The Economic Impact of Climate Change on Wheat and Maize Yields in the North China Plain
Abstract
:1. Introduction
2. Theoretical Framework of Multilevel Model
2.1. Unconditional Means Model
2.2. Random Intercept Model
3. Data Source and Empirical Model
3.1. Data Source
3.2. Empirical Model and Variables
4. Results and Analyses
4.1. The Unconditional Means Model
4.2. The Random Intercept Model
4.2.1. The Determinants of Winter Wheat Yield
4.2.2. The Determinants of Summer Maize Yield
5. Conclusions and Discussion
5.1. Conclusions
5.2. Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Province | County | No. of Households | No. of Plots | Disaster Type | Disaster/Normal Year |
---|---|---|---|---|---|
Henan | Yuanyang | 90 | 167 | D | 2011/2012 |
Huanxian | 90 | 160 | D | 2011/2012 | |
Yongcheng | 90 | 176 | D | 2011/2012 | |
Hebei | Weixian | 90 | 164 | D | 2011/2012 |
Yixian | 56 | 93 | F | 2012/2011 | |
Shandong | Lingxian | 90 | 167 | F | 2012/2011 |
Yuncheng | 90 | 174 | D | 2011/2012 | |
Huishan | 90 | 159 | D | 2011/2012 | |
Jiangsu | Xinghua | 89 | 160 | F | 2011/2012 |
Xiangshui | 90 | 171 | F | 2012/2011 | |
Peixian | 81 | 146 | D | 2011/2012 | |
Anhui | Yongqiao | 90 | 175 | D | 2011/2012 |
Suixi | 90 | 172 | D | 2011/2012 | |
Lixin | 90 | 177 | D | 2011/2012 | |
Total | 14 | 1216 | 2261 | - | - |
Province | County | No. of Households | No. of Plots | Disaster Type | Disaster/Normal Year |
---|---|---|---|---|---|
Henan | Yuanyang | 72 | 128 | D | 2011/2012 |
Huanxian | 90 | 159 | D | 2011/2012 | |
Yongcheng | 62 | 113 | D | 2011/2012 | |
Hebei | Weixian | 90 | 164 | D | 2011/2012 |
Yixian | 90 | 162 | F | 2012/2011 | |
Shandong | Lingxian | 90 | 167 | F | 2012/2011 |
Yuncheng | 90 | 172 | D | 2011/2012 | |
Huishan | 90 | 159 | D | 2011/2012 | |
Jiangsu | Xinghua | 11 | 12 | F | 2011/2012 |
Xiangshui | 82 | 89 | F | 2012/2011 | |
Peixian | 63 | 93 | D | 2011/2012 | |
Anhui | Yongqiao | 67 | 119 | D | 2011/2012 |
Suixi | 62 | 106 | D | 2011/2012 | |
Lixin | 69 | 126 | D | 2011/2012 | |
Total | 14 | 1028 | 1769 | - | - |
Crop Growth Stages | Daily Average Temperature (°C/10a) | Average Precipitation (cm/10a) |
---|---|---|
Winter wheat: | ||
Overwintering stage | 0.519 | 0.115 |
Vegetative stage | 0.675 | 0.66 |
Reproductive stage | 0.305 | 1.137 |
Summer maize: | ||
Vegetative stage | 0.319 | 1.601 |
Concurrent stage | 0.153 | 2.25 |
Reproductive stage | 0.229 | 1.229 |
Variables | Definition | Winter Wheat | Summer Maize | ||
---|---|---|---|---|---|
Mean | S.D. | Mean | S.D. | ||
Explained variables: | |||||
Grain yield (Y) | Kg/ha | 6400 | 1176 | 6615 | 1535 |
Explanatory variables: | |||||
The variables of long-run climate change (wheat): | |||||
Daily avg temperature in overwintering stage (Twheat1) | °C | 5.22 | 1.19 | - | - |
Total avg precipitation in overwintering stage (Pwheat1) | cm | 8.40 | 2.89 | - | - |
Daily avg temperature in vegetative stage (Twheat2) | °C | 9.67 | 1.47 | - | - |
Total avg precipitation in vegetative stage (Pwheat2) | cm | 7.64 | 4.05 | - | - |
Daily avg temperature in reproductive stage (Twheat3) | °C | 20.38 | 0.81 | - | - |
Total avg precipitation in reproductive stage (Pwheat3) | cm | 8.53 | 2.46 | - | - |
The variables of long-run climate change (maize): | |||||
Daily avg temperature in vegetative stage (Tmaize1) | °C | - | - | 26.13 | 0.49 |
Total avg precipitation in vegetative stage (Pmaize1) | cm | - | - | 10.73 | 3.56 |
Daily avg temperature in concurrent stage (Tmaize2) | °C | - | - | 27.12 | 0.41 |
Total avg precipitation in concurrent stage (Pmaize2) | cm | - | - | 16.95 | 2.74 |
Daily avg temperature in reproductive stage (Tmaize3) | °C | - | - | 23.33 | 1.20 |
Total avg precipitation in reproductive stage (Pmaize3) | cm | - | - | 16.93 | 3.20 |
Extreme weather events: | |||||
If it occurred drought disaster at the county-level (DD) | 1 = Yes; 0 otherwise | 0.25 | 0.43 | 0.25 | 0.43 |
If it occurred flood disaster at the county-level (DF) | 1 = Yes; 0 otherwise | - | - | 0.08 | 0.27 |
If it occurred drought disaster on farm plot (DLD) | 1 = Yes; 0 otherwise | 0.41 | 0.49 | 0.36 | 0.48 |
If it occurred flood disaster on the farm plot (DLF) | 1 = Yes; 0 otherwise | 0.03 | 0.16 | 0.16 | 0.36 |
If it occurred continuous rain disaster on farm plot (DLR) | 1 = Yes; 0 otherwise | 0.08 | 0.26 | 0.04 | 0.19 |
If it occurred strong wind disaster on farm plot (DLw) | 1 = Yes; 0 otherwise | 0.08 | 0.27 | 0.16 | 0.37 |
Farmland plot characteristics: | |||||
Farmland area (L1) | Hectare | 0.21 | 0.18 | 0.19 | 0.13 |
Farmland topography (L2) | 1 = flat land; 0 = otherwise | 0.98 | 0.14 | 0.06 | 0.24 |
Low quality of farmland (L31) | 1 = Yes; 0 otherwise | 0.11 | 0.31 | 0.12 | 0.33 |
Medium quality of farmland (L32) | 1 = Yes; 0 otherwise | 0.70 | 0.46 | 0.67 | 0.47 |
High quality of farmland (L33) | 1 = Yes; 0 otherwise | 0.19 | 0.39 | 0.21 | 0.41 |
Production inputs: | |||||
Fertilizer cost (I1) | Yuan/ha | 2863.29 | 1246.98 | 2442.79 | 1063.44 |
Pesticide cost (I2) | Yuan/ha | 331.24 | 263.68 | 472.71 | 321.17 |
Machinery cost (I3) | Yuan/ha | 1678.38 | 577.16 | 1248.26 | 800.56 |
Labor input (I4) | Adult days/ha | 36.26 | 34.52 | 60.90 | 63.69 |
Irrigation water (I5) | m3/ha | 1760.88 | 1753.53 | 1730.09 | 2279.84 |
Household’s characteristics: | |||||
Asset of household (H1) | Durable goods (103 yuan) | 9.67 | 19.24 | 9.86 | 19.48 |
Education of household head (H2) | Attending year | 6.91 | 3.19 | 6.93 | 3.11 |
Producing/technical training (H3) | If attending (1 = Yes; 0 otherwise) | 0.27 | 0.45 | 0.24 | 0.42 |
Village’s characteristics | |||||
Collective enterprise (V1) | Number of collective enterprises | 0.08 | 0.55 | 0.13 | 0.768 |
Ratio of irrigation area to total cultivated area (V2) | % | 83.85 | 23.71 | 83.17 | 27.88 |
Distance between the village committee and the nearest road above the township level (V3) | Km | 1.36 | 1.55 | 1.38 | 1.58 |
Year dummy variables: | |||||
2011 (T2011) | 1 = Yes; 0 otherwise | 0.33 | 0.47 | 0.33 | 0.47 |
2012 (T2012) | 1 = Yes; 0 otherwise | 0.33 | 0.47 | 0.33 | 0.47 |
Observations | - | 6749 | 5212 |
Variance Decomposition | Winter Wheat | Summer Maize | ||
---|---|---|---|---|
Coefficient | S.D. | Coefficient | S.D. | |
Variance of village level (between-group variance) | 0.118 | 0.008 | 0.173 | 0.014 |
Variance of household level (within-group variance) | 0.189 | 0.002 | 0.555 | 0.005 |
Intra-class correlation coefficient ρ | 0.384 | - | 0.238 | - |
Variables | Model I | Model II | Model III |
---|---|---|---|
Twheat1 | 0.080 ** (0.032) | 0.079 ** (0.031) | 0.088 *** (0.032) |
Pwheat1 | −0.087 *** (0.025) | −0.088 *** (0.025) | −0.097 *** (0.026) |
Twheat2 | −0.068 * (0.037) | −0.062 * (0.036) | −0.086 ** (0.038) |
Pwheat2 | 0.054 *** (0.021) | 0.052 ** (0.021) | 0.065 *** (0.022) |
Twheat3 | 0.041 (0.032) | 0.036 (0.032) | 0.051 (0.032) |
Pwheat3 | −0.002 (0.015) | 0.005 (0.015) | −0.002 (0.015) |
DD | −0.032 *** (0.011) | −0.033 *** (0.011) | −0.084 *** (0.022) |
DLD | −0.096 *** (0.006) | −0.094 *** (0.006) | −0.197 *** (0.02) |
DLF | −0.057 *** (0.015) | −0.056 *** (0.014) | −0.055 *** (0.014) |
DLR | −0.158 *** (0.01) | −0.161 *** (0.009) | −0.160 *** (0.009) |
DLW | −0.088 *** (0.009) | −0.084 *** (0.009) | −0.086 *** (0.009) |
T2011 | 0.036 *** (0.01) | 0.035 *** (0.009) | 0.034 *** (0.009) |
T2012 | −0.033 *** (0.005) | −0.033 *** (0.005) | −0.033 *** (0.005) |
L1 | − | 0.005 (0.015) | 0.003 (0.015) |
L2 | − | −0.009 (0.016) | −0.010 (0.016) |
L32 | − | 0.06 *** (0.007) | 0.06 *** (0.007) |
L33 | − | 0.083 *** (0.009) | 0.083 *** (0.009) |
ln(I1) | − | 0.007 (0.005) | 0.006 (0.005) |
ln(I2) | − | −0.002 (0.002) | −0.002 (0.002) |
ln(I3) | − | −0.003 (0.006) | −0.003 (0.006) |
ln(I4) | − | −0.016 *** (0.004) | −0.016 *** (0.004) |
ln(I5) | − | 0.004 *** (0.001) | 0.004 *** (0.001) |
H1 | − | 0.0001 (0.0001) | 0.0001 (0.0001) |
H2 | − | 0.002 ** (0.001) | 0.002 ** (0.001) |
H3 | − | 0.012 ** (0.006) | 0.012 ** (0.006) |
V1 | − | − | 0.011 (0.015) |
V2 | − | − | −0.0001 (0.0003) |
V3 | − | − | 0.002 (0.007) |
V1 × DD | − | − | −0.004 (0.009) |
V1 × DLD | − | − | 0.006 (0.009) |
V2 × DD | − | − | 0.001 *** (0.0002) |
V2 × DLD | − | − | 0.001 *** (0.0002) |
V3 × DD | − | − | 0.001 (0.004) |
V3 × DLD | − | − | 0.01 *** (0.004) |
Cons. | 8.542 *** (0.421) | 8.501 *** (0.418) | 8.447 *** (0.415) |
0.106 (0.007) | 0.105 (0.007) | 0.103 (0.007) | |
0.179 (0.002) | 0.177 (0.002) | 0.176 (0.002) | |
Log likelihood | 1836.415 | 1908.163 | 1935.25 |
AIC | −3640.829 | −3760.326 | −3798.5 |
Variables | Model I | Model II | Model III |
---|---|---|---|
Tmaize1 | −0.167 (0.111) | −0.158 (0.107) | −0.167 (0.104) |
Pmaize1 | −0.023 ** (0.011) | −0.013 (0.01) | −0.011 (0.010) |
Tmaize2 | 0.533 *** (0.181) | 0.427 *** (0.173) | 0.453 *** (0.168) |
Pmaize2 | −0.016 * (0.009) | −0.012 (0.008) | −0.013 (0.008) |
Tmaize3 | −0.083 *** (0.03) | −0.047 (0.03) | −0.047 (0.029) |
Pmaize3 | −0.017 (0.012) | −0.013 (0.012) | −0.012 (0.011) |
DD | −0.127 *** (0.041) | −0.13 *** (0.041) | −0.091 (0.080) |
DF | −0.142 *** (0.043) | −0.138 *** (0.043) | −0.165 *** (0.043) |
DLD | −0.136 *** (0.019) | −0.141 *** (0.019) | −0.489 *** (0.056) |
DLF | −0.224 *** (0.027) | −0.219 *** (0.026) | −0.219 *** (0.026) |
DLR | −0.122 *** (0.042) | −0.127 *** (0.042) | −0.133 *** (0.041) |
DLW | −0.098 *** (0.023) | −0.101 *** (0.023) | −0.107 *** (0.023) |
T2011 | 0.149 *** (0.036) | 0.149 *** (0.035) | 0.137 *** (0.035) |
T2012 | 0.151 *** (0.021) | 0.147 *** (0.021) | 0.147 *** (0.021) |
L1 | − | 0.108 (0.069) | 0.094 (0.069) |
L2 | − | 0.001 (0.047) | −0.009 (0.047) |
L32 | − | 0.114 *** (0.024) | 0.106 *** (0.024) |
L33 | − | 0.147 *** (0.028) | 0.145 *** (0.028) |
ln(I1) | − | −0.006 (0.01) | −0.006 (0.010) |
ln(I2) | − | 0.032 *** (0.008) | 0.033 *** (0.008) |
ln(I3) | − | 0.009 (0.007) | 0.011 (0.007) |
ln(I4) | − | −0.036 *** (0.013) | −0.036 *** (0.013) |
ln(I5) | − | 0.018 *** (0.003) | 0.018 *** (0.003) |
H1 | − | 0.0008 * (0.0004) | 0.001 * (0.000) |
H2 | − | 0.003 (0.003) | 0.003 (0.003) |
H3 | − | 0.033 (0.021) | −0.033 (0.020) |
V1 | − | − | −0.028 (0.023) |
V2 | − | − | −0.001 (0.001) |
V3 | − | − | 0.004 (0.011) |
V1 × DD | − | − | 0.128 *** (0.022) |
V1 × DLD | − | − | −0.11 *** (0.021) |
V2 × DD | − | − | −0.001 (0.001) |
V2 × DLD | − | − | 0.005 *** (0.001) |
V3 × DD | − | − | 0.018 (0.012) |
V3 × DLD | − | − | −0.018 (0.012) |
Cons. | 1.449 (2.052) | 2.678 (1.977) | 2.269 (1.93) |
0.152 *** (0.013) | 0.141 *** (0.012) | 0.133 *** (0.012) | |
0.541 *** (0.005) | 0.537 *** (0.005) | 0.532 *** (0.005) | |
Log likelihood | −4281.319 | −4231.07 | −4177.54 |
AIC | 8596.638 | 8520.14 | 8431.08 |
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Song, C.; Huang, X.; Les, O.; Ma, H.; Liu, R. The Economic Impact of Climate Change on Wheat and Maize Yields in the North China Plain. Int. J. Environ. Res. Public Health 2022, 19, 5707. https://doi.org/10.3390/ijerph19095707
Song C, Huang X, Les O, Ma H, Liu R. The Economic Impact of Climate Change on Wheat and Maize Yields in the North China Plain. International Journal of Environmental Research and Public Health. 2022; 19(9):5707. https://doi.org/10.3390/ijerph19095707
Chicago/Turabian StyleSong, Chunxiao, Xiao Huang, Oxley Les, Hengyun Ma, and Ruifeng Liu. 2022. "The Economic Impact of Climate Change on Wheat and Maize Yields in the North China Plain" International Journal of Environmental Research and Public Health 19, no. 9: 5707. https://doi.org/10.3390/ijerph19095707