Top PDF Projected Economic Growth in China and India: The Role of Demographic Change

Projected Economic Growth in China and India: The Role of Demographic Change

Projected Economic Growth in China and India: The Role of Demographic Change

Within the next decade, China’s labour force will begin to contract, while that of India will expand faster than its population. A straight-forward consideration of this in a neoclassical model with diminishing factor returns leads to the expectation that the impact of these changes will be lower GDP and higher per capita income growth in China, and the reverse in India, and this general pattern does emerge from the analysis provided above. However, the story is considerably more complex than this. In particular, population structure plays a critical role in determining the relative magnitudes of labour force growth to total population growth and the consequent change in dependency ratios, which in turn impact significantly on per capita GDP growth. Moreover, real wage trends influence skilled emigration from these regions and therefore the skill composition of their labour forces. With increasingly open capital accounts, other things equal, both countries stand to attract more foreign investment the faster their labour forces grow. This complements the positive association between fertility and GDP but the necessity to compensate foreign capital owners detracts from the per capita income result. Finally, faster GDP growth tends to shift the terms of trade adversely, which also detracts from per capita performance. Our integrated model of global demography and economic growth offers some insight into all of these complexities.
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Role of Human Capital and Innovation in Economic Growth: Comparative Study of India and China

Role of Human Capital and Innovation in Economic Growth: Comparative Study of India and China

Abstract: The paper evaluates the role of human capital and innovation in economic growth. Human capital and innovation has become crucial for economic growth in the globalized economy. The study compares human capital, innovation parameters and GDP for India and China. Secondary data is used for the study. Patent and GDP data is considered from 2001 to 2015. It is found that China has focused on education and innovation to support aggressive growth oriented policies. A significant positive correlation was found between patent and GDP in India and China. Patent growth rate showed significant differences between India and China. The demographic profile, political activism, and judicious use of information technology can strengthen the innovation ecosystem and economic growth in India.
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Dynamics of Demographic Structure and Economic Growth in Nigeria

Dynamics of Demographic Structure and Economic Growth in Nigeria

Similarly, by incorporating age structure dynamics into the growth equation and applying it to China‘s provincial-level data, Wei and Hao (2010) examined the economic implications of demographic change in China. They found that demographic structure changes, specifically a decline in fertility rate, have helped fuel the growth of the Chinese economy. The channel through which demographic change affects income growth is primarily through its impact on steady state income levels and it is more evident in provinces where market forces operate. The result also showed a significant feedback effect between demographic behaviours (birth rates, life expectancy and marriage age) and economic growth. Furthermore, Joe, Dash and Agrawal (2015) examined the impact of changing population age structure on performance of the Chinese and Indian economy. They found that unlike China, the slow pace of decline in birth rate had adverse effects on India's savings and growth potential, together with the magnitude and timing of her first demographic dividend. They further argued that high domestic savings and investments in the demographic dividend phase are crucial in neutralizing the adverse effects of population ageing and to foster sustainable growth.
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Age Structure, Demographic Dividend and Growth of India

Age Structure, Demographic Dividend and Growth of India

impact of changes in population age structure on real GDP per capita in Australia. However, rapid increase in the dependency ratio as a result of ageing of the population can adversely affect this advantage of the age structure. [13] examine about the rising working population and the gradual shift of rural workers from agriculture into industry and services in China. They found that sectoral change of working population has a significant positive impact on per capita income growth and aggregate productivity growth as predicted by the Lewisian dual economy model and had negative impact on productivity growth in the industrial and service sectors, per capita income and aggregate productivity growth. [31] stated that developed and developing countries are effected differently by demographic transition. An increase in the share of middle-aged workers positively affect economic growth and an increase in the share of the senior population negatively affect economic growth in case of developed country. Whereas for developing country, economic growth is negatively affected by an increase in the share of young workers. [12] found a positive interaction between fertility, education and economic growth. Moreover, education has relatively fostered economic growth and fertility transition. [32] studied the economic implications of demographic age structure in the context of regional development in China and found significant correlation between economic growth and age structure, as reflected by shifts in both the size and internal demographic composition of the working-age population. Analysing the overall effect of demographic transition on economic growth [7] found positive relation between GDP per capita growth and the growth differential between the working-age population and the total population, and negative relation to child and old-age dependency ratios.
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Age Structure, Demographic Dividend and Growth of India

Age Structure, Demographic Dividend and Growth of India

impact of changes in population age structure on real GDP per capita in Australia. However, rapid increase in the dependency ratio as a result of ageing of the population can adversely affect this advantage of the age structure. [13] examine about the rising working population and the gradual shift of rural workers from agriculture into industry and services in China. They found that sectoral change of working population has a significant positive impact on per capita income growth and aggregate productivity growth as predicted by the Lewisian dual economy model and had negative impact on productivity growth in the industrial and service sectors, per capita income and aggregate productivity growth. [31] stated that developed and developing countries are effected differently by demographic transition. An increase in the share of middle-aged workers positively affect economic growth and an increase in the share of the senior population negatively affect economic growth in case of developed country. Whereas for developing country, economic growth is negatively affected by an increase in the share of young workers. [12] found a positive interaction between fertility, education and economic growth. Moreover, education has relatively fostered economic growth and fertility transition. [32] studied the economic implications of demographic age structure in the context of regional development in China and found significant correlation between economic growth and age structure, as reflected by shifts in both the size and internal demographic composition of the working-age population. Analysing the overall effect of demographic transition on economic growth [7] found positive relation between GDP per capita growth and the growth differential between the working-age population and the total population, and negative relation to child and old-age dependency ratios.
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Economic restructuring and demographic growth: demystifying growth and development in Northern Song China, 960 1127

Economic restructuring and demographic growth: demystifying growth and development in Northern Song China, 960 1127

To conclude, a strong growth in population during the Northern Song Period coincided with significant economic restructuring. The main engine for this economic transformation was the monetary and fiscal policies the state implemented out of desperation of the political centre. In the process, labour, capital and land were channeled to non food sectors where returns were higher. Thus we have a story similar in kind to Arthur Lewis’s dualism. The importance of climate change was secondary. Champa Rice had no significant role to play.
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Growth rate of Motor Vehicles in India - Impact of Demographic and Economic Development

Growth rate of Motor Vehicles in India - Impact of Demographic and Economic Development

There is indication in Table 1 that population growth has not contributed substan- tially to motor vehicle growth rate in India. As seen in Table 1, population growth in the country has been relatively moderate. The population growth fell considerably after 2003-04 and in recent years. According to projected population by Ministry of Home affairs, India population growth rate peaked till 2003, at that time, na- tion population grew at nearly 1.75 % annually. As a result, 10 million people are added to population each year. But after that the population growth fell sharply. The reasons of slow down in population growth are due to lower fertility in the country. The nation’s fertility rate declined to 2.65 in 2009 as compared to 2.91 in 2003 and 6.2 in 1951. This fertility decline often contributed overall socio economic develop- ment and rising cost of child bearing and successful voluntary family planning pro- gramme in recent year due to mass awakening (Chaurasia, 2010).The rate of growth of motor vehicles in recent years is much more than that of growth of population. The populations grow at the rate 1.48% annually during last 10 years while motor vehicles grow at 9.82 %. It suggest that population growth has played a very minor role in India’s motor growth rate. Simple arithmetic supports this assertion. If the population growth was the only factor effecting motor vehicle growth rate between 2000-2009, the motorization rate would be remain constant as population growth rate.
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Economic Change in India

Economic Change in India

India’s demographic outlook is also somewhat different from some other Asian countries. India’s population is expected to grow over the coming decades, while the size of the population of most of its east Asian neighbours is expected to begin to fall at some point. Projections from the United Nations suggest that India will become the most populous country in the world in the next 20 years. Furthermore, India’s long-term economic growth is likely to benefit from a working-age population that is expected to grow until at least the middle of this century, unlike countries such as Japan, South Korea and China (for details see RBA (2010) and Hall and Stone (2010)).
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Demographic Change and Economic Growth in Asia

Demographic Change and Economic Growth in Asia

This re-examination of the role of demographic factors reaffirms and highlights their vital role in explaining economic growth in East Asia. While the nature of growth between 1960 and 1990 and then 1990 to 2005 appears very different, demographic factors remain key in explaining economic growth in East Asia. In the late 1970s, China began its turn toward market mechanism. Japan continued its post-WWII effort and effective government policies assisted in moving the economy through the two oil shocks of the 1970s. The Republic of Korea was quick to adopt new technologies as it began to restructure and rebuild following its war. From 1990 to 2005, however, the East Asian economies have entered a more mature era. Japan suffered a financial/housing crisis that depressed the economy throughout the 1990s. China stepped into a new era of economic growth enjoying close to 10% annual average growth rates.
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ECONOMIC GROWTH OF INDIA AND CHINA

ECONOMIC GROWTH OF INDIA AND CHINA

million people aged over 60 by 2050, by which time the ratio of working- age adults to very aged over 60 will be down to just 1.6 compered with 7.7 in 1975. An expected trebling of people aged over 65 by 2040 will impose an increasing strain on country’s pension and health systems, implying a potentially major constriaint on China’s long term economic growth potential and another source of socio-political tension. Joseph S Nye also observes: ‘Almost alone among developing countries, China is ageing extraordinarily fast. By 2030, China will have more elderly dependants than children. Some Chinese demographers worry that the country will get old before getting rich. Geneshan Wignaraja holds that India’s working age population is expected to grow by an astonishing 136 million over the next 10 years, whereas China will experience a relatively modest addition of 23 million new workers.
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POLLUTION, ENERGY CONSUMPTION AND ECONOMIC GROWTH: EVIDENCE FROM INDIA, CHINA AND BRAZIL

POLLUTION, ENERGY CONSUMPTION AND ECONOMIC GROWTH: EVIDENCE FROM INDIA, CHINA AND BRAZIL

consumption pattern to explain EKC hypothesis. The hypothesis of the Environmental Kuznets Curve (EKC) was brought forth for discussion in the early 1990s and after above mentioned events. Kuznets phrase is used here due to similarity with main hypothesis of Kuznets curve in which the hump shape relationships between income distribution and economic growth are examined. From the first studies about the Environmental Kuznets Curve, we can point to Grossman and Krueger (1992) that by examining 52 cities in 32 countries, they confirmed the hump shape curve whose peak was in the range of $4772 to $5965. Shafik and Bandyopadhyay's (1992) study, which was done for 153 countries from 1961 to 1986, found no evidence to confirm EKC. Holtz- Eakin and Selden's papers (1995), for 108 countries over the period of 1951-1986, and Sengupta (1996), for 16 developed countries and a few developing countries, confirmed EKC hypothesis. Tuker (1995), also with annual data over the period of 1971-1991 and for 108 countries reached the same conclusion. The studies about EKC hypothesis got fast, entering other variables in model to test this hypothesis. For example Cole et al (1997) entered technology, population and trade into the model for 7 areas in the world over the period of 1960- 1992, and reached the hump shape. But Agras and
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Structural Change and Growth in India

Structural Change and Growth in India

This paper examines the link between structural change and growth in India. It constructs indices of structural change, and performs a time series analysis of the data. It finds that 1988 marks a break in the time series of growth and structural change. There is one-way causality from structural change to growth in the period 1988-2007, whereas there is no evidence for this linkage before 1988.

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The role of Intellectual property for SMEs, Innovation and Economic Growth in India

The role of Intellectual property for SMEs, Innovation and Economic Growth in India

Intellectual property is a key anxiety in the quest for growth, development and attractiveness. Progression in knowledge broadly considered is a key driver of economic wealth in the twenty-first century. The ongoing rebellion in material and communication technologies (ICT) has melodramatically summary the costs of creating, processing and conveying knowledge, both nationally and across borders. The pace of invention has accelerated meaningfully. These twin growths, of closer international economic addition and more rapid innovation, create new challenges for IP governments and policymaking. At the same time, both the innovation procedures itself, and the production activities of firms are globalizing fast. This raises experiments in terms of handling, protecting and applying intellectual property rights across borders. Countries with economies in changeover face supplementary challenges to assimilate into the progressively global production networks and to find their own niche in the progressively global value chains. To be effective, they need to assign high importance to developing their own innovative capacities, as well as their aptitude to absorb and familiarize technological innovations from abroad, and to move up the value chain over time. Again, IP commands must a key role to play in this regard.
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The Demographic Transition and the Emergence of Sustained Economic Growth

The Demographic Transition and the Emergence of Sustained Economic Growth

The demographic transitions that swept the world in the course of the last century has been identified as one of the prime forces in the transition from stagnation to growth. It brought about significant reduction in fertility rates and population growth in various regions of the world, enabling economies to convert a larger share of the fruits of factor accumulation and technological progress into growth of income per capita. Various mechanisms have been proposed as possible triggers for the demographic transition, and thus as a catalyst in the transition from stagnation to growth. Empirical evidence, however, suggests that the increasing role of human capital in the production process in the second phase of the Industrial Revolution was the central force behind the demographic transition. Unlike episodes of technological progress in the pre- Industrial Revolution era that failed to generate sustained economic growth, the onset of the demographic transition liberated the gains in productivity from the counterbalancing effects of population growth paving the way for human capital formation and the emergence of the modern state of sustained economic growth.
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Demographic change, human capital and endogenous growth

Demographic change, human capital and endogenous growth

In order to quantify the effects of human capital formation in the aging U.S. society, we develop a large scale OLG-model as an extension of the Auerbach and Kotlikoff (1987 ) model with endogenous labor supply and educational decisions as well as endogenous growth. We work out the differences to standard models without human capital by proposing three differ- ent models with increasing degree of sophistication. We start with a standard model where agents only make consumption-saving decisions and endogenously supply raw labor. In a next step, we allow agents to invest time into human capital formation. Finally, we endoge- nize growth by introducing a Lucas (1988 ) type growth mechanism through intergenerational transmission of human capital. 1 Throughout we address the role played by social security
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The effect of compressed demographic transition and demographic gift on economic growth

The effect of compressed demographic transition and demographic gift on economic growth

There are also many famous economic theoretical papers regarding the birth rate. For example, Easterlin (1966), Becker (1960) and Nerlove et al. (1978) are static studies, and Becker and Barro (1988), Barro and Becker (1989), Lapan and Enders (1990), Benhabib and Nishimura (1989), Becker et al. (1990), Kremer (1993), Galor and Weil (1996), Dahan and Tsiddon (1998) and Qi and Kanaya (2010) are dynamic studies. The determinants of birth rate have been sought in the decline of death rate, emphasizing the quality of children, the increase of the opportunity cost of the women, an increase in the status and education of women, urbanization (movement off the farms), social security systems, religious values, social values, etc. 3 Except for religious values and social values, the decrease factors in birth and death rate are deeply related to the economic development. By this, we consider both birth and death rate as functions of GDP per capita. We analyze the demographic transition with the stage of economic development, specifically with GDP per capita.
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Demographic Change, Human Capital and Endogenous Growth

Demographic Change, Human Capital and Endogenous Growth

The main finding of this paper is that endogenous human capital formation is an important channel to adjust to demographic change. Including endogenous education decisions into the model leads to profoundly different quantitative implications for the evolution of relative factor prices and the resulting welfare consequences than the standard model with only physical capital and raw labor. Welfare consequences from the increase in wages and declines in rates of return can be substantial, in the order of up to 1% in lifetime consumption for newborns in 2005 when contribution rates to the pension system are held constant. We also find that newborn low ability agents experience slightly higher welfare gains than high ability agents. In contrast, households that have already accumulated assets loose from the decline in rates of return. Most importantly, we find that welfare gains are substantially higher in the human capital augmented model relative to the standard model. The overall mass of agents alive in 2005 that benefit from demographic change increases from 11% to almost 40% when we move from the standard model to the human capital augmented models. At the same time, the
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Health, demographic transition and economic growth

Health, demographic transition and economic growth

The key dynamics to take into account is the presence of altruistic transfers and endogenous fertility. When the economy reaches the point in the demographic transition where fertility has declined so much that the only motive for having children is the genetic motive, parents realize that they can no longer save child-rearing resources by switching to capital savings and away from having children as an old age savings mechanism. After this point, an increase in public pensions will reduce the steady state capital stock in line with conventional wisdom. However, while altruistic transfers are still operative, a rise in public pensions increases productivity growth and reduces fertility—and therefore speeds up the process by which a country will go through the demographic transition.
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Economic and Socio-Demographic Effects of Global Climate Change

Economic and Socio-Demographic Effects of Global Climate Change

Today there is not one continent, which would have revealed the consequences of climate change. However, the intensity of natural disasters due to climate change is not the same, and as mentioned above, is largely determined by geographical location. The most affected continent is Asia, which accounts for 38% of all natural hazards. This continent is the leader on the total damage from these phenomena. On the second and third areas are the Americas and Africa, with rates of 26% and 14% respectively (Osipov, 2016). Also important is the analysis of the dynamics of natural phenomena, mostly caused by climate change. According to the Brussels Research Centre on epidemiological disasters (The Center for Research on the Epidemiology of Disasters), which tracks all of the major catastrophes of natural and techno genic character, since the 50s of XX century, the growth rate of natural negative phenomena sharply began to rise. Of the many phenomena for analysis from common databases, selected the following: Floods, storms and typhoons, droughts. In our opinion, based on the analysis of scientific reports of scientists and experts, climatologists and geophysicists, it is the intensity of these phenomena is largely influenced by global climate change (Houghton et al., 2001). And here again it should be noted that in most cases under global climate change in the first place, refers to global warming. In the XX century the average temperature on the surface increased the range of 0.6±0.2°C. And the data of the report of the intergovernmental panel on climate change indicate a temperature increase of 0.85° (The official website of UNPO, 2015) the climate models show different scenarios of climatic processes. However, absolutely all of them are united in one: The increase in emissions of greenhouses gases (carbon dioxide, methane, nitrous oxide, tropospheric ozone and water vapour) will lead to average temperature increase in the medium term. With all the arguments of the skeptics of global climate change (warming), that human activity leads to increased concentrations of the greenhouse gases. So the concentration of carbon dioxide in the atmosphere has increased by 31% and nitrous oxide by 17% and methane 151% (Houghton et al., 2001). And it happened in just 260 years, which accounts for dawn of most technologies, the development of new sources of energy (primarily mineral), the development of the chemical industry. The burning of fuel despite the reduction in forest area due to deforestation is the main factor of growth.
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Structural Change, Economic Growth and Trade: Case for Regional Reallocation of Investment in India.

Structural Change, Economic Growth and Trade: Case for Regional Reallocation of Investment in India.

While India has successfully maintained a healthy annual growth rate of 8% during the last ten years, maintaining this growth in the face of challenges (from supply-side bottlenecks, resulting in inflation) and rolling the economy onto a higher growth path of 9% remains an important objective (Economic Survey 2009-10). Moreover, the disconcerting phenomenon of increasing regional inequality has forced policy makers to push for an inclusive growth path in the country, which enhance economic performance of the laggard states. In a large country like India, the rates of growth across the regions are markedly different. This is true for both the overall income per capita growth as well as sector-specific growth across the states. While the high- income states have typically led the Indian growth story with their high growth rates (given their infrastructure capacity and investment advantage), it is recognized that uneven rapid growth brings in its fore disappointing outcomes in terms of progress against poverty as well as other dimensions of well-being (Chaudhuri and Ravallion 2006).
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