Spatial Econometric Analysis of China’s Sports Capital Market
Table 7
Estimation results of spatial econometric parameters of capital market supporting the development of the sports industry.
Variable
Spatial error model (SEM)
Spatial lag model (SLM)
Time fixed
Spatial fixation
Space-time double fixation
Time fixed
Spatial fixation
Space-time double fixation
Bank credit financing, X1
0.006 (0.004)
0.013 (0.004)
0.011 (0.004)
0.016 (0.002)
0.022 (0.002)
0.012 (0.002)
Bond financing, X2
0.009 (0.005)
0.005 (0.005)
0.001 (0.005)
0.001 (0.003)
0.015 (0.003)
0.015 (0.003)
Equity financing, X3
−0.006 (0.002)
−0.009 (0.002)
−0.004 (0.002)
−0.004 (0.002)
−0.002 (0.004)
−0.025 (0.021)
Retained earnings financing, Z1
0.018 (0.002)
0.016 (0.002)
0.014 (0.002)
0.014 (0.001)
0.023 (0.002)
0.008(0.004)
Commercial credit financing, Z2
−0.013 (0.002)
−0.009 (0.003)
−0.006 (0.003)
−0.014 (0.002)
−0.023 (0.003)
−0.017 (0.002)
Asset-liability ratio, Z3
0.438 (0.055)
0.510 (0.053)
0.597 (0.054)
0.284 (0.036）
0.284 (0.036)
0.284 (0.036)
Short-term bank loan, Z4
−0.024 (0.004)
−0.033 (0.005)
−0.033 (0.005)
−0.027 (0.003)
−0.030 (0.003)
−0.021 (0.003)
Intercept, _cons
1.786 (1.319)
1.926 (1.319)
1.346 (1.319)
Spatial error regression coefficient, λ
0.101 (0.042)
0.103 (0.042)
1.000 (0.000)
Spatial autoregressive coefficient, ρ
0.315 (0.029)
0.205 (0.029)
0.415 (0.029)
Variance estimation of random disturbance term, sigma2_e
111.727
96.907
0.000 (0.000)
52.628
39.628
44.628
Log-likelihood function value, lgt_theta
0.3232 (0.330)
0.426 (0.423)
0.381 (0.326)
Sample size, N
231
231
231
231
231
The revised fit, r2_a
0.3854
0.3678
0.2940
0.3952
0.4482
0.3933
∗, ∗∗, and ∗∗∗ are significant at the significant level of 1%, 5%, and 10%, respectively, and the values in parentheses represent the T statistics of each estimated coefficient.
