David Corderí Novoa
Universidad de Navarra

Reference: Received 4th December 2004; Published 26th January 2005.  ISSN 1579-1475

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Resumen Las teorías del crecimiento económico intentan explicar las variaciones en las rentas per capita en los países por diferencias en la acumulación de capital y en la productividad. No obstante, muchos investigadores consideran que integrar instituciones en la teoría y la historia económica es un paso esencial para dar una mejor respuesta a por qué algunas sociedades son más ricas que otras. Este artículo desarrolla el caso empírico y teórico de que las diferencias en las instituciones son la causa fundamental de las divergencias en el cambio tecnológico (productividad) y, por tanto, en el crecimiento económico. En primer lugar, daré una definición de instituciones y cómo influyen en el rendimiento económico, desde un punto de vista de la Nueva Economía Institucional. Seguidamente, introduzco el marco teórico basado en la economía de ideas y en los modelos de crecimiento endógeno. Finalmente, argumento que el gasto en I+D (poder para el cambio teconológico) variará en cada país dependiendo de algunas medidas de calidad institucional. Al final, en este artículo se observa que las instituciones más fuertes (medidas por un conjunto de calidad institucional) fomentan un mayor gasto en I+D. A nivel disgregador, el Estado de Derecho está correlacionado positivamente y la carga reguladora está correlacionada negativamente con el gasto en I+D. El nivel de capital humano (medido por las tasas de matriculación en la educación primaria y superior) también tiene un impacto positivo en el gasto en I+D. Abstract Theories of economic growth try to explain variations in per capita income across countries by differences in capital accumulation and productivity. However, many scholars consider that integrating institutions into economic theory and economic history is an essential step in improving explanations of why some societies are richer than others. This paper develops the empirical and theoretical case that differences in institutions are the fundamental cause of differences in technological change (productivity), hence in economic growth. First, I give a definition of institutions and how they influence economic performance, from a New Institutional Economics point of view. Then, I introduce the theoretical framework based on the economics of ideas and endogenous growth models. Finally, I argue that R&D expenditures -a proxy for technological change- will vary across countries depending on some measures of institutional quality. In the end, this paper finds that stronger institutions (measured by an aggregate of institutional quality) encourage greater R&D expenditures. At a disaggregate level, the rule of law is positively correlated and the regulatory burden is negatively correlated with R&D expenditures. Human capital level (measured by the tertiary and primary school enrolment rates) has also a significant positive impact in R&D expenditures.

INTRODUCTION   The crucial question in the field of economic growth and development is: Why is there an enormous cross-country difference in incomes? Or why are some countries richer than others? Many scholars including Adam Smith, David Landes (1998), Douglass North, Robert Thomas and others have emphasized the importance of institutions for economic development and growth. These scholars consider that integrating institutions into economic theory and economic history is an essential step in improving explanations on why some societies are much richer than others. Theories of economic growth try to explain variations in per capita income across countries by differences in capital accumulation and productivity. Though this theoretical tradition has provided considerable insights about the mechanisms of economic growth, it seems unable to provide a "fundamental" explanation for economic growth. Factor accumulation and innovation are only proximate causes of growth. North and Thomas argue that the fundamental explanation of differences in growth is differences in institutions.   From a New Institutional Economics point of view, institutions are "humanly devised constraints that shape human interaction." Institutions are comprised of formal constraints, informal constraints and enforcement of these constraints. Informal constraints represent codes of conduct and culturally transmitted values. Formal constraints can be divided into political institutions, economic institutions and contracts. Political and economic institutions interact in a variety of ways that are the fundamental cause for economic performance. Enforcement implies that there is an incentive for agents to live up to the formal constraints and cooperate. Institutions affect economic performance because they provide the incentives for economic agents to act in a certain way. Institutions reduce transaction costs, counter market failure and help to solve coordination problems in a world of uncertainty.   According to North (1990), "the emphasis on technology made a salutary contribution to the writing of economic history." After four decades of study about the underlying forces of economic growth, the focus has been on productivity growth. Technology provides the possibilities frontier to realizable economic growth. "In a zero transaction cost world, increases in the stock of knowledge and its application (both physical and human capital) provide a key to the potential well-being of human beings in societies." Endogenous growth models argue that a country may be more prosperous than another depending on the resources allocated to innovation. In fact, the properties of ideas determine the possibility of unbounded growth. Ideas are non rivalrous and allow for increasing returns to happen in the production process. Several externalities can make the private return to R&D (producing ideas) differ from the social return. Thus, institutions play a vital role in bringing private and social return together.   This paper argues that R&D expenditures -a proxy for technological change- will vary across countries depending on some measures of institutional quality. After explaining the theoretical foundations, empirical evidence for several countries is assessed. The paper finds that stronger institutions (measured by an aggregate of institutional quality) encourage greater R&D expenditures. At a disaggregate level, the rule of law is positively correlated and the regulatory burden is negatively correlated with R&D expenditures. Human capital level, measured by the tertiary and primary school enrolment rates, has also a significant positive impact in R&D expenditures. PREVIOUS APPROACHES   Theoretical support for the economic impact of institutions has expanded in the last quarter of this century since North and Thomas (1973) first outlined a "transaction cost view of economic history". The crucial role played by institutions which reduce the costs of bargaining, contracting and enforcement, has achieved the status of conventional wisdom not only in economic history [e.g. North (1990), Weingast (1993)] but also in economic development [Borner et al. (1995), Olson (1996) and the World Bank (1997, 2002 and 2003)]. Each of these above authors reach the conclusion that a government´s ability to credibly commit not to interfere with private property rights is the key factor in obtaining the long-term capital investments required for countries to experience economic growth.   A considerable number of recently published papers support the claim that measures about the degree of commitment of governments to private property rights are empirically correlated with international variation in private investment and growth. Mauro (1995) demonstrates that there is a negative association between corruption and economic growth. Similarly, Knack and Keefer (1995) find that different institutional measures, such as quality of bureaucracy, property rights, and political stability of a country have a positive statistically significant relationship with economic performance. Other significant papers on this relationship are those of Clague et al.(1996), Barro (1996), Sala-i-Martí (1997) and Keefer and Knack (1997). Hall and Jones (1998) quantify the growth promoting effects of superior "social infrastructure," Temple and Johnson (1998) introduce the concept of "social capability" accounting for institutions.   Acemoglu, Johnson and Robinson (2004) develop the empirical and theoretical case that differences in economic institutions are the fundamental cause of differences in economic development. They develop the basic outline of a framework for thinking about why economic institutions differ across countries. This framework is a dynamic one, where the main ingredients are: economic institutions, distribution of resources, political institutions, and political power (de jure and de facto). A number of historical examples are provided in order to illustrate their assumptions.   Haufmann, Kraay, and Zoido-Lobatón (1999) develop aggregate indicators for six different aspects of governance such as: voice and accountability, political instability and violence, government effectiveness, regulatory burden, rule of law, and graft. The authors show that all of these measures of institutional quality are significantly associated with income levels in the expected manner. In other words, the higher institutional quality is, the higher the level of income will be for a given country. Their sample is for 200 countries during the years 1996, 1998, 2000, and 2002. These measures of institutional quality constitute a valuable data set for conducting new research projects.   Henisz (2000) points out the difficulty in identifying which objectively measurable political institutions matter and how various measures should be combined. Henisz finds an explicit link between an objective measure of political constraints and variation in cross-national growth rates.   Chong and Calderón (2000) investigate the direction of causality between institutions and economic performance. The authors´ findings suggest that although institutional quality causes economic growth, it also seems to be the case that economic growth causes institutional quality. The authors further conclude that the influence of institutional reforms on economic performance takes more time than the influence of economic growth on institutional quality.   Rodrik (2000) emphasizes the types of economic institutions which allow markets to perform adequately such as: institutions for property rights, institutions for regulation, institutions for macroeconomic stabilization, institutions for social insurance, and institutions for conflict management. The paper stresses that there is no unique mapping between markets and the non-market institutions that underpin them. Thus, there is a trade-off between local knowledge and best practice blueprints when building institutions. Rodrik concludes that participatory democracies enable higher-quality growth, according to a considerable number of evidences. This paper provides meaningful insights about the most important economic institutions which have an impact in growth.   Clarke (2001) assesses the effect of institutional quality on R&D expenditures in developing countries. His paper finds that the risk of expropriation and the rule of law are correlated with R&D expenditures. This result is interesting because R&D might encourage access to technology in developing countries. INSTITUTIONS AND ECONOMIC PERFORMANCE   Institutions are the fundamental explanation for differences in growth according to North and Thomas´ view (1973). North (1990, p.3) offers the following definition: "Institutions are the rules of the game in a society or, more formally, are the humanly devised constraints that shape human interaction". North tries to emphasize the key implications of institutions since, "In consequence they structure incentives in human exchange, whether political, social, or economic." Institutions are the framework within which the interaction of agents takes place. They consist of formal written rules as well as unwritten codes of conduct and conventions (informal rules) that underlie and supplement formal rules. In addition to this, an essential part of the functioning of institutions is the enforcement of these rules, which constitutes the punishment in the case of a violation of a certain rule. As far as the origin of institutions is concerned, two types of institutions, designed and organic, are recognized. Designed institutions originate in artificially created rules such as the Constitution of a country. Organic institutions, however, are the result of a historical process of accumulation of learning by doing given certain factor endowments.   Informal rules comprise codes of conduct, norms of behavior and conventions. These rules are part of culture, which can be defined as a compendium of knowledge, values, beliefs and factors that influence behavior. Furthermore, culture is a type of information which is transmitted from generation to generation within a society. Thus, a crucial aspect of informal rules implies that they are self-imposed codes of conduct founded in a shared belief system that constrain agents´ behavior. Therefore, informal rules play an important role in determining the choice set for individuals, and also in creating a set of expectations about other people´s actions. Thus, it can be said that there are no institutions per se; institutions will exist as long as they provide incentives to agents and agents have beliefs on them. Informal rules have an impact on the willingness of agents to abide by formal rules.   Unwritten traditions and customs have been generally the basis for written laws in an historical perspective. Formal rules comprise political (and judicial) institutions, economic institutions (such as property rights) and contracts. The rules descend from polities to property rights to individual contracts. Contracts are the provisions to a particular agreement in exchange, which are determined by the structure of property rights. For the subsequent type of institutions, I will adopt the dynamic framework used by Acemoglu, Johnson and Robinson (2004), which explains the relation between economic and political institutions. Economic institutions (time t) define property rights and other rules that affect economic performance (t) and the distribution of resources (t+1). Economic institutions are themselves endogenous and determined by political institutions (t) and the distribution of resources (t). Political institutions (t) such as constitutions or electoral rules determine de jure political power (t) and the distribution of resources (t) determine de facto political power (t). Both political powers affect the choice of economic institutions (t) and influence the future evolution of political institutions (t+1).   As far as enforcement is concerned, parties to an exchange must be able to enforce compliance at a cost such that the exchange is worthwhile to them. Contracts are self-enforcing when it pays the parties to respect the agreement, which means that the benefits from not cheating will exceed the costs. Enforcement can come from second-party retaliation, internally enforced codes of conduct or societal sanctions, or a coercive third party (the state). In a world of impersonal exchange, kinship ties, loyalty or reputation are mechanisms to enforce agreements. However, as the number of individuals and exchanges increase there is less information about the compliance of the agreements. Therefore, under such complex contracting scheme, social sanctions have to be accompanied by third-party enforcement, leading to economic punishment of deviations from the contract. North (1990) concludes that "third-party enforcement means the development of the state as a coercive force able to monitor property rights and enforce contracts effectively, but no one at this stage in our knowledge knows how to create such an entity." An effective judicial system can be an example of such an entity.   Let me now turn to the following related questions: why are institutions needed? In which way do institutions affect economic performance? I will explain the possible origins of institutions and their relation to economic activity. Neoclassical Economics has based its theory on the assumption of a frictionless exchange process in which information has no cost to be obtained and property rights are perfectly defined. However, following Coase´s famous work "The Problem of Social Cost" (1960), institutions do matter when there are transaction costs. Economists have explored the problems of cooperation in a game theoretic approach, trying to state the conditions under which institutions can make cooperation possible under a positive transaction cost world. Furthermore, the effectiveness of institutions in reducing transaction costs is related to the determinants of human behavior. According to the behavioral assumption of limited rationality of agents, the incomplete processing of information by agents is an additional cost in exchange. In other words, agents´ subjective perception of the complex reality plays an important role in their choices, which can be costly. Thus, institutions enable bounded rational agents to economize in the information processing mechanism for decision-making.   Transaction costs are relevant due to asymmetric information between agents engaging in exchange. Transaction costs comprise measurement costs and enforcing costs, which are related to a given structure of property rights provided by institutions. As North (1990) points out in his comparative historical analysis of the development process, there is a tradeoff between specialization, economies of scale, and transaction costs. In a small scale economy, transaction costs are low but production costs are high because specialization and division of labor are limited by the extent of the market. In a large-scale complex economy, as the network of interdependence widens, the impersonal exchange process gives scope for opportunistic behavior, thus the cost of transacting can be high. The institutional framework constrains participants, lowering transaction costs and the uncertainty of social interaction (agency problem) through credible commitment. Institutions, in particular economic institutions such as property rights, matter for economic performance because they shape the incentives of actors in society, for example, they influence the organization of production, and the investments in physical and human capital and technology. Credible commitment by institutions will make agents more willing to commit to investment programs in a context of predictable outcomes, because uncertainty about deviation from a certain policy is reduced. Furthermore, economic institutions not only determine the growth potential of an economy, but also other economic outcomes like the distribution of resources in the future (i.e. the distribution of human, physical capital and wealth).   Institutions counter market failure when transaction costs prevent from internalizing technological or non pecuniary externalities. In fact, models of coordination failure try to explain the strategic government interventions that can produce complementarities, such as getting out of low level traps of investment. In his paper Rodrik (1999 and 2000) argues for the role of institutions for social insurance and conflict management. The former arise in market economies where a welfare state is created in order to promote social cohesion and stability. The latter function in societies constituted of different ethnics, conflict management institutions try to reduce the payoffs of uncooperative strategies by giving incentives for social groups to cooperate. INSTITUTIONS AND TECHNOLOGICAL CHANGE   Traditional neoclassical growth models, following Solow (1956), explain differences in income per capita in terms of different paths of factor accumulation. In these models, cross-country differences in factor accumulation are due either to differences in saving rates, or other exogenous parameters such as total factor productivity growth. More recent incarnations of growth theory built around increasing returns (Romer, 1986) and physical and human capital accumulation (Lucas, 1988), endogenize steady-state growth and technical progress. For instance, in the model of Romer (1990), a country may be more prosperous than another if it allocates more resources to innovation. Yet, preferences and properties of the technology for creating "ideas" essentially determine the incentives for innovation. Furthermore, endogenous growth models crucially depend upon the existence of an implicit incentive structure (institutions) that drives the models.   Endogenous growth models, technological progress and the economics of ideas and R&D   In the paper by Hall and Jones (1998) the differences in output per worker between countries are decomposed into three multiplicative elements: physical capital intensity, human capital per worker, and productivity. The empirical evidence suggests us that "differences in physical capital and educational attainment explain only a modest amount of the difference in output per worker across countries." In this sense, differences in productivity are substantial, which directs the attention to the importance of technology in explaining differences in output per worker.   Technology is the procedure through which productive inputs are transformed into output. Simultaneously, ideas can improve the technology of production because a new idea allows a given bundle of inputs (physical capital, labor, natural resources, etc.) to produce more or better output. In fact, technological change is referred to as the implementation of new ideas in production. Endogenous growth models represent the rate of technological change as a function of the stock of knowledge and the percentage of people dedicated to R&D. Moreover, these models argue that the rate of technological change determines the growth potential of an economy.   According to Romer (1986), an inherent characteristic of ideas is that they are nonrivalrous and partially excludable. In fact, an idea just need to be produced only once, then the cost of using it at the same time is insignificant. Thus, the production of ideas implies incurring in an initial fixed cost (which is quite high in many cases) and then a subsequent marginal cost which is almost zero. The fact that there is a high initial fixed cost and a marginal cost of zero implies that ideas have increasing returns to scale.   The nature of ideas is the essential ingredient for increasing returns to scale, once ideas are produced, they can be used at every scale in production. There are two types of models that try to explain the generation of ideas. The models with perfectly competitive markets (Romer 1986, Lucas 1988) consider that ideas are generated as a by-product of the investment in human and physical capital; hence, ideas do not receive any share of the income produced. The second type of models (Romer 1990) considers markets that are subject to imperfect competition. In this case, ideas are generated purposefully because they are rewarded with rents.   Regarding the imperfect competition models of endogenous growth, there are four distortions to the generation of ideas (R&D) that have received attention in either the new growth literature or in the micro theory literature on patent races. Two of the distortions, the "surplus appropriability problem" and the "knowledge spillover effect," tend to promote underinvestment in R&D. The first distortion argues that innovators are not able to appropriate the entire consumer surplus associated with the good that they have created. Hence, the markup of price over marginal cost prevents innovators from getting the entire consumer surplus (monopoly problem). The second distortion states that researchers are not compensated for their contribution toward improving the productivity of future research. This distortion is also known as the "standing on the shoulders" effect.   On the other side, the "stepping on toes effect" and the "creative destruction," tend to promote overinvestment owing to the rise that each distortion provokes on the private return to R&D above the social return. The former distortion is a negative externality of production, also referred to as congestion externality. Multiple researchers run parallel research programs, which duplicates research efforts and reduces the average productivity of R&D in the economy. The latter distortion deals with the Schumpeterian view of innovations. Thus, it is argued that there is a redistribution of rents from past innovators to current innovators through a process of "creative destruction."  Institutions, technology and economic growth   Until this point, I have focused the attention on theories that try to explain differences in the level and growth rate of output per capita across countries. More specifically, endogenous growth theories emphasize the importance of total factor productivity; hence, technology differences are the fundamental explanation for differences in growth rates. However, another question arises: Why do some countries invest more in technology (technology transfer or R&D) than others? The answer to this question can be addressed from the fact that endogenous growth theory crucially depends upon the existence of an implicit incentive structure (institutions) that drives the models. Examples of incentive structures can be property rights (patent systems), market regulations or economic policies such as taxes, subsidies to research, barriers to technology adoption, and human capital policy.   The endogenous growth models of imperfect competition assume that ideas are nonrivalrous, but they are partially excludable. Expected private benefits constitute the incentives for an innovator to produce new ideas. But, private benefits differ from social benefits due to externalities in the production of ideas such as spillover effects or consumer surplus effects. In some cases, many social valuable ideas are not produced because private benefit is much lower than social benefit. Jones and Williams (1999) develop a model that predicts that "the decentralized economy typically underinvests in R&D relative to what is socially optimal." Institutions such as property rights (patents, copyrights, etc.) can be used to solve this coordination failure (market failure). Property rights make the ideas more excludable, bringing together social and private benefits. Thus, the innovator can limit access to her newly invented technology through patents. Thus, the innovator is able to charge a price for her invention, which in turn allows her to generate monopoly profits out of her invention.   Societies tolerate monopolistic inefficiency in intellectual property protection to provide incentives for the creation and distribution of intellectual assets. According to Quah (2002) "markets for intellectual assets protected by IP rights can produce too much or too little innovation." This and other papers suggest that another important factor that influences innovation is competition. Aghion et al. (2002) develop a growth model which predicts that "the relationship between product market competition (PMC) and innovation is an inverted U-shape." Then, it can be argued that regulatory institutions play a fundamental role in providing "the rules of the game" that will promote competition up to an extent. Hence, depending on the degree to which institutions foster competition, they can indirectly encourage innovation.   In addition to regulating competition, institutions determine the business environment in which firms make investment decisions, in this particular case, investments in R&D. The conceptual framework to be used now is similar to the one adopted by Hall and Jones (1998), in which they envision the two factors affecting the decision to invest in R&D. The first factor is the fixed initial cost, which is that of producing the ideas. The second factor is the actual discounted value of the expected profits. If the value of expected profits is higher than the fixed cost, a firm or an individual will invest in R&D.   The value of the fixed initial cost can be associated with several factors but I will focus on three: the degree of perfection of capital markets; the stock of ideas from basic science research; the regulatory burden and the level of corruption. Capital markets determine access to credit, which will also affect a researcher´s ability to finance her project. Financial institutions play an important role not only in providing funds to R&D, but also in setting the interest rate that determines the returns or the cost of the innovative activity.   Basic research is considered a public good in which government invests its budget. The more ideas that have already been produced the more possibilities of producing new ideas. Thus, governments reduce the information costs for new researchers in the sense that researchers can already use publicly available knowledge (standing on the shoulders effect). Furthermore, basic research provides a supply of scientists and engineers that are familiar with research methodologies or that have problem solving skills, which is another spillover effect of public funded research.   Another possible cost may arise from the regulatory burden of a country. By regulatory burden I mean the cost and time it takes for a researcher to get a license, a patent, or even a credit to perform her activity. This burden can be increased by the level of corruption of a country, which can imply paying for bribes in order to get a license to research. If the regulatory burden and the level of corruption of country are high, the cost of producing ideas will increase. Hence, investment in R&D will be lower.   There are various determinants of the actual value of the expected profits. The most relevant determinants are the government, property rights and the size of the market. As discussed before, property rights constitute a crucial incentive for a producer of ideas to engage in research. Actually, institutions like the government are in charge of establishing the legal framework and conducting the appropriate enforcement of property rights. In the case of several firms competing in a market, an innovation may imply having a technological edge over the rivals (creative destruction). As a result, firms are interested in having intellectual property rights enforced properly over their innovations so that competitors can´t copy their innovations.   In general, firms will need a significant amount of time to recover expenditures, since returns to R&D will often be spread over several years. If the institutional environment of a country is unstable, the level of security of property rights will be lower, and the risk from expropriation will be higher. Firms that make use of the patent system take into account the risk of expropriation. Consequently, the higher the risk the higher the uncertainty about future profits, thus lower willingness to engage in R&D. However, there can be several institutional constraints that prevent a government from deviating in its commitments. Hence, institutional constraints enable a government to make credible commitments and lower the perceived risk of expropriation.   The government can influence not only the quantity of investment but also the type of investment in R&D. The government can foster investment in R&D in a particular sector of the economy by providing incentives through policies such as subsidies to research or special fiscal treatment (excessive taxation or reduction in taxes). Moreover, the government can place barriers to technology adoption (or the contrary), which can be a consequence of lobbying pressures and a corrupted government. As a result, low institutional quality implies that corruption exists, governments can violate contracts, there is risk of expropriation and the quality of bureaucracy is low. These factors can make firms diverge into unproductive rent-seeking activities such as lobbying or giving bribes to the government. As a consequence of rent-seeking activities the benefits of investing in R&D and R&D expenditures themselves are reduced.   The government can also influence education and human capital policies. Human capital and the educational ability of the population of a country are likely to affect the technological capability and investment in R&D. Romer (1992) points out that a country´s endowment of human capital might affect R&D expenditures in several ways. First, high levels of human capital might have a comparative advantage in R&D (complementarity effect) because R&D uses highly trained individuals (scientists, engineers) intensively. Second, a large share of R&D activity is performed in university. Therefore, countries that invest heavily in tertiary education might have higher R&D expenditures. The last factor that can have an impact on the benefits from investing in R&D is the size of the market. A small size of the market may imply that the initial fixed cost of producing ideas can not be recovered. However, if the size of the market augments, then the average total cost can be lowered by selling more units, thus making the investment profitable. An example of increasing the size of the market is a country that opens up to international trade, or a country that merely increases its trade volume.   The final point to be made is that causality runs both ways. Technology also affects institutional quality and institutional reform. In fact, economies that are relatively underdeveloped, technologically speaking, tend to have lower quality of institutions. Technology can enhance capability of governments in establishing new rules and conducting the enforcement of these rules by improving the information flows, hence reducing transactions costs and institutional constraints. However, new technology is likely to take several years to influence economic and institutional variables. THE EMPIRICAL EVIDENCE   To examine the relative importance of institutions as a determinant of technological change, a simple econometric framework is adopted. The data in this empirical section are for 64 countries in the year 1998. Therefore, the purpose of this paper is not to assess the impact of institutional change in technological change, but to conduct a cross-country static analysis on the impact of the level of institutional quality in technological change.   The model regresses R&D expenditures (proxy for technological change measured relative to GDP) on several measures of institutions and some economic control variables for a given country. The direction of causality may be a problem; however, R&D expenditures are likely to take several years to influences economic and institutional variables, therefore this might not be a major concern.   The measures of institutions are taken from the six Kaufmann, Kraay, and Zoido-Lobatón measures of institutional development. These measures are defined as follows: (1) voice and accountability- the extent to which citizens can choose their government, political rights and civil liberties; (2) political stability and absence of violence- the likelihood that the government will be overthrown by unconstitutional measures or violent means; (3) government effectiveness- the quality of public service delivery and competence of the civil service; (4) regulatory burden- the relative absence of government controls on the goods markets, the banking system, and international trade; (5) rule of law- the protection of persons and property against violence or theft, independent effective judges, contract enforcement; (6) control of corruption- absence of public power for private gain or corruption.   Institutional quality measures are based on ratings by country experts, businessmen, and other survey results. Given the subjective nature of the underlying polls and surveys, it is possible that respondent´s answers to questions on institutions are influenced by the respondent´s perception of policies. Nevertheless, these subjective measures intend to capture the expectations on a country´s institutional quality. And expectations are the underlying forces that move agents to invest in a particular country. The values of the six institutional measures range from -2.5 to 2.5, with high values meaning better institutional quality. Therefore, higher institutional quality corresponds, a priori, to higher R&D expenditures.   The economic control variables selected for the model are: GDP per capita, primary school enrolment rate, tertiary school enrolment rate, school life expectancy, tax revenue, and trade. See Table 1.   GDP per capita is measured in constant 1995 US$ (PPP). As the World Bank (1998) notes, R&D expenditures in low and middle-income countries tend to be lower than expenditures in industrial countries (in both absolute terms and relative to GDP). A possible justification of the former evidence can be the fact that other explanatory variable, which varies systematically with income, also affects R&D expenditures. In our model, a dummy variable is introduced to account for the effects of income differences in R&D expenditures. The cutoff point is for countries that have an income per capita of $10,000 or lower. A priori, the expected coefficient of this variable is negative.   In order to reflect a country´s endowment of human capital and the educational policy, several measures are used as a proxy. Primary and tertiary school enrolment rates measure the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. School life expectancy is defined as the total number of years of schooling which a child of a certain age can expect to receive in the future. From our theoretical perspective, R&D expenditures may be positively correlated with these measures of human capital.   Tax revenues aim at capturing government size in a country, particularly capturing by how much a government can intervene in the economy. Tax revenue is measured as a percentage of GDP and it comprises compulsory transfers to the central government for public purposes. As discussed previously, a government can have a positive effect (finance basic research) or a negative effect (excessive distortive taxation) in R&D expenditures.   Trade is used as a proxy of the size of the market for an individual that invests in a particular country. Trade is measured as the sum of exports minus imports of goods and services as a share of GDP. The higher the value of this variable the more open a country is. Consequently, the bigger the market the higher the potential profits from investing in R&D. However, openness to trade implies that a country can also receive FDI and technological transfer, decreasing imitation costs and incentives for researchers. Therefore, the sign of the relationship between trade and R&D expenditures is not clear cut.   A considerable number of variables have proved to be correlated among them when assessing the Pearson coefficients in a correlation matrix. The GDP per capita is highly correlated (0.91) with most of the measures of institutional quality. At the same time, several measures of institutional quality are correlated among each other. For example, the rule of law is highly correlated with control of corruption (0.93), government effectiveness (0.91) and political stability (0.82). Therefore, a selection of variables is conducted so that the problem of multicollinearity is avoided.   Regression results   Table 2 shows the results from the regression which takes into account institutional quality measures separately. The results include some of the economic and institutional variables that have associated the highest explanatory coefficient (adjusted R-squared is 0.649). When both rule of law and regulatory burden are included in the regression, both variables are statistically significant at conventional 10%, 5% and 1% levels. The positive coefficient for the rule of law is consistent with the hypothesis that greater protection of property rights is correlated with greater expenditure on R&D. The negative coefficient for the regulatory burden is not entirely consistent with our previous hypothesis. However, it can be argued that the markets for ideas need more government control. As long as private benefits are lower than social benefits, there can exist market failures, thus government action may be needed to encourage R&D expenditures. Voice and accountability is not statistically significant but it increases the explanatory value of the regression.   As far as control variables are concerned, we find that the only statistically significant variables are the primary and tertiary school enrolment rates. Both variables are significant at 1% level. However, the coefficient of tertiary school enrolment rate tends to be more highly significant throughout the empirical analysis. These results are consistent with the hypothesis that human capital is positively correlated with R&D expenditures. Furthermore, it seems to be logical that the tertiary enrolment rate is more significant because tertiary education is associated with the supply of scientists and engineers of an economy.   The dummy variable introduced to control for the difference in R&D expenditures between low and high income countries is not statistically significant (13% level of significance). However, the F-statistic reveals that its point estimate is significantly different from 0, thus the dummy variable explains partially differences in R&D expenditures. The negative coefficient is consistent with the hypothesis about the relation between GDP level and R&D. Nevertheless, there may be other explanatory variables (different from the GDP) that may account for those differences. Low income countries may invest less in R&D due to other omitted factors that differ systematically between high and low income countries.   Table 3 shows the results from the regression that takes into account an aggregate indicator of institutional quality, which is constructed as an equally weighted average of the six measures defined at the beginning. The control variables included have a point estimate statistically different from zero (F-stat 19.41). However, the tertiary enrolment rate is the only control variable that is statistically significant at a 5% level, showing a coefficient consistent with our previous hypothesis on human capital.   The measure of institutional quality is statistically significant at a 5% level. The positive coefficient is in accordance to our hypothesis that countries with weaker institutions tend to have lower R&D expenditures than countries with stronger institutions. This result appears to be quite robust according to different sets of control variables. There is a contradictory finding with the previous model. Regulatory burden appears to have a positive impact in R&D expenditures once taken into the average. A possible explanation is that once government effectiveness is also taken into account, it counterweights the possible negative impact of regulatory burden. The hypothetical negative effect of the absence of government controls can be out weighted by a higher quality of public service delivery to the market for ideas. For instance, high quality public service delivery would be reducing information costs by funding efficient basic research. Table 1: Summary Statistics of Variables (Number of Observations: 64) Note: WDI World Bank. World Development Indicators. World Bank, Washintong DC. UNESCO. UNESCO Statistical Yearbook. Bernan Press, Lanham MD. Table 2: Regression output 1. Note: ***Statistically significant at 1% **Statistically sifnificant at 5% *Statistically sifnificant at 10% Table 3: Regression output 2. Note: ***Statistically significant at 1% **Statistically sifnificant at 5% *Statistically sifnificant at 10% References Acemoglu, D., S. Johnson, and J. Robinson, 2004, Institutions as the fundamental cause of long-run growth. NBER Working Paper 10481. Aghion, P., N. Bloom, R. Blundell, R. Griffith, P. Howitt, 2002, Competition and Innovation: An Inverted U Relationship. Microeconomic Analysis of Fiscal Policy (IFS). Barro, R., 1996, Democracy and growth. Journal of Economic Growth 1, 1-27. Barro, 1997, Determinants of Economic Growth. A Cross Country Empirical Study (MIT Press, Cambridge, MA). Barro and Sala-i-Martin, X., 1995. Economic Growth. (McGraw-Hill, New York). Borner, S., S. Brunetti and B. Weder, 1995, Political Credibility and Economic Development (St. Martin´s Press, New York) Chong A. and Calderón, C., 2000, Causality and feedback between institutional measures and economic growth. Economics and Politics, 12, 1, 69-81. Clague, C., P. Keefer, S. Knack and M. Olson, 1996, Property and contract rights under democracy and dictatorship. Journal of Economic Growth 1, 243-276. Clarke, G., 2001, How the quality of institutions affects technological deepening in developing countries. Development Research Group (World Bank; Washington). Coase, R., 1960, The problem of social cost. Journal of Law and Economics, 3, 1-44. Hall, Robert E., and Charles I. Jones, 1998, Why do some countries produce so much more output per worker than others? Quarterly Journal of Economics, 114, 1, 83-116. Henisz, W., 2000, The institutional environment for economic growth. Economics and Politics, 12, 1, 1-31. Jones, C. I., 1998, Introduction to Economic Growth (W.W. Norton; New York). Jones C.I., and J. Williams, 1999, Too much of a good thing? The economics of investment in R&D. NBER Working Paper 7283. Kaufmann, D., A. Kraay, and P. Zoido-Lobatón, 1999a, Aggregating governance indicators. World Bank Policy Research Working Paper No. 2195 (World Bank; Washington). Kaufmann, D., A. Kraay, and P. Zoido-Lobatón, 1999b, Governance matters, Aggregating governance indicators. World Bank Policy Research Working Paper No. 2196 (World Bank; Washington). Keefer, P and S. Knack, 1997, Why don´t poor countries catch up? A cross-national test of an institutional explanation. Economic Inquiry 35, 590-602. Knack, S. and P. Keefer, 1995, Institutions and economic performance: cross-country tests using alternative institutional measures. Economics and Politics 7, 207-227. Landes, D., 1998, The Wealth and Poverty of Nations: Why Some Are So Rich and Some So Poor. (W.W. Norton; New York) Lucas, R., 1988, On the mechanisms of economic development. Journal of Monetary Economics, 22, 3-42. Macfarlan, M., H. Edison and N. Spatafora, 2003, World Economic Outlook 2003: Growth and Institutions (Chapter 3) (Washington: International Monetary Found). Mauro, P., 1995, Corruption and growth. Quarterly Journal of Economics 110, 681-712. North, D. C., 1990, Institutions, Institutional Change and Economic Performance (W.W. Norton, New York). North, D. C. and R. P. Thomas, 1973, The Rise of the Western World: A New Economic History (Cambridge University Press, Cambridge) Olson, M., 1995, Big bills left on the sidewalk: why some nations are rich and others poor. Journal of Economic Perspectives 10, 3-24. Quah, D., 2002, Matching demand and supply in a weightless economy: Market-driven creativity with and without IPRs. LSE Economics Department (London). Rodrik, D., 1999, Where did all the growth go? External shocks, social conflict, and growth collapses. Journal of Economic Growth, 4, 385-412. Rodrik, D., 2000, Institutions for high quality growth: what they are and how to acquire them. NBER Working Paper 7540. Romer, P., 1992, Two strategies for economic development: using ideas and producing ideas. Proceedings of the World Bank Annual Conference on Development, 62-69. Romer, P., 1990, Endogenous technical change. Journal of Political Economy, 98, 71-102. Romer, P., 1986, Increasing returns and long-run growth. Journal of Political Economy, 94, 1002-1037. Sala-i-Martin, X., 1997, I just ran a million regressions. NBER Working Paper 6252. Smith, A., 1776, (1999) The Wealth of Nations (Two Volumes). (Penguin Classics; London). Solow, Robert, 1956, A contribution to the theory of economic growth. Quarterly Journal of Economics 70. Temple, J. and P. Johnson, 1998, Social capability and economic growth. Quarterly Journal of Economics, 113, 3, 965-90. Weingast, B., 1993, Constitutions as governance structures: the political foundations of secure markets. Journal of Institutional and Theoretical Economics 149, 286-311. World Bank, 1997, World Development Report 1997: The State in a Changing World (Oxford University Press, New York). World Bank, 1998, World Development Report 1998: Knowledge for Development (Oxford University Press, New York). World Bank, 2002, World Development Report 2002: Building Institutions for Markets (Oxford University Press; New York) World Bank, 2003, World Development Report 2003: Sustainable Development in a Dynamic World: Transforming Institutions, Growth, and the Quality of Life (Oxford University Press; New York) About the Author Autor: David Corderí Novoa Dirección: Departamento de Económicas. Universidad de Navarra Correo electrónico: david.corderi@yale.edu

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