Catálogo de publicaciones - libros

This paper is a short review on the application of continuos-time random walks to Econophysics in the last five years.

Two new reasons are discussed for sluggish behavior of macroeconomic variables such as price indices.

One is slow spread of the news of microeconomic idiosyncratic shocks in the economy, when the economy is organized into tree structures of heterogeneous subgroups or clusters of agents or goods. Clusters are not symmetrically treated, but the concept of ultrametric distances measure disparities or similarities of clusters.

Another is the effects of uncertainties that affect decision processes, such as about the cost surfaces, or about the shapes of cost landscapes which may have many local minima which are not known precisely. Effectiveness of many search algorithm is reduced in the face of this kind of uncertainty. Flat cost landscapes, called entropic barriers, are discussed as an example.

We study the determinants of growth rate volatility in a multisector economy where sectors are heterogeneous in their individual volatility. We propose a model where aggregate volatility is explained by structural change and the size of the economy. We present a first attempt to test these predictions measuring growth volatility by indices based on Markov transition matrices. Growth volatility appears to (i) decrease with total GDP and (ii) increase with the share of the agricultural sector on GDP, although some nonlinearities appear. Trade openness, which we relate to the size of the economy, also plays a role. In accordance with our model, the explanatory power of per capita GDP, a relevant variable in other empirical works, vanishes when we control for these variables.

We present results from human and computer-based experiments aimed at exploring the role of rationality and financial markets in explaining the emergence of some well-known stylized facts regarding industrial and aggregate dynamics. We find that the information conveyed by financial markets helps agents adopt more rational decision processes. Rationality, in turn, is necessary to observe smooth aggregate behaviors.

The Japanese shareholding network at the end of March 2002 is studied. To understand the characteristics of this network intuitively, we visualize it as a directed graph and an adjacency matrix. Especially detailed features of networks concerned with the automobile industry sector are discussed by using the visualized networks. The shareholding network is also considered as an undirected graph, because many quantities characterizing networks are defined for undirected cases. For this undirected shareholding network, we show that a degree distribution is well fitted by a power law function with an exponential tail. The exponent in the power law range is = 1.8. We also show that the spectrum of this network follows asymptotically the power law distribution with the exponent = 2.6. By comparison with and , we find a scaling relation = 2 − 1. The reason why this relation holds is attributed to the local tree-like structure of networks. To clarify this structure, the correlation between degrees and clustering coefficients is considered. We show that this correlation is negative and fitted by the power law function with the exponent = 1.1. This guarantees the local tree-like structure of the network and suggests the existence of a hierarchical structure. We also show that the degree correlation is negative and follows the power law function with the exponent = 0.8. This indicates a degree-nonassortative network, in which hubs are not directly connected with each other. To understand these features of the network from the viewpoint of a company’s growth, we consider the correlation between the degree and the company’s total assets and age. It is clarified that the degree and the company’s total assets correlate strongly, but the degree and the company’s age have no correlation.

Technological innovation requires the gathering of information through a process of searching and learning. We distinguish two different but definitely complementary and overlapping ways through which searching and learning occur. The first exploits the spillover potential that lies in a firm’s network and thanks to which gathering innovation-useful information is actually possible. The second is the autonomous capacity that a firm possesses in order to carry out in-house innovative search. We build a model where rationally bounded firms try to increase their innovative capability through endogenous networking. The paper characterizes the emergence of technological paradigm setters in terms of network properties as they result from searching routines, furthermore the corresponding average efficiency of the system in terms of innovative capability is assessed.

Stability and bifurcation analysis of deterministic systems has been widely used in modeling financial markets. However, the impact of such dynamic phenomena on various statistical properties of the corresponding stochastic model, including skewness and excess kurtosis, various autocorrelation (AC) patterns of under and over reactions, and volatility clustering characterised by the long-range dependence of ACs, is not clear and has been very little studied. This paper aims to contribute to this issue. Through a simple behavioural asset pricing model with fundamentalists and chartists, we examine the statistical properties of the model and their connection to the dynamics of the underlying deterministic model. In particular, our analysis leads to some insights into various mechanisms that may generate some of the stylised facts, such as fat tails, skewness, high kurtosis and long memory, observed in high frequency financial data.

This paper investigates the role of fiscal and monetary shocks in the occurrence of deflationary recessions. Our model is based on a temporary equilibrium approach with stochastic rationing, where inventory dynamics is explicitly taken into account, amplifying spillover effects between markets. This setting allows us to study the driving forces behind disequilibrium phenomena, and to investigate the efficacy of alternative policies in overcoming them. In particular, we provide for an application of our approach to the study of the Japanese deflationary recession.

The Solow-Swan model of economic growth is reviewed on the basis of natural production. Natural growth is a biochemical process based on the laws of thermodynamics. Economic production - like work in thermodynamics - is a non exact differential. The production function () as a function of laborers () and () depends on the path of integration. The production function may be calculated for the special processes like constant mean capital per labor (), (which corresponds to the Carnot process in thermodynamics): () = { + + (ln{){. The elasticity coefficients or exponents with + = 1 are determined by the production factors! The production function () has been applied to optimizing production processes in farming and leads to a Boltzmann distribution of production factors. The main source of economic growth is entropy, the chance of diversification, the variety of know how and ideas. The results lead to a new model of economic growth for interdependent economic systems like Japan and the US, East and West Germany, North and South America, and agrees well with data for these economies.

Decision-making is a crucial task for the business planning of industrial firms, in order to cope with uncertainties in the business environment. A method of firm dynamics simulation, i.e. the game-theoretic stochastic agent, was developed by applying game theory to a stochastic agent model in order to analyze the uncertain business environment. Each stochastic agent is described by a Langevintype equation with an additional term for rational decision-making. In this paper, the dynamics of firms in computer related industries, which consist of three industrial sectors, i.e. the large scale integrated circuit sector, the personal computer sector, and the liquid crystal display sector, are simulated using the game-theoretic stochastic agents model. Then, the importance of the herding behavior of firms is demonstrated to reproduce the formation and collapse of the bubble in the Japanese computer related industry markets during the late 90s.