# Exploring a Moderate Fallow Scale of Cultivated Land in China from the Perspective of Food Security
## 4 Results
### Lost GPP of Cultivated Land
#### 4.2.1 Lost GPP Caused by the Occupation of Construction Land from 1990 to 2017
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{6}{c}{**Low-Speed Economic Growth**} & \multicolumn{6}{c}{**Medium–High-Speed Economic Speed**} \\ \hline \multirow{4}{*}{Year} & \multicolumn{3}{c}{Construction} & \multicolumn{3}{c}{Construction} & \multirow{4}{*}{Occupied} \\  & GDP & Land & & & & & \\  & Expansion & Cultivated & Lost GPP & GDP & Expansion & Cultivated & Lost GPP \\  & (10\({}^{8}\) yuan) & Area & Land Area & (10\({}^{4}\) t) & (10\({}^{8}\) yuan) & Area & Land Area & (10\({}^{4}\) t) \\  & & (10\({}^{4}\) hm\({}^{2}\)) & (10\({}^{4}\) hm\({}^{2}\)) & & & (10\({}^{4}\) hm\({}^{2}\)) & \\ \hline
2017 & 762,262.62 & 15.24 & 12.35 & 75.96 & 784,464.45 & 39.66 & 32.13 & 197.68 \\
2018 & 785,130.50 & 40.40 & 32.72 & 201.33 & 831,532.31 & 91.44 & 74.07 & 455.72 \\
2019 & 808,684.42 & 66.31 & 53.71 & 330.46 & 881,424.25 & 146.32 & 118.52 & 729.25 \\
2020 & 832,944.95 & 92.99 & 75.32 & 463.47 & 934,309.71 & 204.49 & 165.64 & 1019.18 \\
2021 & 857,933.30 & 120.48 & 97.59 & 600.46 & 990,368.29 & 266.16 & 215.59 & 1326.51 \\
2022 & 883,671.30 & 148.79 & 120.52 & 741.57 & 1,049,790.39 & 331.52 & 268.53 & 1652.28 \\
2023 & 910,181.44 & 177.95 & 144.14 & 886.90 & 1,112,777.81 & 400.81 & 324.65 & 1997.60 \\
2024 & 937,486.88 & 207.99 & 168.47 & 1036.0 & 1,179,544.48 & 474.25 & 384.14 & 2363.64 \\
2025 & 965,611.49 & 238.93 & 193.53 & 1190.79 & 1,250,317.15 & 552.10 & 447.20 & 2751.64 \\
2026 & 994,579.83 & 270.79 & 219.34 & 1349.60 & 1,325,336.18 & 634.62 & 514.04 & 3162.91 \\
2027 & 1,024,417.23 & 303.61 & 245.93 & 1513.18 & 1,404,856.35 & 722.09 & 584.90 & 398.87 \\
2028 & 1,055,149.74 & 337.42 & 273.31 & 1681.67 & 1,489,147.73 & 814.82 & 660.00 & 460.98 \\
2029 & 1,086,804.23 & 372.24 & 301.51 & 1855.21 & 1,578,496.59 & 931.10 & 739.61 & 4550.82 \\
2030 & 1,119,408.36 & 408.10 & 330.56 & 2033.95 & 1,673,206.39 & 1017.28 & 824.00 & 5070.05 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Expansion area of construction land and loss of GPP (2017–2030). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variable** & **Coefficient** & **Std. Error** & **T value** & \(p\) **\(>\) |t|** &
\begin{tabular}{c} **Standardization** \\ **Coefficient** \\ \end{tabular} \\ \hline _GDP_ & 0.0014 *** & 0.0002 & 6.08 & 0.000 & 0.635 \\ _PDI_ & 0.0003 & 0.0002 & 1.58 & 0.124 & 0.126 \\ _FI_ & \(-\)0.00006 *** & 0.00001 & \(-\)4.33 & 0.000 & 0.211 \\ _NBC_ & \(-\)3.066 ** & 1.452 & \(-\)2.11 & 0.043 & 0.260 \\ _NT_ & 0.024 ** & 0.011 & 2.14 & 0.041 & 0.110 \\ _ACL_ & 0.057 * & 0.031 & 1.83 & 0.077 & 0.328 \\ _MH_ & 1.091 * & 0.587 & 1.86 & 0.073 & 0.185 \\ _Constant_ & \(-\)5148.210 & 139.332 & \(-\)1.19 & 0.243 & \\ _Sigma_\_\_\_u_ & & & 158.513 & & \\ _Sigma_\_\_e_ & & & 7.003 & & \\ _Rho_ & & & 0.998 & & \\ _Number of_ & & & 279 & & \\ _observations_ & & & & & \\ \hline \hline \multicolumn{6}{l}{Note: (1) *, **, and *** are significantly different from zero at the 10\%, 5\%, and 1\% levels, respectively. (2) Standard error has been clustered to provincial scale, which can reduce the influence of heteroscedasticity. In addition, Taking logarithm of the variables measured in currency also reduced the influence of heteroscedasticity to some extent. On the whole, the influence of heteroscedasticity is small and can be ignored.} \\ \end{tabular}
\end{table} 
Table 3: Simulation results of the key drivers of construction land expansion.