China's fiscal policy on private investment Empirical Analysis of

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Abstract: This paper studies the financial expenditure in infrastructure spending, expenditure on research and innovation, education, culture, health care spending and people's livelihood and social security expenditure impact on private investment through empirical testing, that infrastructure spending in health and education expenditure on medical culture can better promote private investment, while expenditure on research and innovation and people's livelihood and social security spending will not stimulate the growth of private investment.

Keywords: fiscal policy, private investment in economic crisis

I. Introduction of fiscal policy effects on private investment, there are two different points of view, formed on the 'crowding out' and 'crowding effect' argument. Domestic scholars have been based on theoretical results, and using China's data a lot of empirical research, such as: Guoqing Wang, Zhao Zhiyun (1999) believe that interest rates are regulated, the government investment will not out of private investment, but private investment will have to squeeze into effect; Chinese Academy of Social economy macroeconomic issues Group (2000) proposed to enhance the effects of China's fiscal policy means and measures, Liu Rongcang, Mashuan You (2001) based on the deficit, debt and economic growth empirical analysis examines the relationship between the existence of crowding-out effect of fiscal policy, Hu Kun, Chen Weike ( 2004) the use of vector autoregressive (vAR) method, the effectiveness of fiscal policy in China a quantitative analysis.

Current research in this area there is a problem, it is regarded as a whole expenditure analysis, the implementation of fiscal policy 'crowding out' or 'crowding in' private investment. This analysis a bit rough, because increase in expenditure is used in various fields, different areas of expenditure, private investment will have a different effect, of course, some scholars have tried different types of expenditure for the analysis, such as Xu Li, Guo Dingwen (2009) to financial expenditure of expenditures into economic development, social culture and education, defense and administrative costs, analysis of the various categories of expenditure on the impact of private investment, but this classification is only copying the Finance Statistics Yearbook of financial expenditure, there is no effective classification and data processing. This paper attempts to make up for the study of these deficiencies.
Second, data processing and description in this study, focusing on the state finance in infrastructure, research and innovation, education, health and cultural health and livelihood and social security spending on private investment. This fiscal spending Data from the China Financial Yearbook of the expenditure data, private data from China Statistical Yearbook investment in fixed assets investment of the data, select the time period of 1992-2006. chose this time period data, the main is based on the following considerations: (1) 1992, China to further deepen reform and opening, it is from this time began, there has been a large number of private enterprises, private investment has become active. (2) China Finance Yearbook since 2007, the statistics project larger changes, in order to facilitate comparison and statistical standards to maintain data consistency, we only select the data before 2006, and (3) In order to solve the dilemma of deflation in China since 1998 to implement the proactive fiscal policy and monetary policy, this time the data can reflect the economic effects of national fiscal policy, this article contains selected data of this important time in the data selection, the selection of infrastructure investment in national infrastructure for investment expenditure to measure, tapping the potential transformation of research and innovation spending, and 科技三项费 with selection coupled with cultural, educational, scientific and health costs to measure the cost of scientific, educational, medical and cultural selection of cultural, educational and health services expenses, medical and health expenses minus the cost of science to measure people's livelihood and social security expenditure is used to measure the social security benefits expenditure.

In this paper, the data do the following treatment, first in 1978 as the base period for the consumer price index for the nominal value of the data into real value, so you can eliminate price fluctuations in the level of impact on the results, to ensure multi-year data comparability, the second is to do the same variable the natural logarithm of the price change, which not only conforms to the general economic theory, to retain the variables useful information, but also to eliminate collinearity, heteroscedasticity effects. In this paper, measurement software Eviews5. 0 pairs of data to do quantitative analysis.
Third, the empirical analysis (a) variable selection and analysis methods in view of the purpose of this paper is to analyze various types of fiscal policy effects on private investment spending, this article will be divided into infrastructure expenditure spending jCSS, research and innovation spending kycx, education culture of health care spending jyww and people's livelihood and social security expenditure mssb, and analyze them with the effect of private investment mjtz so this article was taken explanatory variable is the natural logarithm of the true value of people ask investment Inmjtz, selected explanatory variables, including taking natural logarithm of the true value of infrastructure spending Injess, after taking the natural logarithm of real expenditure on research and innovation value lnkycx, take the natural logarithm of the expenditure on education, health care and cultural and health undertakings true value lnjyww, take the natural logarithm of the people's livelihood and social the true value of security spending lnmssb.

These variables may be non-stationary series, the empirical test, first test the unit root test using the sequence is stable, then check the data Johansen cointegration test to see whether the cointegration relationship, and gives the cointegration equation, the final Granger test methods used to test the various explanatory variables and is interpreted whether a causal relationship between variables.
(B) smooth test for time series data on the relevant variables to consider stationarity, unit root test them first, usually in case of economic variables are not stable, there is more or less serial correlation, but the variable may exist between cointegration relationship, if you do not take into account the smoothness of the direct variable regression analysis, may lead to 'spurious regression' phenomenon, so we conduct cointegration and causality test, you must first unit of each variable root test, we use ADF test, the test results in Table 1.
Description: D said the first-order differential treatment, D2 said that second-order differential treatment; test type, c that includes the constant term, 0 does not include the constant term, t is time trend included, N that does not include the time trend, n is the lag order number (based on SIC criteria to determine).

From the above unit root test results can be seen, lnmjtz, lnjcss, lnkycx, lnjyww, Inmssb on their level of value are non-stationary time series, but their second-order difference in the 1% confidence level are stationary series, can be determine whether they were significantly stable, so they are second-order single whole I (2) sequence.

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(C) stable cointegration test found lnmjtz, lnjcss, lnkycx, lnjyww, lnmssb the sequences are non-stationary series, but they may have long-term equilibrium relationship, the cointegration test can determine the time series of the long-run equilibrium relationship . cointegration test on the premise that the sequence is the same order single whole, and selected just five time series are second-order single whole sequence, with the co-integration test conditions. In this paper, Johansen maximum likelihood estimation cointegration test on the variables. test results shown in Table 2.

Both trace or maximum eigenvalue statistics reject the variable volume statistics there is no cointegration relationship between the original assumptions, and test results can be considered from private investment and infrastructure spending, expenditure on research and innovation, education, culture, health care spending, people's livelihood and social security expenditure in the 5% confidence level there is a unique cointegration relationship.

Because people ask investment and infrastructure spending, expenditure on research and innovation, education, culture, health care spending, people's livelihood and social security expenditure are second-order single whole, the long-run equilibrium exists between the variables and the cointegration relationship and we can establish a private investment as explanatory variables, other factors as explanatory variables the cointegration equation, as follows: Inmjtz = 0.188114lnjess-1.316937lnkyex +2.5671701 njyww-1.9961151nmssb-12.56158

0.12136 0.42838 0.41904 0.14613 1.02768

Note: the above formula, the number under each coefficient are standard errors.
It can be seen from the above equation, private investment and infrastructure spending, expenditure on research and innovation, education, health

Medical culture and livelihood of social security expenditure on health spending between the long-term cointegration relationship the following order of each factor to make the appropriate interpretation of the meaning, first, lniCSS the coefficient is positive, indicating that investment in infrastructure to increase private investment infrastructure improvement of production and operation for enterprises to create a good environment to attract private investment. This confirms Wang Lu et al (2009) in the <<China's economic growth mode transformation and sustainable growth 'in the conclusion. lnkyex of coefficient is negative, indicating that research and innovation spending increase is not conducive to private investment increase. lnjyww coefficient is positive, indicating that the education of medical culture and health spending is conducive to private investment increase. Inmssb the coefficient is negative, indicating the people's livelihood and social security expenditure is not conducive to private investment increase.
(D) Granger causality test on the correlation with the data, and can not fully explain the problem by Granger causality test between any two variables can know whether a causal relationship, because of who is and who is Fruit. In order to identify areas in which investment expenditure is beneficial to stimulate private investment in the cointegration test, the need for further Granger causality test, the test results in Table 3.
From the above test results, the following important conclusions can be drawn (1) private investment in infrastructure is the reason, because private investment is also able to participate in the construction of part of the infrastructure (2) people's livelihood and social security spending is the reason people ask investment while we can see from the cointegration test results. This effect is negative (3) educational and cultural health of investment spending is the reason people ask, and co-integration test results tell us that this effect is positive.
Fourth, the conclusions and policy recommendations to the above analysis, the following conclusions can be drawn: into infrastructure spending to stimulate the growth of private investment, private investment will also promote the growth of infrastructure, education, medical culture and health services The expenditure on private investment has a strong role in promoting investment in research and innovation is a long-term project aimed at promoting economic growth, fiscal spending should focus on investment in economic development.

Infrastructure in the past for a long period of time are our key areas of financial investment. Into the infrastructure of the financial expenditure, on the one hand, as part of aggregate demand, can better alleviate the economic downturn, a good starting to the role of macro-control the other hand, this analysis shows that infrastructure investment can better stimulate private investment, for long-term economic development is also helpful.

In addition to infrastructure investment in education, health care and cultural health of the investment can be well stimulate private investment, cointegration equation, its coefficient is much larger than the coefficient of infrastructure, we can see, education, health care spending on culture better than private investment, driven by investment in infrastructure, Education, Culture and Health care is a social life, a very important part, if they can get a very good development, it can effectively increase consumer welfare. analysis also shows that education culture of health care has led to the role of private investment.

References:
1 Dai Yuanchen. 'Investment multiplier failure' caused confusion and thinking. Economic Research, 1999 (8)
2 Guoqing Wang, Zhao Zhiyun. On the pull effect of the fiscal deficit. Finance and Trade Economics, 1999 (6)
3 Liu Rongcang, Mashuan You. Deficit, national debt and economic growth Empirical Analysis - Comment on whether there is a positive crowding-out effect of fiscal policy, Economic Research, 2001 (2)
4 Wang Lu, Fan Gang, Liu Peng, China's economic growth mode transformation and growth sustainability. Economic Research, 2009 (1)
5 Zeng China in recent years of whether there is crowding-out effect of fiscal policy, Economic Research, 2000 (3)

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