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ЗАРУБЕЖНЫЙ ОПЫТ УПРАВЛЕНИЯ
INNOVATION, POLICY DIFFUSION AND DECISION-MAKING IN A GLOBAL CONTEXT: WHAT THE RUSSIAN FEDERATION CAN LEARN FROM THE UNITED STATES
D. Schultz
Hamline University Department of Political Science St. Paul, Minnesota, United States of America, 55105
Governments and its officials today face increasing pressure to innovate. But often the reforms and policies proposed are formulated under conditions of limited knowledge. This bounded rationality may foster policy innovation, but in many cases public officials instead may seek to learn from other jurisdictions in the formulation of their policy options. This paper examines how governments learn, innovate, and make decisions. Using the United States as an example, this article contends: 1) There is often a significant gap between social science and scientific knowledge and the information governments use in making policy; 2) That in many cases public officials lack the capacity to digest appropriate information when making policy; and 3) That government decision making under the conditions of bounded rationality often produces less innovation and more similarly in terms of policy responses. Overall, the article will generalize from the experience of the United States to indicate the implications for other nation states as they seek to formulate policies and learn from one another in global political-economic system.
Key words: conditions of limited knowledge, innovation policy, government, conditions of bounded rationality, expirience of United States of America.
1. Introduction. Two realities characterize contemporary policy making across the world. The first is that there is increasing pressure to innovate. The second is that policy making takes place in a world of uncertainty. Unfortunately, these twin realities are often in conflict. Be it in the United States, China, the European Union, or the Russian Federation, one repeatedly hears demands from
or to government officials to innovate [9; 20; 30]. Operators of state owned enterprises (SOEs), regional or local government officials, and public administrators are constantly told or tell others that innovation is needed to solving pressing problems. These could be issues regarding the delivery of health care, modernizing industries, or simply determining how to deliver goods and services more cheaply and of better quality [20]. The belief is that spurring innovation, often by unleashing competition, will solve many policy problems.
Yet promoting innovation is not easy. Encouraging people to abandon old ways is often difficult. Respect for tradition, bureaucratic inertia, lack of creativity, corruption, and perhaps simple fear of change often makes innovation difficult. But innovation is often limited by another factor-uncertainty. Uncertainty occurs in the sense of not knowing the consequences of changes, but uncertainty may also be a result of simply not knowing how to innovate. It may be the product of a lack of knowledge or simply of an inability to be able to secure the data necessary to make appropriate choices. Or it may be that uncertainty is about the lack of time or other resources to gather the information needed to make appropriate decisions. For many reasons, policy making reverts not to real innovation but to adoption or adaption of existing ideas. Policy making that takes place under the constraint of limited knowledge and uncertainty does not produce innovation, but instead replication and convergence.
This article uses the context of policy making in the United States to demonstrate a broader trend in across the world. It describes how different countries often emulate policies adopted elsewhere, often forcing a replication or convergence of policy responses. Such a convergence not only discourages genuine innovation but it also often leads to a repetition of policy failures or mistakes that may undermine the ability of actors in specific countries to respond adequately to unique problems that their country faces.
2. The Scientific Policy Model. Policy making is often depicted as a rational-scientific endeavor. But should policy making be a scientific or fact-driven process? Scholars debate this issue. Woodrow Wilson [57] articulates the classic politics-administration dichotomy, seeing in the former a realm of normative values and the latter a world of scientific rationality. There is a hint here that the two should not be joined, at least in the sense that politics is about value production and thus not readily informed by the kind of research done by administrators. There are some who argue more explicitly that policy making should not be guided by social science evidence. Daniel Patrick Moynihan's Maximum Feasible Misunderstanding is the clearest statement on this point where he asserts: "The role of social science lies not in the formulation of social policy, but in the measurement of its results" [39:193]. Moynihan's argument that the policy process should not be driven by social science research is indebted to the fact/value distinction articulated by David Hume [26]. The making of policy is normative; it is about making
value choices about specific issues of concern. These include, for example, decisions about whether taxes are too high or too low, whether employment should increase or not. These are not factual questions that lend themselves to data or empirical resolution for scholars such as Daniel Moynihan. Instead they are preferences or goals that are less the product of evidentiary choice than they reflect political decisions. Conversely, social science evidence is entirely appropriate to use for the purposes of policy evaluation, providing important data for assessment and testing of policies to improve their efficiency or efficacy.
Moynihan's strict separation of policy making from social science evidence is not shared by all. Others reject this divorce, arguing instead that policy making should be social science-driven if the government is to improve its performance and outcomes. Alice Rivlin's Systematic Thinking for Social Action is the classic book on this point, lamenting the ignorance about service delivery and arguing that we ought to use federalism and random innovation to ascertain what policies work [44:86-90]. Other works such as Edward Tufte's Data Analysis for Politics and Policy [54], Martin Rein's Social Science and Public Policy [43], and Charles Lindblom and David Cohen's Usable Knowledge: Social Science and Social Problem Solving [34] reach similar conclusions. For Rein [43:254-260] there is an inextricable connection between how values structure facts and how the latter help us to understand the former. Lindblom and Cohen (1979:16) see professional social inquiry as providing knowledge for social problem solving.
Finally, Tufte [54] demonstrates how empirical knowledge can facilitate policy choices. He rejects a more wooden model that distinguishes facts from values. Such a perspective also undervalues the important role that social science and other evidence can have not just in terms of helping to evaluate policies, but also in their implementation. In fact, classic models of the policy process, such as those offered by Charles O. Jones [27] suggest a feedback loop from policy evaluation and analysis back to the beginning of the formulation stage. What this means is that once policy is made and implemented, it is then evaluated and the results of the evaluation should provide valuable data to policy makers in terms of what works or does not, providing guidance for correcting or improving the law or policy. Thus, the existence of a feedback loop reveals a preference among the policy making scholars and experts for facts to help guide the crafting of laws. We learn by doing and can improve how things work but learning from experience. Another way to state this is simply to assert that laws and legislating should not be done in a vacuum. Parliaments, dumas, and legislative bodies have fact-finding authority and the presumption is that the purpose of gathering information is to facilitate making better policy. Gather facts so that the laws that are written reflect what is actually known and not what is hoped for.
The classic model of policy making is one indebted to economics and science. It is a rational decision making model. Charles Lindblom describes it as a ra-
tional or comprehensive model [32]. It assumes that policy choices are the product of a rational decision making process whereby policy makers let their choices be data-driven. By that, assume that policy makers legislate to address problems such as health care delivery. The policy making process consists of gathering all relevant information, letting that data inform policy choices, and then rank-ordering these choices to find the one that best maximizes desired preferences. Such a policy process also assumes that rational comprehensive change is possible. This type of model, heavily indebted to economics, assumes that policy choices take place within an environment where one has unlimited information and time to act and where there are no costs surrounding the making of choices. Deborah Stone describes this process as one indebted to market logic where it is assumed that rational consumers and sellers are utility maximizers replete with all the information they need to make choices [50]. It is a model assumed to be both Kaldor-Hicks and Pareto efficient [56].
3. Criticism of the Scientific Model. Yet such a model or depiction of this image of the policy process has been criticized on many fronts. Herbert Simon has argued that real decision making takes place under a bounded rationality. This bounded rationality is an environment where policy makers have limited knowledge or time to gather facts. It is a policy environment characterized by limited information. Ronald Coase's famous theorem emphasizes the problem of transaction costs or the idea that the gathering of information along with negotiations bring with them costs [10]. Charles Lindblom also contended that the ability to gain widespread consensus on major policy change is problematic, often instead requiring incremental changes in order to induce agreement [32]. Additionally, large scale change requires too much information, is plagued with too much uncertainty about what could go wrong or about unintended consequences that again incremental or small scale change is preferred.
But in addition to more theoretical criticisms of this model, the reality is that the policy making process is often biased. Using the United States as a model, distortions can result from a biasing of the political agenda. One type of bias is where ideas or policy options are considered. John Kingdon's Agendas, Alternatives, and Public Policies [29] explains why specific policy ideas make it on to the agenda. He argues that one needs to look to policy windows and entrepreneurs where three streams - problem, policy, and politics - converge. Specifically, while many worthy ideas might merit consideration and compete for space on the limited platform for Congress or legislatures to consider, successful policy makers or entrepreneurs benefit from the luck of a specific issue being perceived as a problem, a particular policy being seen as an appropriate to it, and political timing making consideration of the problem and policy salient.
Cobb and Elder [11], like Kingdon, seek to understand why some ideas are thrust on to the policy agenda. They argue that triggering devices are critical to
that occurring. For example, external events, such as wars or new international conflicts can place items on the agenda. The events of 9/11 placed terrorism on the national and local policy agendas, as did the launching of Sputnik back in 1957 place science and math on the education agenda. Triggering devices can also be internal events. For example, the rise of AIDS as a health threat in the 1980s, or domestic abuse in the 1970s as highlighted by the women's movements of that decade, both fit the bill as events changing the policy agenda. Other writers, such as Jones [27] and Pressman and Wildavsky [41] also examine agenda setting and the difficulty of getting ideas into legislative consideration. Hence, not all ideas or issues worthy of consideration make it on to the policy agenda.
Finally, while the policy literature often tries to describe why items make it on to the agenda, Bachrach and Baratz [1] became interested in explaining why some items are kept off it. Their "Two Faces of Power" was a groundbreaking essay describing non-decision making. For Bachrach and Baratz, the ability to put or not put issues on the agenda is a powerful way to influence debate. Moreover, non-decision making is still a form of policy making, especially if done repeatedly and consistently over time, when done as a result of decisions by powerful interests or elites.
In parallel fashion Schattschneider's [45] concept of the mobilization of bias in American politics is also supposed to explain why certain issues of interest to one social economic stratum are given consideration in American politics, whereas others are not. In fact, the entire pluralist school and its critiques offer suggestions on how the bargaining process among interest groups explains what issues appear or disappear from the policy frontier [3; 12; 13; 14; 15; 28; 35; 37; 48; 53; 60].
Finally, several writers have argued that another bias comes from the lack of technical knowledge or sophistication by policy makers. Paul Gary Wyckoffs Policy and Evidence in a Partisan Age [59] highlights the lack of understanding in economics among members in Congress, finding few with any formal training and literacy in this field. He also points out that often what elected officials use as evidence for their ideas are antidotal stories - the least reliable types of evidence there is. Few seem to grasp statistics, regression, or correlations and what they mean. David Schultz in American Politics in the Age of Ignorance similarly argues that policy makers often are part time, lack experience or technical knowledge in many subjects over which they legislate [46]. The result is that they are rushed for time; borrow ideas or policies from other jurisdictions or countries, often without the ability or inclination to assess their viability in a new policy context.
4. Bounded Rationality and Innovation. So if the reality of the policy making process is one of limited knowledge or bounded rationality, what are the consequences of that when it comes to innovation? First, "Innovation [is] an idea per-
ceived as new by an individual" [24:1174]. Innovation is doing something new or different. Yet innovation in the sense of really doing something brand new is rare; instead it often involves the borrowing of ideas from someone else. In the case of policy makers, it is borrowing ideas from one jurisdiction to use in another.
The policy literature seeks to understand or describe how states generate policy or innovate. Here, diffusion is offered as an answer. For Gray [24:1175], diffusion is "[t]he process by which an innovation spreads is called diffusion; it consists of the communication of new idea in a social system over time." Gray and others, such as Shipman and Volden [48] in the context of anti-smoking policies, and Hall [25] with economic development policies, seek to understand how policy ideas are spread across the states. These scholars offer several reasons for diffusion and innovation, ranging anywhere from the federal government imposing new requirements on states that forces them to adopt similar policies to states looking to neighboring or regional jurisdictions for ideas [2; 4]. They do that by looking to one another as a cost or time savings device, or to see who has done something first to gauge the political waters, or out of a fear of failure. Diffusion of ideas, thus, makes rational policy sense as a way to learn from others without necessarily bearing all the costs of innovation. In addition to looking to other states as a source of ideas, the policy literature sees several other entities or actors as important in facilitating diffusion, including policy entrepreneurs [38], career bureaucrats [52], professional associations [23], and think tanks [2].
So innovation may really be a product of diffusion. By that, the lesson from the United States is that there is a pattern where once one state has legislated on an issue often others emulate or copy what was originally done in that state. While copying or borrowing policy ideas is not wrong, it produces potentially several anomalies that impede innovation. First, replicating policy found elsewhere makes sense in a world of bounded rationality. Lacking real time to hold hearings, gather evidence, and rank order policy options, it is often more efficient simply to borrow ideas from someone else. Second, such borrowing may not always be smart or innovative policy making. The policy may not have been successful in the original jurisdiction. Or the policy may have worked there but under conditions so different that they do not well transplant to a new environment. Third, even if the policy was successful in one context, replicating it several times will dilute or diminish its impact, i.e., it increases the supply of something where there is no necessary increase in demand. Finally, borrowing of policy ideas leads to a final characteristic - widespread adoption of ideas across many jurisdictions. In other words, it produces policy convergence or replication whereby the same policy is adopted by many states.
5. Global Implications. So what are the consequences of this trend in the United States for policy making across the world? Marmor, Freeman, and Okma [36] examine how the field of comparative policy studies examines health care reform
across countries. They find that most of the scholarship is superficial and fails to produce good cross-national data that explains the forces of change and innovation. Their basic claim is that at least in the health care policy area, most comparative studies are deficient in explaining change. Capanoa and Howlettb [8] introduced a symposium addressing this question, noting that it is an under-researched topic. Capanoa [7] contends that policy is not well understood because of a theoretical and epistemological gap in the knowledge of researchers. Zohlnhofera [61] argues that policy change is a consequence of bargaining among veto players. Raynera [42] describes policy change as a historical problem where current models describe innovation using linear models. None of these scholars, however, really offer an adequate discussion of innovation that looks at change from the perspective of learning from others.
So why should comparativists interested in public policy, or those in the Russian Federation, care about decisions made at the state level in the United States? The answer is that the patterns of decision making found here may be generaliz-able in several ways. First, the United States is not the only federal republic or federal system in the world. There are many others. In other federal systems around the world similar patterns of replication of failed policies might also take place as one unit of sub-government borrows from another. Second, the experience of the United States might be a microcosm of decision making that occurs in a more global environment. There is evidence that states across the world borrow or adopt policies brought up or in other countries [6; 16; 18; 19; 22; 51]. Think about the reaction of many countries to the global financial crash in 2008. Across the world many countries adopted similar austerity policies or had similar reactions to the banking and financial crisis [5; 55]. This was due in part to the globalization of world economies that opened economic borders, the ascendency of Neo-liberal political-economic policies [40; 47], and the creation of transnational entities such as the WTO, GATT, NAFTA, and EU. These organizations forced domestic economies to align with international norms, thereby producing similar responses to the economic shocks of 2008.
But in addition to economic policies, there is also evidence of policy convergence or replication across a range of issues including health care [17]. Several post-communist countries, including Russia, adopted similar policies when it came to reforming their economies, bureaucracies, or addressing corruption [21; 31]. The similarly of reforms may be driven by the similarity of problems faced, but also because of policy diffusion and borrowing of ideas. Thus, Russia and many countries, while facing demands to innovate, may resort to policy adoption, further complicating and inhibiting their ability to really craft novel responses to problems that they face.
6. Conclusion. As public officials in countries such as the Russian Federation are pressured to innovate, they often may be forced to make policy under
conditions of bounded rationality. This bounded rationality, if the experiences of the United States and elsewhere are applicable, means that innovation will be significantly limited. Instead, one may seen Russian officials opting instead to borrow ideas from other countries, producing a policy convergence. While in some cases policy convergence is good, often it involves replicating mistakes found elsewhere, thereby not only discouraging real innovation but in the process perhaps generating policies that may be ill-suited for the Russian Federation. In order to be able to improve the capacity to innovate Russia thus may need to attend to the underlying forces that make it difficult to promote a more scientific or evidence-based policy making process.
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ИННОВАЦИИ, РАСПРОСТРАНЕНИЕ ПОЛИТИКИ И ПРИНЯТИЕ РЕШЕНИЙ В ГЛОБАЛЬНОМ КОНТЕКСТЕ: ЧТО РОССИЯ МОЖЕТ ПЕРЕНЯТЬ ИЗ ОПЫТА СОЕДИНЕННЫХ ШТАТОВ АМЕРИКИ
Дэвид Шультц
Университет Хэмлин Департамент политических наук Сент Пол, Миннесота, Соединенные Штаты Америки, 55105
В настоящее время правительства и чиновники сталкиваются с более высокими требованиями к инновациям. Но часто реформы и направления политики формируются в условиях ограниченного знания. Такая ограниченная рациональность может способствовать развитию инновационной политики, но вместо названного подхода во многих случаях государственные чиновники стремятся освоить другие области компетенции для формулирования проводимой ими политики. В данном исследовании рассматриваются вопросы, касающиеся того, как правительство изучает, создает инновации и принимает решения. Используя США в качестве примера, в данной статье сделаны выводы о том, что: 1) часто существует значительный разрыв между социальной наукой и научным знанием и информацией, которую правительство использует при принятии государственных решений; 2) во многих случаях государственные должностные лица не имеют возможности использовать и анализировать соответствующую информацию при проведении государственной политики; 3) правительство принимает решения в условиях ограниченной рациональности, зачастую осуществляет меньше инноваций и чаще использует «готовые решения» при осуществлении политики. В статье обобщен опыт Соединенных Штатов Америки, чтобы указать на последствия для других государств при формулировании собственной политики с учетом обмена опытом в условиях глобальной политико-экономической системы.
Ключевые слова: условия ограниченных знаний, инновационная политика, правительство, условия ограниченной рациональности, опыт Соединенных Штатов Америки.
