Regional innovation system performances based on stochastic frontier analysis

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1 JOURNAL OF SYSTEMS ENGINEERING Vol.28 No.1 Feb ,2, 1,2 (1., ; 2., ) : 31, 31., ,.,.,,. : ; ; ; : F061.5 : A : (2013) 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 , China; 2. Enterprise Innovation Research Institute, Harbin Engineering University, Harbin , 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 , 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,,., : ; : : ( ); ( ); (201 2GXS4D114); (GZ11D203); (2012M520712); (LBH-Z11186); (HEUCF120914; HEUCFR1223).

2 126 28,, [1]., [2] DEA,. [3] DEA, 30,. [4] DEA ,,,. [5] 30,,,. [6] DEA ,. [7], , 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

3 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],.,, %, 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,

4 ,,.,. collaboration.,..,,.,. awareness,.,,,.,.,,.,,. : 16,,, [17]. input,.,,. government., [17].,,,. market,., , ( ) (2005) ( ). SFA (unbalance panel data), , 3 279, Y ( : ),.,,. K, [18, 19], n K it = µ k E i,t k + R t, (5) k=1

5 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] , ( / ), (open) (maturity) (collaboration) (input) (awareness) (government) (market) Table 1 1 Statistical description of the samples ( ) ( ) R&D ( ) (%) (%) (%) (%) ( / ) (%) (%) , 31,.,,., 4 057, 16. 4, Froniter , , 3 279, γ , 1%., γ 0, 1, γ ,,. 1%, ,, LR , 1%, ,,,,, 2.,

6 130 28,. Table 2 2 Stochastic frontier function and efficiency equation estimated results T *** K *** L *** K *** L *** K L *** *** * *** *** * *** γ *** LR *** : *, **, *** 10%, 5% 1% ; LR, ,.,. δ 1 = ,,. 30,,,.,. δ 2 = ,,.,.,. δ 3 = ,., > 2.,.,. δ 4 = ,.,, [19, 20].,. δ 5 = ,.,,.,. δ 6 = ,,.,,

7 1 : 131.,,.,. δ 7 = ,,.,,. 4.3,, 31 11, 3. 3, SFA DEA. DEA,, DEA, 1 [21 23]. DEA, SFA,.,, ,,. Table 3 3 The average performance of all regions y(t) t 1 Fig. 1 Each year of the national performance change 3 1, 0.36, ,.,

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