Total Investment in Fixed Assets and the Later Stage of Urbanization: A Case Study of Shanghai
Abstract
:1. Introduction
2. Literature Review
3. Materials and Method
3.1. Data Source
3.2. Econometric Methodology
3.2.1. Unit Roots Test
3.2.2. Johansen Co-Integration Test
3.2.3. VAR Model and Granger Causality Test
3.2.4. Impulse Response Functions and Variance Decomposition
4. Empirical Results
4.1. Descriptive Statistics Analysis
4.2. Results of Stationarity Test
4.3. Results of Co-Integration Test
4.4. Results of Granger Causality Test
4.5. Impulse Response Analysis
4.6. Variance Decomposition Analysis
5. Discussion and Conclusions
- Both Group (, , , and ) and Group (, ) have a long-term co-integration relationship among the studied variables, and construction project investment plays an important role in promoting the urbanization rate in the studied period.
- Granger causality shows that both Group (, , , and ) and Group (, ) have a bilateral Granger causal relationship; however, the urbanization rate has more Granger causal impact on the studied variable both in Group (, , and ) and Group (, ).
- The impulse response analysis illustrates that the urbanization rate has a positive impact on the total investment in fixed assets in the short term and long term. A similar conclusion is found in [21], that is, government investment policy has substantially affected Egypt and its sustainable development.
- Variance decomposition analysis reveals that the urbanization rate in Group (, , , and ) and Group (, ) accounts for the majority of percentage impacts, and the total investment in fixed assets and its three categories contribute a small minority to the urbanization rate.
6. Policy Implication
- Strengthen the rational total investment in fixed assets. According to our results, the total investment in fixed assets has a one-direction Granger relationship with urbanization rate and a bilateral Granger relationship in the long term. Notably, urbanization is a process that needs time to comply with economic factors, such as the total investment in fixed assets. Thus, the city would not benefit from the higher urbanization rate. Similarly, the total investment in fixed assets also needs a process that would convert its investment into related beneficial interests of the city. Therefore, a rational investment strategy is necessary to ensure the healthy development of urbanization through, for example, conceptual infrastructure planning and investment project appraisal schemes. A similar implication can be found in [57].
- Set a more flexible policy on construction project investment. Generally, construction project investment is a critical factor that plays a substantial role as a drive of urban development. In addition, our results demonstrate a one-way Granger relationship between construction project investment and urbanization rate. Therefore, policymakers must balance the two indicators, for example, the related population policy and construction project investment policy, which can be implemented according to the current condition to solve urban problems (i.e., gentrification, polarization, and urban renewal) caused by urbanization [2].
- More rationally guide the development of the real estate industry. Theoretically, based on the characteristics of the other countries’ urbanization experience, urbanization can be divided into four stages: initial, acceleration, deceleration, and stable.Similarly, the development of the real estate industry follows similar laws of urbanization development, summarized as four stages: formation, growth, maturity, and decline. However, the relationship between urbanization and the real estate industry should be harmonious, or it may cause serious economic problems. Notably, the real estate industry has developed rapidly since the commercial housing reform in Shanghai in 1998. However, the real estate industry has always been the economic pillar of Shanghai and has been criticized for its “excessively high housing price,” the “real estate bubble,” and other problems of the society. Moreover, according to our research, there is a bilateral direction of Granger causality between the real estate industry and urbanization, indicating that the two factors have a close relationship. Therefore, Shanghai should guide the rational development of the real estate industry in the later stage of urbanization. More specifically, the government should coordinate land financing policy [12] and eliminate the negative externalities of the policy, for example, the polarization effect and high housing prices; thus, the government must more practically manage the related social, economic, or environmental problems caused by real estate investment.
- Promote rural revitalization and coordinate the development of urbanization through scientific planning.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
- Unit root test.
- ADF test
Include in Test Equation Variables ADF Test Statistic Test Critical Value Prob.* (5% Level) Level Intercept 1 ln(TI) −2.974150 −3.012363 0.0539 2 ln(CPI) −3.007464 −3.012363 0.0505 3 ln(REI) −1.420050 −3.004861 0.5538 4 ln(FI) −1.901596 −2.976263 0.3266 5 ln(UR) −1.355025 −2.976263 0.5888 Intercept and trend 1 ln(TI) −0.252700 −3.644963 0.9865 2 ln(CPI) −1.271979 −3.644963 0.8668 3 ln(REI) −4.679380 −3.595026 0.0048 4 ln(FI) −2.459441 −3.587527 0.3437 5 ln(UR) −0.067273 −3.587527 0.9928 None 1 ln(TI) 3.398008 −1.956406 0.9995 2 ln(CPI) 0.778335 −1.954414 0.8754 3 ln(REI) 2.492405 −1.956406 0.9953 4 ln(FI) −1.093929 −1.953858 0.2413 5 ln(UR) 2.789532 −1.953858 0.9979 First difference Intercept 1 ln(TI) −6.059505 −2.998064 0.0000 2 ln(CPI) −2.094011 −2.981038 0.2484 3 ln(REI) −8.306588 −2.998064 0.0000 4 ln(FI) −5.777930 −2.981038 0.0001 5 ln(UR) −2.093889 −2.986225 0.2485 Intercept and trend 1 ln(TI) −4.879820 −3.644963 0.0043 2 ln(CPI) −4.235406 −3.644963 0.0159 3 ln(REI) −6.881178 −3.622033 0.0001 4 ln(FI) −5.746140 −3.595026 0.0004 5 ln(UR) −2.566373 −3.603202 0.2969 None 1 ln(TI) −1.380192 −1.954414 0.1516 2 ln(CPI) −1.808925 −1.954414 0.0676 3 ln(REI) −1.989104 −1.954414 0.0465 4 ln(FI) −5.843456 −1.954414 0.0000 5 ln(UR) −1.668758 −1.955020 0.0892 * MacKinnon (1996) one-sided p-values. - PP test
Include in Test Equation Variables PP Test Statistic Test Critical Value Prob. * (5% Level) Level Intercept 1 ln(TI) −3.312157 −2.976263 0.0243 2 ln(CPI) −3.682527 −2.976263 0.0104 3 ln(REI) −2.661924 −2.976263 0.0937 4 ln(FI) −1.860863 −2.976263 0.3447 5 ln(UR) −1.307643 −2.976263 0.6111 Intercept and trend 1 ln(TI) −2.397368 −3.587527 0.3725 2 ln(CPI) −2.393708 −3.587527 0.3742 3 ln(REI) −1.940834 −3.587527 0.6059 4 ln(FI) −2.459441 −3.587527 0.3437 5 ln(UR) −0.327360 −3.587527 0.9853 None 1 ln(TI) 2.056535 −1.953858 0.9883 2 ln(CPI) 1.703675 −1.953858 0.9754 3 ln(REI) 1.134348 −1.953858 0.9293 4 ln(FI) −1.137367 −1.953858 0.2258 5 ln(UR) 2.473166 −1.953858 0.9955 First difference Intercept 1 ln(TI) −1.982617 −2.981038 0.2921 2 ln(CPI) −2.168164 −2.981038 0.2218 3 ln(REI) −2.562258 −2.981038 0.1134 4 ln(FI) −5.982451 −2.981038 0.0000 5 ln(UR) −4.333654 −2.981038 0.0023 Intercept and trend 1 ln(TI) −2.624646 −3.595026 0.2732 2 ln(CPI) −2.640510 −3.595026 0.2670 3 ln(REI) −3.060382 −3.595026 0.1362 4 ln(FI) −5.963815 −3.595026 0.0003 5 ln(UR) −4.602260 −3.595026 0.0058 None 1 ln(TI) −1.579302 −1.954414 0.1058 2 ln(CPI) −1.765214 −1.954414 0.0738 3 ln(REI) −2.158700 −1.954414 0.0321 4 ln(FI) −5.890789 −1.954414 0.0000 5 ln(UR) −3.550310 −1.954414 0.0010 * MacKinnon (1996) one-sided p-values. - DF GLS test
Include in Test Equation Variables DF GLS Test Statistic Test Critical Value (5% Level) Level Intercept 1 ln(TI) −0.131325 −1.95502 2 ln(CPI) −1.086410 −1.954414 3 ln(REI) −0.735425 −1.955020 4 ln(FI) −1.624687 −1.953858 5 ln(UR) −1.150360 −1.955020 Intercept and trend 1 ln(TI) −4.177963 −3.190000 2 ln(CPI) −3.193654 −3.190000 3 ln(REI) −2.093001 −3.190000 4 ln(FI) −2.676590 −3.190000 5 ln(UR) −1.442210 −3.190000 First difference Intercept 1 ln(TI) −1.744151 −1.954414 2 ln(CPI) −2.116516 −1.954414 3 ln(REI) −9.221668 −1.956406 4 ln(FI) −5.899968 −1.954414 5 ln(UR) −1.968365 −1.955020 Intercept and trend 1 ln(TI) −5.179672 −3.190000 2 ln(CPI) −4.189617 −3.190000 3 ln(REI) −2.770603 −3.190000 4 ln(FI) −5.980730 −3.190000 5 ln(UR) −2.593204 −3.190000 - KPSS test
Include in Test Equation Variables KPSS Test Statistic
(LM-Stat.)Test Critical Value (5% Level) Level Intercept 1 ln(TI) 0.635611 0.463000 2 ln(CPI) 0.609767 0.463000 3 ln(REI) 0.586319 0.463000 4 ln(FI) 0.552366 0.463000 5 ln(UR) 0.630447 0.463000 Intercept and trend 1 ln(TI) 0.148130 0.146000 2 ln(CPI) 0.155706 0.146000 3 ln(REI) 0.149842 0.146000 4 ln(FI) 0.110950 0.146000 5 ln(UR) 0.116601 0.146000 First difference Intercept 1 ln(TI) 0.326506 0.463000 2 ln(CPI) 0.348473 0.463000 3 ln(REI) 0.283457 0.463000 4 ln(FI) 0.146240 0.463000 5 ln(UR) 0.286196 0.463000 Intercept and trend 1 ln(TI) 0.090225 0.146000 2 ln(CPI) 0.083030 0.146000 3 ln(REI) 0.074952 0.146000 4 ln(FI) 0.094182 0.146000 5 ln(UR) 0.171965 0.146000
- VAR model stability test
- Lag length Criteria
Endogenous Variables: LNUR LNREI LNFI LNCPI Lag LogL LR FPE AIC SC HQ 0 107.3996 NA 2.13 × 10−9 −8.616631 −8.420289 −8.564541 1 190.6542 131.8198 8.03 × 10−12 −14.22118 −13.23947 −13.96073 2 224.7761 42.65236 * 2.02 × 10−12 −15.73134 −13.96426 * −15.26253 3 247.1822 20.53895 1.70 × 10−12 * −16.26518 −13.71273 −15.58802 4 273.5519 15.38233 1.74 × 10−12 −17.12933* −13.79151 −16.24380 * Endogenous variables: LNUR LNTI 0 69.43158 NA 4.04 × 10−6 −6.743158 −6.643585 −6.72372 1 117.7289 82.10542 4.84 × 10−8 −11.17289 −10.87417 −11.11458 2 126.0379 12.46350 * 3.20 × 10−8 * −11.60379 −11.10592 * −11.5066 3 128.7788 3.563223 3.78 × 10−8 −11.47788 −10.78087 −11.34182 4 131.0546 2.503410 4.85 × 10−8 −11.30546 −10.40931 −11.13053 5 136.7627 5.137205 4.67 × 10−8 −11.47627 −10.38096 −11.26245 6 137.7866 0.716748 7.90 × 10−8 −11.17866 −9.884206 −10.92597 7 145.8918 4.052623 7.75 × 10−8 −11.58918 −10.09558 −11.29762 8 157.9017 3.602975 7.24 × 10−8 −12.39017* −10.69743 −12.05973 * Endogenous variables: LNCPI LNUR 0 71.68151 NA 3.23 × 10−6 −6.968151 −6.868578 −6.948713 1 109.4189 64.15355 1.11 × 10−7 −10.34189 −10.04317 −10.28358 2 118.8922 14.21001 * 6.54 × 10−8 * −10.88922 −10.39136 * −10.79203 3 122.6084 4.831030 7.00 × 10−8 −10.86084 −10.16383 −10.72478 4 127.2259 5.079235 7.11 × 10−8 −10.92259 −10.02643 −10.74765 5 132.6427 4.875137 7.06 × 10−8 −11.06427 −9.968966 −10.85046 6 134.5060 1.304267 1.10 × 10−7 −10.8506 −9.556144 −10.5979 7 136.5102 1.002104 1.98 × 10−7 −10.65102 −9.157418 −10.35945 8 153.0950 4.975459 1.17 × 10−7 −11.90950 * −10.21676 −11.57906 * Endogenous variables: LNUR LNFI 0 50.94417 NA 2.57 × 10−5 −4.894417 −4.794844 −4.87498 1 83.34779 55.08616 1.51 × 10−6 −7.734779 −7.43606 −7.676466 2 84.98780 2.460008 1.94 × 10−6 −7.49878 −7.000914 −7.401591 3 87.31935 3.031019 2.39 × 10−6 −7.331935 −6.634923 −7.195871 4 88.61514 1.425366 3.38 × 10−6 −7.061514 −6.165355 −6.886574 5 92.24668 3.268384 4.01 × 10−6 −7.024668 −5.929362 −6.810853 6 107.4306 10.62873 1.65 × 10−6 −8.143058 −6.848606 −7.890368 7 125.0243 8.796877 6.24 × 10−7 −9.502434 −8.008835 −9.210868 8 160.3043 10.58400* 5.69 × 10−8 * −12.63043 * −10.93769 * −12.29999 * Endogenous variables: LNUR LNREI 0 53.23147 NA 2.04 × 10−5 −5.123147 −5.023573 −5.103709 1 107.0701 91.52568 1.40 × 10−7 −10.10701 −9.808291 −10.0487 2 112.5153 8.167730 1.24 × 10−7 −10.25153 −9.75366 −10.15434 3 117.7268 6.774992 1.14 × 10−7 −10.37268 −9.675666 −10.23661 4 119.7344 2.208402 1.50 × 10−7 −10.17344 −9.277284 −9.998503 5 136.9797 15.52072 * 4.57 × 10−8 −11.49797 −10.40266 −11.28415 6 143.5897 4.627038 4.42 × 10−8 −11.75897 −10.46452 −11.50628 7 148.7749 2.592569 5.81 × 10−8 −11.87749 −10.38389 −11.58592 8 175.3801 7.981562 1.26 × 10−8 * −14.13801 * −12.44526 * −13.80757 * * indicates lag order selected by the criterion. LR: sequential modified LR test statistic (each test at 5% level). FPE: Final prediction error. AIC: Akaike information criterion. SC: Schwarz information criterion. HQ: Hannan-Quinn information criterion - JJ test
Variables Group JJ Co-Integration
ConfigurationCo-Integration Equation
NumberLog Likelihood Value Trace Test Max-Eigenvalue Test LNUR and LNTI no intercept or trend in test VAR; Lags interval (in first differences): 1 to 1 1 1 152.0092 LNUR and LNCPI, LNREI, LNFI no intercept or trend in test VAR; Lags interval (in first differences): 1 to 1 1 1 193.6514 - Granger causality test
Lag Length Urbanization Rate and Total Investment in Fixed Assets Urbanization Rate and Construction Project Investment Urbanization Rate and Real Estate Investment Urbanization Rate and Farmers’ Investment Null Hypothesis F-Statistic p-Value Accept/
RejectConclusion Null Hypothesis F-Statistic p-Value Accept/
RejectConclusion Null Hypothesis F-Statistic p-Value Accept/
RejectConclusion Null Hypothesis F-Statistic p-Value Accept/
RejectConclusion 1 ≠> 0.95 0.34 R ≥ ≠> 1.69 0.21 R ≥ ≠> 0.77 0.39 R ≥ ≠> 5.27 0.03 R ≥ 1 ≠> 0.8 0.38 R ≥ ≠> 0.5 0.49 A ≠> ≠> 0.19 0.66 A ≠> ≠> 0.04 0.84 A ≠> 2 ≠> 0.14 0.86 A ≠> ≠> 0.45 0.64 A ≠> ≠> 0.34 0.71 A ≥ ≠> 3.02 0.07 R ≥ 2 ≠> 9.37 0 R ≥ ≠> 3.89 0.04 R ≥ ≠> 3.66 0.04 R ≥ ≠> 0.09 0.92 A ≠> 3 ≠> 1.9 0.16 R ≥ ≠> 1.63 0.22 R ≥ ≠> 0.66 0.59 R ≥ ≠> 2.46 0.1 R ≥ 3 ≠> 7.23 0 R ≥ ≠> 4.86 0.01 R ≠> 2.23 0.12 R ≥ ≠> 0.23 0.88 A ≠> 4 ≠> 1.34 0.3 R ≥ ≠> 1.29 0.32 R ≥ ≠> 0.43 0.78 A ≠> ≠> 2.82 0.06 R ≥ 4 ≠> 1.37 0.29 R ≥ ≠> 1.69 0.2 R ≥ ≠> 14.2 0 R ≥ ≠> 0.25 0.91 A ≠> 5 ≠> 0.75 0.6 R ≥ ≠> 0.97 0.47 R ≥ ≠> 0.45 0.81 A ≠> ≠> 1.6 0.23 R ≥ 5 ≠> 0.55 0.74 A ≠> ≠> 1.19 0.37 R ≠> 6.62 0 R ≥ ≠> 0.16 0.97 A ≠> 6 ≠> 0.78 0.61 R ≥ ≠> 0.52 0.78 A ≠> ≠> 1.08 0.44 R ≥ ≠> 5.02 0.02 R ≥ 6 ≠> 0.44 0.83 A ≠> ≠> 1.05 0.45 R ≠> 2.5 0.11 R ≥ ≠> 0.57 0.75 A ≠> 7 ≠> 0.94 0.54 R ≥ UR ≠> 0.3 0.93 A ≠> ≠> 0.92 0.55 R ≥ ≠> 6.06 0.02 R ≥ 7 ≠> 0.58 0.75 A ≠> ≠> 0.59 0.75 A ≠> ≠> 2.67 0.13 R ≥ ≠> 1.63 0.28 R ≥ 8 ≠> 0.93 0.59 R ≥ UR ≠> 0.46 0.83 A ≠> ≠> 2.79 0.22 R ≥ ≠> 10.08 0.04 R ≥ 8 ≠> 0.26 0.94 A ≠> ≠> 0.34 0.9 A ≠> ≠> 11.01 0.04 R ≥ ≠> 3.36 0.17 R ≥ - Impulse response function analysis
Response of LNUR: Period LNUR LNREI LNFI LNCPI 1 0.008015 0.000000 0.000000 0.000000 (0.00111) (0.00000) (0.00000) (0.00000) 2 0.007424 −0.001344 −0.000835 0.002355 (0.00229) (0.00124) (0.00185) (0.00160) 3 0.006740 −0.000817 −0.001057 0.001661 (0.00226) (0.00141) (0.00236) (0.00166) 4 0.005870 −0.000669 2.39E−06 0.001433 (0.00218) (0.00171) (0.00249) (0.00172) 5 0.005507 −0.000256 −0.000388 0.001391 (0.00208) (0.00193) (0.00254) (0.00167) 6 0.004987 9.76E−05 −0.001033 0.001346 (0.00211) (0.00201) (0.00265) (0.00158) 7 0.004529 0.000333 −0.001445 0.001203 (0.00207) (0.00190) (0.00259) (0.00146) 8 0.004191 0.000402 −0.00159 0.001090 (0.00200) (0.00165) (0.00233) (0.00129) 9 0.003953 0.000366 −0.001581 0.001016 (0.00193) (0.00135) (0.00195) (0.00109) 10 0.003759 0.000277 −0.001454 0.000963 (0.00189) (0.00109) (0.00157) (0.00090) Response of LNREI: Period LNUR LNREI LNFI LNCPI 1 −0.021352 0.050006 0.000000 0.000000 (0.01024) (0.00693) (0.00000) (0.00000) 2 0.004724 0.055465 −0.071406 0.050022 (0.02428) (0.02024) (0.01846) (0.01266) 3 0.021578 0.049850 −0.104369 0.061358 (0.03640) (0.02913) (0.03148) (0.02220) 4 0.034252 0.034144 −0.076669 0.049433 (0.03881) (0.02893) (0.03889) (0.02755) 5 0.048198 0.019811 −0.045606 0.033325 (0.03291) (0.02846) (0.03992) (0.02656) 6 0.054488 0.011126 −0.029232 0.018094 (0.02957) (0.02910) (0.03853) (0.02476) 7 0.052776 0.006943 −0.022126 0.005269 (0.02800) (0.02850) (0.03916) (0.02311) 8 0.047439 0.004342 −0.018585 −0.002232 (0.02600) (0.02578) (0.03815) (0.02179) 9 0.041997 0.001767 −0.016069 −0.003654 (0.02363) (0.02184) (0.03352) (0.01967) 10 0.037861 −0.001002 −0.012863 −0.00066 (0.02151) (0.01822) (0.02756) (0.01649) Response of LNFI: Period LNUR LNREI LNFI LNCPI 1 −0.070103 −0.009286 0.135964 0.000000 (0.02844) (0.02670) (0.01885) (0.00000) 2 −0.032795 0.034758 0.009469 −0.007008 (0.03859) (0.02216) (0.03418) (0.02987) 3 −0.051116 0.043485 −0.0504 −0.012088 (0.02356) (0.02032) (0.03346) (0.02007) 4 −0.052888 0.039885 −0.058855 −0.025699 (0.03005) (0.02250) (0.03215) (0.02133) 5 −0.04586 0.022481 −0.040059 −0.024572 (0.02866) (0.02281) (0.03554) (0.02250) 6 −0.034499 0.005305 −0.019324 −0.017462 (0.02281) (0.02208) (0.03446) (0.02165) 7 −0.025916 −0.007593 0.002268 −0.009639 (0.01949) (0.02136) (0.02998) (0.01886) 8 −0.019954 −0.013841 0.018508 −0.003767 (0.01816) (0.02021) (0.02832) (0.01626) 9 −0.01687 −0.014011 0.025670 −0.00043 (0.01738) (0.01770) (0.02747) (0.01580) 10 −0.016266 −0.010069 0.024340 0.000185 (0.01604) (0.01462) (0.02505) (0.01563) Response of LNCPI: Period LNUR LNREI LNFI LNCPI 1 0.021433 −0.004447 −0.01131 0.032548 (0.00743) (0.00679) (0.00657) (0.00451) 2 0.028201 −0.006838 −0.005661 0.043433 (0.01383) (0.01037) (0.01248) (0.00998) 3 0.032984 −0.004054 0.003783 0.037967 (0.01573) (0.01118) (0.01579) (0.01157) 4 0.034250 0.001798 0.002753 0.026742 (0.01538) (0.01204) (0.01707) (0.01203) 5 0.031342 0.008494 −0.007333 0.013502 (0.01436) (0.01292) (0.01718) (0.01153) 6 0.026088 0.012557 −0.017562 0.002152 (0.01413) (0.01363) (0.01771) (0.01083) 7 0.021456 0.012505 −0.023114 −0.004478 (0.01429) (0.01345) (0.01818) (0.01066) 8 0.018772 0.008894 −0.022676 −0.005843 (0.01380) (0.01229) (0.01776) (0.01060) 9 0.018018 0.003566 −0.017313 −0.003345 (0.01252) (0.01075) (0.01602) (0.00986) 10 0.018456 −0.001428 −0.009603 0.000901 (0.01125) (0.00948) (0.01362) (0.00841) Cholesky Ordering: LNUR LNREI LNFI LNCPI. Standard Errors: Analytic, The standard errors are marked in parentheses.Response of LNUR: Period LNUR LNTI 1 0.007795 0.000000 (0.00108) (0.00000) 2 0.007575 0.000307 (0.00211) (0.00079) 3 0.007027 0.000552 (0.00218) (0.00121) 4 0.006589 0.000687 (0.00220) (0.00133) 5 0.006245 0.000722 (0.00228) (0.00129) 6 0.005952 0.000687 (0.00237) (0.00120) 7 0.005682 0.000614 (0.00242) (0.00109) 8 0.005415 0.000531 (0.00244) (0.00098) 9 0.005144 0.000456 (0.00243) (0.00087) 10 0.004871 0.000399 (0.00242) (0.00077) Response of LNTI: Period LNUR LNTI 1 0.010648 0.025808 (0.00527) (0.00358) 2 0.015947 0.035379 (0.00980) (0.00567) 3 0.025087 0.033296 (0.01215) (0.00717) 4 0.034156 0.025147 (0.01302) (0.00780) 5 0.040534 0.015488 (0.01384) (0.00782) 6 0.043394 0.007214 (0.01488) (0.00782) 7 0.043130 0.001613 (0.01575) (0.00797) 8 0.040723 −0.001224 (0.01618) (0.00799) 9 0.037249 −0.001894 (0.01621) (0.00764) 10 0.033580 −0.001234 (0.01599) (0.00694) Cholesky Ordering: LNUR LNTI. Standard Errors: Analytic, The standard errors are marked in parentheses. - Variance decomposition analysis
Variance Decomposition of LNUR: Period S.E. LNUR LNTI 1 0.007795 100.0000 0.000000 2 0.010874 99.92033 0.079668 3 0.012959 99.76276 0.237236 4 0.014554 99.58902 0.410983 5 0.015854 99.44595 0.554046 6 0.016948 99.35094 0.649055 7 0.017886 99.29944 0.700557 8 0.018695 99.27812 0.721876 9 0.019395 99.27393 0.726070 10 0.020001 99.27756 0.722442 Cholesky Ordering: LNUR LNTI.Variance Decomposition of LNUR: Period S.E. LNUR LNREI LNFI LNCPI 1 0.008015 100.0000 0.000000 0.000000 0.000000 2 0.011287 93.68445 1.416877 0.546892 4.351780 3 0.013318 92.90239 1.394456 1.022664 4.680485 4 0.014640 92.95874 1.362949 0.846329 4.831987 5 0.015710 93.01351 1.210128 0.796065 4.980294 6 0.016570 92.66779 1.091239 1.104283 5.136685 7 0.017284 92.04011 1.040078 1.713907 5.205907 8 0.017893 91.36200 1.020946 2.388455 5.228599 9 0.018424 90.77305 1.002354 2.988863 5.235735 10 0.018887 90.34507 0.975413 3.436823 5.242690 Cholesky Ordering: LNUR LNREI LNFI LNCPI.
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Trace Test | Maximum Eigenvalue Test | |||||||
---|---|---|---|---|---|---|---|---|
No. of CE(s) | Eigenvalue | Statistic | Critical Value | Prob. ** | Eigenvalue | Statistic | Critical Value | Prob. ** |
LNUR and LNCPI, LNREI, LNFI | ||||||||
None * | 0.7678 | 59.0405 | 40.1749 | 0.0002 | 0.7678 | 37.9662 | 24.1592 | 0.0004 |
At most 1 | 0.3335 | 21.0744 | 24.2760 | 0.1202 | 0.3335 | 10.5505 | 17.7973 | 0.4289 |
At most 2 | 0.3078 | 10.5239 | 12.3209 | 0.0982 | 0.3078 | 9.5664 | 11.2248 | 0.0965 |
At most 3 | 0.0362 | 0.9575 | 4.1299 | 0.3799 | 0.0362 | 0.9575 | 4.1299 | 0.3799 |
LNUR and LNTI | ||||||||
None * | 0.5069 | 19.6435 | 12.3209 | 0.0025 | 0.5069 | 18.3839 | 11.2248 | 0.0024 |
At most 1 | 0.0473 | 1.2596 | 4.1299 | 0.3056 | 0.0473 | 1.2596 | 4.1299 | 0.3056 |
Lag | LR | FPE | AIC | SC | HQ |
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1 | / | / | / | / | / |
2 | ) | / | / | ) | / |
3 | / | ) | / | / | / |
4 | / | / | ) | / | ) |
5 | / | / | / | / | / |
6 | / | / | / | / | / |
7 | / | / | / | / | / |
8 | / | / | ) | / | ) |
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Luo, Y.; Wang, C.; Chen, C.; Ding, K.; Zeng, W. Total Investment in Fixed Assets and the Later Stage of Urbanization: A Case Study of Shanghai. Sustainability 2021, 13, 3661. https://doi.org/10.3390/su13073661
Luo Y, Wang C, Chen C, Ding K, Zeng W. Total Investment in Fixed Assets and the Later Stage of Urbanization: A Case Study of Shanghai. Sustainability. 2021; 13(7):3661. https://doi.org/10.3390/su13073661
Chicago/Turabian StyleLuo, Yulong, Can Wang, Chen Chen, Kangle Ding, and Weiliang Zeng. 2021. "Total Investment in Fixed Assets and the Later Stage of Urbanization: A Case Study of Shanghai" Sustainability 13, no. 7: 3661. https://doi.org/10.3390/su13073661