Alan Kirman

Communication in markets : A suggested approach

Abstract This paper draws attention to the problem of the communication of information between individuals. It suggests a mathematical tool, the theory of stochastic graphs which should prove particularly useful when modelling situations in which such communication is imperfect. Examples of the sort of result which may be obtained using this tool are given.

Rethinking Economics Using Complexity Theory

In this paper we argue that if we want to find a more satisfactory approach to tackling the major socio-economic problems we are facing, we need to thoroughly rethink the basic assumptions of macroeconomics and financial theory. Making minor modifications to the standard models to remove “imperfections” is not enough, the whole framework needs to be revisited. Let us here enumerate some of the standard assumptions and postulates of economic theory. 1. An economy is an equilibrium system. In other words, it is a system in which all markets systematically clear at each point of time, but where the equilibrium may be perturbed, from time to time by exogenous shocks. 2. Selfish or greedy behaviour of individuals yields a result that is beneficial to society – a modern, widespread, but inaccurate reformulation of the principle of the “invisible hand”. 3. Individuals and companies decide rationally. By this it is meant that individuals optimize under the constraints they are facing and that their choices satisfy some standard consistency axioms. 4. The behaviour of all the agents together can be treated as corresponding to that of an average or representative individual. 5. When the financial sector is analysed, it is assumed that financial markets are efficient. Efficiency here means that all the relevant information concerning an asset is reflected in the price of that asset. 6. For financial markets it is assumed that they function better if their liquidity is greater. 7. In financial markets, the more connected the network of individuals and institutions the more it reduces risks and the more stable and robust is the system. Below, we discuss the fundamental problems with these assumptions and outline some of the policy implications of improved assumptions.

Reconstructing economics: Agent based models and complexity

In this paper we argue that a view of the economy as a complex interactive and adaptive system allows one to explain phenomena such as “phase transitions” which are not consistent with the equilibrium models of standard models. A growing strand of economists is now following a different methodology based upon the analysis of systems with many heterogeneous interacting agents. We explain how Agent Based Models (ABM), and, in particular Agent based Computational Economics (ACE), and Analytically Solvable Heterogeneous Interacting Agent (ASHIA) models based on statistical physics or Markov chains can be used to deal with economies in which direct interaction between agents is important. This interaction leads to empirical regularities, which emerge from the system as a whole and cannot be identified by looking at any single agent in isolation: these emerging properties are, according to us, the main distinguishing feature of a complex system. In this way economics can free itself from the limitations of the static equilibrium approach, the use of the implausible Representative Agent approach and analyze the, possibly out of equilibrium, dynamics which seem more consistent with observed empirical data. The complexity approach is a very challenging line of research whose empirical results are very promising. Modeling an agent-based economy, however, remains a complex and complicated adventure.

Ants And Nonoptimal Self-Organization: Lessons For Macroeconomics

This paper suggests that we need an alternative approach to economic modeling in general, and macroeconomic modeling in particular, if we are to capture salient characteristics of recent economic developments. Rather than focusing on models built on the basis of isolated, rational, optimizing agents, we should recognize that much simpler individuals following basic rules can collectively generate complex behavior. We have lessons to learn from studying the behavior of social insects for example. Noisy systems of interactive agents can generate aggregate phenomena such as sudden changes in the state of an economy or market, with no external shock. I give two examples of simple models of financial markets to illustrate this but would argue more generally that such models are indispensible if we are to understand aggregate economic phenomena.

Complex Financial Networks and Systemic Risk: A Review

In this paper we review recent advances in financial economics in relation to the measurement of systemic risk. We start by reviewing studies that apply traditional measures of risk to financial institutions. However, the main focus of the review is on studies that use network analysis paying special attention to those that apply complex analysis techniques. Applications of these techniques for the analysis and pricing of systemic risk has already provided significant benefits at least at the conceptual level but it also looks very promising from a practical point of view.

BUBBLES IN FOREIGN EXCHANGE MARKETS

We consider a model in which foreign and domestic traders buy the assets of both of two countries. Speculators in both countries use chartist or fundamentalist rules for forecasting the exchange rate. Demand for the assets of each country is determined by these forecasts. Perceptions of the fundamentals in each country are not necessarily the same. Rules are used with a certain probability depending on an agents previous experience with them. The demands of the fundamentalist and chartist agents in the two countries determine the temporary equilibrium exchange rate at each point in time. This is unique under certain assumptions. With traders of both nationalities there is no need, as in other models, for an exogenous supply of foreign exchange. The model produces realistic features of the equilibrium exchange rate series. Periods in which the exchange rate tracks the fundamentals of one of the countries alternate with others in which bubbles appear.

Bank Insolvencies, Priority Claims and Systemic Risk

We review an extensive literature debating the merits of alternative priority structures for banking liabilities put forward by financial economists, legal scholars and policymakers. Up to now, this work has focused exclusively on the relative advantages of each group of creditors to monitor the activities of bankers. We argue that systemic risk is another dimension that this discussion must include. The main message of our work is that when bank failures are contagious then when regulators assign priority rights need also to take into account how the bankruptcy resolution of one institution might affect the survival of other institutions that have acted as its creditors. When the network structure is fixed the solution is straightforward. Other banks should have priority to minimize the risk of their downfall. However, if the choice of policy can affect the structure of the network, policy design becomes more complex.This is a fruitful avenue for future research.

Looking Ahead: Part II

We propose a number of possibilities for future research on issues related to systemic risk in financial markets and its relationship to the macroeconomy. Some of the proposals aim to improve our understanding of the behavior of aggregate credit. Other proposals involve the development or richer agent-based models that potentially can help us understand the time-series properties of national output.

Systemic risk and macroeconomic fat tails

We propose a mechanism for shock amplification that potentially can account for fat tails in the distribution of the growth rate of national output. We argue that extreme macroeconomic events, such as the Great Depression and the Great Recession, were preceded by significant turmoil in the banking system. We have developed a model of bank network formation and presented numerical simulations that show that, for the benchmark case, aggregate credit follows a random walk. When we introduce fire sales the model does not only produce larger variations in the growth of aggregate credit but also shows that there is an asymmetry between booms and busts that is also consistent with empirical evidence.

Economic Crises: Natural or Unnatural Catastrophes?

Whilst models of the environment and particularly of the climate have come to be ones of evolving complex systems with non-linear dynamics and complicated feedbacks, macroeconomic models have remained essentially in an equilibrium framework in which the only major changes that can occur are the result of exogenous shocks. I explain why this has been the route taken by macroeconomists However, the purpose of this paper is to suggest that, in fact, the economy shares many of the features of the environment and that it should also be viewed as a complex system which experiences major, sudden and sometimes catastrophic, changes. These changes are largely due to the evolution of the system and not to some outside influence. However, in the anthropocene era we have to take account of the co-evolution of two complex systems, the environment and the economy, and the economic models that have been proposed in “integrated” models do not capture the complexity of the economy nor of its interactions with the environment. To successfully do this will provide a better explanation of the evolution of the economy but will mean that economists have to be much more modest their claims.