28 1 2013 2 JOURNAL OF SYSTEMS ENGINEERING Vol.28 No.1 Feb. 2013 1,2, 1,2 (1., 150001; 2., 150001) : 31, 31., 0.362 258,.,.,,. : ; ; ; : F061.5 : A : 1000 5781(2013)01 0125 09 Regional innovation system performances based on stochastic frontier analysis Su Yi 1,2, Li Baizhou 1,2 (1. School of Economics and Management, Harbin Engineering University, Harbin 150001, China; 2. Enterprise Innovation Research Institute, Harbin Engineering University, Harbin 150001, China ) Abstract: The paper selects China s 31 provinces and cities as research subjects and makes an empirical study using stochastic frontier based on the 31 provinces and cities unbalanced panel data. The empirical results show that: firstly, innovation performances of regional innovation systems in different provinces or cities are greatly different. The National average regional innovation performance is 0.362258, indicating that nonefficiency is very common in these provinces and cities. Secondly, openness of regional innovation systems, maturity of technology markets, collaboration of regional innovation systems, intellectual property protection and marketization can promote innovation performances of regional innovation systems. What is more, under China s special national conditions, the relationship between enterprise technology input, government investment and regional innovation performance is negative. Key words: stochastic frontier analysis; regional innovation systems; performance; panel data 1,,., : 2011 10 23; : 2012 06 07. : (20122304120021); (71073034); (201 2GXS4D114); (GZ11D203); (2012M520712); (LBH-Z11186); (HEUCF120914; HEUCFR1223).
126 28,, [1]., [2] DEA,. [3] DEA, 30,. [4] DEA 2002 2003,,,. [5] 30,,,. [6] DEA 2006 30,. [7], 2001 2005, DEA,.,, DEA. DEA,,. DEA,, BCC, (SFA). DEA (SFA),,,., (SFA) [8 11] [9, 10], GDP R&D R&D, [11]. (SFA),.,,. (SFA),,,, [11]., (open) (maturity) (collaboration) (input) (awareness) (government) (market),. 2,,,. (SFA) 20 70, Meeusen Broeck [12], H it = G it β + (V it U it ), i = 1, 2,, N; t = 1, 2,, T, (1) m it = z it δ, (2) H it i t, G it i
1 : 127 i.i.d. t, β. V it N (0, δv 2 ), U it ; U it, N (m it, δu), 2 U it t i. TE it = exp( U it ),.,,,. TE,.,, TE. TE it = exp( U it ) i t. (2), z it, δ, γ = δ 2 u/(δ 2 v + δ 2 u) SFA. γ (0, 1), γ 0, V it, U it, ; γ 1, U it V it, SFA, γ χ 2., Battese&Coelli [8] ln Y it = β 0 + β 1 ln K it + β 2 ln L it + β 3 ln 2 K it + β 4 ln 2 L it + β 5 (ln K it )(ln L it ) + (V it U it ), (3) m it = δ 0 + δ 1 open it + δ 2 maturity it + δ 3 collaboration it + δ 4 input it + δ 5 awareness it + δ 6 government it + δ 7 market it. (4) (3) Y., [13, 14],.,,. 2008 20%, 5%, 30%( 65% 85% ), 5%, 8%,.,.,,, ( ),. K., (R&D),., ( ),. (R&D).,,,., R&D. L R&D. Jaffe [15],,,. R&D,,,, R&D. (4), : open.,. GDP [16],,,,. maturity,
128 28.,,.,. collaboration.,..,,.,. awareness,.,,,.,.,,.,,. : 16,,, [17]. input,.,,. government., [17].,,,. market,.,. 3 3.1, (1999 2009) 1949 2004 (2005) (1999 2009). SFA (unbalance panel data), 31 1998 2008 11, 3 279,. 3.2 3.2.1 Y ( : ),.,,. K, [18, 19], n K it = µ k E i,t k + R t, (5) k=1
1 : 129 µ k, E, R, θ, k = θ, µ k = 1;, µ k = 0., 2, K it = E i,t 2 + R t. L ( : )., [16]. 3.2.2, ( / ), (open) (maturity) (collaboration) (input) (awareness) (government) (market). 3.3 1 31 1998 2008. Table 1 1 Statistical description of the samples ( ) 332 12 142 445 18 908 609 28 135 513 426 ( ) 341 2 045 827.3 2 830 088.2 5 694.8 18 256 390 R&D ( ) 341 38 484.526 38 757.01 204 238 683.79 (%) 235 2.211 3 7.532 68 0.01 76.01 (%) 328 0.772 4 1.400 58 0.01 10.98 (%) 341 2.575 8 7.632 79 0.22 93.42 (%) 338 3.040 2 5.902 64 0.03 43.11 ( / ) 341 5.057 7 8.632 18 0.02 81.14 (%) 341 4.210 2 5.716 49 0.37 37.98 (%) 341 44.021 6 20.672 2 5.6 88.64 1, 31,.,,., 4 057, 16. 4, Froniter4.1 31 1998 2008, 2. 4.1 2, 3 279, γ 0.679 99, 1%., γ 0, 1, γ 0.679 99,,. 1%,. 597.571 53,, LR 64.805 212, 1%,. 0.362 258,,,,, 2.,
130 28,. Table 2 2 Stochastic frontier function and efficiency equation estimated results T 43.942 7*** 2.294 7 19.149 4 K 2.469 8*** 1.052 5 2.346 6 L 7.839 1*** 1.800 9 4.353 0 K 2 0.551 2*** 0.210 1 2.623 8 L 2 0.829 2*** 0.284 4 2.921 5 K L 1.734 9*** 0.496 6 3.493 5 3.668 4*** 0.557 5 6.578 0 0.833 9* 0.053 4 1.544 4 0.103 5*** 0.427 2 2.422 0 0.130 0*** 0.017 4 7.481 7 0.008 2 0.028 9 0.282 4 0.067 3 0.059 8 1.124 4 0.083 1* 0.053 5 1.553 0.050 8*** 0.010 6 4.803 2 γ 0.679 99*** 0.079 36 8.568 1 597.571 53 LR 64.805 212*** 0.362 258 3 279 : *, **, *** 10%, 5% 1% ; LR,. 4.2 2,.,. δ 1 = 0.833 9,,. 30,,,.,. δ 2 = 0.103 5,,.,.,. δ 3 = 0.130 0,., 1 + 1 > 2.,.,. δ 4 = 0.008 2,.,, [19, 20].,. δ 5 = 0.067 3,.,,.,. δ 6 = 0.083 1,,.,,
1 : 131.,,.,. δ 7 = 0.050 8,,.,,. 4.3,, 31 11, 3. 3, SFA DEA. DEA,, DEA, 1 [21 23]. DEA, SFA,.,, 1998 2008 1.,,. Table 3 3 The average performance of all regions 0.760 829 1 0.272 627 20 0.311 636 16 0.616 356 5 0.502 261 9 0.207 075 24 0.296 867 19 0.222 888 22 0.170 909 26 0.196 811 25 0.568 467 8 0.037 49 31 0.242 676 21 0.305 647 18 0.158 011 29 0.403 177 11 0.314 896 15 0.129 329 30 0.318198 14 0.305959 17 0.217587 23 0.162 085 28 0.662 597 3 0.384 232 12 0.705 383 2 0.341 832 13 0.170 404 27 0.642 898 4 0.576 114 7 0.608 224 6 0.453 379 10 0.50 0.45 0.40 y(t) 0.35 0.30 0.25 0.20 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 t 1 Fig. 1 Each year of the national performance change 3 1, 0.36, 1999 2008.,.,
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