Spatial Agglomeration Pattern and Driving Factors of Grain Production in China since the Reform and Opening Up
Abstract
:1. Introduction
2. Materials and Methods
2.1. Variable Selection
2.2. Data Sources and Regional Distribution
2.3. Model Specification
2.3.1. Standard Deviation Elliptic-Gravity Center Model
2.3.2. Spatial Econometric Models (SEM, SLM)
3. Results
3.1. The Gravity Center and Standard Deviation Ellipses of China’s Grain Production
3.1.1. Overall Grain Production
3.1.2. Wheat Production
3.1.3. Maize Production
3.1.4. Rice Production
3.2. Analysis of the Driving Factors of Grain Production in China
3.2.1. Spatial Correlation Test and Econometric Model Selection
3.2.2. At the Level of GP and Different Crops
3.2.3. At the Level of Different Regions
4. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable/Unit | Variable Definition | ||
---|---|---|---|
Explained variable | grain production (GP)/million tons | Production of food and three crops (wheat, maize, rice) | |
Explanatory variables | Natural conditions | temperature(TEM)/°C | air temperature measured in the field when the air is circulated without direct sunlight |
precipitation (PRE)/mm | the depth at which rainfall accumulates on the horizontal plane without evaporation, infiltration and loss | ||
sunshine hours (SUN)/h | the time of the day when direct sunlight hits the ground | ||
grain disaster area (GDA)/khm2 | Food sown area × (disaster area of crops/crops total sown area) | ||
Socio-economic environment | economic growth (pGDP)/yuan RMB | GDP per capita | |
urbanization (URBAN)/% | Urbanization rate of the resident population | ||
rural labor transfer (RLT)/ten thousand people | (Rural workers—agriculture, forestry and fishery workers) × (food sown area/crops total sown area) | ||
non-farm income (NFI)/% | Wage income per capita/net income per capita | ||
Other conditions | arable land resources (AL)/(Mu/person) | arable land resources per capita = arable land area/rural population | |
multiple cropping index (MCI)/% | crops total sown area/cultivated area | ||
agricultural mechanization (MECH)/(kW/person) | Total power of agricultural machinery/agriculture, forestry and fishery workers × (sown area of grain/total sown area of farm) | ||
transportation conditions (TRANS)/(m/km2) | Mileage of land transport (road + railway)/land area | ||
agricultural policy adjustment (APA) | Dummy variables: 0 before 1993, 1 after 1993 |
Variables | GP | Wheat | Maize | Rice | Variables | GP | Wheat | Maize | Rice |
---|---|---|---|---|---|---|---|---|---|
SEM | SEM | SEM | SLM | SEM | SEM | SEM | SLM | ||
lnTEM | 0.131 (0.90) | −0.317 (−1.35) | −0.101 (−0.69) | 0.270 *** (4.55) | lnMCI | 0.693 *** (4.73) | 0.843 *** (2.96) | 0.684 *** (4.81) | 0.631 *** (4.09) |
lnPRE | 0.089 * (1.71) | −0.025 (−0.19) | 0.128 ** (2.21) | −0.009 (−0.33) | lnMECH | 0.258 *** (3.87) | 0.442 (1.32) | 0.209 ** (2.13) | 0.211 *** (3.88) |
lnSUN | 0.080 (0.59) | 0.526 (0.81) | 0.222 (1.05) | −0.132 (−1.56) | lnTRANS | 0.049 (0.45) | 0.452 (1.56) | 0.093 (0.85) | −0.040 (−0.63) |
lnGDA | 0.016 (0.83) | 0.059 (0.76) | 0.018 (0.64) | −0.011 (−0.80) | lnAPA | 0.141 * (1.78) | 0.459 (1.23) | 0.142 (1.63) | 0.082 *** (2.74) |
lnpGDP | −0.192 ** (−2.09) | −0.535 ** (−2.06) | −0.149 (−1.27) | −0.165 *** (−4.05) | ρ/λ | 0.550 *** (7.26) | 0.656 *** (7.48) | 0.467 *** (6.84) | 0.399 *** (4.79) |
lnURBAN | −0.151 ** (−2.31) | 0.272 (0.43) | −0.261 ** (−2.22) | −0.062 (−0.79) | R2 | 0.643 | 0.415 | 0.648 | 0.636 |
lnRLT | 0.114 *** (4.30) | −0.466 (−0.90) | 0.115 *** (4.25) | 0.115 *** (3.75) | Sigma2 | 0.017 *** (6.15) | 0.183 ** (2.22) | 0.018 *** (5.69) | 0.014 *** (6.89) |
lnNFI | −0.004 (−0.09) | 0.092 (0.49) | −0.073 (−1.10) | 0.019 (0.77) | LogL | 580.81 | −427.03 | 414.15 | 468.95 |
lnAL | 0.382 *** (3.54) | 0.180 (1.62) | 0.437 *** (3.36) | 0.211 ** (2.19) | AIC | −1131.62 | 884.06 | −798.29 | −907.89 |
Variables | South and North | Six Agricultural Zones | ||||||
---|---|---|---|---|---|---|---|---|
North: SEM | South: SLM | NEC: SEM | NC: SEM | NWC: POLS | SWC: SLM | MLY: SLM | SEC: POLS | |
lnTEM | −0.165 (−1.14) | 0.112 (0.37) | 0.125 (1.30) | 0.055 (0.23) | −0.352 *** (−5.95) | −0.389 *** (−3.01) | 0.169 (1.08) | −0.151 (−0.37) |
lnPRE | 0.176 *** (3.22) | −0.039 (−1.02) | −0.066 (−0.90) | 0.206 ** (2.34) | 0.130 ** (2.16) | 0.084 *** (2.73) | −0.113 *** (−3.66) | 0.036 (0.54) |
lnSUN | 0.456 * (1.86) | −0.044 (−0.47) | −0.628 (−1.54) | 0.206 (0.71) | 0.055 (0.19) | −0.006 (−0.03) | −0.115 * (−1.85) | −0.044 (−0.32) |
lnGDA | 0.013 (0.68) | 0.009 (0.73) | −0.069 ** (−2.24) | −0.008 (−0.60) | 0.059 (1.53) | −0.027 ** (−2.54) | 0.0162 (0.80) | −0.009 (−0.62) |
lnpGDP | −0.075 (−0.69) | −0.214 *** (−4.40) | −0.068 (−0.59) | −0.148 * (−1.78) | 0.051 (1.13) | 0.070 (1.64) | −0.237 *** (−6.76) | −0.075 ** (−2.05) |
lnURBAN | −0.369 ** (−2.37) | −0.192 ** (−2.24) | −0.085 (−0.49) | −0.310 ** (−2.32) | −0.706 *** (−9.22) | −0.287 *** (−8.62) | 0.061 (0.34) | −0.153 ** (−2.52) |
lnRLT | 0.168 ** (2.48) | 0.088 *** (3.25) | 0.082 * (1.78) | 0.274 ** (2.01) | 0.171 *** (3.98) | 0.074 *** (7.66) | 0.126 ** (2.41) | 0.168 *** (3.59) |
lnNFI | −0.079 (−1.20) | −0.010 (−0.29) | −0.026 (−0.35) | −0.085 (−0.97) | −0.109 ** (−2.22) | 0.126 (1.43) | 0.048 (0.68) | −0.011 (−0.44) |
lnAL | 0.667 *** (4.74) | 0.155 * (1.83) | 0.719 *** (7.36) | 0.728 *** (5.40) | 0.424 *** (7.30) | 0.170 *** (3.17) | 0.269 (1.42) | 0.077 (1.48) |
lnMCI | 0.910 *** (5.73) | 0.603 *** (3.51) | 1.071 *** (7.31) | 0.901 *** (5.20) | 0.336 *** (2.65) | 0.291 *** (5.39) | 0.087 (0.65) | 0.607 *** (8.17) |
lnTECH | 0.177 * (1.69) | 0.296 *** (7.19) | 0.182 *** (9.55) | 0.192 * (1.92) | 0.454 *** (5.58) | −0.248 ** (−2.16) | 0.261 *** (4.32) | −0.065 (−1.02) |
lnBCT | 0.061 (0.64) | −0.099 (−1.31) | 0.253 *** (2.66) | 0.087 (0.69) | −0.122 ** (−2.39) | −0.009 (−0.02) | −0.140 *** (−3.08) | −0.305 *** (−5.46) |
lnAPA | 0.119 (1.57) | 0.118 *** (3.09) | 0.116 ** (2.35) | 0.109 ** (2.15) | −0.019 (−0.40) | 0.017 (0.36) | 0.079 ** (2.15) | 0.081 ** (2.05) |
C | −0.822 (−0.33) | 0.346 (0.19) | ||||||
ρ/𝜆 | 0.301 *** (4.30) | 0.310 *** (3.99) | 0.284 *** (4.20) | 0.204 *** (3.91) | 0.187 ** (2.41) | 0.274 *** (4.02) | ||
R2 | 0.714 | 0.758 | 0.833 | 0.932 | 0.661 | 0.705 | 0.749 | 0.897 |
Sigma2 | 0.016 *** (6.12) | 0.011 *** (5.93) | 0.007 *** (3.93) | 0.014 *** (4.10) | 0.004 *** (6.63) | 0.006 *** (3.68) | ||
LogL | 333.298 | 434.561 | 105.892 | 167.738 | 182.766 | 235.977 | ||
AIC | −638.596 | −841.122 | −207.783 | −325.477 | −355.532 | −461.954 |
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Hou, M.; Deng, Y.; Yao, S. Spatial Agglomeration Pattern and Driving Factors of Grain Production in China since the Reform and Opening Up. Land 2021, 10, 10. https://doi.org/10.3390/land10010010
Hou M, Deng Y, Yao S. Spatial Agglomeration Pattern and Driving Factors of Grain Production in China since the Reform and Opening Up. Land. 2021; 10(1):10. https://doi.org/10.3390/land10010010
Chicago/Turabian StyleHou, Mengyang, Yuanjie Deng, and Shunbo Yao. 2021. "Spatial Agglomeration Pattern and Driving Factors of Grain Production in China since the Reform and Opening Up" Land 10, no. 1: 10. https://doi.org/10.3390/land10010010