تاثیر پیری جمعیت بر نابرابری درآمد در کشورهای در حال توسعه : شواهد از مناطق روستایی چین
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7383||2011||10 صفحه PDF||سفارش دهید||8010 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : China Economic Review, Volume 22, Issue 1, March 2011, Pages 98–107
Population aging is an emerging issue in developing countries. In this paper, we argue that it is largely responsible for the sharp increase in income inequality in rural China at the beginning of this decade. As a result of the one-child policy implemented in 1979, fewer young adults have reached working age during this period. This leads to a fall in the ratio of household members in working age. Regression-based inequality decomposition shows that labor shortages and the expansion of industrialization significantly increases the return of a higher ratio of household members in working age to household income while the distribution of this ratio becomes increasingly unequal. The interaction of two effects significantly increased income inequality in rural China.
Income inequality in the development context has been a subject of long-standing interest among economists. Since Kuznets's (1955) seminal paper, numerous studies have examined the relationship between inequality and a number of processes associated with development. These processes include industrialization, factor-specific technical change, the development and prevalence of education systems, participation of women in the labor force and population aging. The experience of developed countries shows that those processes did not appear simultaneously and occurred across a very large time span. The process of population aging began unfolding only at the end of the 20th century. Compared to other processes, the effects of population aging on income inequality have received little attention. Existing studies on the relationship between population aging and income inequality have mainly explored this relationship in the context of developed countries, and many of them found that population aging accounts for only a minor fraction of the overall increase of income inequality (e.g., Barrett et al., 2000, Bishop et al., 1997 and Jantti, 1997). Although economically less developed countries have been slow to recognize population aging as a major public policy concern, their older population groups are growing more rapidly than those of industrialized nations as a result of rapid declines in fertility and the broad diffusion of medical knowledge. In 1975, the majority of the world's population aged over 65 resided in developed countries. However, in 2000, more than 59% of persons aged over 65 lived in developing countries. In the near future the distribution of the world's elderly will continue to shift considerably. A United Nations (UN) projection estimates that by 2020, 67% of persons aged over 65 will live in developing countries. In 2000, all developing countries except some Eastern European countries had elderly populations that were less than 7% of their total populations, which is the definition of an “aging population” by the UN. However, by 2020, the elderly population of China, India, Asia (excluding South–Central Asia), Latin America and the Caribbean will increase to 11.5%, 7.3%, 10.5% and 8.3% of their total populations respectively (Shrestha, 2000). The socio-economic and industry structures are significantly different between developed and developing countries, thus the impact of population aging on income inequality in a developing country may be significantly different to that in a developed country. The reduction of income inequality is an important policy objective for the Chinese government over the next few years. The national campaign of “western development” and the government's commitment to “building a harmonious society” exemplifies their recognition of this problem. Furthermore, these concerns were expressly discussed during the two most important national conferences on the People's Republic of China's (PRC) political calendar, the National Party's Congress and the National People's Congress.1 China is among the few developing countries that will step into an aging society first. As a result of socio-economic development and the one-child policy, the fertility rate in China has dramatically dropped from 6.0 in 1957 to 2.3 in 1980, to 1.7 since the 1990s (Cai & Wang, 2006). At the same time, life expectancy at birth has risen continually from 35 in 1949 to 63 in 1975, 69.2 in 1985, 71.3 in 2000 and 73.2 in 2008 (Bergaglio, 2008 and CIA, 2008). According to the UN's projection, 11.5% of Chinese will be aged 65 and older in 2020, the ratio of the working age population to the total population in China will begin to fall from 2010 and the absolute number of the working population will begin to fall from 2015 (UN, 2003). In the 1980s and 1990s, many observers believed that China was characterized by surplus and underemployed rural labor (Bowlus and Sicular, 2003, Knight and Song, 1995 and Taylor, 1988). However, by 2003 a shortage of rural migrant workers occurred in the Pearl River Delta area, a region with a high concentration of labor-intensive manufacturing enterprises. At that time, most observers believed that this was just a cyclical phenomenon. However, over time, this phenomenon continued and spread to the Yangtze River Delta area, another region dominated by labor-intensive manufacturing enterprises, and even to some central provinces such as Jiangxi, Anhui and Henan, from which migrant laborers are generally sent out (Cai & Wang, 2006). One possible explanation is that as a result of the one-child policy, the growth of the working age population has slowed from the beginning of this decade. Consequently, the ratio of China's working population to total population may have fallen since then. In this paper, we examine the evolution of income inequality in rural China from 1997 to 2006, and try to identify its relationship with the demographic changes. We focus our study on rural areas for several reasons. First, the majority (about 75%) of the population in the developing countries reside in rural areas (Anríquez & Stloukal, 2008). Thus, such a study might be more useful to the policy makers in the developing countries. Secondly, there are compelling reasons to anticipate that the impact of population aging may be more pronounced in a rural setting. As von Weizsacker (1996) emphasizes, there is a substantial danger of underrating the distributional significance of an aging population if we ignore the critical role of age-related redistributive tax-transfer systems, such as public pension schemes and health care systems, which are usually non-existent or very poorly established in rural areas compared with those for the urban population. Moreover, for those rural workers in a developing country like China, they are more likely to exit the labor force before reaching the official retirement age in urban areas. This is due to a combination of factors including the nature of the work undertaken by the majority of workers, i.e. agricultural or low skilled labor-intensive work, and the poorer physical health of workers compared to developed countries. Thirdly, aging in developing countries usually occurs earlier and proceeds more rapidly in rural areas than in the cities (Marcoux, 1994, Marcoux, 2001 and Stloukal, 2004).2 This is mainly caused by rural-to-urban migration which comprises mainly younger adults and thus increases the proportion of older persons in the villages. Therefore, the consequences of aging are felt most by the rural population. In this study, we also try to identify the other causes of income inequality in rural China and the ways in which they affect income inequality. While the problem of population aging cannot be solved in the short run, the information about other inequality determinants is important for the reduction of income inequality. Our paper contributes to the existing literature in a number of ways. It is one of the first studies on the relationship between population aging and income inequality in the context of a developing economy. Since China is one of the first developing countries to experience population aging, our results may be of use not only to the policy makers in China, but also to policy makers in other developing nations. China accounts for about a quarter of the world's population, and the majority of its population resides in rural areas. As the largest developing country in the world, any advancement in the knowledge of causes and consequences of China's rural income inequality and its changes is not only important for understanding the economic development and well-being of the people in China, but also important in a global context. Secondly, as emphasized in Wan and Zhang (2006), since existing studies on income inequality in China are mostly descriptive rather than prescriptive, one area that deserves further research efforts is the cause of the inequality. We employ two different regression-based inequality decomposition methods in this paper. The Shapley value decomposition method allows us to identify the relative contribution of each cause of income inequality, including the measure of demographic change. In addition to that, we introduce a decomposition method commonly used in the health-related inequality literature to analyze income inequality. This approach allows us to identify not only the relative contribution of an income determinant, but also the underlying mechanism through which that income determinant affects income inequality. Finally, our study provides more updated information on the evolution of income inequality in China. One primary focus of existing literature on income inequality in China has been on estimating the levels and changes of inequality over time. Due to data limitations, the information for the period after 2002 is lacking. Based on newly available cycles of the China Health and Nutrition Survey (CHNS), we find that the level of income inequality has risen sharply between 2000 and 2006 and a significant portion of this increase can be attributed to the demographic change. The paper is organized as follows. In the next section, we describe the methods and data used in this analysis. Section 3 contains our empirical results, and in the last section we discuss the policy implications arising from these results and submit our conclusion.
نتیجه گیری انگلیسی
In this paper, we investigated the relationship between population aging and income inequality in rural China using the CHNS data. We found that a significant portion of the sharp increase of income inequality at the beginning of this decade can be attributed to demographic change. Population aging is emerging as an important matter of policy issue in developing countries, and its relationship with income inequality has received little attention. Chu and Jiang (1997) examined the impact of demographic transition in Taiwan on the changes in income inequality from 1978 to 1993. They found that population aging was negatively associated with income inequality. One possible explanation for this result is that the source-specific Gini decomposition approach used in their study could not control the influence of the development and prevalence of education system, industrialization and establishment of social security systems occurred in this period. Cameron (2000) uses a semi-parametric decomposition approach to examine poverty and inequality in Java. She found that 5.8% of the change in the Gini coefficient between 1984 and 1990 could be explained by population aging. Although the semi-parametric approach imposes few structural assumptions, it tells us little about the mechanism through which population aging may affect income inequality. Comparing both of these studies to ours, we find that the degree of population aging, increase of inequality in the examination period, and contribution of population aging to inequality are all much more severe in rural China. A theory on the link between population aging and income inequality in developing countries is an interesting research question that deserves further study. The process of population aging began unfolding only at the end of the 20th century. Existing empirical studies find little impact of population aging on income inequality in the developed countries, and thus this relationship has received little attention in the theoretical literature. The WVW decomposition employed in our study may provide some basic intuitions for developing a formal theory on the relationship between population aging and income inequality in developing countries as follows. As we discussed in the last section, the WVW approach can decompose the relative contribution of a particular variable to the total income inequality into two terms: the elasticity of income with respect to this variable, and the distribution of this variable. The process of population aging began to emerge at the first half of this decade in China. Labor shortage and expansion of industrialization significantly increased the elasticity of income with respect to the labor ratio in the household. At the same time, the distribution of labor ratio also became increasingly unequal. The interaction of these two effects significantly increased income inequality in rural China. The reduction of income inequality is an important policy objective for the Chinese government over the next few years. The results of our study indicate that population aging makes a significant contribution to the sharp increase in income inequality in rural areas in recent years. We conducted similar analysis with the urban samples of the CHNS data, and could not find a statistically significant relationship between demographic changes and increase of income inequality in urban China.9 A plausible explanation for this result is that, as in developed countries, most seniors in urban areas are covered by well-established public pension schemes, which were basically non-existent in rural areas during the examining period in our study. With pensions, the impact of the exit from the labor force on household income is much milder in urban areas, and thus has a much smaller impact on income inequality. Therefore, one policy implication of our analysis is that the establishment of a basic old age security system in rural areas might be useful to reduce income inequality. Considering other results in the last section, we know that there are some variables that may have important policy implications for the reduction of income inequality. For example, the government can encourage the development of local industry in less affluent regions, subsidize the education of children in lower income households, and establish public health insurance plans for the poor. As shown by the WVW decomposition, successful implementation of those policies should change either the mean or distribution of the relevant variables and consequently reduce income inequality. Population aging is an important issue not only from the perspective of income inequality, an imbalanced population structure will influence the social and economic development from many other respects. In the long run, the Chinese government should reconsider whether the one-child policy should be continued. As an interim policy, it has achieved its objective, and now is the time for adjusting the policy (see Cai, 2006). Although the CHNS data used in this study covers nine provinces that vary substantially in geography, economic development and public resources, it is not nationally representative. Gustafsson and Li (2002) show that different combinations of provinces may lead to different results for inequality analysis. One area that deserves further exploration is a comparison of the results using different datasets. Unfortunately, very few recent cycles of most household surveys in China are publicly available. As emphasized in Benjamin, Brandt, and Giles (2005), it would be helpful to broaden participation in the evaluation of inequality issues by opening up the survey data to more users. Population aging will impact society in multiple ways, and it is therefore crucial for policy makers to produce a development strategy that tackles the socio-economic challenges of an aging population.