The Impact of Rural Population Aging on Agricultural Cropping Structure: Evidence from China’s Provinces
Abstract
:1. Introduction
2. Theoretical Analysis and Research Hypotheses
3. Data Sources and Variable Settings
3.1. Model Setup
3.1.1. Two-Way Fixed Effects Model
3.1.2. Moderating Effects Test
3.2. Variable Selection and Data Description
- 1.
- Explained variable: agricultural cultivation structure, measured using the ratio of area sown under grain crops to total area sown under crops and the ratio of area sown under cash crops to total area sown under crops together, i.e., the ratio of area planted to grain crops and the ratio of area planted to cash crops. Meanwhile, grain crops investigate the cropping structure of rice, wheat and corn, and cash crops mainly investigate the cropping structure of oil crops and vegetables. The data for this indicator comes from the China Rural Statistics Yearbook.
- 2.
- Core explanatory variable: level of aging of the rural population, measured by the ratio of the total number of people aged 65 and above to the total population in rural areas, with data from the China Population and Employment Statistical Yearbook of past years.
- 3.
- Moderating variables: the development level of agricultural mechanization. First, the comprehensive mechanization rate of agriculture in province i (autonomous regions and municipalities directly under the central government) in year t is used to reflect the level of full-scale mechanized operation, calculated according to the formula (ploughing rate × 40% + sowing rate × 30% + harvesting rate × 30%); second, indicators of the rate of ploughing, sowing, and harvesting are used, expressed as the ratios of the area of mechanized ploughing, sowing, and harvesting to the total area of sowing of crops, respectively, to reflect the level of mechanized operation of different production segments. mechanized operation level of different production stages. The data for this indicator are from the China Agricultural Machinery Industry Yearbook.
- 4.
- Control variables. Referring to the existing studies [39,41], the control variables include the income level of rural residents (per capita disposable income of rural residents), the proportion of agricultural employment (number of people employed in the primary industry/total employment of the whole society), the effective irrigation area, the amount of fertilizer applied to agriculture (discounted amount of fertilizer applied to agriculture), the financial support to agriculture (financial expenditures on agriculture, forestry, and water), the proportion of crops affected by disasters (crop affected area/total sown area of crops), agricultural policy, all the above indicators are from the China Rural Statistical Yearbook.
4. Results and Analysis
4.1. Baseline Regression
4.2. Robustness Check
4.3. Heterogeneity Analysis
4.3.1. Analysis of Crop Variety Heterogeneity
4.3.2. Analysis of Regional Heterogeneity
4.4. Mechanism Testing
5. Discussion and Conclusions
5.1. Discussion
5.1.1. Similarities and Differences with Existing Studies
5.1.2. Limitations and Future Recommendations
5.2. Conclusions and Policy Recommendations
5.2.1. Conclusions
5.2.2. Policy Recommendations
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
Appendix A
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Aging rural population | 0.5198 *** (0.1648) | 0.3996 *** (0.1296) | −1.7478 *** (0.2268) | −0.7443 *** (0.2210) |
Comprehensive mechanization rate | 0.2347 *** (0.1261) | −0.3068 *** (0.0432) | ||
Mechanized plowing rate | −0.1647 *** (0.0169) | −0.1823 *** (0.0340) | ||
Mechanized seeding rate | 0.3174 *** (0.0299) | 0.1980 *** (0.0402) | ||
Mechanized harvesting rate | 0.0178 (0.0176) | −0.0434 * (0.0231) | ||
Rural population aging × Comprehensive mechanization rate | 3.8311 *** (0.3363) | |||
Rural population aging × Mechanized plowing rate | 0.5945 ** (0.2550) | |||
Rural population aging × Mechanized seeding rate | 0.6775 * (0.3496) | |||
Rural population aging × Mechanized harvesting rate | 0.6973 * (0.3816) | |||
Proportion of agricultural employment | 0.0998 ** (0.0386) | 0.0302 (0.0360) | −0.0060 (0.0318) | −0.0176 (0.0327) |
Agricultural fertilizer application | −0.0166 (0.0167) | −0.0597 *** (0.0106) | −0.0200 (0.0150) | −0.0540 *** (0.0097) |
Effective irrigation area | 0.0114 (0.0220) | 0.0334 ** (0.0163) | −0.0047 (0.0180) | 0.0211 (0.0151) |
Proportion of crops affected by disasters | −0.0134 (0.0160) | 0.0188 * (0.0114) | 0.0038 (0.0156) | 0.0240 ** (0.0120) |
Income level of rural residents | −0.0455 (0.0464) | 0.0130 * (0.0076) | 0.0704 * (0.0413) | 0.0163 ** (0.0080) |
Financial support for agriculture | −0.0206 *** (0.0037) | −0.0080 *** (0.0027) | −0.0144 *** (0.0032) | −0.0065 ** (0.0027) |
Agricultural policy | −0.0195 (0.0285) | −0.0224 (0.0241) | −0.0329 (0.0214) | −0.0270 (0.0217) |
Constant | 0.9702 ** (0.4020) | 0.3386 *** (0.1009) | 0.3017 (0.3522) | 0.4923 *** (0.1035) |
Province-fixed effects | Yes | Yes | Yes | Yes |
Year-fixed effects | Yes | Yes | Yes | Yes |
Observations | 650 | 680 | 650 | 680 |
R2 | 0.8875 | 0.9347 | 0.9133 | 0.9419 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Rural population aging | −0.3502 ** (0.1738) | −0.1412 (0.1594) | 1.8397 *** (0.3051) | 1.1288 *** (0.3081) |
Comprehensive mechanization rate | −0.2277 ** (0.0646) | 0.3012 *** (0.0526) | ||
Mechanized plowing rate | 0.1571 *** (0.0173) | 0.1992 *** (0.0388) | ||
Mechanized seeding rate | −0.2666 *** (0.0312) | −0.1016 ** (0.0446) | ||
Mechanized harvesting rate | −0.0297 (0.0184) | −0.0341 (0.0305) | ||
Rural population aging × Comprehensive mechanization rate | −3.6998 *** (0.4192) | |||
Rural population aging × Mechanized plowing rate | −0.9442 *** (0.3104) | |||
Rural population aging × Mechanized seeding rate | −1.3336 *** (0.3573) | |||
Rural population aging × Mechanized harvesting rate | 0.2460 (0.4073) | |||
Proportion of agricultural employment | −0.1146 ** (0.0448) | −0.0424 (0.0411) | −0.0124 (0.0405) | 0.0395 (0.0430) |
Agricultural fertilizer application | 0.0447 ** (0.0225) | 0.0765 *** (0.0209) | 0.0480 ** (0.0213) | 0.0725 *** (0.0209) |
Effective irrigation area | −0.0189 (0.0214) | −0.0473 *** (0.0176) | −0.0034 (0.0184) | −0.0337 * (0.0175) |
Proportion of crops affected by disasters | 0.0131 (0.0201) | −0.0106 (0.0176) | −0.0036 (0.0205) | −0.0202 (0.0180) |
Income level of rural residents | −0.0096 (0.0471) | −0.0288 (0.0253) | −0.1216 *** (0.0442) | −0.0296 (0.0261) |
Financial support for agriculture | 0.0122 *** (0.0042) | 0.0005 (0.0032) | 0.0062 (0.0038) | −0.0003 (0.0033) |
Agricultural policy | 0.0389 (0.0618) | 0.0384 (0.0599) | 0.0519 (0.0546) | 0.0451 (0.0576) |
Constant | 0.4126 (0.4058) | 0.7508 *** (0.2248) | 1.0581 *** (0.3722) | 0.5433 ** (0.2234) |
Province-fixed effects | Yes | Yes | Yes | Yes |
Year-fixed effects | Yes | Yes | Yes | Yes |
Observations | 650 | 679 | 650 | 679 |
R2 | 0.8025 | 0.8516 | 0.8360 | 0.8625 |
References
- Andrews, R.; Dollery, B. Guest editors’ introduction: The impact of aging and demographic change on local government. Local Gov. Stud. 2021, 47, 355–363. [Google Scholar] [CrossRef]
- Choi, K.H.; Shin, S. Population aging, economic growth, and the social transmission of human capital: An analysis with an overlapping generations model. Econ. Model. 2015, 50, 138–147. [Google Scholar] [CrossRef]
- Milovanovic, V.; Smutka, L. Populating Aging in Rural India: Implication for Agriculture and Smallholder Farmers. J. Popul. Aging 2020, 13, 305–323. [Google Scholar] [CrossRef]
- Saiyut, P.; Bunyasiri, I.; Sirisupluxana, P.; Mahathanaseth, I. The impact of age structure on technical efficiency in Thai agriculture. Kasetsart J. Soc. Sci. 2019, 40, 539–545. [Google Scholar] [CrossRef]
- Burholt, V.; Dobbs, C. Research on rural aging: Where have we got to and where are we going in Europe? J. Rural Stud. 2012, 28, 432–446. [Google Scholar] [CrossRef]
- Xu, D.; Shang, Y.F.; Yang, Q.; Chen, H. Population aging and eco-tourism efficiency: Ways to promote green recovery. Econ. Anal. Policy 2023, 79, 1–9. [Google Scholar] [CrossRef]
- Guimaraes, S.D.; Tiryaki, G.F. The impact of population aging on business cycles volatility: International evidence. J. Econ. Aging 2020, 17, 100285. [Google Scholar] [CrossRef]
- Sander, M.; Oxlund, B.; Jespersen, A.; Krasnik, A.; Mortensen, E.L.; Westendorp, R.G.J.; Rasmussen, L.J. The challenges of human population aging. Age Aging 2015, 44, 185–187. [Google Scholar] [CrossRef]
- Yang, X.Y.; Li, N.; Mu, H.L.; Ahmad, M.; Meng, X.Y. Population aging, renewable energy budgets and environmental sustainability: Does health expenditures matter? Gondwana Res. 2022, 106, 303–314. [Google Scholar] [CrossRef]
- de Albuquerque, P.C.A.M.; Caiado, J.; Pereira, A. Population aging and inflation: Evidence from panel cointegration. J. Appl. Econ. 2020, 23, 469–484. [Google Scholar] [CrossRef]
- Lee, H.-H.; Shin, K. Nonlinear effects of population aging on economic growth. Jpn. World Econ. 2019, 51, 100963. [Google Scholar] [CrossRef]
- Bai, C.; Lei, X. New trends in population aging and challenges for China’s sustainable development. China Econ. J. 2020, 13, 3–23. [Google Scholar] [CrossRef]
- Wang, S. Spatial patterns and social-economic influential factors of population aging: A global assessment from 1990 to 2010. Soc. Sci. Med. 2020, 253, 112963. [Google Scholar] [CrossRef]
- Hsu, M.; Liao, P.-J.; Zhao, M. Demographic change and long-term growth in China: Past developments and the future challenge of aging. Rev. Dev. Econ. 2018, 22, 928–952. [Google Scholar] [CrossRef]
- Li, S.; Lin, S. Population aging and China’s social security reforms. J. Policy Model. 2016, 38, 65–95. [Google Scholar] [CrossRef]
- Wu, F.; Yang, H.; Gao, B.; Gu, Y. Old, not yet rich? The impact of population aging on export upgrading in developing countries. China Econ. Rev. 2021, 70, 101707. [Google Scholar] [CrossRef]
- Peng, X. Coping with population aging in mainland China. Asian Popul. Stud. 2021, 17, 1–6. [Google Scholar] [CrossRef]
- Ye, C.S.; Ma, Y. How does human capital and its fit with technological progress affect the structure of agricultural cultivation? China Rural Econ. 2020, 4, 34–55. [Google Scholar]
- Population aging in China: Crisis or opportunity? Lancet 2022, 400, 1821. [CrossRef]
- Gu, H.; He, Y.; Wang, B.; Qian, F.; Wu, Y. The Influence of Aging Population in Rural Families on Farmers’ Willingness to Withdraw from Homesteads in Shenyang, Liaoning Province, China. Land 2023, 12, 1716. [Google Scholar] [CrossRef]
- Wang, H.; Yang, Q.X. 70 years of demographic change and the challenges of aging in new China: A review of literature and policy studies. MacroQual. Res. 2019, 7, 30–54. [Google Scholar]
- Li, L.; Li, Y. Research on the aging of China’s agricultural labor force: An analysis based on data from the second national agricultural census. Probl. Agric. Econ. 2009, 30, 61–66+111. [Google Scholar]
- Liao, L.; Long, H.; Gao, X.; Ma, E. Effects of land use transitions and rural aging on agricultural production in China’s farming area: A perspective from changing labor employing quantity in the planting industry. Land Use Policy 2019, 88, 104152. [Google Scholar] [CrossRef]
- Ji, D.Y.; Ma, X.L.; Shi, X. Impact of aging on agricultural planting structure and its influence mechanism: An analysis based on the literature. Res. Aging Sci. 2022, 10, 52–67. [Google Scholar]
- Zhou, X.; Feng, W. Investigating the Impact of Demographic and Personal Variables on Post-Retirement Migration Intention of Rural Residents: Evidence from Inner Mongolia, China. Sustainability 2023, 15, 14050. [Google Scholar] [CrossRef]
- Ma, Y.; Gao, Q.; Yang, X. Aging of rural labor force and upgrading of agricultural industrial structure: Theoretical mechanisms and empirical tests. J. Huazhong Agric. Univ. (Soc. Sci. Ed.) 2023, 2, 69–79. [Google Scholar]
- Luo, F.M. The impact of demographic transition on the adjustment of agricultural planting structure. J. Yunnan Agric. Univ. (Soc. Sci.) 2022, 16, 60–65. [Google Scholar]
- Jiang, C.Y.; Du, Z.X. Reflections on promoting structural reform of agricultural supply side. J. Nanjing Agric. Univ. (Soc. Sci. Ed.) 2017, 17, 1–10+144. [Google Scholar]
- Lin, J.Y. New structural economics: A framework of studying government and economics. J. Gov. Econ. 2021, 2, 100014. [Google Scholar] [CrossRef]
- Lin, J.Y. State-owned enterprise reform in China: The new structural economics perspective. Struct. Chang. Econ. Dyn. 2021, 58, 106–111. [Google Scholar] [CrossRef]
- Lin, J.Y.; Xu, J. Rethinking industrial policy from the perspective of new structural economics. China Econ. Rev. 2018, 48, 155–157. [Google Scholar] [CrossRef]
- Lin, Y.F. New Structural Economics—Reconstructing the Framework of Development Economics. China Econ. Q. 2011, 10, 1–32. [Google Scholar]
- Jiang, Y.; Chang, F. Influence of aging trend on consumption rate of rural residents—Empirical analysis based on provincial panel data. Asian Agric. Res. 2018, 10, 1–7. [Google Scholar]
- Shao, X.; Yang, Y. A Study of Population Aging and Urban–Rural Residents’ Consumption Habits from a Spatial Spillover Perspective: Evidence from China. Sustainability 2023, 15, 16353. [Google Scholar] [CrossRef]
- Li, Q.; Han, H.; Li, C.; Li, C.X. Aging, terrain differences and farmers’ planting decisions. Econ. Rev. 2019, 6, 97–108. [Google Scholar]
- Ma, Y.T.; Gao, G. Research on the impact of agricultural mechanization on agricultural planting structure under the perspective of grain security. Mod. Econ. Discuss. 2023, 10, 98–111. [Google Scholar]
- Jiang, Y.; Wang, X.; Huo, M.; Chen, F.; He, X. Changes of planting structure lead diversity decline in China during 1985–2015. J. Environ. Manag. 2023, 346, 119051. [Google Scholar] [CrossRef]
- Wang, X.; Zhao, D. Study on the Causes of Differences in Cropland Abandonment Levels among Farming Households Based on Hierarchical Linear Model-13,120 Farming Households in 26 Provinces of China as an Example. Land 2023, 12, 1791. [Google Scholar] [CrossRef]
- Wei, J.Y.; Han, L.Y. Impact of rural demographic changes on crop planting structure: A comprehensive FGSL estimation based on panel data from China’s main grain producing areas. Rural. Econ. 2019, 3, 55–63. [Google Scholar]
- Li, L.; Khan, S.U.; Guo, C.; Huang, Y.; Xia, X. Non-agricultural labor transfer, factor allocation and farmland yield: Evidence from the part-time peasants in Loess Plateau region of Northwest China. Land Use Policy 2022, 120, 106289. [Google Scholar] [CrossRef]
- Wang, S.G.; Tian, X. A study on the impact of aging rural labor force on agricultural production—An empirical analysis based on cropland topography. Agric. Technol. Econ. 2018, 4, 15–26. [Google Scholar]
- Ji, Y.; Hu, X.; Zhu, J.; Zhong, F. Demographic change and its impact on farmers’ field production decisions. China Econ. Rev. 2017, 43, 64–71. [Google Scholar] [CrossRef]
- Zhang, Y.; Li, X.; Song, W. Determinants of cropland abandonment at the parcel, household and village levels in mountain areas of China: A multi-level analysis. Land Use Policy 2014, 41, 186–192. [Google Scholar] [CrossRef]
- Zou, B.; Mishra, A.K.; Luo, B. Aging population, farm succession, and farmland usage: Evidence from rural China. Land Use Policy 2018, 77, 437–445. [Google Scholar] [CrossRef]
- Potter, C.; Lobley, M. Aging and succession on family farms: The impact on decision-making and land use. Sociol. Rural. 1992, 32, 317–334. [Google Scholar] [CrossRef]
- Hu, X.Z.; Zhong, F.N. Impact of population aging on plantation production—An analysis based on wheat and cotton crops. Probl. Agric. Econ. 2013, 34, 36–43+110. [Google Scholar]
- Yang, J.; Zhong, F.N.; Chen, Z.G.; Peng, C. Impacts of rural labor prices and demographic changes on the structure of grain cultivation. Manag. World 2016, 1, 78–87. [Google Scholar]
- Liu, Y.; Li, Y. Revitalize the world’s countryside. Nature 2017, 548, 275–277. [Google Scholar] [CrossRef]
- Prettner, K. Population aging and endogenous economic growth. J. Popul. Econ. 2013, 26, 811–834. [Google Scholar] [CrossRef]
- Zhang, X. Study on employment structure of rural labors. Chin. Rural Econ. 2000, 10, 68–72. [Google Scholar]
- Liu, T. Super-aging and social security for the most elderly in China. Z. Gerontol. Geriatr. 2018, 51, 105–112. [Google Scholar] [CrossRef]
- Pecchenino, R.A.; Utendorf, K.R. Social security, social welfare and the aging population. J. Popul. Econ. 1999, 12, 607–623. [Google Scholar] [CrossRef]
- Chen, Q.; Chi, Q.; Chen, Y.; Lyulyov, O.; Pimonenko, T. Does Population Aging Impact China’s Economic Growth? Int. J. Environ. Res. Public Health 2022, 19, 12171. [Google Scholar] [CrossRef]
- Hashimoto, K.-I.; Tabata, K. Population aging, health care, and growth. J. Popul. Econ. 2010, 23, 571–593. [Google Scholar] [CrossRef]
- Zhang, H. Employment Structural Adjustment & The Chinese Rural Laaborer’s Full Employment. Issues Agric. Econ. 2003, 7, 10–15. [Google Scholar]
- Liu, S.; Zhu, M.; Ling, W. Research on the impact of population aging and endowment insurance on household financial asset allocation- Evidence on CFPS data. Financ. Res. Lett. 2023, 54, 103719. [Google Scholar] [CrossRef]
- Zhang, J. The effects of plant structure adjustment on agriculture water use in plain area of Ningxia. J. Arid Land Resour. Environ. 2012, 26, 57–61. [Google Scholar]
- De Brauw, A.; Rozelle, S. Migration and household investment in rural China. China Econ. Rev. 2008, 19, 320–335. [Google Scholar] [CrossRef]
- Li, H. Effects of agricultural mechanization on agricultural production in Guangdong Province. J. Jilin Agric. Univ. 2010, 32, 575–578. [Google Scholar]
- Zhang, C.; Peng, C.; Mao, X. Off-farm Employment, Agricultural Mechanization and Adjustment of Agricultural Planting Structure. China Soft Sci. 2022, 6, 62–71. [Google Scholar]
- Kuang, Y.P.; Peng, Y. Research on the impact of farmland transfer on the level of agricultural mechanization—An empirical test based on a dynamic panel model. Science Decision. Sci. Decis. Mak. 2023, 9, 124–137. [Google Scholar]
- Luo, Q.; Liu, Y.; Tang, H.; Zhou, Z.; You, F.; Gao, M. Strategic Study on Agricultural Structure Adjustment in China in the New Era. Strateg. Study CAE 2018, 20, 31–38. [Google Scholar] [CrossRef]
- Hou, M.; Hao, J.; Li, X.; Qin, L. Agricultural structure adjustment and mode in Huang-Huai-Hai plain. Trans. Chin. Soc. Agric. Eng. 2004, 20, 286–291. [Google Scholar]
- Liu, C.K. The nonlinear impact of rural population aging on agricultural mechanization—An empirical analysis based on a panel threshold model. J. Xiangtan Univ. (Philos. Soc. Sci. Ed.) 2022, 46, 51–57. [Google Scholar]
- Chen, F.; Wu, L.; Qin, X. Intrinsic driving force and trend of planting structure adjustment in the suburban area in North China Plain. J. China Agric. Univ. 2003, 8, 51–54. [Google Scholar]
- Chen, T.; Yang, J.Y.; Chen, C.P. Mechanism and path of agricultural mechanization to promote farmers’ income increase: Based on the separability of agricultural production chain. J. Huazhong Agric. Univ. (Soc. Sci. Ed.) 2022, 4, 129–140. [Google Scholar]
- Caulfield, M.; Bouniol, J.; Fonte, S.J.; Kessler, A. How rural out-migrations drive changes to farm and land management: A case study from the rural Andes. Land Use Policy 2019, 81, 594–603. [Google Scholar] [CrossRef]
- Luo, B.L.; Zhang, L.; Qiu, T.W. The Logic of Small Farmers’ Grain Growing-The Transformation of China’s Agricultural Cultivation Structure in the Past 40 Years and Future Strategies. South. Econ. 2018, 8, 1–28. [Google Scholar]
- Li, M.; Zhao, L.G. The phenomenon of “aging” of agricultural labor force and its impact on agricultural production: An empirical analysis based on Liaoning Province. Probl. Agric. Econ. 2009, 30, 12–18+110. [Google Scholar]
- Shi, S.; Han, Y.; Yu, W.; Cao, Y.; Cai, W.; Yang, P.; Wu, W.; Yu, Q. Spatio-temporal differences and factors influencing intensive cropland use in the Huang-Huai-Hai Plain. J. Geogr. Sci. 2018, 28, 1626–1640. [Google Scholar] [CrossRef]
Variables | Definition | Mean | SD | |
---|---|---|---|---|
Explanatory variables | Aging rural population | Population over 65 years old/total population (%) | 0.106 | 0.039 |
Explained variables | Proportion of grain crops planted | Grain crops sown area/total sown area of crops (%) | 0.661 | 0.133 |
Proportion of rice planted | Rice sown area/total sown area of crops (%) | 0.311 | 0.303 | |
Proportion of wheat planted | Wheat sown area/total sown area of crops (%) | 0.200 | 0.172 | |
Proportion of corn planted | Corn sown area/total sown area of crops (%) | 0.272 | 0.215 | |
Proportion of cash crops planted | Cash crops sown area/total sown area of crops (%) | 0.271 | 0.112 | |
Proportion of oil crops planted | Oil crops sown area/total sown area of crops (%) | 0.083 | 0.090 | |
Proportion of vegetables planted | Vegetable sown area/total sown area of crops (%) | 0.135 | 0.090 | |
Moderator variables | Comprehensive mechanization rate | Full mechanical operation level (%) | 0.452 | 0.231 |
Mechanized plowing rate | Machine plowed area/total sown area of crops (%) | 0.582 | 0.242 | |
Mechanized seeding rate | Machine seeded area/total sown area of crops (%) | 0.388 | 0.308 | |
Machine harvesting rate | Machine harvested area/total sown area of crops (%) | 0.365 | 0.267 | |
Control variables | Income level of rural residents | Per capita disposable income of rural residents (in millions of dollars) | 0.857 | 0.641 |
Proportion of agricultural employment | Employment in primary industry/total employment in the whole society (%) | 0.555 | 0.166 | |
Effective irrigation area | Effective irrigation area (million hectares) | 197.233 | 154.873 | |
Agricultural fertilizer application | Discounted amount of agricultural fertilizers applied (million tons) | 159.567 | 138.194 | |
Financial support for agriculture | Financial Expenditure on Agriculture, Forestry and Water Affairs (billions of dollars) | 450.654 | 295.602 | |
Proportion of crops affected by disasters | Crop-affected area/total sown area of crops (%) | 0.222 | 0.171 | |
Agricultural policy | Yes = 1, No = 0 | 0.773 | 0.419 |
Proportion of Grain Crops Planted | Proportion of Cash Crops Planted | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
Aging rural population | 0.731 *** (4.57) | 0.634 *** (4.12) | −0.378 * (−2.21) | −0.345 * (−2.09) |
Proportion of agricultural employment | 0.103 ** (3.03) | −0.103 * (−2.52) | ||
Agricultural fertilizer application | −0.0229 (−1.69) | 0.0425 (1.95) | ||
Effective irrigation area | 0.0186 (0.89) | −0.0330 (−1.56) | ||
Proportion of crops affected by disasters | −0.00443 (−0.32) | 0.00987 (0.54) | ||
Income level of rural residents | 0.0172 (1.47) | −0.0321 (−1.43) | ||
Financial support for agriculture | −0.0213 *** (−6.05) | 0.0121 ** (3.00) | ||
Agricultural policy | −0.0211 (−0.79) | 0.0367 (0.59) | ||
Constant | 0.576 *** (24.86) | 0.418 ** (2.92) | 0.336 *** (12.48) | 0.679 ** (3.06) |
Province-fixed effects | Yes | Yes | Yes | Yes |
Year-fixed effects | Yes | Yes | Yes | Yes |
R2 | 0.8887 | 0.887 | 0.8072 | 0.797 |
Observations | 681 | 680 | 680 | 679 |
Proportion of Grain Crops Planted | Proportion of Cash Crops Planted | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
Rural elderly dependency ratio | 0.00348 *** (4.88) | 0.00360 *** (5.16) | −0.00302 *** (−3.55) | −0.00313 *** (−3.51) |
Proportion of agricultural employment | 0.0823 * (2.13) | −0.0918 * (−2.35) | ||
Agricultural fertilizer application | −0.0255 (−1.89) | 0.0430 * (2.02) | ||
Effective irrigation area | 0.0226 (1.07) | −0.0387 (−1.84) | ||
Proportion of crops affected by disasters | 0.00103 (0.08) | 0.0047 (0.26) | ||
Income level of rural residents | 0.0044 (0.34) | −0.0154 (−0.66) | ||
Financial support for agriculture | −0.0208 *** (−4.38) | 0.0114 ** (2.84) | ||
Agricultural policy | −0.0353 (−1.34) | 0.0528 (0.87) | ||
Constant | 0.556 *** (21.84) | 0.500 *** (3.40) | 0.372 *** (15.95) | 0.602 ** (2.76) |
Province-fixed effects | Yes | Yes | Yes | Yes |
Year-fixed effects | Yes | Yes | Yes | Yes |
R2 | 0.8895 | 0.8994 | 0.8121 | 0.8201 |
Observations | 681 | 680 | 680 | 679 |
Proportion of Wheat Planted | Proportion of Maize Planted | Proportion of Rice Planted | |
---|---|---|---|
(1) | (2) | (3) | |
Aging rural population | −0.0232 (−0.20) | 0.145 (1.45) | −0.0191 (−0.16) |
Proportion of agricultural employment | −0.0245 (−0.48) | 0.0558 (1.69) | 0.234 *** (4.13) |
Agricultural fertilizer application | −0.00413 (−0.37) | 0.0879 *** (8.51) | −0.0483 *** (−4.88) |
Effective irrigation area | 0.0175 (1.35) | −0.0449 * (−2.27) | 0.0733 *** (9.09) |
Proportion of crops affected by disasters | 0.0214 (1.81) | −0.0477 *** (−3.48) | −0.0150 (−1.57) |
Income level of rural residents | 0.00334 (0.38) | 0.0152 (1.71) | −0.0226 ** (−2.78) |
Financial support for agriculture | −0.0174 *** (−5.26) | −0.00358 (−1.12) | 0.00471 (1.42) |
Agricultural policy | −0.00365 (−0.21) | 0.0124 (0.76) | 0.00175 (0.12) |
Constant | 0.231 ** (2.69) | 0.470 *** (4.15) | −0.159 * (−2.06) |
Province-fixed effects | Yes | Yes | Yes |
Year-fixed effects | Yes | Yes | Yes |
R2 | 0.9679 | 0.9732 | 0.9923 |
Observations | 658 | 680 | 658 |
Proportion of Vegetables Planted (1) | Proportion of Oilseed Planted (2) | |
---|---|---|
Rural population aging | −0.228 ** (−2.44) | 0.169 *** (2.83) |
Proportion of agricultural employment | −0.108 *** (−5.17) | −0.0367 ** (−2.49) |
Agricultural fertilizer application | −0.0340 *** (−3.63) | 0.0271 *** (3.63) |
Effective irrigation area | 0.0199 (1.44) | −0.0143 ** (−2.20) |
Proportion of crops affected by disasters | 0.0151 (1.46) | −0.00201 (−0.34) |
Income level of rural residents | −0.000826 (−0.09) | −0.00709 (−0.64) |
Financial support for agriculture | 0.0130 *** (4.68) | −0.00241 (−1.53) |
Agricultural policy | −0.00943 (−0.56) | 0.0132 (1.01) |
Constant | 0.255 ** (2.62) | 0.119 (1.14) |
Province-fixed effects | Yes | Yes |
Year-fixed effects | Yes | Yes |
Observations | 680 | 680 |
Eastern Region | Central Region | Western Region | ||||
---|---|---|---|---|---|---|
Cereals | Cash Crop | Cereals | Cash Crop | Cereals | Cash Crop | |
(1) | (2) | (3) | (4) | (5) | (6) | |
Aging rural population | 1.083 *** (3.94) | −0.772 *** (−3.38) | 0.474 ** (1.88) | −0.253 ** (−0.73) | −0.204 ** (−1.38) | 0.122 ** (0.36) |
Proportion of agricultural employment | 0.0431 (0.89) | −0.129 ** (−2.89) | −0.101 (−1.17) | 0.130 (1.13) | 0.179 *** (3.41) | −0.0619 (−0.53) |
Agricultural fertilizer application | 0.0522 (1.15) | −0.0317 (−0.70) | −0.0232 (−1.09) | −0.00638 (−0.19) | 0.0507 * (2.44) | −0.0104 (−0.25) |
Effective irrigation area | −0.104 * (−2.13) | 0.117 * (2.60) | 0.0400 ** (3.20) | −0.0533 ** (−2.70) | −0.0367 (−1.85) | −0.0306 (−0.72) |
Proportion of crops affected by disasters | −0.0220 (−0.86) | 0.00259 (0.10) | 0.00265 (0.20) | −0.0163 (−0.84) | 0.00416 (0.27) | −0.00278 (−0.08) |
Income level of rural residents | 0.0282 (0.72) | −0.405 *** (−3.64) | 0.00861 (0.78) | −0.0244 (−1.38) | −0.108 * (−2.55) | 0.0811 (0.93) |
Financial support for agriculture | −0.0187 ** (−3.19) | 0.0130 (1.84) | 0.0163 *** (5.12) | −0.0166 *** (−3.49) | −0.0481 *** (−5.52) | −0.0103 (−0.57) |
Agricultural policy | −0.0167 (−0.41) | −0.0647 (−0.72) | −0.00739 (−0.57) | 0.0651 * (2.32) | 0.398 *** (4.10) | −0.115 (−0.56) |
Constant | 0.772 (1.81) | 3.263 *** (3.39) | 0.551 *** (5.66) | 0.759 ** (3.19) | 1.650 *** (4.14) | −0.156 (−0.15) |
Province-fixed effects | Yes | Yes | Yes | Yes | Yes | Yes |
Year-fixed effects | Yes | Yes | Yes | Yes | Yes | Yes |
R2 | 0.8587 | 0.7648 | 0.9804 | 0.9572 | 0.9563 | 0.8344 |
Observations | 241 | 240 | 175 | 175 | 264 | 264 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, T.; Lu, H.; Luo, Q.; Li, G.; Gao, M. The Impact of Rural Population Aging on Agricultural Cropping Structure: Evidence from China’s Provinces. Agriculture 2024, 14, 586. https://doi.org/10.3390/agriculture14040586
Li T, Lu H, Luo Q, Li G, Gao M. The Impact of Rural Population Aging on Agricultural Cropping Structure: Evidence from China’s Provinces. Agriculture. 2024; 14(4):586. https://doi.org/10.3390/agriculture14040586
Chicago/Turabian StyleLi, Tingting, Hongwei Lu, Qiyou Luo, Guojing Li, and Mingjie Gao. 2024. "The Impact of Rural Population Aging on Agricultural Cropping Structure: Evidence from China’s Provinces" Agriculture 14, no. 4: 586. https://doi.org/10.3390/agriculture14040586