The Biased Technical Change And Its Effect On Factor Income Distribution In USA

The nature of directed technical change is technical change will cause an increase in relative marginal product of the factor which technical change directs at. Meanwhile, technical change directing at a specific factor will improve output efficiency of the factor, resulting in a higher return and a larger income gap. Among the existing literature, there is great progress in theory research and estimated methods of technical change. Based on research on neoclassical technical change and embodied technical change, more and more scholars focus on directed technical change. Many scholars admit current technical change directs at capital or skilled labor, however, are the situations the same both in developed countries and developing countries? Moreover, technical change are introduced to analyze economic growth, factor resource arrangement, employment structure, skill premium and other issues involving economic development, especially research on effect of directed technical change on factor income shares become the focus of the study. Is technical change directing at capital or skilled labor the reason for decrease in proportion of labor income or skill premium? Holding the question, the paper analyzes directed technical change and its effect on factor income distribution, which is helpful to sustain development of economic, perfect income structure, narrow income gap.Through the review of literature on technical change and factor income distribution, the paper tries to construct multi-sector model differentiating capital and labor, skilled and unskilled labor to analyze the reason how directed technical change is formed among production factors and the role of technical change plays in factor income distribution. In empirical analysis, according to the theoretical model the paper first develops the index measuring directed technical change, and estimats the feature of directed technical change of the U.S. Then the paper studies the factor income distribution of capital and labor, skilled and unskilled labor, employs structure decomposition method and builds a fisher index to study effects of directed technical change on factor income distribution of capital and labor, skilled and unskilled labor respectively. At last, the paper applies the above methods to the data of China, studying directed technical change in China and its effect on factor income distribution. Through the comparison of the relevant results between the U.S. and China, I hope the study on directed technical change and factor income distribution of the U.S. can provide references and solutions to the economic development and problems of factor income distribution in China. The conclusions in the paper are as follows: Firstly, through reading and analysis of literature on technical change, I find the scholars study technical change in different perspectives from neoclassical technical change, embodied technical change to directed technical change, and existence of directed technical change, the extent to which technical change direct at and the effect become the key contents. The development of theoretical research can be divided into three stages:at the first stage, the definition of directed technical change is put forward, but the point of view is criticized and questioned because of lack micro-fundamentals. At the second stage, after1960s, directed technical change attracts scholars because of introduction of innovative possible frontier to research on induced technology innovations. Contributed to lack of micro fundamentals, preference of neoclassical technical change,"Kaldor fact" and limitations on research methods, directed technical change is not attached importance. At the third stage, after1990s, research on directed technical change is developed by Acemoglu in his series of studies who lays the micro foundation of this field. His finding interprets "Kaldor fact" and skill premium which are applied in various fields.Secondly, the nature of technical change is the change in factor marginal product caused by technical change, and technical change can direct at a certain factor. Particularly, the relative and absolute biasedness represent the biased feature of technical change effects on the relative and absolute values of marginal products of production factors. While the strong and weak biasedness of technical change differ in conduction mechanism of directed technical change and factor supply, which is considering bias of technical change for factors marginal output effect will be more than supply change on its role.Thirdly, the endogenous model with capital and labor shows, technical change directing at capital will leads increase in relative marginal product of capital to labor, and technical change will direct at the abundant factor. Whether substitutes or complements relationship between production factors, increase in relative supply of capital to labor leads to rise in both relative technology and relative marginal product. Between skilled and unskilled labor factor, when the two types of labor factor as gross substitutes and elasticity of substitution is big enough, factors the increase of the relative supply and raising the level of technology will lead to an increase relative rewards and the income share.Fourthly, focusing on capital and labor, based on the data of the U.S. during1971-2011, indicate technical change in the U.S. directs at capital under different elasticity of substitution on the whole, which tends to increase the relative marginal product of capital leading rise in relative income share of capital to labor. The situation coincides with the change of factor income distribution in the U.S.. In the U.S. the characteristic skill bias shows, with three different values of elasticity of substitution, technical change directs at skilled labor during2000to2013. At the same time there is skill premium, when technical change directs at skilled labor more and more, skill premium will be larger, and the relative income share of skilled labor to unskilled labor is increased,too. In China, technical change directs at capital duiring1978to2011and at skilled labor during2000to2011.Fifthly, through calculating factor income distribution in the U.S. and China, I find capital and labor incomes in the U.S. are both higher than China. But different from low labor income share in China, the labor income on factors of income distribution pattern is larger in the U.S.. On the other hand, through the comparison, the U.S. capital and labor income levels are higher than China's, and the gap is widening, only in2007after subprime crisis does the gap narrowed. In the study between skilled and unskilled labor factor, labor factors relative income share are rise, but it is tardiness in China and craggy in the U.S.. Income of skilled labor is higher than unskilled labor in both countries with skill premium.Sixthly, make use of structural decomposition method to investigate the biased technical change and its effect on the different factor income distribution. The U.S. the biased technical change characteristics of capital and labor, or skill labor and unskill labor factor what its contribution to relative income share changes are always a positive contribution. The capital-biased technical change will improve capital income share relative to labor. The skill-biased technical change will improve skill income share relative to unskill labor. In China there is a positive contribution, too.But each time the effect of the biased technical change to factor income share has great difference with the U.S.. On the whole, in the U.S. and China, the capital-biased or skill-biased technical change will improve capital income share and skill income share, and the contribution of the biased technical change is growing.