Impact of labor transfer differences on terraced fields abandonment: Evidence from micro-survey of farmers in the mountainous areas of Hunan, Fujian and Jiangxi

doi:10.1007/s11442-023-2149-z

Abstract

Abstract:

In recent years, the phenomenon of abandonment of cultivated land in mountainous areas has occurred frequently, and the problem of abandonment has become a focus of attention of government agricultural departments and academic circles. However, few studies have paid attention to the impact of differences in labor transfer on the abandonment behavior of farmers’ terraced fields. Based on this, this paper takes the terraced fields of Hunan, Fujian and Jiangxi provinces as the research area, combined with data from 1438 farmer households, and uses the Probit and Tobit models to analyzed the impact of the difference in the quantity, distance and quality of labor off-farm transfer on the decision-making and scale of terraced field abandonment of farmer households. The results show that: (1) The greater the quantity of labor transfer, the farther the transfer distance and the higher the quality of non-agricultural employment, can promote the decision of farmers to abandon terraced fields; (2) With the deepening of the degree of non-agricultural transfer, the scale of abandoned terraced fields by farmers in hilly and mountainous areas will also expand; (3) The distance and quality of labor transfer can strengthen the impact of labor transfer quantity on farmers’ decision to abandon land. To alleviate the phenomenon of abandoned terraced fields, the government should pay attention to the labor substitution role of agricultural service outsourcing and mechanization in mountainous areas. The government should actively promote the transformation of terraced fields into mechanized farming, improve the cultivated land transfer market, and encourage farmers to transfer terraced fields.

Key words: terraced fields abandonment, behavior mechanism of abandonment, labor transfer difference, hilly and mountainous area

XIE Hualin, WU Qing, LI Xiubin. Impact of labor transfer differences on terraced fields abandonment: Evidence from micro-survey of farmers in the mountainous areas of Hunan, Fujian and Jiangxi[J].Journal of Geographical Sciences, 2023, 33(8): 1702-1724.

Figures/Tables 9

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Table 1

Table 2

Table 3

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Table 5

Table 6

Model robustness test of core variable replacement

Variables		Dependent variable: Whether household abandon terrace (0=no;1=yes)
		Probit model 4-1	Probit model 4-2	Tobit model 5-1	Tobit model 5-2	Tobit model 5-3
		Coefficients	Coefficients	Coefficients	Coefficients	Coefficients
Replaced core independent variables
Labor transfer quantity		0.106* (0.057)		0.386** (0.167)
Labor transfer quality			0.254* (0.140)		0.725* (0.400)
Original core independent variables
Labor transfer distance						0.365*** (0.100)
Control variables
Labor characteristics	Amount	-0.099* (0.056)	-0.047 (0.043)	-0.364** (0.164)	-0.160 (0.123)	-0.155 (0.121)
	Average age	-0.001 (0.006)	-0.002 (0.006)	-0.008 (0.019)	-0.012 (0.018)	0.004 (0.018)
	Education level	-0.036 (0.044)	-0.041 (0.044)	-0.091 (0.131)	-0.112 (0.131)	-0.081 (0.130)
	Health status	0.098 (0.164)	0.128 (0.165)	0.280 (0.482)	0.360 (0.486)	0.199 (0.480)
	Elderly labor proportion	0.263 (0.198)	0.247 (0.198)	0.961* (0.571)	0.905 (0.568)	0.756 (0.563)
	Village cadre or not	0.065 (0.098)	0.083 (0.098)	0.038 (0.277)	0.095 (0.275)	0.244 (0.278)
Income characteristic	Total income	-0.114 (0.117)	-0.121 (0.120)	-0.418 (0.346)	-0.411 (0.353)	-0.454 (0.344)
Terrace endowment characteristic	Farmland transfer	-0.117 (0.072)	-0.103 (0.073)	-0.408* (0.210)	-0.373* (0.211)	-0.441** (0.210)
	Farmland plots	0.002 (0.001)	0.002 (0.001)	0.007* (0.004)	0.007* (0.004)	0.007* (0.004)
	Farmland area	0.026** (0.012)	0.028** (0.012)	0.136*** (0.037)	0.140*** (0.038)	0.138*** (0.037)
	Farmland soil quality	-0.630*** (0.060)	-0.625*** (0.060)	-1.617*** (0.199)	-1.599*** (0.198)	-1.597*** (0.197)
Substitution degree of labor input	Mechanization degree of agricultural production	-0.474*** (0.086)	-0.480*** (0.086)	-1.374*** (0.275)	-1.401*** (0.276)	-1.354*** (0.274)
Regional characteristics	Regional variable	Yes	Yes	Yes	Yes	Yes
Chi-square /F value		223.857	223.892	7.249	7.230	7.352
Prob > chi2/ Prob > F		0.000	0.000	0.000	0.000	0.000
No of Samples		1438	1438	1438	1438	1438

Table 6

References 42

[1]	Aide T M, Grau H R, 2004. Ecology enhanced: Globalization, migration, and Latin American ecosystems. Science, 305(5692): 1915-1916. (in Chinese) doi: 10.1126/science.1103179
[2]	Bezu S, Holden S, 2014. Are rural youth in Ethiopia abandoning agriculture? World Development, 64(12): 259-272. doi: 10.1016/j.worlddev.2014.06.013
[3]	Cai F, 2001. Two processes of labor migration and its institutional obstacles. Sociological Studies, (4): 44-51. (in Chinese)
[4]	Cai F, 2018. Has China’s labor mobility exhausted its momentum? Chinese Rural Economy, (9): 2-13. (in Chinese)
[5]	Chen D, Wei W, Chen L D et al., 2016. Progress of the ecosystem services and management of terraces. Mountain Research, 34(3): 374-384. (in Chinese)
[6]	He Z H, 2005. An analytic framework of concurrent business of farmers. China Rural Survey, (1): 2-9, 78. (in Chinese)
[7]	Hou C P, 1999. The new trend in the adjustment of employment structure: A preliminary study on the phenomenon of part-time employment. Population Journal, (2): 17-22. (in Chinese)
[8]	Huang L J, Zhang D Q, 2005. The institutional basis of benign transfer of rural surplus labor force. Rural Economy, (1): 120-122. (in Chinese)
[9]	Huang M L, Li X Y, 2019. The impacts of rural labor price rising on crop structure among provinces. Economic Geography, 39(6): 172-182. (in Chinese)
[10]	Huang M L, Li X Y, You Z L et al., 2018. Impact of agricultural labor investment on grain production and its elasticity of substitution. Journal of Huazhong Agricultural University (Social Sciences Edition), (2): 37-45, 156. (in Chinese)
[11]	Huang M Q, Li Y B, Ran C H et al., 2021. Dynamic changes and transformation of agricultural landscape pattern in mountainous areas: A case study in the hinterland of the Three Gorges Reservoir area. Acta Geographica Sinica, 76(11): 2749-2764. (in Chinese) doi: 10.11821/dlxb202111011
[12]	Li S F, Li X B, 2016. Progress and prospect on farmland abandonment. Acta Geographica Sinica, 71(3): 370-389. (in Chinese) doi: 10.11821/dlxb201603002
[13]	Li Y L, Ma W Q, Jiang G H et al., 2021. The degree of cultivated land abandonment and its influence on grain yield in main grain producing areas of China. Journal of Natural Resources, 36(6): 1439-1454. (in Chinese) doi: 10.31497/zrzyxb.20210607
[14]	Li Z J, Guo J X, 2011. The influence of selective labor transfer on the change of production preference of rural family population. China Rural Survey, (3): 40-49. (in Chinese)
[15]	Lieskovský J, Bezák P, Špulerová J et al., 2013. The abandonment of traditional agricultural landscape in Slovakia: Analysis of extent and driving forces. Journal of Rural Study, 32(2): 356-365.
[16]	Liu H Y, 2011. Economic growth effect of rural labors’ employment in non-agricultural industry in China. Population & Economics, (2): 23-27. (in Chinese)
[17]	Liu J W, Liang J Y, 2021. Life rationality: the action logic of rural women in industrial poverty alleviation with national characteristics based on the experience of “Jinxiu Plan” project in Ceheng county, Guizhou province. China Rural Survey, (2): 15-27. (in Chinese)
[18]	Lu C, 2020. Does household laborer migration promote farmland abandonment in China? Growth and Change, 51(4): 1-33. doi: 10.1111/grow.v51.1
[19]	Lu H, Hu H, 2017. Off-farm labor supply: Does land fragmentation work? Based on the perspective of Lewis turning-point. Economic Review, (1): 148-160. (in Chinese)
[20]	Ma L, Long H L, Zhang Y N et al., 2018. Spatio-temporal coupling relationship between agricultural labor changes and agricultural economic development at county level in China and its implications for rural revitalization. Acta Geographica Sinica, 73(12): 2364-2377. (in Chinese) doi: 10.11821/dlxb201812007
[21]	Ma Z D, Zhang W M, Liang Z et al., 2004. Labor migration as a new determinant of income growth in rural China. Population Research, (3): 2-10. (in Chinese)
[22]	Miao J Q, Wang Z Q, Ma Y Q et al., 2018. Comprehensive evaluation of sustainable development of the Hakka terrace ecosystem of Chongyi. Acta Ecologica Sinica, 38(17): 6326-6336. (in Chinese)
[23]	Shao H, Huang J, Zuo T Y, 2011. Analysis of balanced water supply and demand in Longji terraced field regulation of Longsheng county, Guilin. Chinese Agricultural Science Bulletin, 27(14): 227-232. (in Chinese)
[24]	Sheng L Y. 2007. The economic impact of rural labor flow. Statistical Research, (10): 15-19. (in Chinese)
[25]	Shi T, Li X, Xin L et al., 2018. The spatial distribution of cropland abandonment and its influential factors at the township level: A case study in the mountainous area of China. Land Use Policy, 70(1): 510-520. doi: 10.1016/j.landusepol.2017.10.039
[26]	Stark O, Bloom D E, 1985. The new economics of labor migration. American Economic Review, 75(2): 173-178.
[27]	Sun X T, 2021. The transfer of rural labor and improvement of farmland efficiency from the perspective of disequilibrium. Economic Survey, 38(5): 41-50. (in Chinese)
[28]	Tan Z P, Hong W J, Luo B L, 2019. The transfer effect of agricultural labor force and grain-oriented planting structure. Reform, (7): 111-118. (in Chinese)
[29]	Tian Y J, Li X B, Ma G X et al., 2010. Influences of labor emigration from agriculture on the production abandonment of cultivated land in ecological sensitive areas. China Land Science, 24(7): 4-9. (in Chinese)
[30]	Xiang G C, Han S F, 2005. Farmers’ part-time industrialization: An analysis from the perspective of division of labor. Chinese Rural Economy, (8): 4-9, 16. (in Chinese)
[31]	Xie H L, Huang Y Q, 2022. Impact of non-agricultural employment and land transfer on farmland abandonment behaviors of farmer: A case study in Fujian-Jiangxi-Hunan mountainous areas. Journal of Natural Resources, 37(2): 408-423. (in Chinese) doi: 10.31497/zrzyxb.20220210
[32]	Yao Y F, Wang L X, 1991. Formation and development of terrace in China. Soil and Water Conservation in China, (6): 56-58. (in Chinese)
[33]	Yuan W, 2018. Endogenous test methods, procedures and Stata applications of binary selection model. Statistics & Decision, 34(6): 15-20. (in Chinese)
[34]	Zhang B L, Yang Q Y, Yan Y et al., 2011. Characteristics and reasons of different households’ farming abandonment behavior in the process of rapid urbanization based on a survey from 540 households in 10 counties of Chongqing municipality. Resources Science, 33(11): 2047-2054. (in Chinese)
[35]	Zhang K Z, Gao Z B, Zhang L N et al., 2020. Migratory-bird flow or permanent migration? Public services accessibility and population migration options based on the perspective of social integration. Research on Economics and Management, 41(7): 112-133. (in Chinese)
[36]	Zhang X Z, Zhao C S, Dong J W et al., 2019. Spatio-temporal pattern of cropland abandonment in China from 1992 to 2017: A meta-analysis. Acta Geographica Sinica, 74(3): 411-420. (in Chinese) doi: 10.11821/dlxb201903001
[37]	Zhang Y, Li X B, Song W, 2014a. Determinants of cropland abandonment at the parcel, household and village levels in mountain areas of China: A multi-level analysis. Land Use Policy, 41(11): 186-192. doi: 10.1016/j.landusepol.2014.05.011
[38]	Zhang Y, Li X B, Song W et al., 2014b. Effect of agricultural laborer on cropland abandonment under land circulation at different levels in Wulong county, Chongqing city. Progress in Geography, 33(4): 552-560. (in Chinese)
[39]	Zhang Y X, Min Q W, 2016. A review of conservation of rice terraces as agricultural heritage systems. Chinese Journal of Eco-Agriculture, 24(4): 460-469. (in Chinese)
[40]	Zhao S C, Xu Q, Liu J, 2020. Labor migration, capital deepening, and agricultural land circulation in China. Journal of Agrotechnical Economics, (3): 4-19. (in Chinese)
[41]	Zhao W Y, Li Y B, Li Y Y et al., 2018. Evolution and landscape pattern of abandoned land in center region of Three Gorges Reservoir area: A case study in Pingan and Zhuyuan township of Fengjie county, Chongqing municipality. Bulletin of Soil and Water Conservation, 38(3): 256-262. (in Chinese)
[42]	Zhu W J, Luo B L, 2020. Labor migration, gender differences, farmland transfer and its contract selection. China Population, Resources and Environment, 30(1): 160-169. (in Chinese)

Variables		Description	Mean	Standard deviation
Dependent variables
Terrace abandonment behavior		Whether household abandon terrace (0=no;1=yes)	0.405	0.491
Terrace abandonment rate		Proportion of abandoned terrace to the total farmland (%)	0.170	0.271
Independent variables
Agricultural labor transfer differences	Transfer quantity	Proportion of non-agricultural employment labor to the total labor (%)	0.678	0.324
	Transfer distance	Weighted processing of non-agricultural employment	1.797	1.244
	Transfer quality	Working times of non-agricultural employment (Month)	18.593	13.114
Control variables
Labor characteristic	Amount	(Number)	2.797	1.203
	Average age	Average age of labor (Year)	48.164	9.512
	Education	Labors with middle school education level (Number)	1.060	0.969
	Health status	Proportion of labor with poor health to the total labor (%)	0.126	0.233
	Elderly labor proportion	Proportion of elderly labor to the total labor (%)	0.149	0.277
	Village cadre or not	Are there village cadre among labors (0=no; 1=yes)	0.153	0.368
Income characteristic	Total income	Processed with logarithm (yuan, 1 USD≈6.8974 yuan)	4.804	0.424
Terrace endowment characteristic	Farmland transfer	Whether transfer farmland (0=no; 1=yes)	0.516	0.5
	Farmland plots	(Number)	33.004	46.361
	Farmland area	(Mu, 1 Mu≈0.067 ha)	5.307	4.012
	Farmland soil quality	(1=poor; 2=medium; 3=good)	2.016	0.654
Substitution degree of labor input	Mechanization degree of agricultural production	Assign values from whether terrace can be plowed, seeded, and harvested mechanically	0.445	0.454
Regional characteristic	Regional variable	N/A
No of samples		1438

Variables	Dependent variable: Whether household abandon terrace (0=no;1=yes)
	Probit model 1-4		Probit model 1-5
	Coefficients	Robust standard error	Coefficients	Robust standard error
Core independent variables
Labor transfer quantity	0.012	0.178	0.029	0.203
Labor transfer quantity × Labor transfer distance	0.120***	0.042
Labor transfer quantity × Labor transfer quality			0.350**	0.202
Controls	Yes		Yes
Control regional characteristic	Yes		Yes
Prob > chi2	0.000		0.000
No of samples	1438

Variables		Dependent variable: Households’ terrace abandonment rate
		Tobit model 2-1		Tobit model 2-2		Tobit model 2-3
		Coefficients	Robust standard error	Coefficients	Robust standard error	Coefficients	Robust standard error
Core independent variables
Agricultural labor transfer differences	Labor transfer quantity	0.218***	0.065
	Labor transfer distance			0.068***	0.015
	Labor transfer quality					0.010***	0.003
Control variables
Labor characteristic	Amount	-0.016	0.020	-0.034*	0.019	-0.100***	0.027
	Average age	-0.002	0.003	-0.001	0.003	-0.002	0.003
	Education level	-0.016	0.021	-0.013	0.021	-0.005	0.021
	Health status	0.107	0.077	0.079	0.077	0.083	0.077
	Elderly labor proportion	0.198**	0.096	0.146	0.093	0.148	0.094
	Village cadre or not	-0.035	0.043	0.003	0.043	-0.068	0.044
Income characteristic	Total income	-0.108*	0.059	-0.099*	0.057	-0.132**	0.059
Terrace endowment characteristic	Farmland transfer	-0.111***	0.034	-0.119***	0.034	-0.113***	0.034
	Farmland plots	0.001***	0.0004	0.001**	0.0004	0.001**	0.0003
	Farmland area	0.008*	0.004	0.009**	0.005	0.009**	0.004
	Farmland soil quality	-0.245***	0.027	-0.24***	0.026	-0.245***	0.027
Substitution degree of labor input	Mechanization degree of agricultural production	-0.244***	0.043	-0.244***	0.042	-0.240***	0.043
Regional characteristic	Regional variable	Yes		Yes		Yes
	F	16.23		17.35		16.56
	Prob > F	0.000		0.000		0.000
No of samples		1438		1438		1438

Variables	Model 3-1		Model 3-2		Model 3-3
Variables	IV-Probit	IV-Tobit	IV-Probit	IV-Tobit	IV-Probit	IV-Tobit
Instrumental variable
Labor transfer quantity	1.750*** (0.567)	0.984*** (0.312)
Labor transfer distance			0.746** (0.309)	0.376*** (0.129)
Labor transfer quality					0.053** (0.20)	0.027*** (0.008)
Wald-test	5.53**	7.02**	5.62**	7.22**	4.09**	4.51**
P-value of Wald endogeneity test	0.0186	0.0080	0.0178	0.0072	0.0431	0.0337
Constants	0.475	0.499	-0.014	0.202	2.269	1.435
Weak instrumental variable test
Weakiv-wald	6.45***	8.35***	5.8**	7.16***	6.96***	9.00***
Weakiv-AR	7.11***	9.23***	7.17***	9.12***	7.2***	9.25***
No of samples	1438		1438		1438