wide variations. While to HSS disciplines, the annually average of efficiency scores
are relatively low, around 0.4 over the period. It means that HSS disciplines of
211Us are in greater need to improve their relative efficiency.
Second, we analyze the annually average of environmental indicators at macro
level. The variables of GDP per capita, S&T output index, High-tech output index
are all in the uptrend, which reflect the stable development of China’s society and
economy, and higher degree of emphasis on the development of science and
technology, as well as the stable development of regional innovation and high
technology. The variables of number of 985Us or 211Us in a particular province are
both measure for university cluster. Since there is no new university entering the
clubs of 985Us after 2006, the annually average isfixed across thefive-year period.
Similarly, there is no new university entering the clubs of 211Us after 2008, the
annually average only changes a little in 2008, and remains stable in the rest of
years.
Third, we analyze the annually average of sectoral and institutional indicators.
The annual international cooperation and exchange frequency is in the uptrend,
which means Chinese universities further into line with international. Concerning
the variable of university reputation, to NEAM disciplines, there are 63% of total
universities directly administered by MOE, and 37% titled“985 Project”university,
27% entering ARWU2012. Thefigures are similar in HSS sample, but the pro-
portion of 985Us is 35%, and the proportion of entering ARWU2012 is 26%.
Last, we analyze the annually average of internal indicators at micro level.
Women account for around 39.5% of total faculty on average, and the value is
relatively stable over the period. The annual proportion of staff with senior title is
around 27.5%, without wide variations over the period. The annual proportion of
staff with PhD increase substantially from 2006 to 2010, which means that uni-
versities tend to raise the threshold of recruitment, and also make greater efforts to
recruit high-profile talents.
Table 6.4 Descriptive statistics on key variables
Variables Means
2006 2007 2008 2009 2010
DEA efficiency Scores NEAM 0.826 0.812 0.793 0.812 0.806
HSS 0.330 0.413 0.336 0.381 0.424
GDP per capita (¥1000) 27.529 32.322 36.982 39.730 44.944
S&T output index 47.216 47.872 50.416 50.960 52.188
High-tech output index 41.96 50.667 89.659 51.994 55.036
Number of 211Us 9.04 9.04 9.09 9.09 9.09
Number of 985Us 2.930 2.930 2.930 2.930 2.930
International exchanges (100
times)1.6 1.64 1.82 2.19 2.09
% Female staff 39.426 39.504 39.695 39.473 39.336
% Staff with senior title 27.960 27.547 27.680 27.601 27.882
% Staff with PhD 23.999 26.552 28.896 31.836 34.5236.2 Econometric Analysis of Factors... 275