
In this paper, we present an agent-based general equilibrium model of a simple transition economy (an economy, such as those of Poland and Hungary, that is moving from a centrally planned system to a competitive market system) that draws on methods developed in the field of artificial life. The agents in our artificial life model use only local information to arrive at the equilibrium price. The dynamics of reaching the equilibrium price are of particular interest when studying transition economies. Because of the generality of artificial life methods, our model is not restricted to homogeneous agents like most standard economic models are. As a result of these enhancements, macroeconomic outputs of our simulated economy, such as production, pricing, and profits, qualitatively resemble those of real-world transition economies.
Modeling the transition from centrally planned to market economies of former communist countries poses a particular challenge. Economies in transition are economies that are making marked changes in their market structure. Since the demise of the Soviet Union, this has become a relevant and hot research topic. Many countries have begun to move away from a centrally planned economy to a more market-based economy. The transition from communism can be analyzed in terms of four basic tasks of economic reform [Sachs1996] :
The transition economies of Eastern Europe and the former Soviet Union have demonstrated that it is possible to introduce the institutions of a market economy within five years. According to Jeffrey Sachs [Sachs1996]:
...liberalization of the economy surely proved to be the quickest and most effective area of change. In the fastest-reform economies, currency convertibility was quickly established; prices were freed, and shortages eliminated; and international barriers were cut, resulting in significant growth of trade.
...Without question the most difficult aspect of institutional reform has been privatization.
Economic theories do not provide definite answers to the questions that are most central: What is the optimal speed of reforms and what is the best sequencing of reforms? The ``shock therapy'' proponents favor simultaneous reforms throughout the economy [Lipton & Sachs1990,Boycko1992,Frydman & Rapaczynski1994,Sachs1993], whereas ``gradualists'' emphasize the sequencing of reforms [Portes1991,McKinnon1991,Dewatriport & Roland1992,Murrell1992].
Empirical evidence shows important similarities and differences in the experiences of transitioning economies which contribute to the lack of consensus. Gross Domestic Product (GDP) in a lot of transition economies has followed a U-shaped pattern, an initial decline followed by growth. However, the severity of the fall and its duration has differed [Blanchard1996]. The private sector's share of the GDP has increased, but the increase has been anywhere from double to tenfold [Selowsky & Martin1997]. Countries that have adopted similar reform packages have differed drastically in their responses [Frye & Schleifer1997].
Examining phenomena such as the U-shaped pattern in output requires modeling the dynamics of the economy. We adopt an artificial life methodology that lends itself with greater ease to modeling these dynamics.
Artificial life techniques hold out the promise of overcoming some of the problems associated with the traditional approach. Artificial life researchers have shown that local rules of behavior can lead to identifiable global regularities. The emphasis on exploiting local information, emergent behavior, and self-organization make artificial life techniques an ideal tool for studying transition economies.
In this paper, we take a first step towards addressing some of the vexing problems posed by transition economies. We present a general equilibrium model of a simple transition economy. It is a general equilibrium model, not because the solution assumes equilibrium, but in the traditional sense that all prices and quantities are determined within the model. We focus on the behavior of firms in a single market, but we also have markets for labor and capital. We analyze the transition from a controlled economy where production is undertaken by one state-owned enterprise (SOE) to a market economy. The agents in this economy do not have access to global information and act on simple rules. We show that equilibrium can be reached. We are also able to replicate qualitatively the U-shaped pattern of output observed in transition economies.