fficiency of using the investment. On the other hand, as the ranking order decreased from 1st to 14th during the six years, Guangdong province is an example of the typical provinces which are significant slippage. The decision makers need to do more work to reverse the disadvantageous situation by improving the efficiency of resource use.

3.3. Correlational Analysis between the Efficiency Scores and Investment

The above Figure 2 shows the trend of the cross-efficiency scores of all the 30 provinces during 2003 to 2008. Some provinces express an upward tendency (such as Tianjin, Gansu, Qinghai, Ningxia and Xinjiang), while some others show a downward tendency (such as Jiangsu, Fujian, Guangdong and Anhui). Besides, note that, most of the provinces in west region keep their efficiency ascendant in these years.

Figure 3 gives the curves of ratio of provincial investment to the nationwide total investment during 2003 to 2008. A noticeable feature is the curve trends in figure 3, indicating significant changes of investment. Specifically, the decreasing and increasing tendency could be respectively found in about 10 provinces (such as Beijin, Shanghai, Jiangsu, Zhejiang, Guangdong, Hainan, Guizhou, Qinghai, Ningxia and Xinjiang) and 8 provinces (Hebei, Neimenggu, Jilin, Anhui, Henan, Guangxi, Chongqi and Shanxi). Another noteworthy feature is that no province in middle region shows a decreasing trend on investment ratio in the six years, which illustrates that

Figure 2. Cross-efficiency scores of provinces during 2003 to 2008.

Figure 3. Ratio of provincial investment to the nationwide total investment during 2003 to 2008.

Table 6. Results of Spearman correlation between efficiency score and investment ratio.

more investment shift to middle region.

It is seen from Table 6 that the efficiency scores of eight provinces (Jiangsu, Guangdong, Neimenggu, Anhui, Guizhou, Qinghai, Ningxia and Xinjiang) have significant correlation1 with the investment ratios. Then, these eight provinces can be divided into four categories. The two east region provinces Jiangsu and Guangdong belong to the first category, whose efficiency scores decline with the investment ratios falling. However, on the contrary, the four west region provinces (Guizhou, Qinghai, Ningxia and Xinjiang) improve their performance as the investment ratios decreasing and compose the second category. Lastly, two middle region provinces, Neimenggu and Anhui, are respectively called the third and fourth category because of their different response to the increasing investment ratio. The efficiency score of Neimenggu grow with the increasing of investment ratio, while the performance of Anhui gets worse significantly as investment raise sharply.

4. Conclusions

This paper applies a cross-efficiency DEA model to measure the investment efficiency of 30 provinces in China in order to provide a detailed regional analysis of Chinese investment inefficiency. Three inputs (Fixedasset investment, Net fixed asset of industry and Number of employee of industry) and two outputs (GDP and Value-added of industry) and provincial-panel data for the period 2003-2008 are considered in this study. A number of interesting results with important implications are found:

Based on the empirical results, there are very significant differences between the three economic regions in China: the east region is the best performance while the west region is the worst. This is very understandable because of the disparities in the infrastructure. Better investment environment is provided by the east region through years of accumulation, while the mid and west regions do not have a requirement to make full use of the investment.

On the other hand, the assimilation appears in nationwide: the difference of the performances between the three regions is diminishing by comparing the trend of efficiencies during 2003-2008. That phenomenon is not only an expression of the improvement of allocative efficiency but also the inevitable result that economy grows. Moreover, more work need to be done to narrow the gap between different regions in the further.

Investment is driving force for some east province such as Jiangsu and Guangdong that is expressed as the significant positive correlation between the decrease of investment and efficiency, while the over-investment does exist in some west provinces such as Guizhou, Qinghai, Ningxia and Xinjiang because of the significant negative correlation between the investment decreasing and performance improving.


  1. G. C. Chow, “A Model of Chinese National Income Determination,” Journal of Political Economy, Vol. 93, No. 4, 1985, pp. 782-791. doi:10.1086/261330
  2. G. C. Chow, “Capital Formation and Economic-Growth in China,” Quarterly Journal of Economics, Vol. 108, No. 3, 1993, pp. 809-867. doi:10.2307/2118409
  3. L. X. Sun, “Estimating Investment Functions Based on Cointegration: The Case of China,” Journal of Comparative Economics, Vol. 26, No. 1, 1998, pp. 175-191. doi:10.1006/jcec.1997.1501
  4. H. Song, Z. Liu and P. Jiang, “Analysing the Determinants of China’s Aggregate Investment in the Reform Period,” China Economic Review, Vol. 12, No. 2-3, 2001, pp. 227-242. doi:10.1016/S1043-951X(01)00052-9
  5. X. He and D. Qin, “Aggregate Investment in People’s Republic of China: Some Empirical Evidence,” Asian Development Review, Vol. 21, 2004, pp. 99-117.
  6. J. Zhang, “Capital Formation, Industrialization and Economic Growth,” Economic Research Journal, Vol. 7, 2002, pp. 3-13 (in Chinese).
  7. Q. Yu, “Capital Investment, International Trade and Economic Growth in China: Evidence in the 1980-90s,” China Economic Review, Vol. 9, No. 1, 1998, pp. 73-84. doi:10.1016/S1043-951X(99)80005-4
  8. A. C. C. Kwan, Y. Wu and J. Zhang, “Fixed Investment and Economic Growth in China,” Economics of Planning, Vol. 32, No. 1, 1999, pp. 67-79. doi:10.1023/A:1003424418042
  9. D. Qin, M. A. Gagas, P. Quising and X. He, “How Much Does Investment Drive Economic Growth in China?” Journal of Policy Modeling, Vol. 28, No. 7, 2006, pp. 751-774. doi:10.1016/j.jpolmod.2006.02.004
  10. D. Qin and H. Song, “Sources of Investment Inefficiency: The Case of Fixed-Asset Investment in China,” Journal of Development Economics, Vol. 90, No. 1, 2009, pp. 74- 145. doi:10.1016/j.jdeveco.2008.06.001
  11. A. Young, “The Razor’s Edge Distortions and Incremental Reform in the People’s Republic of China,” The Quarterly Journal of Economics, Vol. 115, No. 4, 2000, pp. 1091-1136. doi:10.1162/003355300555024
  12. J. Zhang, “Investment, Investment Efficiency, and Economic Growth in China,” Journal of Asian Economics, Vol. 14, No. 5, 2003, pp. 713-734. doi:10.1016/j.asieco.2003.10.004
  13. A. Charnes, W. W. Cooper and E. Rhodes, “Measuring the Efficiency of Decision Making Units,” European Journal of Operational Research, Vol. 3, No. 4, 1970, pp. 429- 444. doi:10.1016/0377-2217(79)90229-7
  14. T. R. Sexton, R. H. Silkman and A. J. Hogan, “Data Envelopment Analysis: Critique and Extensions,” In: R. H. Silkman, Ed., Measuring Efficiency: An Assessment of Data Envelopment Analysis, Jossey-Bass, San Francisco, 1986, pp. 73-105.
  15. J. Doyle and R. Green, “Efficiency and Cross Efficiency in DEA: Derivations, Meanings and the Uses,” Journal of the Operational Research Society, Vol. 45, 1994, pp. 567- 578.
  16. T. Jian, J. Sachs and A. Warner, “Trends in Regional Inequality in China,” China Economic Review, Vol. 7, No. 1, 1996, pp. 1-21. doi:10.1016/S1043-951X(96)90017-6


1Correlation is significant at the 0.05 level (2-tailed).

Journal Menu >>