收入不均與經(jīng)濟增長的關(guān)系.docx

Panel data analysis: Income inequality and Economic growth in credit controlBy1459823University of Warwick9th Sep 2015Supervisor: Prof. Omer Moav Word count: 810032DeclarationI hereby confirm that the present paper is my own work and that if any text passages or diagrams from books, papers, the Web or other sources have been copied or in any other way used, all references including those found in electronic media have been acknowledged and fully cited. Tan Xin9th Sep 2015AcknowledgementsI would like to thank Professor Omer Moav for providing core literatures and thoughtful comments. All errors remain mine.AbstractOpposite sign of correlation between inequality and growth have been reported in different researches and dataset. This research uses panel technique investigating the correlation by incorporating maturity level of credit market. The result of the research indicate that country-specific effect positively correlate with both inequality and growth, Advanced credit market help alleviate loss in growth due to inequality, which, coincide with previous literature.ContentsDeclarationiAcknowledgementsiiAbstractiii1. Introduction11.1Negative correlation between income inequality and economic growth11.2.Non-monotonic relationship between income inequality and economic growth22.Literature review32.1.Inequality and the financial market32.2.Human capital and credit constraints32.3.Physical capital and credit constraints32.4.Choice between less income inequality and greater economic growth43.The theoretical model53.1.Structure of the economy53.2.The overlapping generation system63.3.The definition of the second best economy123.4.The definition of first best economy and credit friction124.Methodology174.1.Dataset and basic model174.2.The control for conditional convergence and country-specific effect174.3.The role of credit control194.4.Arellano and Bond estimation205.Estimation results and Analysis.226.Concluding Remarks287.References . 298. Appendix.31Tables and FiguresDiagram 19Diagram 211Diagram 311Table 122Table 225Table 326Graph 321. Introduction The relationship between income inequality and economic growth has been substantially analysed in existing literature, both empirically and theoretically. In the existing empirical researches, there is ambiguity in the relationship between income inequality and growth, as both positive and negative signs of correlation have been found. For example, Perotti (1996) reported a negative effect of income inequality on growth. However, Forbes (1997) reported a positive effect on growth. In a theoretical context, various theories claiming about effect of inequality on growth have been proposed, and these theories are distinct in the perspectives on which they focus. In order to investigate the ambiguous relationship between inequality and growth, this paper will endogenize income inequality in the financial market to expose more information on their relationship. To motivate the investigation of endogeneity in inequality, this paper will firstly discuss the relevant theoretical claim and empirical findings about inequality. Then it will propose an analytical model incorporating growth, inequality, credit market. Finally it will interpret the findings and reconcile the findings to existing literatures. 1.1 Negative correlation between income inequality and economic growth Political economics arguments describe the relationship between inequality and growth through the conflict between the rich and the poor (see Alesina and Rodrik, 1994). Consider an economy that consists of two groups: the poor and the rich. Whenever there is a chance of economic growth due to technological progress, the poor group can choose to hold up the economy and ask for a financial transfer from the rich group. Whenever the poor group choose to hold up the economy, the timing of the technological boost is missed and, naturally, the economic growth is discounted at a rate less than one. The more output and resources the richer group owns in the economy, the higher the incentive for the poor group to choose to sacrifice the interest from technological progress and seize resources from the rich. This high probability of hold-up behaviour will have negative effect on growth. Conflict between the rich and the poor has also been considered in the context of democratic election (See Benabou, 2000). Consider an economy where the government levies a tax on labour income and redistributes the collected payoff evenly to everyone in the economy. Taxation will be accompanied by a distortion of economic decision. For example, taxing people will reduce the marginal benefit of working relative to leisure and discourage people to work. In such an economy, the rich group will always object to redistribution, since their payoff decreases. However, the extremely poor group will benefit from redistribution because, even though the redistribution is distortionary, the benefit extracted from the rich will outweigh the loss from the distortion. A more unequal economy will bring a higher proportion of extremely low-income people and, therefore, gain greater support for distortionary redistribution, which retards economic growth. These political claims all have the essence that greater income inequality has a positive effect on the probability or magnitude of distortionary redistribution, through which economic growth is reduced. Income inequality can also affect economic growth through the wealth effect. Galor and Zeria (1993) propose a model which depicts how income inequality retards economic growth via the accumulation of human capital. Their claim is that the credit market imperfection will generate a gap between the marginal benefit of investing human capital and the interest rate (marginal cost). The gap between the marginal benefit and marginal cost will induce efficiency loss, which will be exacerbated when more people are considered to be poor in that economy. Under the assumption that the mean income is higher than the benchmark income, greater income inequality will label more people as poor and block them from investing in human capital. In this theory, the efficiency loss due to inequality relies on the assumption of an imperfect credit market. Therefore, a country with a more advanced credit market will have less of a problem with human capital loss due to income inequality.1.2. Non-monotonic relationship between income inequality and economic growth Theoretical claims do not always support the theory that inequality has a negative effect on growth. There exists a theory suggesting a non-monotonic relationship between inequality and growth as the economy develops. In 1955, Kuznet claimed that economic growth has non-monotonic effect on income inequality via structural change of labour. First of all, the economy is divided into agricultural and industrial sectors. Labourers in the agricultural sector have relatively low income per capita and a low level of inequality. The industrial sector has a relatively high level of income per capita and starts on a small scale. The relationship between inequality and growth is initially positive. This is because, at the beginning of industrialization, well paid jobs in urban districts encourage farmers to shift to the cities, which creates high inequality. The rural-urban inequality gap will then decrease after inequality has reached its maximum, as further industrial extension means more poor workers joining the industrial sector. Moreover, the decreasing amount of labour in the agricultural sector makes those who stay in that sector more competitive, leading to a negative correlation between inequality and output as the negative force starts to outweigh the positive force. The relationship between inequality and output will exhibit an inverted U-shape, and be negative overall. Empirical research also suggests a non-monotonic relationship between inequality and growth in previous literature. Barros empirical research (2000) indicates that higher inequality tends to slow down economic growth in poor countries. However, in richer countries, a higher level of inequality is associated with greater economic growth. The results have been confirmed by later research (see Fawaz, Rahnama and Valcarcel 2014). Barros findings also reported the inverted U-shaped curve of income inequality against GDP level, which coincides with the claims of Kuznet. The structure of this paper is as follows. Section 2 will be the literature review, which presents the relevance of existing literature to the proposed model. Section 3 will propose a theoretical model and Section 4 will give the methodology used to prove the theory. Section 5 will give the regression result combined with analysis and interpretation. Section 6 will conclude the research. 2. Literature review2.1. Inequality and the financial market The financial market might have an impact on the non-monotonic relationship between inequality and growth. Greenwood and Jovanovic (1990) comment that, in Kuznets curve, the movement of inequality depicts a shift from a financially unsophisticated environment to one with an advanced financial system. They claim that economic growth could facilitate the formation of financial institutions, which in turn feed higher economic growth and lower inequality. A similar statement can be found in Barros (2000) comment on the Galor and Zeria model: as a country develops, its financial institutions and credit market will improve. A country will suffer less efficiency loss by having less income inequality, because a better financial market will help alleviate inequality by closing the margin between investing in human capital and borrowing. The development of the financial market might have an impact on both growth and inequality.2.2. Human capital and credit constraints The Galor and Zeria model shows the link between inequality and growth. In the meantime, it also connects inequality with human capital and credit constraints. There is also other empirical research investigating the role of human capital in the relationship between inequality and credit constraints. It claims that a better credit market can reduce income inequality via a better educational background. Li Jie and Han Yu (2014) have demonstrated that in Asian districts, poor people with a better educational background can benefit more efficiently from financial reform, raising their marginal productivity and ultimately reducing the income gap. Meanwhile, they have proved that a country with a better financial market will have less income inequality in general. From their research, human capital is an important channel through which credit liberation can effectively alleviate income inequality. 2.3. Physical capital and credit constraints A better credit market will serve to close the gap between the marginal benefit of having more human capital and the marginal cost to finance education in the Galor and Zeria model. This idea can also be applied to the accumulation of physical capital. Firms decision making will also involve the level of credit constraints. With more credit available to a credit-constrained firm, the firms production, expenditure and profit will increase (see Banerjee and Duflo, 2014). A constrained firm will have marginal productivity of capital that is greater than the interest rate of the economy. An extension of credit availability will help to close the gap between marginal productivity and market interest rate, and release the potential productivity of the firm. Fewer credit constraints will also feed a multi-industry economy with higher output growth. Francesco Caselli and James Feyrer (2007) pointed out that credit friction is the distortion that prevents capital from being distributed to its ideal allocation to achieve maximization of the total output. This ideal allocation is unique, and required to achieve the equalization of MPK (marginal product of capital), which means, given the technological level and human capital in each of the industries 1, 2, 3, j fixed, an economy with ideal capital allocation should have the condition:MPK=MPK1=MPK2=MPKjAn economy with credit friction will block the economy from its ideal capital allocation and slow down growth. Therefore, an economy with a better credit market and greater availability of bank loans will have a higher growth rate. The arguments of the above two researches indicate a direct relationship between credit constraints and growth through physical capital, without any concern of income inequality. 2.4. Choice between less income inequality and greater economic growth As previously discussed, inequality will reduce growth through the support of distortionary redistribution. However, a country that has special “taste” for less inequality will choose to reduce inequality at the price of less growth. Thus, ex-post economic growth and inequality will exhibit a positive correlation due to that special taste. This taste can be interpreted as a particular culture or preference that partly determine a countrys latent utility function. An example of such a taste can be derived from conspicuous consumption (see Omer Moav and Zika Neeman, 2012), indicated by certain cultures. In this kind of culture, individuals can improve latent relative ranking by consuming more goods like alcohol, drugs and prostitution that are useless to escape from the poverty trap. Therefore, the latent utility function will depend not only on the physical use of consumption, but also on the relative ranking of consumption to others. In this case, extra equality is required to maximize the total utility in order that fewer people are ranked lower than others. Inequality will not just have an exogenously causal effect on growth. Inequality and growth can also be endogenously determined by the taste or country-specific effect.3. The theoretical model3.1. Structure of the economySuppose an economy is divided into J industries, 1, 2, 3, and 4, J.Each industry produces its own goods, and, for the sake of simplicity, all the goods are normalized into one identical good.The production function for industry m is: Fm=AmHmKm1- (1) Where F is the total production of industry m, H is the total level of human capital, K is the total level of physical capital and A is the level of technology. The above function can be normalized into: fm=Amkm1- (2)Where f is the level of production of one unit of human capital and k is the level of physical capital per unit of human capital. km=KmHm (3)There are w