The Cognitive Mechanics of Economic Development and Institutional Change

Bertin Martens

• Publisher: Routledge
• Year: 2004
• Topic: Business
• eBook ISBN:
  9781134340163
• Subtopic: Business General
• Index: Business

This book seeks to explain long-term economic development and institutional change in terms of the cognitive features of human learning and communication processes. Martens links individual cognitive processes to macroeconomic growth theories, including economies of scale and scope, and to theories of institutional development based on asymmetric i

1: Introduction

This book aims to construct a plausible explanatory model of the emergence and co-evolution of economic systems and institutions that guide behaviour in human societies. The model revolves around cognition—the capacity of human beings to acquire and store knowledge, communicate it and use it for behavioural purposes.¹ The emergence of trade, or economic systems, is explained as an efficient form of communication of knowledge through embodiment in goods and services. Trade circumvents cognitive capacity constraints because, contrary to symbolic communication, the recipient is not required to process and store all embodied knowledge in his own mind. Furthermore, trade enables the emergence of specialisation—the asymmetric distribution of knowledge across groups of individuals. The book argues that specialisation has allowed human societies to overcome the limits on individual cognitive capacity and achieve rapid growth in knowledge, far beyond the possibilities of individual learning capacity. Specialisation and trade require institutional incentives, however, to allocate property rights to knowledge and handle the uncertainties generated by lack of knowledge of the traded goods. Society’s ability to develop more powerful institutional incentives for specialisation and efficient exchange has marked the pace of cognitive and economic development. The evolution of many important organisational features in human societies, including production, markets, legal and political institutions, etc., can be interpreted in terms of a relentless search for ever more cognitive economy through more efficient handling of distributed knowledge.

More specifically, this book seeks to demonstrate the validity of two propositions:

• First, specialisation (or distributed knowledge) is a consequence of the search for cognitive economy. Since individual cognitive capacity is limited, any features of human society that help to relax this constraint carry an evolutionary advantage. Economic systems are such a feature because they generate cognitive economy through specialisation or the asymmetric distribution of knowledge over a group of individuals. The cognitive economy resides in the fact that not every individual has to acquire the same knowledge. Rather, we can make use of the specialised knowledge acquired by somebody else by trading our products for the products that embody his knowledge. As a result, specialisation has enabled human societies to achieve rapid growth in knowledge accumulation and storage capacity, far beyond the possibilities of individual learning capacity.
• Second, specialisation requires matching institutions in order to foster economic development. Institutions reduce transaction costs and regulate the residual uncertainties that are inherent to the exchange of specialised knowledge embodied in goods and services. They are a prerequisite for the efficient exchange of specialised embodied knowledge, which is necessarily a partial exchange only: the buyer does not possess all the knowledge that went into the production of the good. Society’s ability to develop ever more efficient institutions, both in terms of individual property rights and collective decision-making, facilitates specialisation and marks the pace of economic development. Economic and institutional development run in parallel, and are both endogenous to the cognitive development of human societies.

The centrality of cognition

This is an essay in cognitive economics. The view that knowledge plays a central role in economic development is now broadly accepted, especially since the late 1980s. In 1988, Robert Lucas published a paper on The mechanics of economic development’ (Lucas 1988). It triggered a wave of new research on economic growth that has become well known under the label of ‘New’ or ‘Endogenous’ Growth Theory. Lucas’ aim was to endogenise the so-called Solow Residual, the unexplained variation in economic growth that kept popping up in empirical tests of neo-classical growth models. This residual was generally attributed to technological innovation, or changes in knowledge. Lucas suggested that this problem could be solved by introducing knowledge as an explicit production factor in growth models, alongside the conventional production factors of capital and labour. Despite the initial optimism surrounding these new models, they quickly ran into methodological problems, due to two specific properties of knowledge: non-rivalry and partial excludability. Partial excludability implies that it is hard to keep knowledge as an exclusive property of an individual or company; it can spill over to other economic agents. Non-rivalry implies that many users can use the same knowledge at the same time. Romer (1994) demonstrated that these two properties are difficult to reconcile with the diminishing returns or convergence requirement of the neo-classical mainstream economics paradigm. For a number of years, the endogenous growth school was torn between proponents and opponents of convergence, waging battle with an endless series of empirical tests of their models, without settling the issue. At the end of the day however, the concrete mechanisms through which knowledge plays a role in economic development remained by and large a black box. The debate in economic growth theory has gradually returned to its starting position in recent years. Accumulation of production factors in neo-classical growth models, including accumulation of knowledge, provides but a partial explanation for economic growth. Attention is focused once more on the unexplained Solow Residual—re-baptised as ‘Total Factor Productivity’—that is widely recognised to be a major explanatory factor behind economic growth. At the same time, growth theory is back to square one in trying to open up the black box of Total Factor Productivity (Easterly and Levine 2000; Easterly 2001).

The view that institutions—humanly devised constraints on human behaviour—play a central role in economic development, and more specifically in Total Factor Productivity, has also gained wide acceptance in the last decade or so (Acemoglu et al. 2001; Rodrik et al. 2002; Sala-I-Martin 2002). This view goes back at least to North (North and Thomas 1973; North 1981), who argued that the quality of institutions determines the level of transaction costs that, in turn, affects economic efficiency. Modern institutional economics is a tree with many branches and twigs, with one common characteristic: all these schools of institutional economics examine how asymmetries in the distribution of information, or knowledge, affect economic performance. That is precisely what distinguishes neo-classical from neo-institutional economics. While the former generally assumes that (near-) perfect information is available in transactions at (near-) zero costs, the latter assumes positive information costs. Transaction cost economics looks at the cost of obtaining information required to conclude a contract or exchange (North 1990) and the potential costs of post-contractual uncertainty or absence of information (Williamson 1985). Incomplete contracts theory is based on quite similar principles, but focuses on the incentives embedded in a contract and the likely behavioural outcomes that they produce under imperfect information (Tirole 1999). Property rights theory examines how different allocations of this residual contractual uncertainty create different incentive structures. Modern organisation theory combines these different techniques to study incentives in large organisations or hierarchies where tasks are delegated and information is inevitably widely distributed across agents. Institutions—rules of behaviour—exist precisely because they are means to partially overcome these informational problems and the resulting uncertainties. While institutional economics is often associated with micro-economic applications at the level of individuals and organisations, a lot of these findings can be transposed to the macro-economic level. Its focus on incomplete and asymmetric information provides a useful starting point to study the role of information and knowledge² in economic growth.

Modern institutional economics has revealed the role that institutions play in the management of knowledge in societies. Institutions regulate the property rights on knowledge and the spill-over of knowledge between individuals—a very important issue in endogenous growth theory. Institutions also affect transaction costs and post-contractual uncertainties, and thereby play a vital role in enabling market transactions. Whereas markets exist to trade knowledge, whether or not embodied in goods and services, institutions exist to deal with the unknown aspects of the goods and services that are being traded and cause uncertainties. While macroeconomic growth theory has focused on the volume of knowledge as a driver of economic development, institutional economics and its offshoots in organisation theory have focused on the asymmetric distribution of that knowledge, and the way in which that distribution is being managed through behavioural constraints—property rights, spill-overs, contracts to handle residual uncertainties, etc.

Economic institutions point to another key aspect of this book: the role of distributed knowledge—or specialisation, division of labour and division of knowledge³—in economic and institutional development. Against this institututional economics background, one can see why Lucas’ (1988) attempt to solve the Solow Residual issue by integrating knowledge as a production factor in the growth model was too simple. He assumed that knowledge could be treated like any other production factor. That treatment becomes increasingly difficult to defend, not only because of the properties of partial excludability and non-rivalry that undermine the convergence requirement in neoclassical general equilibrium models, but even more so because the institutional implications of distributed knowledge management are not accounted for in this approach. In short, it is not just accumulation of knowledge that is important for economic performance; it is also the distribution of knowledge, and the way in which the problems associated with that distribution are handled by institutions. While there is by now a vast amount of literature that emphasises the importance of learning and knowledge accumulation in economic growth, very little has been written so far on the importance of distributed knowledge for economic growth, including the role that institutions play in the management of distributed knowledge. Despite the fact that distributed knowledge—or rather, the division of labour—figured prominently in the first paragraph of Adam Smith’s (1776) Wealth of Nations, the book that signalled the start of modern economics, the concept rapidly disappeared in the course of the history of economic thought. This book argues that there are good reasons to revive it, though in a cognitive interpretation that differs somewhat from the interpretation originally proposed by Adam Smith. It will demonstrate why asymmetrically distributed knowledge is a crucial explanatory factor for the emergence and evolution of institutions. More importantly, it will show how the evolution of institutions is closely linked not only to the accumulation of knowledge, but even more so to the distribution of that knowledge across society. This book looks at institutions as endogenous outcomes of knowledge accumulation and distribution in society, not as rules of behaviour exogenously invented by social or political geniuses.

That brings us to the title and the purpose of this book. One can see how institutional economics and macro-economic growth theory, the main schools of thought in the economic growth debate of the last two decades, are slowly converging around (distributed) knowledge as a common driver for economic growth, or in a broader sense (distributed) cognition. This book seeks to further explore the role of knowledge, or cognition, as a common denominator of neo-classical and neo-institutional economic growth and development theories. It does not seek to produce a new and fully fledged economic growth theory, but rather to integrate into economics a number of concepts from cognitive science that may shed light on the nature and mechanics of distributed cognition, with a view to establishing a cognitive approach to economic development and providing the conceptual foundations for an integration of current economic growth and institutional economics theories into a single unified approach.

The wider picture

Above, I provided a first and purely economic reason why this book’s focus is on cognition, namely that it is justified by recent developments in economic theory that point towards a convergence of growth theory and institutional economics around the common denominator of (distributed) knowledge, or cognition. However, there are at least two other reasons to put cognition at the core of an explanatory framework for the emergence and evolution of economic and institutional development in human societies.

The second reason is that a general theory of economic development of human societies should be capable of explaining the transition from preeconomic to economic societies, on the basis of a unifying concept that is present in both stages but underwent a change that explains the transition. I will argue in Chapter 5 that cognition constitutes such a unifying concept, and that changes in cognitive features of human behaviour—in this case communication features—can explain why economic systems and institutions emerged, and why they constitute an evolutionary (and cognitive) advantage for societies that have them.

The proposed model should be able to trace an uninterrupted line of cognitive, economic and institutional development of human societies, that stretches, say, from Olduvai Gorge in the Great Rift Valley, Tanzania (2.5 million years BC), to Palo Alto in Silicon Valley, California (2002 AD). While there is unlikely to be any significant genetic difference between the peoples that populate both valleys, there is an enormous difference in the knowledge sets that both peoples have at their disposal to cope with the threats and opportunities of their environment. This difference is not only due to cumulative learning across history, but more so due to differences in the organisation of knowledge storage and communication techniques in these societies, facilitated by institutions, and consequently differences in the degree of knowledge specialisation and the level of economic development. Silicon Valley is just the latest—and by no means the last—step in the cognitive development of primate societies.

The emphasis on the central role of cognition in the development of human societies, and cognitive continuity therein, implies that this book could be considered as an extension of the evolutionary epistemology tradition into the domain of the social sciences, and in particular into economics. Evolutionary epistemology (Hahlweg and Hooker 1989; Callebaut and Pinxten 1987) is an interdisciplinary school of thought that subscribes to the view that all cognitive evolution is just a continuation of biological evolution: all organic bodies are repositories of knowledge, even if they are not equipped with an active mind or with the ability to learn. Darwinian selection processes, with random mutations and selective retention, are also considered learning processes, though spread out over many generations rather than within a single lifetime. This results in accumulation of environmental and behavioural knowledge in genetic structures in living organisms. Organisms with central nervous systems have developed independent cognitive capacity: the ability to learn and adapt behaviour within a single lifetime, even at very short notice. Moreover, some animals are good at imitation and can thereby transmit knowledge between them. Human beings have done even better. We have developed symbolic communication systems that are a far more efficient means to transfer very complex knowledge, and even entire thought processes, from one individual to another. Finally, we have developed economic systems that allow us to transfer knowledge embodied in goods, so that the recipient can economise on his scarce cognitive capacity. There is no need for him to store all that knowledge in his own brain. He can simply make use of that knowledge in embodied form. However, this form of cognitive economy requires individual incentives to invest in learning and derive the benefits from it. That is where economic institutions that enable gainful trade come into play. I will argue in Part II of this book that both symbolic communication and exchange of embodied knowledge—trade and property rights—emerged as an evolutionary advantageous response to circumvent the limited cognitive capacities of human brains.

The third reason for the centrality of cognition is related to the quote from Boulding (1966) in the preliminary pages of this book. I have selected this quote because it provides a good starting point for this research and also because it connects two ‘spheres’ of the world: the physical world, governed by the first and second law of thermodynamics, that is often associated with economic production and exchange, and the cognitive world of knowledge, that counters the second law of thermodynamics—the entropy law—and is responsible for shaping and transforming the world, creating new order. Boulding (1966) points out that the quantity of matter and energy is for all practical purposes a constant, and energy is even subject to decay (rather than growth) as a result of the entropy law. As a result, it is somewhat difficult to see how mere production of goods and services, which requires matter and energy, could represent growth. The only thing that can grow over time is knowledge, our understanding of the world around us. We can use this knowledge to produce ever more sophisticated and complex transformations of matter and energy, via a process that he describes as the ‘three-dimensional printing’ of knowledge. However, a lot of knowledge may not be used for transformation and embodiment in matter, but rather for the transformation of the organisation of society, the way in which people behave and interact and to shape the institutions that guide human behaviour. (And some knowledge may of course not be used for any behavioural purposes at all and remain in a purely symbolic format.) At the time when Boulding wrote and pronounced these words, economists began to agree that knowledge accumulation is an important driver for economic growth. It took nearly four decades more for economists to begin to see that it also drives institutional change in societies, through the mechanism of distributed knowledge.

A summary of the main arguments

The book starts by taking a few steps back from the economic realm to examine some basic cognitive mechanisms that enable the accumulation and communication of knowledge in human societies. Cognition is not only about learning processes in the human brain, but also about external knowledge storage devices, asymmetric distribution of knowledge between individuals and the organisation of communication between them.

Part I of this book contains an overview of the relevant economics literature on economic growth (Chapter 2) and distributed knowledge (Chapter 3). It explores the uneasy relationship between (distributed) knowledge and modern economics. I do not present any new arguments. My only aim here is to prepare the ground for the cognitive and institutional arguments in PartsII and III. Knowledge itself is now widely recognised as an important variable in economic growth, but existing growth models have a hard time in handling the properties of knowledge. By contrast, the distribution of knowledge is not recognised as a relevant variable in mainstream macro-economic growth models. Only modern institutional economics theories implicitly or explicitly recognise that institutions exist in order to facilitate handling of asymmetries in the distribution of knowledge.

Chapter 2 presents an in-depth exploration of the arguments that were advanced above, at the start of this introductory chapter. It reviews in detail the role of knowledge in m...

Table of contents

• Cover Page
• Routledge Frontiers of Political Economy
• Title Page
• Copyright Page
• Illustrations
• Acknowledgements
• 1: Introduction
• Part I: Knowledge and economics
• Part II: The principle of cognitive economy
• Part III: The cognitive mechanics of institutional change
• Notes
• Bibliography