Within the past half-century, the world has seen unprecedented global economic growth. The global GDP increased by roughly 800 percent from 1950 to 2000 while population grew by less than 300 percent. Much of this increase however pertain to the now developed nations. The important policy question then with respect to economic growth has always been that – why do some nations grow faster than others? What determines the variation in economic performance?
Achieving economic growth is one of the primary objectives of public policy as it is a necessary step towards the broader goal of human development. With economic growth, governments can have the means to deliver much needed social services and redistribute income to achieve equity. Hence, determining the factors that contribute to economic growth is a very important subject of inquiry. This essay aims to review the literature on economic growth and its determinants. The ultimate objective is to draw useful insights for institutional reform and, from the researcher’s perspective, on how to approach the different theoretical and empirical issues that researchers are sure to face in this highly complex field of research.
Theories of Economic Growth
The differences in performance across economies have been explained by the standard economic growth theory as due to variations in physical capital, human capital, and technological progress. This comes from the Solow Growth Model which has been the main theoretical foundation of economic growth analyses since the mid-20th century. In the Solow Growth Model, output is a function of capital, which is measured in unit per worker and the savings rate of an economy is a crucial element that affects the accumulation of capital. The more money saved, the larger amount there is to be used as capital. But capital accumulation alone cannot cause sustained economic growth; there has to be technological progress but where does technological innovation come from?
Unfortunately, the Solow model takes technological progress as exogenous, an idea rejected by several scholars. This led to the development of the Endogenous Growth Theory which takes knowledge as part of a broader concept of capital. In this model, savings and investment can lead to sustained economic growth because they view capital broadly to include “knowledge,” not just plant and equipment that obviously depreciates through time. Knowledge creation in universities for instance has been a key explanatory factor in the unprecedented pace of innovation.
If innovation and knowledge creation is endogenous, what then causes economies to innovate? The emergence of the New Institutional Economics (NIE) through the works of notable scholars like Ronald Coase, Douglas North, Oliver Williamson, and Elinor Ostrom, among others have provided the foundation of many recent economic growth literature that looked not just at the standard factors of production but, more importantly, on the role of institutions. Many of these are involved in explaining the enabling environment for technological innovation and investment. North (1990) argued that the role of institutions is in the establishment of incentive structure conducive to investment. The role of institutions in ensuring security of property rights, for instance, is very important so that economic agents have the incentive to conduct business.
Meanwhile, the realization of the importance of political institutions and processes in economic performance is illustrated by a significant number of theoretical works on political economy within high quality economics journals (Dewan and Shepsle, 2008). Persson, Roland, and Tabellini (2000) for instance, provided micro-foundations by examining public spending in different political regimes. They have contributed in solving the black box of political mechanisms by laying the groundwork when they analysed how alternative regimes affect tax-rate decisions. In a similar tone, the work by Lizzeri and Persico explored variation in electoral system. In particular, they analysed the nature of strategies that candidate-politicians would take in equilibrium under proportional representation (PR) compared to winner-takes-all system.
A related theoretical study that actually tackled the effect of political arrangements on economic variables is that by Austen-Smith (2000) which studied income distribution under two electoral systems. He showed that the pivotal voter differs under these two systems, and this difference implies different tax rates and therefore different income distributions. Moreover, his work is very important for its identification of the so-called political-economic equilibrium. However, there is an issue about whether there exists a causality between regimes and public economics decisions such as taxation. That is, are these policy decisions consequences of the political arrangements or do they merely "hang together" and determined by some underlying unobservable factors?
Another set of scholars have earlier pointed out the role of geography in explaining variations in economic development. Notably, the works of Diamond (1997) and Bloom et al (1998) state that geography helps shape development processes. Physical locations have directly affected societies’ ability to establish key institutions or to develop important attributes like immunity against diseases. Apart from economic policy and governance, various aspects of tropical geography, demography, and public health are vital.
While the effects of human and physical capital accumulation, savings, and technological innovation on economic performance have already gained consensus among scholars as the more immediate determinants of economic growth, the recent debates surround those factors (e.g. geography, institutions, and policies) that determine these immediate determinants. The hunt for these “deep” determinants of economic performance is therefore the main focus of this paper.
Summary of evidences
The argument for geography as a determinant of economic performance is based on the direct and indirect effects of resource endowments, diseases, and other physical limitations like being landlocked or remote, among others, which are determined by geophysical environment. Bloom et al. (1998) pointed out that, at least in the context of Africa, there is a complex interplay among geography, epidemiology, agronomy, economics, and demography that researchers need to carefully examine (p.271). Sachs (2003a) contributed to the empirical literature by using various measures of geography such as malaria risk and share of the national population living within 100km of the coast. He found in all of his estimations that it is not only the quality of institutions but also geography that matter in explaining variations in GNP per capita. His results are robust to both larger and smaller samples of countries (see also Carstensen and Gundlach, 2006). This comes as a critic to the institution-only argument of Acemoglu et al. (2001) and Rodrik et al. (2004). The malaria channel through which geography may directly affect economic performance is also supported in the micro-level analysis by Bleakley (2010, p.34) who found in his study on the US, Brazil, Columbia, and Mexico cases that malaria has a large and direct adverse effect on adult labor productivity.
The importance of geography in economic development can be analysed through its effect on trade as shown in gravity model literature. The gravity model that seeks to explain international trade is one of the most robust empirical ﬁnding in economics (Chaney, 2011). This shows that the bilateral trade between two countries is proportional to their respective sizes, measured by their total GDP, and inversely proportional to the geographic distance between them. In this case, geography is taken not in absolute terms but in relative terms depending on whether a country is situated near its major trading partner or not. The recent literature notes a significant, albeit declining, effect of distance on trade. This decline is said to be due to trade openness (Bleaney and Neaves, 2013). Moreover, spatial distance is seen as an important factor that explain resistance to trade flows even when multilateral and regional integration efforts are promoted (Linders et al. 2011).
The primacy of institutions in explaining economic growth has been argued by Acemoglu, et al. (2001) and Rodrik et al (2004). According to the former, institutions today reflected by expropriation risk instrumented by settler mortality data during the colonial era have large impacts on the present day’s income per capita. The finding is robust to controlling for geographical and cultural variables. This is supported by Rodrik et al. (2004) who found that institutions “trump” other deep determinants of growth like geography and convergence (i.e. integration through trade).
Following the Acemoglu et al work, the literature has been more active than ever before, looking at certain institutional variables like rule of law, democracy, and economic freedom, among others. But before moving on these, an important recent work by Efendic, et al. (2011) provides an aggregative look at the literature through a meta-analysis. They used 200 studies including 40 econometric analyses to determine the empirical impact of the quality of institutions on economic performance. They found a positive and large empirical effect of institutional quality on levels of economic performance. Their investigation also showed no evidence of publication bias.
However, they investigated the sub-sample of analyses on effect of institutional quality on economic growth and found substantive positive publication bias but found no evidence of authentic empirical effect. The key source of variation in their findings therefore is whether the analysis is about output levels or growth. The other sources of differences are model specification and whether or not the study addressed the endogeneity of institutions. The authors specifically noted that the evidence base for the positive effect of institutions on economic performance is “not as robust as it should be.” Analysing economic growth may prove to be more challenging than analysing levels of economic development. The authors note that non-robustness of results in growth studies may be attributed to unrepresentative samples of impermanent growth processes. Meanwhile, economic levels are more reflective of the entire histories of economies even with growth performances that vary through time.
The meta-analysis, though insightful, does not really say which aspects or types of institutions matter for economic performance. Therefore unbundling institutions or institutional quality is the key. Moreover, the use of disaggregated measures has been proposed since studies show that the use of such tend to reduce publication bias.
Perhaps a key subject in debates is whether or not democracy leads to economic progress. However, the evidence on the direct effects of democracy is quite inconclusive. One study shows that it does not tend to positively affect economic growth in general, but it is said to matter in growth of developing countries (Butkiewicz and Yanikkaya (2006). Another study found that democracy reduces economic volatility (Klomp & de Haan, 2009). These results are however found to be sensitive to the methodology and sample.
Using a meta-analysis may provide a more representative answer. Doucouliagos and Ulubasoglu (2008) analysed 84 published works on democracy-economic growth relationship. They found no “accumulated evidence of democracy being detrimental to economic growth” (p.78). Democracy is shown to have a zero direct effect on development based on all countries data but has significant indirect effect on economic growth via several channels. It has positive effects on human capital formation, political instability, inflation and economic freedom. Their study also shows that democracy is correlated with greater government expenditure but less free international trade. If increased government expenditure leads to economic growth, then that could be one channel for which democracy can lead to economic growth. But if it impedes free trade, and if free trade leads to greater consumption and therefore growth, then democracy may indirectly cause less growth. The net effect depends on which effect is larger.
Interestingly, democracy has region-specific effects based on this same meta-analysis. Its impact on economic growth is larger in Latin America and smaller in Asia. One-third of the variation in the results of empirical works can be attributed to differences in research design and econometric model specification and most of the difference are a result of sampling error or research process. The authors conclude that the net effect of democracy in economic growth is non-negative.
An important institutional variable that enjoys a strong evidence is economic freedom. A meta-analysis on studies that looked into the relationship between economic freedom and economic growth was conducted by Doucouliagos and Ulubasoglu (2006). Economic freedom is a pillar of a country’s institutional structure along with political freedom and civil liberties (p. 61). The central elements of economic freedom are freedom of personal choice, freedom of exchange, freedom to compete, and protection of persons and private property (see Gwartney and Lawson, 2003; De Haan, Lundstrom and Sturm, 2006). The analysis included 52 empirical works, 33 of which used the Fraser Institute’s measure of economic freedom. They found solid evidence that economic freedom directly and positively affect economic growth, regardless of the measure, level of aggregation, and sample of countries. They also found an indirect, significant effect, through its positive relationship with physical capital formation. They also found that economic freedom has a larger effect than political freedom.
The importance of institutions that promote market-oriented economic policies is illustrated in a similar critical review of the empirical literature by De Haan, Lundstrom and Sturm (2006). They found that better quality analyses (those which employs sensitivity analysis and sensible model specifications) support the positive relationship between economic growth and economic freedom. They also found evidence that political liberalization enhances economic freedom (p.182). Additionally, if economic freedom is manifested in say financial liberalization policies, the meta-analysis of Bumann et al. (2013) further supports its importance in their robust finding of a positive, albeit weak, effect of financial liberalization on economic growth. Their robust analysis likewise shows that financial liberalization may have more value in countries with less developed systems.
Another active research area is the effect of rule of law. Empirical studies show that rule of law tends to positively affect economic growth. Furthermore, Haggard and Tiede (2010) tried to unbundle the effect of rule of law by including discreet components into growth estimations. They found, however, that measures of both property rights and contract viability were insignificant. This was quite unexpected because the aggregate measure was shown to be significant. They argued several reasons for this result. One is the possible high correlation between the aggregate measure and corruption; hence the aggregate measure may be driven by corruption. Another possible reason is that the measure is simply problematic. The authors also pointed out that the aggregate measure may also capture complementary institutions that collectively lead to economic growth but which cannot be easily observed (p.679).
Such complementarity among institutions and their interaction with other factors are also highlighted in a group of literature that looks at how institutions interplay with human capital to influence economic performance. There is one argument that states human capital shapes institutions, policies, and political outcomes, and in turn contributes to economic progress (Lipset, 1960; Glaeser et al. 2004, Castello- Climent, 2008). In contrary, Acemoglu et al. (2005) found that education, measured in lagged average years of schooling, is insignificant after controlling for country heterogeneity. In fact, they found that education does not have an impact on other political institution variables.
In a more recent work, Dias and Tebaldi (2012) contributed to the debate by proving that human capital and institutions interrelate in providing the foundations for long term economic development. Using dynamic panel data estimation, they found that it is the growth and not levels of physical and human capital which determines long-run economic performance. They argue that the quality of institutions determines an economy’s amount of human capital. Institutions that provide effective human capital markets are crucial in the endogenous process of human capital accumulation. It is through this that institutional quality is related to economic development. More importantly, they found that while structural institutions have a significant positive effect on long-term economic growth, political institutions are not correlated with it.
It is also essential to shed light on the debate about the effect of population growth on economic growth. The meta-regression analysis done by Headey and Hodge (2009) found that growth of adult population has a positive and significant effect on economic growth while the young population growth has a negative effect. Interestingly, the effects of the young population growth tend to outweigh the positive effects of the adult population growth. They found strong evidence that the burden of higher population growth has increased since 1980. They also found, albeit through limited evidence, that when governance quality or rule of law variables and public education expenditure are controlled, the significance of population growth on economic growth increases. This implies that policies that properly enforce property rights tend to enhance the relationship between labour demand and economic growth. There is no strong evidence to say that the adverse effect of population growth on economic growth is more severe for developing countries.
Methodological and Conceptual Issues
Studies that explain the so-called deep determinants of economic growth suffer from various methodological issues. The primary issue is endogeneity whether of institutional variables or human capital. For example, the instrumental variable approach in addressing the endogeneity of institutions employed by seminal work of Acemoglu et al. has been heavily criticized. The criticisms focus on the instrument not meeting the exogeneity criterion. Although the instrument settler mortality during the colonial era is highly correlated with present-day measures of property rights protection, it is also a good instrument for many other institutional variables and indices (Haggard and Tiede, 2010: 678). In fact, its correlation coefficients with these variables are even higher than with the expropriation risk, argued to reflect protection of property rights. Because of this, the instrument may be affecting economic levels not only through security of property rights but also through other components, a violation of the exogeneity requirement. This affects the internal validity of the argument that security of property rights determine variation in economic levels.
The settler mortality data is also criticized for its validity as an instrument for institutions in general because it is shown to be even more highly correlated with the present disease environment (correlation coefficient of 0.67) than with expropriation risk (correlation coefficient is 0.51). Because disease environment is shown to have direct effects on human capital, the evidence shows that the first order effect comes from human and social capital and these shape the productive and institutional capacities of the society. Institutions therefore is argued to have a second-order effect on economic performance (Glaeser et al., 2004:298).
A significant point of debate in studies linking institutions to economic growth concerns conceptualization. Therefore, one critical way to move towards consensus is achieving theoretical or conceptual clarity. In institution-growth studies, the outcomes tend to be highly sensitive to different measures (Arndt and Oman, 2006). This is problematic because of issues of construct validity. Are these studies referring to institutions in the first place? Do they mean the same thing when they talk about institutions? There are several criteria that have been proposed to determine whether a measure reflects the concept of institutions as defined by Douglas North. Glaeser et al. (2004) pointed out that because institutions are defined as constraints or limitations that structure the way humans interact, the measures then should so reflect this. Moreover, institutions have the element of durability or stickiness as institutions change incrementally through time (Glaeser et al. 2004; Kurtz and Schrank, 2007). This is the reason why history has been used to instrument institutions.
It has been argued that many of the traditional measures such as that from ICRG, Kaufmann and Polity IV data, do not meet the “constraint” requirement and that these are in fact “outcomes” that reflect the choices of dictators (Glaeser, et al. 2004). It is noted that the economic success of East Asian countries including China, has been an outcome of “good-for-growth” dictatorship, and not of institutions that constrain them. The traditional measures have exhibited huge amounts of volatility, rather than stickiness, often with regime change or short-term economic changes.
Aside from failing to serve as constraints and being volatile and mean-reverting, evidences show that these measures capture different aspects or dimensions. Regardless of what these measures actually measure, it is important to see high correlations between these to have a sense that they are measuring the same thing. However, it is shown that there are loose correlations across these measures and the correlations are significantly lower among those in developing countries suggesting different institutional “complexes” in these countries (see rule of law example from Haggard and Tiede, 2011: 673; Haggard, McIntyre, and Tiede, 2008).
Another issue pertains to the use of de facto versus de jure measures. De jure measures of institutions are associated to objective measures, the statutory language that reflect salient features of the legal system. Using objective measure of judicial independence, it was found that it positively affects property rights. Others found that it does not affect long-run economic growth.. The critics of objective measures however argue that they do not reflect the actual legal system. Using subjective measures may help capture the interesting gaps between de jure and de facto institutions (Feld & Voigt, 2003; Rios-Figueria & Staton, 2008). Meanwhile, the problem with subjective measures is the risk of bias.
Assessment of the Evidence
The literature explaining economic growth is a vast and very dynamic field of inquiry. Like in many fields, it is plagued by inconsistencies in measures, methods, and research designs. These inconsistencies and variations define the differences in the findings. Outliers and parameter heterogeneity are also posing problems in the analyses. Therefore, meta-analyses, especially those that carefully set out inclusion criteria in the studies to include, are useful because they help pinpoint similarities across diverse works so that one can gain solid evidences.
Notwithstanding the presence of high quality meta-analyses in this field, there remains a lot of questions unanswered. Since these meta-analyses explain economic performance using broad institutional variables, they do not lend much utility in terms of public policy. For instance, although some works have been devoted in unbundling the effects of aggregate indices, they have not been very productive at zeroing in on what factors really matter and under what conditions. Nevertheless, the empirical literature is gradually progressing in terms of unbundling aggregate measure, pinpointing the channels and dimensions that are important, and awareness about the sensitivity of analyses to the measures being used. The literature is also tightly-knit and studies tend to “talk” to one another. Since the works of Acemoglu, et al., scholars have been playing around the same data and instrument, augmenting them if necessary, and analysing their consistency and correlation so that they can come up with more convincing and reliable insights. Such efforts, if continued, will improve the understanding about the nuances in the relationship between economic performance and institutional and social variables.
It is also important to distinguish between economic level and growth analyses. Scholars have noted, for instance, that while country characteristics may be useful in explaining relative income levels, this may not be the case for economic growth because it lacks persistence. Analysing temporary shocks and how these affect long-term economic growth has been rather suggested (see Butkiewicz and Yanikkaya, 2005; Easterly et al. 1993). Indeed, growth accelerations have been found to be predominantly caused by idiosyncratic changes. Contrary to popular belief, rapid growth episodes that took place between 1957 and 1992 in 60 of 110 countries were not accompanied by significant changes in economic policies, political conditions, institutional arrangements, or exogenous shocks.
Moreover, if the explanatory variables used in economic analysis measure outcomes, then there is all the more reason to believe that these determinants and economic performance “hang together” and determined by yet deeper factors that are not yet fully known. Political violence in low-income countries has been found to have negative and significant effect perhaps because they do not have the means to prevent violence in their jurisdictions and this is a function of their inability for intervening and negotiating unlike in richer countries which do have the strategies and resources. What determines these capacities requires extensive analysis.
Suggestions for refining concepts and methods
To move forward towards greater consensus, it is important that scholars work towards developing measures of institutions and its dimensions in a more theoretically grounded manner. The presence of diverse sets of institutional variables with low degree of association reflect the lack of conceptual clarity. The measures of institutions that should be developed must reflect its durable and constraining nature.
Also, to succeed in econometric methods relating to economic growth determinants, researchers must tackle the serious problems posed by endogeneity by using approaches that exploit the full temporal aspects and in determining valid instruments that meet the strict exogeneity criterion. This is crucial because “a weak instrument can be worse than no instrument” (Bound, Jeager, and Baker 1995). If these issues are not addressed, econometric analyses do not have that much use in explaining economic growth.
Because geography proves to be a useful variable, owing to its exogeneity, analyses that set out from this area may provide a better understanding about how development processes unfold. The need for better tools for such an area of study have already been reiterated by Bloom et al (1998). They suggested a human ecology-based approach that would provide a framework for the analysis of economic development and social and political activity within the context of physical environment.
Also, owing to the difficulties of setting up quantitative techniques that address methodological issues, other methods such as comparative institutional analysis or analytic narratives could be useful to elucidate nuanced relationships between economic outcomes and endogenous variables such as institutions and human capital. For instance, one can analyse studies that have worked on exactly the same measure of institution such as objective indicators of judicial independence and see if the results vary across contexts. Historical approaches may also prove fruitful in analysing growth accelerations to see what factors and policy decisions have driven episodes of continued economic growth. Furthermore, analyses on the experience of developing countries that use the traditional measures of institutions must be separated from those of the developed countries’ experiences because of the different “complexes” of institutions between the two groups.
Recommendations for institutional reform
Despite the rich pool of knowledge that the literature lends, answering the question “how to design institutions and policies to achieve economic progress” remains a formidable task. The literature that determines the institutional mechanisms that matter in a given context is still being developed. Nevertheless, there are some broad areas that provide encouraging insights. While the evidence about the impact of broad institutional variables like democracy is not very conclusive in a general sense that of economic freedom proves more promising. Policies that promote freedom in exchange and competition and the protection of persons and private property should therefore be recommended.
Whether economic freedom is more likely to develop within democratic regimes needs more careful examination. One should not overlook, as pointed out in the literature, that the variations in economic performance have been, in non-negligible occasions, largely determined by policy actions often chosen by dictators or regimes. Whether or not the developmental state model will apply in an increasingly globalized world is taken up by Hayashi (2010). He noted that the model that is largely responsible for the success of East Asia remains valid. In particular, the proactive role of the state is important in developing strategies so that countries can be integrated into global markets. However, this does not serve as a basis for the forging of authoritarian regimes. The evidence, which corroborates his view, simply points to the direction that it is the strategic implementation of policies that matters for economic growth and not the type of regime per se.
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