The truth about convergence of living standards across the world - Essay Example

?Introduction Convergence issue is very prominent in economic growth literature. There are many theories associated with finding empirical evidences to explain economic growth of a country. In this paper, the proponent tries to integrate pragmatic evidences and various theoretical frameworks that could explain economic growth and productivity. Concerning this, reviewing the academic literature in this issue would make sense. A certain study was able to probe and contribute to the upward spiral number of economic growth literatures by employing other social indicators alternative to per capita income (Hobijn and Franses, 2001; Ciscar and Soria, 2000; Fung, 2009; Welsch and Bonn, 2008). Some of these papers found that the convergence in GDP per capita does not necessarily mean convergence in other social indicators. However, as observed the gap between rich and poor can be examined in real GDP per capita and in living standards. Another study stood in stark contrast with the findings generated by Hobijn and Franses (Neumayer, 2003). In this research, various tests of convergence were employed including regression analysis, the coefficient of variation, kernel density estimates and transition probability matrices. This study contains an argument that convergence should be measured based on the living standards and not in achievement index. Concerning this, the proponent of the study chose to include life expectancy, infant survival, educational enrolment, literacy and telephone and television availability as important aspects of living standards. Neumayer found that there was a strong evidence to support the convergence of the mentioned aspects of living standards. However, based on the investigation initiated by Kenny (2005) it is possible that the quality of life variables may potentially converge even if incomes diverge. For example, Kenny pointed the Indian state of Kerala as an example of state with low income per capita below $300 but the life expectancy in it would reach 72, with infant mortality of 13 per 1000 and 9 percent illiterate. This at some point, if properly analysed, would surpass the prevailing living standard of some well-off countries and states. This therefore suggests that the convergence of other aspects of living standards may not potentially and positively reflect on the per capita incomes to grow faster in poor countries than in rich nations. Based on the above findings, it is imperative to consider that economic convergence remains a very important economic issue for more relevant academic explorations. Regarding this, the proponent of this paper tries to understand up to what extent is the hypothesis that there will eventually be convergence of living standards across the world supported by theoretical and empirical research. Per capita GDP (Gross Domestic Product) In many convergence studies, per capita GDP (Gross Domestic Product) is the common measure of the country’s economic growth. After all, it measures the total output of a country by dividing the GDP with the number of people in it (Todaro and Smith, 2011; Angeles, 2008; Egger et al., 2004; ). Based on this logical approach behind the meaning of per capita GDP, many economists find it useful to use it for comparing relative performance between countries. When one wants to know the level of productivity of a certain country, a rise in per capita GDP could potentially signal economic growth. Therefore, per capita income of poor countries should relatively higher than developed countries in order to realize convergence of living standards. However, this argument is widely debatable because there are also many studies trying to point out that there is continuing divergence of living standards all over the world (Cole and Neumayer, 2003; Portnov and Erell, 2004; Allen, 2012; Ravallion and Jalan, 1996; Morgan, 2009; Rakowski, 1994; Decancq et al., 2009). In the first place, there are also many empirical measures associated with finding the living standards. It turns out that per capita GDP is just one of them. Convergence of per capita GDP between nations would therefore signify that poor countries are relatively catching up with the rich ones. However, various questions arise if this could probably stand alone as ultimate measure of living standards across the world and in every country. Other living standards parameters International index of standards of living is usually constructed in order to compare living standards between countries. Concerning this, social indicators are usually incorporated including economic output that usually would undergo scaling and weighting procedures, in which Dowrick and colleagues (2003) suggested, should include welfare-economic foundations. Thus, they were able to achieve a meaningful comparison of living standards between countries by comparing GDP and life expectancy between 58 countries. However, the result seems not so remarkable in formulating international index of standards of living using these measures, so they proposed it would be better to formulate a utility-consistent index that would incorporate both consumption and life expectancy. Biological standard of living could also be used in order to determine living standards, the very measure used in a study trying to find inequality and living standards under early communism from 1946-1966 in Czechoslovakia (Cvrcek, 2009). Primarily, real wages, age-heaping and anthropometrics were used in order to create historical implications of the evolution of living standards and human capital in China in the 18-20th centuries (Baten et al., 2010). The above are some probable measures used to identify the level of living standards across and within every country. Absolute convergence In understanding economic growth, there is a prevailing idea about poor countries catching up or converging as they tend to grow faster per capita than developed ones. The major justification of this claim is based on the point that diminishing returns particularly to capital in poorer countries are not that strong compared to rich ones. Furthermore, poorer countries have the odds of replicating what rich countries already have started in their respective economies. The summary of idea behind absolute convergence is shown in the next diagram. Absolute convergence illustration Source: Class lecture notes The idea of absolute convergence can be clearly illustrated by the Solow model. This model is usually used to predict that an economy converges to a point of a steady state of growth as it faces technological progress and a certain rate of labour force growth. The Solow growth model has three important source of GDP, which include labour, capital and knowledge. Just like any other neoclassical growth models, the Solow model tries to look at productivity, capital accumulation, population growth and technological progress. Shown below is an illustration of Solow model. Solow model and convergence Source: Class lecture notes In the article written by Islam (2003), the study of Baumol in 1986 found that there was empirical evidence to support absolute convergence between 16 OECD countries as there was confirmation of negative coefficient on the initial income variable in a growth-initial level regression for these nations. Below are illustrations that developing countries try to catch up with developed economies. If economic growth will be observed by region, it was remarkable that from 1992 to 2010, the per capita GDP of developing countries were relatively higher than developed countries. From the definition, there must be existing convergence in this case as the per capita GDP of developing countries tend to catch up with developed economies. Gross domestic product per capita by region, 1992-2010 (Percentage and $) (United Nations Conference on Trade and Development, 2012) As already stated, there could be a remarkable convergence based on the per capita GDP of economies per region from 1992 to 2010. There is significant implication of this as could be clearly observed in the following graph. Based on the acquired data of real gross domestic product at market prices from 2002 to 2011, developing and transition economies tend to have more stable productivity compared to developed economies. One could potentially observe this through the trend during the period of economic recession starting from 2008. As shown, performance and productivity of developing and transition economies based on real gross domestic product at market price were not relatively highly affected by economic crunch as linear trends suggest. This primarily could support the fact that even in hard economic conditions, developing and transition economies could catch up with developed economies and would tend to become stable when there is probable exposure to some associated global economic change. Real gross domestic product at market prices, 2002-2011 (Index numbers, 2002 = 100) (United Nations Conference on Trade and Development, 2012) Convergence in income could mean convergence in living standard. For this reason, convergence studies that are aimed at making inferences of the world income distribution focus on countries in order to either prove or disprove neoclassical growth model (Cole and Neumayer, 2003). Cole and Neumayer reported that the lacking evidence of absolute convergence leads to the idea that global income inequality is deteriorating. However, they wanted to disprove this by making inference of the world income through people’s income. In doing so, they were able to find out that the income of poor people are growing faster than rich people’s income, resulting to the point that global income inequality is improving. In their study, Cole and Neumayer were able to prove the neoclassical growth theory suggesting that poor economies grow faster than rich economies because they are further away from their steady state, which could be determined by finding evidence for convergence in population weighted income levels. Thus, Cole and Neumayer believe that poor people could potentially catch up with rich people even though absolute divergence would mean that poor countries cannot catch up with rich countries. To illustrate further this point, they chose to use data coming from Penn World Tables (PWT) income data and those taken from World Bank with different methodology for computing GDP per capita data in purchasing power parity. They made a remarkable point of excluding China at some specific part of the ?-convergence test because this country covers high population, and then they tested the actual sensitivity level of convergence. Below are the summaries of results from the actual conducted sensitivity level of convergence they initiated (Cole and Neumayer, 2003). The above empirical results prove that the sensitivity of absolute convergence could be highly influenced by population income, rather than country-specific determination of economic convergence. Based on the stated correlation results using ?-convergence test, there is an indication that poorer countries with poor populations grow faster. This should be the case because there is a remarkable suggestion of negative correlation between the initial income level and the subsequent growth rate (Islam, 2003). In this case, the actual income level was determined by each population and not country specific. ?-convergence According to Islam (2003), ?-convergence is required in convergence when it comes to growth rate and income level, following the assumptions of diminishing returns, implying further that a capital-poor country has higher marginal productivity of capital. Thus, assuming that there would be the same savings rates, poorer countries will therefore grow faster based on the definition of absolute convergence. This would therefore imply that with the presence of ?-convergence there would be negative correlation between the initial income level and following growth rate. The above empirical evidence is just one of the elemental proofs of the existence of absolute convergence. However, the problem with ?-convergence test is its inability to determine the economic growth dispersion which can only be observed. Thus, there is also a need to find for empirical evidence associated with global income distribution dynamics (Bussolo et al., 2008). Conditional convergence Conditional convergence is a variant of neoclassical growth model which tries to explicate the idea that a certain economy converges to its own steady state. Furthermore, conditional convergence also shows that convergence is faster the farther an economy to its steady state. However, convergence only takes place if determinants of the steady state could be controlled such as population growth rate, savings per capita, depreciation, capital stock, labour force skills, property rights and more. Below is an illustration of conditional convergence. An illustration of conditional convergence Source: Class lecture notes As shown in the above illustrations, there are three production function curves. The value for ? represents a significant change to the production function curves. This would be the case when there is a specific control on the determinants of the steady state. Based on neoclassical growth theory, differences in technological and behavioural parameters could be linked with economies with varying steady states. For this reason, Cole and Neumayer identify the actual conditional convergence when poor countries grow faster after controlling the differences in parameters. When economists would fail to prove the presence of absolute convergence, they tend to specify the existence of conditional convergence. Based on the conventional convergence of Mankiw et al, it was found that countries with lower income per adult are above their steady-state positions and it was the other way around for countries with higher income (Cho and Graham, 1996). Cho and Graham were trying to discuss the other side of conditional convergence. However, the classical point of view of conditional convergence would suggest that an economy converges to its own steady sate and convergence could be observed at a high level of haste when it is relatively further from its own steady-state value (Todaro and Smith, 2011). This further supports the empirical findings of Mankiw et al. Rodrik (2011) found that there was indeed convergence taking place between developed and developing countries as shown in the following graph of growth trends in developed and developing countries from 1950 to 2008. However, Rodrik pointed out that this convergence could substantially go on if developing countries continue to adapt and adopt technologies, physical and human capital investment which should be constrained by domestic saving, borrow from global financial market, and put a limitation of production to small domestic markets. These are remarkable conditions in order to ensure convergence. Growth trends in developed and developing countries, 1950-2008 Source: Rodrik (2011) Rodrik therefore would want to emphasise the point that a higher per capita growth rate could only be generated out of a lower starting value of per capita income provided that the determinants of the steady state, as stated earlier should be under control. It is at this point that Islam explained that unlike absolute convergence, there are equilibriums in conditional convergence which must vary by the economy, and each of these economies approaches it own but unique equilibrium. Let us look closely on the detail of conditional convergence based on the case of China and Asia’s ‘four tigers’ to prove its probable existence. Perhaps, the best way to look at Rodrik’s idea is to observe the economic foundations in each economy. In the case of China, based on the stated economic foundations below, it seems the country has to relatively improve more of its economic foundations compared to developed economies. India is even excelling in some other aspects, but needs to increase its rank with other important economic foundations. In the table below, Singapore and Hong Kong, two of the Asian’s ‘four tigers’ were excelling, an indication that they have already established relevant economic foundations. Thus, this clearly suggests that even if China or India may be converging, their ability to recover and gain high economic performance will still be influenced by how they establish their economic foundations. Thus, it is clear that converging economies would probably not hold on a top economic productivity if they would not be able to establish a good economic foundation in the first place. Based on the article written by World Bank (2012), it is therefore implied that the following measures or criteria of inequality shown in the following table could substantially define why there must be varying equilibriums in each economy. For this reason, China for instance in order to ensure higher convergence must be able to take control of the determinants of the steady state to satisfy the idea of Rodrik and Islam about conditional convergence as mentioned earlier. World Bank report of economies’ economic foundations Source: World Bank (2012) Since the ‘Asia’s four tigers’ for instance have established substantial economic foundations, so based on the following table, they have generated the fastest growth rate over three decades compared to China. China may be excelling based on per capita GDP, but the said country still needs to go a long way to formulate a better economic foundation to sustain its economic performance. Source: Rodrik (2011) Club convergence There are two essential criteria for an economy to be counted in as member of the convergence club (Foldvari and van Zanden, 2009). To be part of the convergence club, a country should grow faster on average than the technological leader. Second, a country should have achieved at least a certain percentage of the GDP per capita of the technological leader. These are essential requirements that should be integrated in the inference in order to test if a country belongs to a convergence club. Source: Foldvari and van Zanden (2009) Based on the above test, the 16 OECD countries belong to convergence club because of high statistical significance based on the Kolmogorov-Smirnov test. Endogenous growth theories Unlike the mentioned neo-classical growth theories concerning economic convergence, endogenous growth theory postulates that economic growth is usually the result of endogenous forces which can be contributed by human capital, innovation and knowledge (Onyemelukwe, 2005). This theory was created due to certain limitations associated with neo-classical growth theories. Mankiw, Romer and Weil model Mankiw is among the theorists who contributed to the empirics of economic growth. Mankiw together with Romer and Weil augmented Solow’s model with human and physical capital. These theorists found significant aspects of convergence of living standards through augmented Solow model by setting population growth and capital accumulation constant (Mankiw et al., 1992). From the class discussion, we learned that Mankiw’s main point associated with economic convergence and divergence of living standards could be due to the linked variations with the quantities of human and physical capital. This point of view is largely different from Romer’s point of view. Among the theories associated with endogenous growth theory are Romer’s competitive equilibrium model and Lucas’s ‘new classical’ version (Capello and Nijkamp, 2009). Romer’s competitive equilibrium model focuses on idea gaps, productivity differences as an upshot of technology gaps. These according to Romer are main sources of divergent living standards (Capello and Nijkamp, 2009). Based on this concept, poor countries must therefore be suffering from idea gaps then it would imply that technological catch-up would be a good way to help poor nations converge. Nations must therefore not isolate themselves in order to ensure free-flowing of ideas, and so they have to engage in foreign direct investment to expose them further to probable innovations. Below is a diagram showing the probable technology gaps between economies as primarily stated based on the idea of Mankiw, Romer and Weil. Probable economic growth curves associated with technology gap Source: Class notes Lucas and Schumpeterian growth model Lucas’s ‘new classical’ version on the other hand is another theory emphasising policy measures have important impact on the growth rate of the economy by creating savings, new technology, human capital that could lead to divergence economic performance (Capello and Nijkamp, 2009). This substantially would point out why European countries and the US States have become widely converging but diverging in economic performance when compared to other countries. Schumpeterian growth model on the other hand tries to point the idea that the reasons why there are economies that are growing at a substantial haste are due to innovation and entrepreneurial ability. Policies associated with this model are all primarily for creating profit. Based on Schumpeterian model, below are two opposite effects of entry on innovation by incumbent firms. Entry and growth Source: http://www.uni-graz.at/schumpeter.centre/download/aghion2009/schumpeter_graz_lec1_part1.pdf Lewis model The Lewis model is also known as the dual-sector model, emphasising capitalist sector and subsistence sector, and it also involves dual social structure which includes politics, law, society and economy (Mendes and Srighanthan, 2009). Below is an illustration of this economic growth model. Lewis model Source: Economics in Plain English (2012) China is a very special case employing the dual social structure. It is therefore important to find out empirical evidence how this structure influenced China’s actual economic growth. China started with traditional agricultural sector, but as manufacturing sector starts to initiate economic activities in the country, the sleeping giant started to increase its capital growth. This can be elaborated as how the labour capital and marginal output converge. Based on the stated World Bank report earlier, China’s economic foundations need further improvement compared to highly developed and established economies. However, China was getting a higher rank for its economic foundation in enforcing contracts, the key to why it would be desirable to conduct business with this developing economy. Furthermore, with the opportunity to maximise one’s profitability because of cheap labour, capitalist and subsistence sectors could substantially function together for economic growth and productivity. For this reason, it would make sense to observe empirical evidence associated with marginal product and wage of labour. As China develops into advanced economy, the marginal product and wage of labour converge, implying that capitalist sector and subsistence sector have ultimately functioned for China’s economic growth. China’s marginal product and wage of labour Source: Islam and Yokota (2008) Conclusion Considering the above discussion and stated information, there are various ways to understand economic growth and convergence. From the stand point of neo-classical approach, there could be substantial point to believe about the existence of economic convergence. Subsequently, the development of endogenous economic theories in line with economic growth could also pave the way to understand probable reasons associated with economic divergence. These theories are contributing to the expanding knowledge linked up with understanding growth of an economy. To justify this point, it is important to consider that economic growth literature contains a wide area of concerns particularly on the issue of economic convergence. From neo-classical economic growth to endogenous theory, convergence and divergence economic growth have relevant theoretical frameworks that could help prove that the world economies either converge or diverge. For this reason, economists believe and even argue that the world economies may either have increased economic gaps or so. For this reason, it is important to find out the actual empirical evidence that would test the hypothesis concerning world economic convergence or divergence. However, there are some associated challenges and limitations linked with the neo-classical economic model, but it is clear that these are addressed by the endogenous growth theories. These economic theories and models could be backed up with empirical evidences in order to prove their associated perspectives, even if they have corresponding limitations at some point. However, what is clear is the fact that there is associated either proven convergence or divergence when one would employ the economic principles correlated with each of the theoretical frameworks of both economic convergence and divergence theories. Thus, the probable implication of these varying theories, like those discussed in this paper is a probable contribution to the increasing body of knowledge for understanding the prevailing world economy that could be readily described based on various empirical evidence. Therefore, the hypothesis that there will eventually be convergence of living standards across the world supported by theoretical and empirical research is tantamount to continuing quest for actual refinement of modern knowledge about today’s world economy. References Allen, R. C. (2012). Technology and the great divergence: Global economic development since 1820. Explorations in Economic History. 49(1): 1-16. Angeles, L. (2008). GDP per capita or real wages? Making sense of conflicting views on pre-industrial Europe. Explorations in Economic History. 45(2): 147-163. Baten, J., Ma, D., Morgan, S., and Wang, Q. (2010). Evolution of living standards and human capital in China in the 18-20th centuries: Evidences from real wages, age-heaping and anthropometrics. Explorations in Economic History. 47(3): 347-359. Bussolo, M., De Hoyos, R. E., Medvedev, D. (2008). Is the developing world catching up? Global convergence and national rising dispersions. [Online]. Retrieved from: http://elibrary.worldbank.org/content/workingpaper/10.1596/1813-9450-4733 [Accessed: 25 December 2012]. Capello, R., and Nijkamp, P. (2009). Handbook of regional growth and development theories. Cheltenham: Edward Elgar Publishing. Cho, D., and Graham, S. (1996). The other side of conditional convergence. Economics Letters. 50(2): 285-290. Ciscar, J. C., and Soria, A. (2000). Economic convergence and climate policy. Energy Policy. 28(11): 749-761. Cole, M. A., and Neumayer, E. (2003). The pitfalls of convergence analysis: is the income gap really widening? [Online]. Retrieved from: http://eprints.lse.ac.uk/603/1/AppliedEconomicsLetters_10(6).pdf [Accessed: 27 December 2012]. Cvrcek, T. (2009). Inequality and living standards under early communism: Anthropometric evidence from Czechoslovakia. Explorations in Economic History. 46(4): 436-449. Decancq, K., and Decoster, A., and Schokkaert, E. (2009). The evolution of world inequality in well-being. World Development. 37(1): 11-25. Dowrick, S., Dunlop, Y., and Quiggin, J. (2003). Social indicators and comparisons of living standards. Journal of Development Economics. 70(2): 501-529. Economics in Plain English (2012). Models of economic growth and development. [Online]. Retrieved from: http://welkerswikinomics.com/blog/2012/01/30/models-for-economic-growth-ib-economics/ [Accessed: 29 December 2012]. Egger, P., Larch, M., Pfaffermayr, M. (2004). Multilateral trade and investment liberalization: effects on welfare and GDP per capita convergence. Economics Letters. 84(1): 133-140. Foldvari, P. and van Zanden, J. L. (2009). Global income distribution and convergence 1820 – 2003. World Economics. 20(2): 117-148. Fung, M. K. (2009). Financial development and economic growth: convergence or divergence? Journal of International Money and Finance. 28(1): 56-67. Islam, N., and Yokota, K. (2008). Lewis growth model and China’s industrialization. [Online]. Retrieved from: http://file.icsead.or.jp/user03/847_186.pdf [Accessed: 27 December 2012]. Kenny, C. (2005). Why are we worried about income? Nearly everything that matters is converging. World Development. 33(1): 1-19. Hobijn, B., and Franses, P. H. (2001). Are living standards converging? Structural Change and Economic Dynamics. 12(2): 171-200. Islam, N. (2003). What have we learnt from the convergence debate? Journal of Economic Surveys. 17(3): 309-362. Mankiw, N. G., Romer, D., and Weil, D. N. (1992). A contribution to the empirics of economic growth. The Quarterly Journal of Economics. 107(2): 407-437. Mendes, E. P., and Srighanthan, S. (2009). Confronting discrimination and inequality in China: Chinese and Canadian perspectives. Ontario: University of Ottawa Press. Morgan, S. L. (2009). Stature and economic development in South China, 1810-1880. Explorations in Economic History. 46(1): 53-69. Neumayer, E. (2003). Beyond income: convergence in living standards, big time. Structural Change and Economic Dynamics. 14(3): 275-296. Onyemelukwe, C. C. (2005). The science of economic development: The theory of factor proportions. Armonk, NY: M. E. Sharpe. Portnov, B., and Erell, E. (2004). Interregional inequalities in Israel, 1948-1995: divergence or convergence? Socio-Economic Planning Sciences. 38(4): 255-289. Rakowski, C. A. (1994). Convergence and divergence in the informal sector debate: A focus on Latin America, 1984-92. World Development. 22(4): 501-516. Ravallion, M., and Jalan, J. (1996). Growth divergence due to spatial externalities. Economics Letters. 53(2): 227-232. Rodrik, D. (2011). The future of economic convergence. [Online]. Retrieved from: http://www.kansascityfed.org/publicat/sympos/2011/2011.Rodrik.paper.pdf [Accessed: 25 December 2012]. Todaro, M., and Smith, S. (2011). Economic Development. 11th ed. London: Pearson. United Nations Conference on Trade and Development (2012) Gross Domestic Product. [Online]. Retrieved from: http://dgff.unctad.org/chapter2/2.1.html [Accessed: 27 December 2012]. Welsch, H., and Bonn, U. (2008). Economic convergence and life satisfaction in the European Union. The Journal of Socio-Economics. 37(3): 1153-1167. World Bank (2012). Economic report of economies’ foundations. [Online]. Retrieved from: http://www.worldbank.org/ [Accessed: 27 December 2012]. Read More