Industry and Labor Dynamics

CONTENTS

No abstract received.

This paper presents a view of the economy as a complex system with heterogeneous interacting agents who collectively organise themselves to generate aggregate phenomena which cannot be regarded as the behaviour of some average or representative individual. There is an essential difference between the aggregate and the individual and such phenomena as bubbles and crashes, herd behaviour the transmission of information and the organisation of trade are better modelled in the sort of framework suggested here than in more standard economic models.

This paper aims at presenting the methodological approach to simulations, proposed at the beginning of the sixties by a group of scholars of the Carnegie Mellon University. This approach can be defined cognitive and behavioural, because of the attention to real perception and decision-making and to the role assigned to learning processes. One of the main points of departure is constituted by the wish to relay on more realistic assumptions, as a condition for better an understanding and forecast of the reality. Simulations are seen as the most important, even if not unique, way to model the resulting complexity.

This paper shows how agent-based modelling technique is a suitable approach for social scientists to model complex adaptive systems, using computer as experimental environment. Unfortunately advanced tools are lacking as well as an unified language supporting its development. We present JAS, a new agent-based simulation tool, developed with the aim to improve AB models designing. We give a brief methodological introduction to its use and a short description of its architecture.

In this paper, we present an agent-based, evolutionary, model of output- and labor-market dynamics. Firms produce a homogeneous, perishable, good under constant returns to scale using labor only. Labor productivities are firm-specific and change stochastically due to technical progress. The key feature of the model resides in an explicit microfoundation of the processes of: (i) matching between firms and workers; (ii) workers search; (iii) wage setting; (iv) endogenous formation of aggregate demand; (v) endogenous price formation. Moreover, we allow for a competitive process entailing selection of firms on the basis of their revealed competitiveness. Simulations show that the model is able to robustly reproduce Beveridge, Wage and Okun’s curves under quite broad behavioral and institutional settings. The system generates endogenously an Okun’s coefficient greater than one even if individual firms employ production functions exhibiting constant returns to labor. Montecarlo simulations also indicate that statistically detectable shifts in Okun’s and Beveridge curves emerge as the result of changes in institutional, behavioral, and technological parameters, Finally, the model generates sharp predictions about how system parameters affect aggregate performance (i.e. average GDP growth) and its volatility.

The matching function has become a popular tool in labor economics. It relates job creation (a flow variable) to two stock variables: vacancies and job searchers. In most studies the matching function is considered to be exogenous and assumed to fulfill certain properties. The present study, instead, looks at the properties of an endogenous matching function. For this purpose we have programmed an agent-based computational labor market model with endogenous job creation and endogenous job search behavior. Our simulations suggest that the endogenous matching technology is subject to decreasing returns to scale. The Beveridge curve reveals substitutability of job searchers and vacancies for a small range of inputs, but is flat for relatively high numbers of job searchers and vertical for relatively high numbers of vacancies. Moreover, the matching technology changes with labor market policies. This raises concerns about the validity of labor market policy evaluations conducted with flow models of the labor market that employ exogenous matching functions.

An urn-ball probabilistic model of the labor market is developed. Agents can be employed, (voluntary or involuntary) unemployed or entrepreneurs. The analytical long run equilibrium probabilities for each state and the matching function are derived. In equilibrium, a higher reservation wage increases the number of start-ups, but has an overall negative impact on the unemployment rate. A more buoyant economy (higher average growth rate and higher average wages) is shown to be associated with a lower unemployment rate. Higher start-up costs discourage entrepreneurship and increase unemployment. More active search behavior leads first to a decrease in the unemployment rate, and then to a small increase, due to increased coordination failure induced by the higher number of applications sent by job seekers. The out-of-equilibrium dynamics are investigated through an agent-based simulation, which also provides results on firm demography. Important empirical regularities such as the Beveridge and the Okun curve are recovered. Finally, the simulation model is used to investigate departures from maximizing individual behavior and the effects of more realistic assumptions about profits and the business cycle.

This study experimentally tests the effects of a non-employment payment on work-site behaviors and market efficiency in the context of an agent-based computational labor market model with autonomous strategically-interacting workers and employers. On average, we find that a low but positive non-employment payment is most efficient, especially over the short and intermediate run. A high non-employment payment encourages those who enter employment relationships to be cooperative, but the cost of the non-employment payment program significantly reduces efficiency. Having no non-employment payment encourages the formation of employment relationships, but non-cooperation is common and this reduces efficiency. These “average” results should be viewed with caution, however. Because of strong network and learning effects, quite different paths and ultimate outcomes can result from the same initial structural conditions.

The substantial changes in the Italian pension system over the last decade subsequent to the Amato, Dini, Prodi and Berlusconi reforms have given raise to a renewed debate on re-designing pension system and in particular seniority pensions. Workers respond quickly to different incentives present in the pension systems and to expected government policies, especially through their retirement choices. These reactions, in turn, can or should inform government policy design to contrast the consequences of the ageing process. Based on the not fully satisfactory way of addressing such issues, this paper aims to shed some new light on the transition from one pension regime to another. After a brief review of the economic literature, this paper presents a bit more evidence on early retirement and its future evolution using dynamic ageing methodology, considering an economy, with heterogeneous workers, whose retirement age depends on expected utility. We examine behavioural changes estimating the age of retirement along the current pension reform path, assuming different behavioural regimes and policies, using a model calibrated to reproduce the main Italian demographic and economic features and retirement dynamics. We find a tendency to postpone the exit from labour market, especially when workers maximise their benefits flow coming from all incomes, instead of sole pension benefits. In this case, pension expenditures grow faster, because savings, due to retirement postponement, are compensated by higher benefits. Finally, we consider how future trends of inequality and poverty among pensioners can be negatively affected by the government seniority pension reform and propose possible remedies.

Power law behavior is an emerging property of many economic models. In this paper we emphasize the fact that power law distributions are persistent but not time invariant. In fact, the scale and the shape of the firms’ size distribution fluctuate over time. In particular on a log-log space both the intercept and the slope of the power law distribution of firms’ size change over the cycle: during expansions (recessions) the straight line representing the distribution shifts up and becomes less steep (steeper). We show that the empirical distributions generated by simulations of the model presented by [11] mimic real empirical distributions remarkably well.

Most innovations are the result of contributions from many agents. Not only the firm which eventually commercializes the innovation but also suppliers, service firms, customers, banks, venture capital providers, universities, contract research organizations or technology centres may have participated in this process. Often the collaborating organizations belong to different societal systems like business, science or politics. As a consequence, they face the problem how to deal with the different rationalities of these systems. They have to establish rules and routines how to integrate them in order to avoid conflicts and to benefit from the diversity of rationalities. As far as innovation is concerned there is a lot of evidence that the interaction between different rationalities, especially between the business and science systems, stimulates more advanced or so-called “radical” innovations, Far more ambiguous is the problem of organizing such multi-system based innovation projects. Two basic types of multi-system innovation processes can be distinguished: on the one hand, hybrid organizations which integrate two or more rationalities within the organization and, on the other hand, co-operations and market transactions between single-system based organizations. The aim of the paper is to present the concept of a simple multi-agent system model that simulates the effects of the interaction between the rationalities of the business and science systems on the innovation process of firms and that enables us to compare the two modes of organization — the internal mode of multi-system based hybrid organizations versus the external mode of co-operation or market transaction between single-system based organizations.

We provide a model of hierarchical organization where artificial agents with limited individual capacities allocate their efforts in two activities. Different incentives schemes are considered and individual diversity and social norms are approached.

We propose a Nelson-Winter model with an explicitly defined landscape to study the formation of high-tech industrial clusters such as those in Silicon Valley. The existing literature treats clusters as the result of location choices and focuses on how firms may benefit from locating in a cluster. We deviate from this tradition by emphasizing that high-tech industrial clusters are characterized by concentrated entrepreneurship. We argue that the emergence of clusters can be explained by the social effect through which the appearance of one or a few entrepreneurs inspire many followers locally. Agent-based simulation is employed to show the dynamics of the model. Data from the simulation and the properties of the model are discussed in light of empirical regularities. Variations of the model are simulated to study policies that are favorable to the high-tech economy.

An agent-based simulation model representing a theory of the dynamic processes involved in innovation in modern knowledge-based industries is described. The agent-based approach allows the representation of heterogeneous agents that have individual and varying stocks of knowledge. The simulation is able to model uncertainty, historical change, effect of failure on the agent population, and agent learning from experience, from individual research and from partners and collaborators. The interactions between the agents occur on two levels: through a market with firms supplying and consuming goods for a price, and through the exchange of knowledge. A brief description of the implementation of the model and its user interface is given.

In the present work we describe a model of production processes, with a detailed representation of vertical interactions across sectors, in an input-output framework. Firms are heterogeneous agents, each with its competencies in production, using different inputs with different characteristics, acting in a specific sector. Firms within each sector produce similar goods, but with different quality features appealing to the sector’s demand. We show, through different simulation settings, that the way in which the process is modelled is both extremely flexible and its results are robust under standard basic economics assumptions. As discussed in a methodological section we argue that those characteristics of the model are important in order to study the production structure to understand different industrial dynamics through a micro perspectives. In particular, we propose one particular framework, which synthesises the aspects of a broader research for which this model has been developed.

The paper describes an agent-based prototype that has been created to investigate relations among local labor markets, entrepreneurship and human capital in industrial districts. It basically describes the building blocks of the prototype, the agents acting in it and the forces that drive its most interesting dynamics. Some interesting hypotheses to investigate are sketched, too.

The main idea of this paper is to prove that economic structures that are based on small businesses function better than oligopolies. Small business structures promote growth inducing innovation, while oligopolies seek incremental and continuous innovations. Thus the former system creates employment, and the latter modifies employment. To prove this claim, six propositions are introduced and analysed. The main argument used for the analysis is the nature of the tasks performed, and its relation to innovation. The six propositions use the variable of the tasks performed in various aspects of the comparison of the two systems.

The clustering of agents in the market is a typical problem dealt with by the new approaches to macroeconomic modeling, that describe macroscopic variables in terms of the behavior of a large collection of microeconomic entities. Clustering has a lot of economical interpretations, that are often described by Ewens’ Sampling Formula (ESF). Contrary to the usual complex derivations, we suggest a finitary characterization of the ESF pointing to real economic processes, Our approach is finitary in the sense that we probabilize a system of n individuals considered as a closed system, a population, where individuals can change attributes as time moves on. The intuitive meaning of the probability is the fraction of time the system spends in the considered partition. As ESF represents an equilibrium distribution satisfying detailed balance, some properties difficult to prove are derived in a simple way. Besides the mean distribution of the cluster sizes, we study the probabilistic time behavior of clusters, in particular the mean survival as a function of the actual size and the correlation between size and age.

The preceding papers have shown the impressive versatility and potential of agent-based modelling in developing an understanding of industrial and labour dynamics. The main attraction of agent-based models is that the actors - firms, workers, and networks - which are the objects of study in the ‘real world’, can be represented directly in the model. This one-to-one correspondence between model agents and economic actors provides greater clarity and more opportunities for analysis than many alternative modelling approaches. However, the advantages of agent-based modelling have to be tempered by disadvantages and as yet unsolved methodological problems. In this brief summary drawn from the discussion at the closing session of WILD@ACE, I review three of these open problems in the context of the papers presented at the conference: How can agent-based models be empirically validated? What criteria should be used to evaluate the explanatory success of agent-based models? And how can the conclusions of research on similar topics be integrated?