Rethinking the Theory of Economic Policy: Some Implications of the New Institutionalism
The early postwar domination of welfare economics (Samuelson, 1947: Ch. 8; Bergson, 1938), the Keynesian revolution, and the new field of development economics (Kindleberger, 1958) ushered in an age of excessive expectations for the potency of economic policy. To organize their thoughts about the contribution of economics to policy, and confident of their capacity to control social systems, many economists relied on a popular framework, the theory of economic policy (Tinbergen, 1956). In the 1970s, this excessive optimism changed as policy failures and a clearer recognition of the role of private incentives buried naive hopes of fine-tuning the economic system or individual markets (Lucas, 1976; Posner, 1986:Part III). Events also diminished early hopes that development economics would provide strategies for rapid transition in the Third World (Hirschman, 1981). In economics, a new emphasis on information scarcity suggested that transaction costs seriously limit effective social engineering and complicate economic organization (Furubotn and Richter, 1993; Kreps, 1990; Milgrom and Roberts, 1992; North, 1990; Stiglitz, 1994; Williamson, 1985).
Growing pessimism about traditional approaches produced neither systematic reevaluation of development strategies nor a new consensus on the appropriate scope for public policy. Economists offer conflicting explanations of economic successes and failures among Third World countries, while the Eastern European revolution of 1989 took social science unawares when it required guidance for rapid transition to markets. Mainstream economics has lacked a general theory of economic systems and structural change. In recent
years, however, a new theory of institutions based on the economics of property rights and transaction costs has earned a measure of recognition among economists.
Although institutional analysis could potentially complement standard macro- and microeconomic theory in the design of policies for economic development, it has yet to develop a strong policy orientation.1 This chapter introduces institutional analysis to the old theory of economic policy—to its policy models and its instruments, targets, and policy measures—in the hope that the new institutionalism will reveal its policy implications when viewed against the background of the traditional policy world. More particularly, the chapter explores the ways information scarcity affects policies aimed at social transformation.
The next section briefly summarizes the old theory of economic policy, associated with the Dutch economist Jan Tinbergen (1956). This is followed by an examination of three policy issues that were not a central concern of mainstream economics in the early post-war period: (1) the requirements of structural policy, (2) the need to extend the policy model, and (3) the implications of information scarcity. The chapter then presents a public policy view of the new institutionalism; problems of incomplete data and control and of incomplete models and decisions suggest an intricate policy world. Next is a discussion of the policy determinacy implicit in rational-choice political economy. The final section looks at the general policy implications of institutional analysis for major social transformations, such as those attempted in Eastern Europe and in the Third World.
THE OLD THEORY OF ECONOMIC POLICY
In a perceptive discussion of the theory of economic policy, Hansen ( 1963) emphasizes the central role of models in policy formulation. As almost all policy aims at influencing economic outcomes or processes, policymakers—politicians, administrators, social scientists, voters, or rulers—must rely on a model, or a description of the economic system, which sometimes is little more than a rough qualitative picture (Hansen, 1963:3). It is argued below that the information assumptions of institutional analysis assume that actors employ incomplete and variable models of their environments when attempting to advance their public or private policies.
A formal model of an economic system, such as a firm, a market, or an economy, can be written in the following general way:
In equation (1), xl, … , xn are n endogenous variables, and a1, … , am are m exogenous variables, lagged variables, or parameters, some of which (for instance, exchange rates, tax rates, base money, price ceilings, import restrictions, plan indicators, or agricultural production quotas) are controlled by the policy actor (Hansen, 1963:5). Note a subtle distinction here in the meaning of exogeny. All the exogenous variables in equation (1) are exogenous to the actors of the social system that the model attempts to describe. The policymakers are distinct from the social system and control some of the exogenous variables, whereas other exogenous variables constrain their actions.
The policy model describes the choices open to policymakers: their opportunities to reach targets (desired values of endogenous variables) by applying instruments (exogenous variables they control). Policy targets (goals) are derived from the preferences of policymakers. The structure of the policy model prescribes what target values are attainable and how they are attained. Policy targets may be absolute, or the policymaker may weigh target variables together in a target preference function, T(x1, … , xn).2Economic policy uses policy instruments either to attain absolute targets or to maximize the target preference function. When targets are fixed (or when target preference functions are maximized without limitations), basic logic suggests two well-known rules of thumb: (1) in general, "the number of instruments should be (at least) equal to the number of targets," and (2) individual instruments should not be assigned to specific targets, but all instruments should be coordinated and directed toward the set of targets (Hansen, 1963:7).
Finally, the structure of the policy model has important implications for policy. It describes the interrelationships among the variables in the model (equation ) and determines whether the model can be divided into autonomous departments. Following Simon (1953), all endogenous variables and instruments in a policy model can be arranged according to causal ordering from the first order to the highest, nth, order. Instruments of the nth order influence targets of the nth order without affecting lower orders of the system. However, the use of first-order instruments has repercussions not only for first-order target variables, but also for endogenous variables at higher levels, possibly throughout the system (Hansen, 1963:18-22).
NEW PERSPECTIVES AND THE OLD THEORY
The Tinbergen (1956) framework continues to be an essential part of our mental apparatus. When prescribing policy, economists think, explicitly or implicitly, in terms of instruments and target preference functions, and the notion of a model intervening between preferences and policy remains relevant. A new outlook in social science, however, has weakened economists' belief in their ability to prescribe economic outcomes and mold economic systems. We turn now to three related issues: (1) the requirements of structural policy, (2) the need to extend the policy model, and (3) the implications of information scarcity.
The Requirements of Structural Policy
The old theory of economic policy distinguished quantitative policy from qualitative or structural policy. Quantitative policy takes as given the basic structure of the economic system (or subsystem), i.e., equation (1), and seeks to manipulate existing economic relationships toward some particular end. Until recently, the findings of mainstream economic theory were relevant primarily for quantitative policy, because the theory made few attempts to endogenize or explain (parts of) the economic system. Structural policy, on the other hand, seeks to change the structure of equation (1), and sometimes to add new variables or new relationships. The (immediate) goal is not to achieve a new value for a target variable in the quantitative policy model, but to create a new relationship between (new) instruments and targets.
The discussion in this chapter emphasizes the distinction between quantitative and structural policy, although, as we shall see, the new emphasis on information and incentives has blurred this distinction. Economists have recognized that over time, what were assumed to be quantitative policy initiatives (e.g., rent control, increases in tax rates, or new welfare benefits) have often altered the structure of equation (1). However, it is useful conceptually to distinguish fundamental system transformations from behavioral responses to changes in relative prices within a given system.
Structural policy obviously invites new quantitative policy (and a new quantitative policy model) because the new system must be managed. Furthermore, if the transition to the target structure is slow, appropriate quantitative policy is required to ensure the orderly operation of the system during the transition period (McKinnon, 1991).
Unlike quantitative policy, structural policy cannot be employed effectively without a theory of institutions and institutional change. Policymakers can conserve their mental energy and use relatively simple models, however, as long as low-order instruments can generate spontaneous adjustments in higher-order variables—i.e., in critical institutions—throughout the system. For instance, policymakers would not require complex policy models to guide
the transition to markets in Russia and Eastern Europe if they believed that appropriate market institutions and organizations will emerge autonomously once "prices are set free" (Murrell, 1995). In the final analysis, the structure of the social system is an empirical question, but as a rule of thumb, policymakers in a world of scarce information usually do well to search for powerful low-order instruments.
The Need to Extend the Policy Model
The old theory, which was concerned primarily with quantitative microand macroeconomic relationships, assumed that the target preference functions of policymakers coincide with the normative standards of economic theory. Traditional policy analysis usually ignored the incentives and behavior of political actors or the influence of political processes on targets for growth, stability, pollution abatement, regulation, or the division of investment funds among sectors. Macroeconomics was concerned with stability and growth, while microeconomics focused on allocative efficiency, assuming that policymakers shared these goals.
In recent decades, various scholars have extended the policy model to incorporate endogenous politicians, and analyses of the latter's policies now appear in the literature. Fields such as public choice, political economy, and political macroeconomics attempt to endogenize the choice of targets and instruments, and to provide the elements for a positive theory of structural change (Mueller, 1989; Alt and Shepsle, 1990; Hettich and Winer, 1993; Alesina, 1991).
Pure quantitative economic policy typically (though not always) leaves the political equilibrium intact, particularly when the policy achieves the intended results. In political equilibrium, those in power tend to agree on traditional normative economic goals, such as stability, growth, and allocative efficiency, within the existing institutional framework.3 Of course, the prevailing institutional framework may leave little or no scope for economic progress. In a relatively stable world, the role of those who control and coordinate key policy instruments is usually well known and clearly established. Generally, there is little doubt about the policy sphere of actors such as the central bank, the finance ministry, the environmental protection agency, or the central planning bureau. Policy analysts have relatively little need for elaborate positive political theory to identify the set of politically sustainable policies.4
Structural policy, on the other hand, is frequently associated with political instability. Substantial structural measures usually alter the distribution of wealth and power and often emerge in times of political upheaval. The choice of new economic structures frequently involves political disputes and struggles that render the control and coordination of policy instruments uncertain, especially over time. To formulate viable economic policy in an unstable environment and minimize the likelihood of policy reversals, the analyst needs to model interactions among economic, political, and social forces. The need to expand the policy model to incorporate this interaction is particularly obvious when policy experts seek strategies for instituting economic measures that (at least in the short run) have tenuous support among the general public, those in power, and those seeking power. Some policy analysts, for instance, recommended shock treatments or big-bang measures in part because strong measures are likely to overwhelm a disillusioned public and unreliable politicians. They are also more likely to create irreversible structural change (Åslund, 1995).5
Implications of Information Scarcity
The last decades of the twentieth century have seen increasingly explicit concern with the role of information in social systems and in social science (Coase, 1960; Diamond and Rothschild, 1989; Hirshleifer and Riley, 1979, 1992; Stiglitz, 1994). The very concept of a social system operating with full information staggers the imagination, yet the impression that early postwar neoclassical economics assumed full information is widespread.
A theory of social systems that explicitly models the information environment of its participants confronts three types of information problems: (1) data are scarce, (2) actors economize on scarce information by formulating simplifying models of their environments (as do scientists), and (3) actors have limited capacity to absorb and process data (learn and make decisions). These three issues can be characterized as incomplete data, incomplete models, and incomplete decisions, respectively. The information revolution that has taken place in the social sciences during the last few decades has focused on problems of incomplete data, although the notion of incomplete models and decisions has received some attention.6 Yet it can be argued that a new theory of economic policy must recognize all three information problems. It must also determine their impact on public policy and the interaction between private and public policy.
The old theory of macroeconomic policy, or rather several scholars in that field, did acknowledge that incomplete data and models can undermine the efforts of policymakers (Hansen, 1963:31-36; Friedman, 1961). In particular, it was argued that various lags of uncertain length can pervert the timing of corrective measures and even turn them into destabilizing impulses.7 In the 1970s, when macroeconomics acquired formal microfoundations, the theory even attempted to incorporate the interplay between public and private policy models. The early rational expectations school assumed that economic actors would be able to absorb the policy models used by the authorities, thereby enabling the actors to second-guess the authorities' intentions and undertake actions that would undermine economic policy. Random policy measures, however, would not produce this effect (Lucas, 1976).8
Similarly, the interactions between public and private policy models in individual markets are implicit in the work of Steven N. S. Cheung, who pioneered the economics of contracts (Cheung, 1969). For instance, in his studies of rent control in Hong Kong, Cheung recognized that public policy models were incomplete in that regulators lacked knowledge of how economic actors would establish a new equilibrium in response to official price ceilings in rental markets (Cheung, 1975, 1976). As rent control constrained the price mechanism, the new equilibrium (and private policy) involved various nonprice margins, including the transformation of residential buildings into unregulated warehouses and (premature) demolition and rebuilding. Cheung's empirical work demonstrates, however, that skillful regulators are often able to use trial and error to acquire knowledge about private models, which they may then use to revise the public policy model, design more effective policy measures, avoid unwanted side effects, and eventually come tolerably close to their policy targets.
INSTITUTIONS, INFORMATION, AND CONTROL
We now turn to a discussion of the general implications of the new economics of institutions for the theory of economic policy.
In its initial phase, as is common for new fields of scholarship, the economics of institutions has emphasized explanation, empirical work, and policy analysis—in that order. Most studies, whether examining institutional change or the economic consequences of alternative institutions, are concerned with
the link between institutions and wealth or the social dividend. Therefore, wealth is frequently the (implicit) policy target in these studies. The distribution of power and wealth usually enters into these works as a determinant of economic outcomes or as an important force propelling institutional change.
Incomplete Data and Control
Information and incentives are the driving forces behind theories of social systems that rely on methodological individualism. Institutions are of critical importance for economic performance because they affect both incentives and the cost of information. The economics of institutions derives the structure of the policy model (our equation ) from the systems underlying institutions or, in other words, from the rules that, in the language of game theory, affect the expected payoffs of the actors.9 Therefore, a change in the formal or informal rules that leaves all payoff equations unaffected does not count as institutional change. Institutions emerge from the fusion of social customs and habits; formal rules and regulations; and various enforcement mechanisms, including internalized social norms. The primary weakness of the economics of institutions is its limited understanding of this amalgam of formal and informal rules and their attendant enforcement mechanisms. Most studies ignore social values, while others treat them either as constants or as exogenous variables.10
In the economics of institutions, the notion of information scarcity usually enters into the analysis through the assumption of incomplete data, but it is the union of incomplete data and what may be called the control problem that gives the new institutionalism its distinctive flavor.11 Simply stated, costly measurement is responsible for incomplete data. Incomplete data raise the cost of verifying quality and monitoring behavior. This draws attention to one of the central complexities of economic life: commodities and behavior usually have multiple valuable dimensions or margins. Rising marginal cost in acquiring data suggests that actors are usually unable to control fully all margins of the resources over which they have nominal control. Therefore, in-
complete control is a general condition, and, as economics first recognized in the case of open-access fisheries, lack of control generates incentives that can lead actors to dissipate wealth (Barzel, 1989).
The control actors exercise over resources can derive from both external and internal sources: institutions, which represent socially assigned control, are external sources; the various measures actors take themselves, such as monitoring, fencing and locking up valuables, and contracting with other actors, are internal sources. In the literature, the costs of establishing and maintaining control over resources both in exchange and in use are commonly known as transaction costs. High transaction costs act as barriers to productive activities. The policy lesson is clear: structural policy that seeks to increase the capacity of an economic system in order to generate wealth must design institutions that lower transaction costs (North, 1990).
An increase in the social dividend has the potential to benefit all members of a social system, but imperfect institutions (imperfect in terms of the wealth criterion) often persist. To explain imperfect institutions, the new institutionalism typically looks to the political domain and uses high transaction costs in the political process to explain why actors are unable to agree on institutions that would be more conducive to economic growth (Bates, 1990; Moe, 1990; Weingast, 1995). The literature also recognizes that many social institutions and structures that facilitate economic growth emerge spontaneously and not through design. The role of shared social values in economic growth is of particular interest (North, 1990). Scholars in the rational choice tradition have had little success in explaining the emergence and evolution of social values, and it is not clear how policymakers could target social values. Consequently, the role of norms and customs in structural policy is ambiguous. A poor society that attempts to create incentives and information environments for economic growth by launching institutional change can hope for rapid success (1) if its underlying social values are consistent with the new institutions of growth, (2) if social values are malleable and adjust quickly to other aspects of the institutional environment, and (3) if the importance of social values in lowering transaction costs has been overrated. We return to these issues in the final section of the chapter.12
Incomplete Models and Incomplete Decisions
In a world of scarce information, those who seek to accomplish structural
change must recognize that they are dealing with incomplete, competing models. Although the theory of economic policy has always been stated in terms of policy models, institutional analysis and the information perspective suggest that additional elements are needed:
When attempting to advance their private goals, the subjects of public policy (economic actors, households) rely on private policy models of the physical world, the social system, and the moral order.
Successful structural policy must allow for interactions between public policy models and private models, and revisions to both in response to new data.
An important aspect of public policy is to provide the subjects of policy—actors whose behavior the policymaker seeks to change—with the information needed to revise their private models. This will assist in coordinating models at different levels.13
When we recognize that revision of models (learning) is often critical for the success of public policy, the revision process itself becomes of great practical interest. Rational-choice social science relies on rules drawn from logic, mathematics, and probability theory, and assumes that social actors use the universal logical rules of science for updating their beliefs or models. Even when this approach treats the origins of private models as exogenous, the assumption that actors use the general rules of science to update their models (for instance, Bayes' rule) implies that the models originate as purely logical or statistical interpretations of available data. In general, the logical approach cannot explain creative and selective interpretation of available data.
For many purposes, however, scholars can use standard logic to explain how actors revise their models and behavior. For instance, in a recent study, Bates and Weingast (1995) investigate revolutionary transformations in Zambia (movement to democracy) and in the former Yugoslavia (eruption of violent communal conflict) in terms of the updating of shared private beliefs (models). Bates and Weingast model interactions among the players as signaling games, where Bayes' rule is used to update models when new data (signals) become available. The paper demonstrates how a policymaker (Milosevic) can bring about a major change in social systems by manipulating signals.
Some scholars question whether actors use standard mathematical logic to update their models. Cognitive psychology and evolutionary biology argue that the human mind relies on ''a large and heterogeneous network of functionally specialized computational devices," rather than functioning as a general-purpose computer (Cosmides and Tooby, 1994:329; Tooby and Cosmides, 1992). A union of evolutionary psychology and economics "might be able to create a science of preferences" (Cosmides and Tooby, 1994:331) and im-
prove our understanding of how actors model their environment, especially the moral order.
In sum, a new theory of structural policy must recognize variable and incomplete models at different levels and allow for interactions between public policy models and private models. In its present state, social science is equipped to do this only on the basis of the general-purpose rational methods of science.
A DIGRESSION ON POLICY DETERMINACY
Rational-choice social science, which assumes that all actors optimize under constraints, implicitly suggests a high degree of policy determinacy. As long as neither social nor political actors were seen as rigorous optimizers, analysts believed there still was considerable scope for reforms. However, when the policy model was expanded to include political and social activity, and optimization under constraints was assumed throughout the social system, the policy choice set seemed to shrink and approach an empty set. This meant that structural policy appeared to have zero degrees of freedom.
The notion of incomplete data, incomplete models, and incomplete decisions changes this picture and expands the policy choice set. The changing fortunes of the Nordic welfare state illustrate this point. Lindbeck (1994, 1995) discusses the ways in which welfare state policies created not only a virtuous circle of benefits, but also an unexpected, undesired, and vicious circle of problems. The problems were associated with delayed changes in the behavior of households, interest groups, public-sector administrators, and politicians. These changes in behavior affected work effort, labor force participation, savings, asset choice, entrepreneurship, and short-term macroeconomic stability, and thereby shrank the tax base of the welfare state.
In analyzing these changes in behavior, Lindbeck recognizes the importance of incomplete data (for instance, delays in obtaining information about new welfare programs), but he puts the greatest weight on what might be called incomplete and variable private policy models. As the welfare system unfolded, the various types of actors, from households to politicians, revised their policy models. Lindbeck (1995) argues that the actors did more than revise their positive models of the social system and adjust their strategies for a new environment; they also revised their models of the moral order and updated their shared social values.
Lindbeck's analysis suggests, therefore, that we need to examine social policies in the Nordic welfare state in terms of incomplete public and private models. At the highest level, public policy models (presumably) did not allow for delayed regime changes in various structural relationships with the system as a whole (for instance, in labor supply or in savings ratios). This policy failure at the top is related to a misreading of private policy models, in particu-
lar a failure to recognize that actors will revise their models, targets, and policies. A revision of private policy models may change not only individual behavior, but also the structure and performance of organizations (households, social networks, firms, public agencies) that are the engine of social action (North, 1990). In Nordic social networks, the interactive revision of private models apparently first lowered the cost (stigma) of being a bona fide welfare recipient, and then the cost of being a welfare chiseler (Lindbeck, 1995).
The notion of policy determinacy, which introduced this section, is an in-house problem in the social sciences and relates to broader ambiguities in the concept of efficiency in the economics of institutions (Furubotn, 1994). A world of incomplete information cannot be determinate: with variable and changing policy models, there is ample scope for new policy directions.
PUBLIC POLICY AND SOCIAL TRANSFORMATIONS
The new institutionalism has paid little attention to the role of policymakers and to the specification of policy instruments for institutional change. With few exceptions, the theory provides only implicit policy lessons.14 The chapter concludes with a few thoughts about these implicit lessons for major structural transformations.
A General Theory?
Institutional analysis emphasizes that the creation of wealth depends in complex ways on institutions, and argues that institutions are rooted in political and social domains. Social science, however, is fragmented into insular disciplines and offers only partial, and often contentious, insights, rather than a reliable, comprehensive view of social systems.15
Furthermore, major advances in social science need not provide policymakers with the means to orchestrate major structural changes. Successful transition requires a strategy that will overcome opposition, particularly when the short-term costs of structural adjustment are high, which they frequently will be. In a world of uncertainty, this is a formidable task (Dewatripont and Roland, 1995). As social science evolves and provides better strategies for institutional change, it is also likely to supply the opponents of change with more sophisticated counter-policies. More knowledge can be a two-edged sword, unless conflict over structural policy involves primarily dispute over the effectiveness of different means to a common end.
Complexity, Learning, and Feedback
The current strength of the new institutionalism (and related fields, such as the new theory of the firm, industrial organization, and positive political economy) lies in partial or sectoral analysis where theory offers various policy insights. The policy implications include (1) methods for containing the control problem and thereby reducing misallocation and the waste of resources, and (2) measures to facilitate the revision of incomplete private and public policy models, thus allowing actors to reach their goals more effectively. The old theory of economic policy explicitly demanded the coordination of a set of policy instruments toward clear-cut goals, but many of the policy insights of institutional analysis are far less specific, particularly concerning the measures needed to restructure actors' information environments.
The literature on property rights, agency theory, asymmetric information, organization, and related topics contains a growing body of theories that examine how to structure control and align incentives with policy goals (Milgrom and Roberts, 1992; McMillan, 1995; Williamson, 1985).
At the macro level, the state contributes to low transaction costs and effective control structures in several ways:
By providing stable standards of measurement in exchange, including stable prices, and generally by creating a solid macroeconomic environment.
By credibly committing to honor ownership rights and avoid using state power to seize resources capriciously, and by following a stable and predictable policy of taxation (Weingast, 1993).
By protecting economic actors from each other through various means, including legal processes, and by facilitating (central) organizations that help establish reputation and detect fraud (Greif et al., 1994).
The extent to which private rules and private enforcement are able to substitute for an effective legal system and provide the necessary foundation for long-term economic growth is an unresolved issue. Recent empirical evidence shows that private actors often invent mechanisms for strengthening
control and lowering transaction costs when they encounter permissive regimes (China) or bureaucratic and inefficient states (Latin America) (McMillan, 1995; Stone et al., 1996). Although these private arrangements often appear to be quite effective, two types of uncertainty surround them: first, private arrangements may create forces that eventually challenge the political status quo, and thus it is uncertain how long permissive or bureaucratic regimes will tolerate unofficial control systems; and second, it is uncertain whether in the long run, private control systems are capable of supporting a modern, integrated national economy.
A final point about the design of control systems concerns the choice between centralization and decentralization. The direct links among measurement costs, incomplete data, and control, combined with the propensity of measurement costs to increase with distance, slant structural policy toward decentralization in structuring both economic organizations and public administration. As a result, concern with the limits of central control is a recurrent theme in the new institutional analysis (Ostrom et al., 1993).
The idea of incomplete and competing models has various implications for policy, although the literature is particularly weak in this area. This outlook weighs against attempts at great experiments or the rapid implementation of structural changes, and suggests modesty, incrementalism, and learning by doing. A new category of instruments emerges in a world of incomplete models: measures for changing the information environment and for creating incentives for actors to revise their models and make them more compatible with policy targets. In a closed society, for instance, policymakers can alter the information environment dramatically by opening the system and facilitating international contacts, such as trade, telecommunications, direct investments, and educational exchanges. Although such measures may have profound implications for structural change, the actual outcome in a dynamic environment is inherently uncertain and generally cannot be modeled in specific terms as a relation between instruments and targets in a Tinbergen policy world.
Various feedback mechanisms are crucial both for coping with incomplete and competing models and for directing outcomes in social processes. Makers of public policy can advance their aims if they are able to design, or facilitate, feedback mechanisms that inform or punish actors who operate with policy models, data, or even goals that are inconsistent with public policy. A properly structured competitive market provides effective feedback in terms of the aggregate wealth criterion. Public policy can push economic enterprises in the direction of more efficiency by fostering various forms of competition and by providing suitable institutions for structuring exit and entry. Empirical evidence from various parts of the world, including China, indicates that not only private firms, but also various hybrid forms of organization will operate relatively efficiently in a competitive environment (McMillan and Naughton, 1996).
The feedback from competition also constrains political units. If the members of agricultural cooperatives operated by local governments can easily exit and join more desirable cooperatives in other localities, poor management is likely to bring corrective feedback and compel local authorities to revise their policy models or targets. Similarly, free entry and exit discipline higher political units, such as the states of a federation, as Weingast (1995) has shown in his work on market-preserving federalism.
Policy Lags and Pathological Path Dependence
With incomplete models, there will be lengthy lags between when a policy is initiated and when relevant actors have the new structures right. During transitions, public and private actors need to experiment for some time once the fundamental incentives are in place before they are able to master the organizations of a modern market economy, including financial organizations, manufacturing firms, apolitical legal systems, and public administration. Few scholars doubted that structural change would involve substantial lags in learning and adjustment, but the institutional literature increasingly refers to far more dramatic lags, which are attributed to increasing returns and path dependence (Arthur, 1994; David, 1994; North, 1990). Several scholars have argued (1) that communities that share specific private policy models (and related informal institutions) resist public policy measures aimed at lowering transaction costs and increasing efficiency, and (2) that these models are extremely durable, enduring sometimes for centuries or even millennia.
In his study of modern reforms in regional administration in Italy, Putnam (1993) explains regional variations in the success of these reforms by variations in social capital and finds the roots of perverse policy models in the twelfth century. For Russia, Hedlund and Sundström (1996:32) trace perverse policy models to the Middle Ages and argue "that the future for Moscow represents a choice between a hierarchy dominated by strong, authoritarian 'organs', or a total breakdown of all organized societal functions."
This strong version of path dependence (which is still controversial) can be compared to the discovery of debilitating genes in specific human groups, and the implications for structural policy are devastating. The new institutionalism does not appear to propose any instruments or measures for manipulating models at this level, which indicates a new type of policy determinacy and calls for more research.
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