Two of the most remarkable stories of growth in the past 3 decades has been the growht of China and India's economies, two countries. Their populations, when added together, make up one-third of the total population of the world. While India and China's development paths have been different, there are many similarities to their approaches. Both countries developed their private sector, deregulated laws, liberalized prices and opened their countries to foreign direct investment (Reddy 3). However, China and India have relied on different economic drivers for growth. China has focused its efforts on manufacturing and exporting goods, while much of India's growth has resulted from services output (Reddy 3). In his discussion of the two countries' economic growth paths, Reddy argues that the real reason China has grown faster than India is because of its high savings and investment rates. (Reddy 3). It is helpful to consider the growth trajectories of both countries over the past 3 decades to see how their experiences can offer lessons to other countries on the brink of growth.
This paper seeks to capture this growth and how it has affected the populations by considering a series of economic growth indicators. In this paper I focus on the growth and development of both countries after 1980, when eonomic reforms started in both countries. I seek to compare each countries' experience and understand the any trends, patterns or important context between the two.
Figure 1. GDP Growth Rate
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
As illustrated in Figure 1, average annual GDP growth rate was higher in China by 4.6 percent during 1980-1990, 3.9 percent in 1990-2003 and 2.6 percent in 2004. China's move towards attracting foreign investment flows into its economy, coupled with a high savings and investment rate contributed to this more explosive growth. Reddy notes that China was more successful in targeting FDI flows as most of it came from Chinese Diaspora related countries based in Hong Kong, Macau, Singapore and Taiwan (Reddy 215). In India, FDI flows were promoted to an extent via export promotion zones (EPZs), but turned out unsuccessful in bringing in FDI and promoting exports. The FDI India received also came largely from transnational corporations (TNCs) (Reddy 216).
In order to highlight a comparison of India and China’s structure of GDP in the years from 1990-2013. Mukhopadhaya, P., Shantakumar, G., & Rao refer to data from OECD Main Economic Indicators: India’s share of agriculture was 22.3 percent of total GDP, share of industry was 26.4 percent, and share of services was 51.2 percent; China’s respective shares are 14.8 percent for agriculture, 52.9 percent for industry, and 32.3 percent for services (Mukhopadhaya, Shantakumar, & Raor 30). Other considerations for differences in economic growth have been partly accounted for by looking at the timing of increased openness and integration with the world economy: while China’s exports of goods and services as a share of GDP have been increasing since 1979, India’s export share began to increase later, beginning in 1990 (Mukhopadhaya, Shantakumar, & Rao 32). Another important difference between the two nations is that in the Indian economy, exports of primary commodities, such as food, metal ore, and petroleum products, continue to account for over one-fifth of total exports; alternatively, China’s share of food and primary commodities has declined to less than 8 percent of total exports (Mukhopadhaya, Shantakumar, & Rao 32).
Figure 2. GDP Per Capita
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
During the past quarter of a century, China has experienced rapid growth in per capita income in both absolute and relative terms. In 1980 when China began its market reforms and entered the global economy, its per capita income was $190. By 2005, it had increased a singificant amount by 2005 to 1, 720. This made it rank 108th in the world. This impressive record of economic growth also reduced income inequality among China’s provinces.(Bosworth & Collins 9). India's growth per capita, while significant, remains lower by an average of 4 percent between the years 1993 - 2004. After 1993, the difference in China and India's labor productivity are explained with reference to much greater contributions from the industrial sector of China. India has grown as a result of resource reallocations as well as tripling of the economic impact to GDP from its growing services sector over this period (Bosworth & Collins 7).
Figure 3. Population Growth
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
Population growth rates in China and India have both fallen over the years 1980 – 2014 and this is reflected in the figure (Figure 3) above. Government policies have been instituted by both countries as development has continued. It is sometimes thought that controlling population growth is one of the keys to raising the growth rate of per-capita GNP. Amartya Sen argues that for countries like India and China, policies surrounding population are actually not likely to make much difference in the rate of per-capita economic growth. (Sen 42). If China's population growth rate double and similar to India's, its growth rate of per-capita GDP (assuming no changing in total GDP growth rate) would only fall from 7.7 percent a year to 7.0 percent. In the same way, if India actually cuts down its growth rate of population to 1.4 per cent a year like China, its growth rate of per-capita GDP would only actually increase from 3.1 to 3.8 percent. Sen argues that the contrast in growth rates of per-capita incomes between India and China is mostly because of China's much quicker rate of growth of total income and the difference in population does not play a very big role if any in the contrast (Sen 42). That said, population control policies can have positive effects on the health and education levels of women of the country. There are good reasons to enforce population control because it can hedge against women burdened by frequent pregnancies and it protects against environmental resource degradation.
Figure 4. Gini Coefficient
Source: World Bank. World Development Indicators 2015.
World Bank Publications, 2015.
Over the past 3 decades, China's rapid and accelerating growth has brought an increase in inequality. In the early 1980s China was seen as one of the more equal countries in the world. It had a Gini coefficient of less than 0.35. By 2000, after more than ten years of very quick growth, China's Gini had increased to approximately 0.42. This level has sustained for the most part through the 2000s, with the coefficient moving from 0.4259 in 2002 to 0.4206 in 2009. Brandt & Rawlski write that 0.42 is considered a mid to high-level of inequality on global comparison rates compared to other countries.(Brandt & Rawlski 44) They also state that this level of inequality is comparable to Mexico and Nigeria (Brandt & Rawksli 44). Figure 4 reflects these movements.
Figure 5. HDI ındex
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
Since it began in 1990, the UN Human Development report has defined human development in terms of a process of widening the choices people have, the most critical being a long life, health, to have education, and to have a decent standard of living (Sen 9). Human development is an important index to consider as it puts people back on the central focus of fundamental concern when considering global economic analysis. There is also the fact that growth in per capita income does not necessarily lead to an improved status of human well being or welfare. The Human Development Index (HDI) is a summary statistic which combines three indices: (1) life expectancy; (2) education index (a standardized index which uses the adult literacy rate and the ratio of primary and secondary enrollments) and(3) income index (adjusted real per capital GDP, weighted for purchasing power parity)(Sen 9).
Interestingly, HDI and education indices diverge but the life expectancy index does not. The results would seem to indicate that life expectancy has had positive impact on output growth, yet change in education was negatively related to output growth. Since the 1980s, the Chinese government has realized the importance of its national education system (which was disrupted during the Cultural Revolution). However, the government has faced many problems in delivering full reforms due to lack of funds, job switching by teachers because of lack of incentives and high dropout rates. (Reddy 93)
Through the 2000s, China has implemented various reforms to increase funding for education. An educational trust and educational development were instituted to support national education development (Sen 46). Teachers' wage reform has been on the agenda and the The Communist Party vowed to eliminate illiteracy by 2000. (Sen 46). Though these measures have improved, the data indicate need for further measures to lower regional disparities.
Why is China's Gini coefficient so high? Dianqing Xu quotes Wang Xiaulu and Fan Gang who argue that the gap in the income distribution for Chinese residents is of three factors, which are also called three gaps: the gap in income between urban and rural people, the income gap between region and then the income gap that exists between all classes in the society (Xu 24). Xu explains that there is a very diverse spread of people across the vast land of China. In fact, the per capita income spreads from 10 to 13 times across one of the 6 regions. These 6 regions are how the Chinese government divid divides the country urban and rural areas across eastern, central and western areas. Stressing that the country is so vast and diverse, Xu argues that this income disparity is natural and that it may not be possible to equalize the income disparity across the country. He argues that regional factors including geography necessitate different adaptations to the land and the way that people must conform while living there. Different regions present different economic opportunities, his argument state. (Xu 26). In discussing the Gini coefficient with reference to India, Mukhopadhaya et. al. state that the Gini coefficient is empirically shown to reveal poverty levels in a reliable way, yet the situation in India is very complicated like China (Mukhopadhaya et. al. 61). There are many regions, both rural and urban. Gini coefficient data typically are taken from household data on monthly expenditures combined with a survey on employment that includes wage and salaries. Interestingly, this coefficient does not take into account self-employed groups. Mukhopadhaya et. al. write that self-employed people tend to make up a big part of the population, particularly in urban areas (Mukhopadhaya et. al. 60). Self-employed often make up a robust middle class in part from their ability to run their own enterprise. In this way, the authors find that there are large parts of the labour force even in India - particularly self employed - not covered, and which put some limitations on how well the Gini coefficient is able to represent the nation's people.
Figure 6. Years of Schooling
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
Mean number of years of schooling for adults in India increased from just over 1
years to nearly 4.5 years in India between 1980 and 2013. In China, the rise was substantial, from 3.7 years to 7.5 years in 2013. Increasing education is important for modernizing a workforce, reducing poverty and reducing inequality. The mean years of schooling for China is comparatively higher than that of India. Yet, in India, the Gini coefficient has remained relatively lower than that of China. This would suggest that China's upper class citizens are receiving the majority of education in the country and the rural residents are left to work low skill factory jobs and support the country's industrial production boom. In India, the education continues to remain low, but inequality is also also lower across the country. This would suggest that a greater percentage of its population may occupy jobs which do not require education and only a very small percentage of its population are those receiving the highest amounts of education in the country, such as ones being trained for engineering roles and other specialties like medicine.
Figure 7. Life Expectancy
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
Life expectancy in China has increased substantially since 1966 for both India and China. In 1966, India's life expectancy was 45 years and China's life expectancy was 51 years. By 1995, India's life expectancy had increased to 60 years of age while China's had increased to 69 years of age. By 2010, China's expectancy reached 76 and India's expectancy reached 66. In 2014, India's expectancy further increased to an average of 68 and China's expectancy remained at 75. Sen writes that the major cause of China's increase in life expectancy jumped before it began its market reforms (Sen 18; Reddy 26). Historically, China maintained a social welfare system financed by enterprises. Basic necessities like public goods such as health care were egalitarian to all residents including poor or other socially disadvantaged people. This took place through communes in rural areas of China and also in urban areas. Equal access to health care was very helpful in letting China reduce its mortality, morbidity and malnutrition. During the reform period, the average life expectancy continued on the upward trend.
Figure 8. Expenditure on Health
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
Health and wellness of a country's people are directly reflected in the level and access of health care services available to its people. Governmental policy can control this by instituting proper health care systems, as well as devising policies and available funding to provision health care across the population. The figure above shows the health care expenditure as a proportion of GDP for both India and China since 1995. The graph reflects an increase starting in 1995, some years after both engaged in post-reform eras. Since 1995, health care expenditure has increased from 3.89 percent to 4.68508833 in India and 3.78 to 5.54 percent in China.
Figure 9. Infant Mortality rate
Source: World Bank. World Development Indicators 2015. World Bank Publications, 2015.
Infant mortality rate indicators are important to consider country progress. The rate is indicative of the health care quality and access in the country, the level of malnutrition, as well as sanitation and infrastructure development. Infant mortality rates increase as development continues. In the figure above, development and growth of India and China is reflected with successes in the area of decreases in infant mortality. From 1980, India had a rate of 114.3 mortalities. By 2000, it had reduced this rate by more than half, and by 2015 this rate was even lower, at 37.9. China's explosive growth reflects a similar experience, with a 1980 starting rate of 46.1 which it had reduced by 2015 to just over 9.
As the world’s two most populous nations, both China and India have long been viewed as imminent economic powers, soon to capitalize on their untapped economic growth potential. The results of the economic growth indicators discussed here reflect the real, tangible concrete gains made by fiscal realignment, and integration in the global economy. While China has more demonstrably begun to reap the benefits of its economic growth, many are optimistic that India, through increasing liberalization and openness of its economy, will catch up and overtake China’s growth in the years to come.
Works Cited
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Brandt, Loren, and Thomas G Rawski. China’s Great Economic Transformation. Cambridge University Press, 2008. Print.
World Bank. World Development Indicators 2015. World Bank Publications, 2015. Print.
Mukhopadhaya, Pundarik, G Shantakumar, and Bhanoji Rao. Economic Growth and Income Inequality in China, India and Singapore: Trends and Policy Implications. Vol. 93. Routledge, 2013. Print.
Reddy, B Sudhakara. Economic Reforms in India and China: Emerging Issues and Challenges. SAGE Publications India, 2008. Print.
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Xu, Dianqing, and Xin Li. Income Disparity in China: Crisis within Economic Miracle. World Scientific, 2014. Print.
