Marco Valente

Norms as emergent properties of adaptive learning: The case of economic routines

Interaction among autonomous decision-makers is usually modelled in economics in game-theoretic terms or within the framework of General Equilibrium. Game-theoretic and General Equilibrium models deal almost exclusively with the existence of equilibria and do not analyse the processes which might lead to them. Even when existence proofs can be given, two questions are still open. The first concerns the possibility of multiple equilibria, which game theory has shown to be the case even in very simple models and which makes the outcome of interaction unpredictable. The second relates to the computability and complexity of the decision procedures which agents should adopt and questions the possibility of reaching an equilibrium by means of an algorithmically implementable strategy. Some theorems have recently proved that in many economically relevant problems equilibria are not computable. A different approach to the problem of strategic interaction is a “constructivist” one. Such a perspective, instead of being based upon an axiomatic view of human behaviour grounded on the principle of optimisation, focuses on algorithmically implementable “satisfycing” decision procedures. Once the axiomatic approach has been abandoned, decision procedures cannot be deduced from rationality assumptions, but must be the evolving outcome of a process of learning and adaptation to the particular environment in which the decision must be made. This paper considers one of the most recently proposed adaptive learning models: Genetic Programming and applies it to one the mostly studied and still controversial economic interaction environment, that of oligopolistic markets. Genetic Programming evolves decision procedures, represented by elements in the space of functions, balancing the exploitation of knowledge previously obtained with the search of more productive procedures. The results obtained are consistent with the evidence from the observation of the behaviour of real economic agents.

Interdependencies, nearly-decomposability and adaptation

In this paper we discuss some limitations that selection mechanisms face when the entities subject to selection are complex systems of interdependent elements. We briefly present Kauffman’s NK model which addresses this problem in biological systems. It is argued that, contrary to the myopic search behaviour, underlying biological fitness landscapes, social organisations are not bound in their search dynamics. This amounts to say that the problem of finding optima on a fitness landscape can be decomposed in many different ways. Following work by Page (1996), we present some measures of the complexity of a fitness landscape in terms of the complexity (size) of the algorithm that decomposes the problem most accurately, while still being able to locate the global optima with full certainty. We then extend this measures to allow for nearly-decomposability in a sense close to Simon (1969). Finally we study some evolutionary properties of populations of agents characterised by different decompositions of the same given problem.

The Effect of Consumption and Production Structure on Growth and Distribution: A Micro to Macro Model

The paper offers a theoretical analysis of long-run economic growth as an outcome of structural changes. We model the microeconomic behaviour of firms in the final good and capital sectors, and the evolution of classes of workers/consumers. We carefully craft economic behaviour onto empirical evidence, and solve the model numerically. The results illustrate the microeconomic properties of the simulated growth patterns. In particular, we observe and explain the interactions between technological change, firm organization, income distribution, consumption behaviour and growth. We confirm the relevance and interdependence of these structural changes, and underline their microeconomic sources.

The Value and Costs of Modularity: A Problem‐Solving Perspective

This paper discusses the issue of modularity from a problem-solving perspective. Modularity is in fact a decomposition heuristic, through which a complex problem is decomposed into independent or quasi-independent sub-problems. By means of a model of problem decomposition, this paper studies the trade-offs of modularity: on the one hand finer modules increase the speed of search, but on the other hand they usually determine lock-in into sub-optimal solutions. How to balance effectively this trade-off depends upon the problem environment and in particular on its complexity and volatility: we show that in stationary and complex environments there exists an evolutionary advantage to over-modularization, while in highly volatile environments, contrary to usual wisdom, modular search is inefficient in the long run. The empirical relevance of our findings is discussed especially with reference to the literature on systems integration.

The Geography of Internet Infrastructure: An Evolutionary Simulation Approach Based on Preferential Attachment

In this paper, the evolution of infrastructure networks is modelled as a preferential attachment process. It is assumed that geographical distance and country borders provide barriers to link formation in infrastructure networks. The model is validated against empirical data on the European Internet infrastructure network covering 209 cities. The average path length and average clustering coefficient of the observed network are successfully simulated. Furthermore, the simulated network shows a significant correlation with the observed European Internet infrastructure network. The paper ends with a discussion on the future uses of preferential attachment models in the light of the literature on world cities and global cities.

Appropriability, patents, and rates of innovation in complex products industries

The economic theory of intellectual property rights is based on a rather narrow view of both competition and technological knowledge. We suggest some ways of enriching this framework with a more empirically grounded view of both and, by means of a simulation model, we analyse the impact of different property right regimes on the dynamics of a complex product industry, that is an industry where products are complex multi-component objects and competition takes place mainly through differentiation and component innovation. We show that, as the complexity of the product spaces increases, stronger patent regimes yield lower rates of innovation, lower product quality, and lower consumers’ welfare.

Endogenous Networks in Random Population Games

Population learning in dynamic economies traditionally has been studied in contexts where payoff landscapes are smooth. Here, dynamic population games take place over “rugged” landscapes, where agents are uncertain about payoffs from bilateral interactions. Notably, individual payoffs from playing a binary action against everyone else are uniformly distributed over [0, 1]. This random population game leads the population to adapt over time, with agents updating both actions and partners. Agents evaluate payoffs associated to networks thanks to simple statistics of the distributions of payoffs associated to all combinations of actions performed by agents out of the interaction set. Simulations show that: (1) allowing for endogenous networks implies higher average payoff compared to static networks; (2) the statistics used to evaluate payoffs affect convergence to steady-state; and (3) for statistics MIN or MAX, the likelihood of efficient population learning strongly depends on whether agents are change-averse or not in discriminating between options delivering the same expected payoff.

Innovation and competition in complex environments

Summary The paper aims to shed light on the relation between technological research, competition and market dynamics, focussing on the role of product modularity. This relation is analysed via qualitative simulation modelling using a simple agent-based model. We define an economic system in which firms compete on the quality characteristics of a certain complex good, in a market where consumers have shown preferences for them. Firms are conceived as bounded rational agents that explore complex product technologies in order to improve their fitness in relation to the selection environment (i.e. the consumers’ evaluation of the characteristics of the final good). The architecture of the good produced in the system is characterised by different degrees of modularity (i.e. the lower the correlations between the contributions of the different product components to the fnal product fitness, the simpler the good’s technology and the higher the degree of modularity). On the other hand, the impact of product modularity on industrial dynamics is analysed using a set of quite homogeneous firms. First, the model yields highly differentiated dynamics for firms that start from similar initial conditions, pointing to the importance of their research strategies. Second, the dynamic patterns obtained show that firms may easily end up in technological lock-in in spite of initial good performance, suggesting that path-dependence could be broken. Third, modularity impinges directly upon market results: a decrease in modularity, by increasing the difficulty in searching the complex technology, selects a limited number of firms, thus determining concentration in market shares. Finally, the industrial dynamics are influenced by the evolution of the quality of the fnal good.

The Complex Interactions between Economic Growth and Market Concentration in a Model of Structural Change

We study the relation between variety, market concentration, and economic growth, along different phases of economic development which entail a number of changes to the structure of production and consumption in the economy. We focus on three aspects of structural change, which are connected and are correlated to variety, market concentration, and economic growth: (i) product quality; (ii) firms’ mark-ups; and (iii) imitation of consumer preferences for price and quality. We model the interactions among several aspects of structural change such as firm size and hierarchical structure, innovation in capital vintages, the emergence of social classes, income distribution, and consumer preferences across and within classes. We find that market concentration has a significant and positive impact on economic growth only in the presence of sufficiently large demand. The strongest effects emerge in the presence of a more skewed firm size distribution and firms producing higher priced and higher quality goods. We find also that this effect is influenced strongly by different aspects of structural change. Changes in the behaviour (or income) of the less wealthy income classes is crucial as is investment in new capital vintages, and the emergence of diverse income classes with heterogeneous consumption preferences. In contrast, we find that supply side product variety, coeteris paribus, has no significant effect on growth.

Organisation of Industry and Innovation Dynamics

The paper aims at investigating how the organization of a certain industry evolves once the competition among its firms, producing a ‘complex’ (i.e. non-modular) product, is modeled as the intertwining of innovative search and organizational change. In order to take the full roster of participants into account, and to retain the inner complexity of their decisions, a Pseudo–NK model is built–up in which a population of firms is called to match a technological frontier. By evolving along different stagesof the sector’s life-cycle, such a kind of technological calls for a trade–off between two strategies of cost–reduction through either outsourcing ortechnological search. Overall, the simulation results confirm previous literature as, for example, in the introductory stage of the industry life–cycle,marked by frequent and intense jumps of the technological frontier, firms need to vertically integrate in order to have higher chances to win the competition for a new standard. On the contrary, in the decline stage,in which the technological frontier almost stabilizes, deverticalization allows firms to better compete on costs. These results change if suppliers are allowed to innovate, as they are more likely to lock the market in sub–optimal configurations.