Temporal and spatial changes of China’s agricultural total factor productivity based on the framework of input-output unity

doi:10.3969/j.issn.1004-1524.20221431

Acta Agriculturae Zhejiangensis ›› 2024, Vol. 36 ›› Issue (2): 441-454.DOI: 10.3969/j.issn.1004-1524.20221431

• Agricultural Economy and Development • Previous Articles Next Articles

Temporal and spatial changes of China’s agricultural total factor productivity based on the framework of input-output unity

WANG Manman¹(), SHEN Zhou¹, GAO Qizheng²^,^*()

1. Colleges of Economics & Management, China Three Gorges University, Yichang 443002, China
2. Economics and Management School, Wuhan University, Wuhan 430072, China

Received:2022-10-04 Online:2024-02-25 Published:2024-03-05

Abstract

Abstract:

In order to measure China’s (excluding Hongkong, Macao, Taiwan) agricultural total factor productivity in a standard way and identify the regional differences, the input variables of land, labor and intermediate inputs under the framework of input-output unity were clarified, and the agricultural capital stock of provincial-level regions were estimated by using the minimum deviation method. The SFA-KLH model, suitable for China’s agricultural production, were introduced to measure the growth of agricultural total factor productivity since the implementation of reform and open policy, and the trend sources, spatial and regional distribution of agricultural total factor productivity from 1978 to 2020 were also discussed. It was found that the China’s agricultural total factor productivity showed an overall fluctuating growth trend during 1978-2020. But, after 2006, China’s agricultural total factor productivity showed a slowing down and stable growth trend. The average annual growth rate of China’s agricultural total factor productivity measured by SFA-KLH was 2.27%, and technical progress was the main growth source. There was spatial difference of agricultural total factor productivity, and the growth of agricultural total factor productivity decreased as central>east>west. On the whole, there was no absolute convergence of agricultural total factor productivity in China, but the conditional convergence did exist, and different provincial-level regions had different convergence rates.

Key words: agricultural total factor productivity, capital stock, spatial distribution

CLC Number:

F127

WANG Manman, SHEN Zhou, GAO Qizheng. Temporal and spatial changes of China’s agricultural total factor productivity based on the framework of input-output unity[J]. Acta Agriculturae Zhejiangensis, 2024, 36(2): 441-454.

Figures/Tables 7

Table 1 Descriptive statistics of input and output indexes

指标 Index	描述 Description	平均值 Average	最大值 Maximum	最小值 Minimum	标准差 Standard deviation
产出 Output/(10⁸ yuan)	农林牧渔业总产值 Total output of agriculture, forestry, animal husbandry and fishery	249.60	1 408.93	3.92	262.07
土地 Land/(10⁴ hm²)	农作物播种面积+本年采摘茶园面积+果园面积+瓜果类面积+ 林地面积+草地面积+水产品养殖面积 Crop sown area+tea garden area picked this year+orchard area+melon and fruit area+forest land area+grass land area+aquaculture area	2 215.97	9 687.22	29.06	2095.22
劳动 Labor/10⁴	第一产业劳动力数目 Primary industry practitioners	651.51	1 292.00	37.09	374.77
资本 Capital/(10⁸ yuan)	农业资本存量 Agricultural capital stock	196.66	2 316.79	2.08	266.28
中间投入 Intermediate input/ (10⁸ yuan)	农林牧渔业总产值-农林牧渔业增加值 Total output of agriculture, forestry, animal husbandry and fishery- added value of agriculture, forestry, animal husbandry and fishery	88.75	877.24	0.07	107.64

Table 2 Estimation results of test models

变量 Variable	模型1 Model 1	模型 2 Model 2	模型3 Model 3	模型4 Model 4	模型5 Model 5
β_t	0.011 4 (0.36)	0.026 4^*** (24.74)	0.028 2^*** (28.39)	—	0.011 4 (0.36)
β_K	-0.071 5 (-1.21)	0.045 2^*** (5.65)	-0.210 4^*** (-4.79)	—	-0.071 5 (-1.21)
β_L	0.243 0 (0.76)	0.668 6^*** (10.44)	0.654 5^** (2.28)	—	0.243 0 (0.76)
β_N	0.300 8^** (2.17)	0.085 3^*** (3.63)	0.468 9^*** (3.54)	0.629 0^*** (6.73)	0.300 8^** (2.17)
β_M	1.075 9^*** (12.70)	0.392 2^*** (30.19)	0.885 5^*** (19.91)	0.859 4^*** (21.66)	1.075 9^*** (12.70)
$β t 2$	-0.000 2^** (-2.59)	—	—	0.000 3^*** (3.80)	-0.000 2^** (-2.59)
$β K 2$	0.016 9^** (2.52)	—	0.013 7^** (2.21)	0.003 9 (1.29)	0.016 9^** (2.52)
$β L 2$	0.057 1^* (1.87)	—	0.036 4 (1.26)	0.076 3^*** (6.30)	0.057 1^* (1.87)
$β N 2$	0.030 9^** (2.18)	—	0.014 7 (1.13)	0.003 1 (0.26)	0.030 9^** (2.18)
$β M 2$	0.024 1^* (1.92)	—	0.030 9^*** (5.51)	0.014 6^*** (5.59)	0.024 1^* (1.92)
β_tK	-0.001 2 (-1.17)	—	—	—	-0.001 2 (-1.17)
β_tL	0.001 2 (1.33)	—	—	—	0.001 2 (1.33)
β_tN	0.002 7^* (1.87)	—	—	0.002 2^*** (4.36)	0.002 7^* (1.87)
β_tM	0.001 4 (0.73)	—	—	—	0.001 4 (0.73)
β_KL	0.046 6^*** (6.74)	—	0.048 9^*** (8.19)	0.053 9^** (11.52)	0.046 6^*** (6.74)
β_KN	-0.044 5^*** (-3.85)	—	-0.022 7^*** (-2.94)	-0.059 9 (-9.10)	-0.044 5^*** (-3.85)
β_KM	-0.019 8 (-1.44)	—	-0.023 8^** (-2.04)	—	-0.019 8 (-1.44)
β_LN	-0.046 1^* (-1.92)	—	-0.058 5^** (-2.45)	-0.048 4^*** (-2.14)	-0.046 1^* (-1.92)
β_LM	-0.082 0^*** (-7.86)	—	-0.072 5^*** (-11.35)	-0.079 9^*** (-17.26)	-0.082 0^*** (-7.86)
β_NM	-0.032 5 (-1.55)	—	-0.013 2 (-1.39)	—	-0.032 5 (-1.55)
u	—	—	—	—	0.046 6^*** (6.01)
η	—	—	—	—	1.040 2^*** (29.36)
样本数Sample size	1 333	1 333	1 333	1 333	1 333

Table 2 Estimation results of test models

变量 Variable	模型1 Model 1	模型 2 Model 2	模型3 Model 3	模型4 Model 4	模型5 Model 5
β_t	0.011 4 (0.36)	0.026 4^*** (24.74)	0.028 2^*** (28.39)	—	0.011 4 (0.36)
β_K	-0.071 5 (-1.21)	0.045 2^*** (5.65)	-0.210 4^*** (-4.79)	—	-0.071 5 (-1.21)
β_L	0.243 0 (0.76)	0.668 6^*** (10.44)	0.654 5^** (2.28)	—	0.243 0 (0.76)
β_N	0.300 8^** (2.17)	0.085 3^*** (3.63)	0.468 9^*** (3.54)	0.629 0^*** (6.73)	0.300 8^** (2.17)
β_M	1.075 9^*** (12.70)	0.392 2^*** (30.19)	0.885 5^*** (19.91)	0.859 4^*** (21.66)	1.075 9^*** (12.70)
$β t 2$	-0.000 2^** (-2.59)	—	—	0.000 3^*** (3.80)	-0.000 2^** (-2.59)
$β K 2$	0.016 9^** (2.52)	—	0.013 7^** (2.21)	0.003 9 (1.29)	0.016 9^** (2.52)
$β L 2$	0.057 1^* (1.87)	—	0.036 4 (1.26)	0.076 3^*** (6.30)	0.057 1^* (1.87)
$β N 2$	0.030 9^** (2.18)	—	0.014 7 (1.13)	0.003 1 (0.26)	0.030 9^** (2.18)
$β M 2$	0.024 1^* (1.92)	—	0.030 9^*** (5.51)	0.014 6^*** (5.59)	0.024 1^* (1.92)
β_tK	-0.001 2 (-1.17)	—	—	—	-0.001 2 (-1.17)
β_tL	0.001 2 (1.33)	—	—	—	0.001 2 (1.33)
β_tN	0.002 7^* (1.87)	—	—	0.002 2^*** (4.36)	0.002 7^* (1.87)
β_tM	0.001 4 (0.73)	—	—	—	0.001 4 (0.73)
β_KL	0.046 6^*** (6.74)	—	0.048 9^*** (8.19)	0.053 9^** (11.52)	0.046 6^*** (6.74)
β_KN	-0.044 5^*** (-3.85)	—	-0.022 7^*** (-2.94)	-0.059 9 (-9.10)	-0.044 5^*** (-3.85)
β_KM	-0.019 8 (-1.44)	—	-0.023 8^** (-2.04)	—	-0.019 8 (-1.44)
β_LN	-0.046 1^* (-1.92)	—	-0.058 5^** (-2.45)	-0.048 4^*** (-2.14)	-0.046 1^* (-1.92)
β_LM	-0.082 0^*** (-7.86)	—	-0.072 5^*** (-11.35)	-0.079 9^*** (-17.26)	-0.082 0^*** (-7.86)
β_NM	-0.032 5 (-1.55)	—	-0.013 2 (-1.39)	—	-0.032 5 (-1.55)
u	—	—	—	—	0.046 6^*** (6.01)
η	—	—	—	—	1.040 2^*** (29.36)
样本数Sample size	1 333	1 333	1 333	1 333	1 333

Fig.1 Agricultural total factor productivity, technical efficiency changes and technical progress changes from 1978 to 2020

Table 3 Agricultural total factor productivity of provincial-level regions at different periods

省份 Provincial-level regions	1978—1985	1986—1990	1991—1995	1996—2000	2001—2005	2006—2010	2011—2015	2016—2020
北京Beijing	1.009	0.994	0.993	1.019	1.014	1.080	1.029	1.017
福建Fujian	0.995	0.995	1.000	1.071	1.049	1.026	1.030	1.008
广东Guangdong	0.990	0.988	0.974	1.002	1.024	1.086	1.036	1.095
海南Hainan	0.994	0.989	1.020	0.963	0.924	1.078	0.984	0.997
河北Hebei	1.004	0.994	0.990	1.059	1.059	1.056	1.022	1.129
江苏Jiangsu	0.991	0.984	0.991	1.048	1.078	1.073	1.080	1.161
辽宁Liaoning	0.991	0.992	0.979	1.040	1.043	1.038	1.044	1.037
山东Shandong	0.996	1.004	0.991	1.074	1.010	1.020	1.020	1.039
上海Shanghai	1.021	1.017	1.010	1.049	1.052	1.049	1.072	1.080
天津Tianjin	1.031	1.024	1.017	1.059	1.045	1.005	0.935	0.948
浙江Zhejiang	0.990	0.989	0.996	1.043	0.976	0.986	1.004	1.023
吉林Jilin	0.997	0.990	0.970	0.996	1.111	1.109	1.046	0.996
安徽Anhui	1.000	1.006	1.023	1.056	1.034	1.041	1.044	1.096
内蒙古Inner Mongolia	1.004	0.997	0.985	1.024	1.032	1.049	1.050	1.034
河南Henan	1.000	0.998	0.994	1.053	1.033	1.000	1.023	0.999
黑龙江Heilongjiang	1.006	1.007	0.993	1.052	1.035	1.024	1.042	1.046
湖北Hubei	1.000	0.983	0.995	1.043	1.033	1.276	1.109	1.186
湖南Hunan	0.977	0.962	1.008	1.017	1.008	1.048	1.071	1.079
江西Jiangxi	1.005	0.990	1.003	1.033	1.025	1.032	1.032	1.017
山西Shanxi	1.013	1.012	0.992	1.048	1.032	1.056	1.041	1.015
广西Guangxi	0.999	0.988	0.984	1.022	1.020	1.029	1.042	1.079
甘肃Gansu	1.000	1.004	0.966	1.045	1.029	1.009	1.052	1.048
贵州Guizhou	1.010	1.007	1.000	1.026	1.020	1.014	1.005	1.093
宁夏Ningxia	0.997	1.012	1.012	1.047	1.048	1.024	1.014	1.040
青海Qinghai	1.007	1.010	1.005	1.033	1.020	1.027	1.020	1.061
陕西Shaanxi	1.008	1.013	1.007	1.045	1.044	1.023	1.041	1.024
四川Sichuan	0.990	0.987	0.984	1.036	0.995	1.021	1.012	1.089
西藏Xizang	1.000	1.004	1.000	1.007	1.027	1.087	1.059	1.074
新疆Xinjiang	0.989	1.002	0.994	1.071	1.048	1.023	1.035	1.018
云南Yunnan	1.012	1.017	1.001	1.044	1.034	1.051	1.060	1.058
重庆Chongqing	0.995	1.017	1.032	0.996	0.946	0.923	0.971	1.057

Table 3 Agricultural total factor productivity of provincial-level regions at different periods

省份 Provincial-level regions	1978—1985	1986—1990	1991—1995	1996—2000	2001—2005	2006—2010	2011—2015	2016—2020
北京Beijing	1.009	0.994	0.993	1.019	1.014	1.080	1.029	1.017
福建Fujian	0.995	0.995	1.000	1.071	1.049	1.026	1.030	1.008
广东Guangdong	0.990	0.988	0.974	1.002	1.024	1.086	1.036	1.095
海南Hainan	0.994	0.989	1.020	0.963	0.924	1.078	0.984	0.997
河北Hebei	1.004	0.994	0.990	1.059	1.059	1.056	1.022	1.129
江苏Jiangsu	0.991	0.984	0.991	1.048	1.078	1.073	1.080	1.161
辽宁Liaoning	0.991	0.992	0.979	1.040	1.043	1.038	1.044	1.037
山东Shandong	0.996	1.004	0.991	1.074	1.010	1.020	1.020	1.039
上海Shanghai	1.021	1.017	1.010	1.049	1.052	1.049	1.072	1.080
天津Tianjin	1.031	1.024	1.017	1.059	1.045	1.005	0.935	0.948
浙江Zhejiang	0.990	0.989	0.996	1.043	0.976	0.986	1.004	1.023
吉林Jilin	0.997	0.990	0.970	0.996	1.111	1.109	1.046	0.996
安徽Anhui	1.000	1.006	1.023	1.056	1.034	1.041	1.044	1.096
内蒙古Inner Mongolia	1.004	0.997	0.985	1.024	1.032	1.049	1.050	1.034
河南Henan	1.000	0.998	0.994	1.053	1.033	1.000	1.023	0.999
黑龙江Heilongjiang	1.006	1.007	0.993	1.052	1.035	1.024	1.042	1.046
湖北Hubei	1.000	0.983	0.995	1.043	1.033	1.276	1.109	1.186
湖南Hunan	0.977	0.962	1.008	1.017	1.008	1.048	1.071	1.079
江西Jiangxi	1.005	0.990	1.003	1.033	1.025	1.032	1.032	1.017
山西Shanxi	1.013	1.012	0.992	1.048	1.032	1.056	1.041	1.015
广西Guangxi	0.999	0.988	0.984	1.022	1.020	1.029	1.042	1.079
甘肃Gansu	1.000	1.004	0.966	1.045	1.029	1.009	1.052	1.048
贵州Guizhou	1.010	1.007	1.000	1.026	1.020	1.014	1.005	1.093
宁夏Ningxia	0.997	1.012	1.012	1.047	1.048	1.024	1.014	1.040
青海Qinghai	1.007	1.010	1.005	1.033	1.020	1.027	1.020	1.061
陕西Shaanxi	1.008	1.013	1.007	1.045	1.044	1.023	1.041	1.024
四川Sichuan	0.990	0.987	0.984	1.036	0.995	1.021	1.012	1.089
西藏Xizang	1.000	1.004	1.000	1.007	1.027	1.087	1.059	1.074
新疆Xinjiang	0.989	1.002	0.994	1.071	1.048	1.023	1.035	1.018
云南Yunnan	1.012	1.017	1.001	1.044	1.034	1.051	1.060	1.058
重庆Chongqing	0.995	1.017	1.032	0.996	0.946	0.923	0.971	1.057

Table 4 Agricultural total factor productivity, technical efficiency changes and technical changes in the east, central, and west regions from 1978 to 2020

时段 Period	TFP			TC			EC
时段 Period	东部East	中部Central	西部West	东部East	中部Central	西部West	东部East	中部Central	西部West
1978—1985	1.001	1.000	1.000	1.003	1.002	1.002	0.998	0.998	0.998
1986—1990	0.997	0.994	1.006	1.001	0.997	1.009	0.997	0.997	0.996
1991—1995	0.997	0.996	0.999	1.002	1.001	1.004	0.994	0.995	0.994
1996—2000	1.039	1.036	1.034	1.049	1.043	1.045	0.990	0.993	0.990
2001—2005	1.025	1.038	1.021	1.046	1.050	1.044	0.977	0.989	0.977
2006—2010	1.045	1.071	1.021	1.093	1.089	1.055	0.960	0.982	0.967
2011—2015	1.023	1.051	1.028	1.098	1.107	1.084	0.935	0.950	0.949
2016—2020	1.048	1.052	1.058	1.129	1.131	1.144	0.933	0.934	0.928
1978—2020	1.022	1.030	1.021	1.053	1.053	1.048	0.973	0.980	0.975

Fig.2 δ-convergence of agricultural total factor productivity The east region consists of Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan. The central region consists of Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan, Guangxi. The west region consists of Sichuan, Chongqing, Guizhou, Yunnan, Xizang, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.

Table 5 Absolute β-convergence of agricultural total factor productivity

区域 Region	α	β	校正决定系数 Adjusted R²
全国 Total	0.022 6^*** (16.97)	-0.000 1 (-0.07)	-0.034 3
东部 East	0.010 5^** (3.00)	-0.025 6^** (-3.17)	0.474 3
中部 Central	0.024 0 (-0.88)	-0.001 2^*** (16.68)	-0.025 8
西部 West	0.025 2^*** (10.31)	0.001 9 (1.38)	0.092 2

References 42

[1]	COELLI T. An introduction to efficiency and productivity analysis[M]. 2nd ed. New York: Springer, 2005
[2]	BUREAU J C, FÄRE R, GROSSKOPF S. A comparison of three nonparametric measures of productivity growth in European and United States agriculture[J]. Journal of Agricultural Economics, 1995, 46(3): 309-326.
[3]	ZELLER M, DIAGNE A, MATAYA C. Market access by smallholder farmers in Malawi: implications for technology adoption, agricultural productivity and crop income[J]. Agricultural Economics, 1998, 19(1/2): 219-229.
[4]	OLESEN J E, BINDI M. Consequences of climate change for European agricultural productivity, land use and policy[J]. European Journal of Agronomy, 2002, 16(4): 239-262.
[5]	MCMILLAN J, WHALLEY J, ZHU L J. The impact of China’s economic reforms on agricultural productivity growth[J]. Journal of Political Economy, 1989, 97(4): 781-807.
[6]	FAN S G. Effects of technological change and institutional reform on production growth in Chinese agriculture[J]. American Journal of Agricultural Economics, 1991, 73(2): 266-275.
[7]	WEN G J. Total factor productivity change in China’s farming sector: 1952—1989[J]. Economic Development and Cultural Change, 1993, 42(1): 1-41.
[8]	CHEN P C, YU M M, CHANG C C, et al. Total factor productivity growth in China’s agricultural sector[J]. China Economic Review, 2008, 19(4): 580-593.
[9]	米建伟, 梁勤, 马骅. 我国农业全要素生产率的变化及其与公共投资的关系: 基于1984—2002年分省份面板数据的实证分析[J]. 农业技术经济, 2009(3): 4-16.
	MI J W, LIANG Q, MA H. Changes of China’s agricultural total factor productivity and its relationship with public investment: an empirical analysis based on provincial panel data from 1984 to 2002[J]. Journal of Agrotechnical Economics, 2009(3): 4-16. (in Chinese)
[10]	高帆. 我国区域农业全要素生产率的演变趋势与影响因素: 基于省际面板数据的实证分析[J]. 数量经济技术经济研究, 2015, 32(5): 3-19.
	GAO F. Evolution trend and internal mechanism of regional total factor productivity in Chinese agriculture[J]. The Journal of Quantitative & Technical Economics, 2015, 32(5): 3-19. (in Chinese)
[11]	周端明. 技术进步、技术效率与中国农业生产率增长: 基于DEA的实证分析[J]. 数量经济技术经济研究, 2009, 26(12): 70-82.
	ZHOU D M. Technical progress, technical efficiency, and productivity growth of China’s agriculture[J]. The Journal of Quantitative & Technical Economics, 2009, 26(12): 70-82. (in Chinese)
[12]	LAMBERT D K, PARKER E. Productivity in Chinese provincial agriculture[J]. Journal of Agricultural Economics, 1998, 49(3): 378-392.
[13]	XU Y F. Agricultural productivity in China[J]. China Economic Review, 1999, 10(2): 108-121.
[14]	吴方卫. 中国农业的增长源泉分析[J]. 中国软科学, 2000(1): 48-52.
	WU F W. Analysis on the source of agricultural growth in China[J]. China Soft Science, 2000(1): 48-52. (in Chinese)
[15]	赵芝俊, 张社梅. 近20年中国农业技术进步贡献率的变动趋势[J]. 中国农村经济, 2006(3): 4-12.
	ZHAO Z J, ZHANG S M. The tendency of the contribution rates of technological advances to the growth of China’ agriculture in the past nearly 20 years[J]. Chinese Rural Economy, 2006(3): 4-12. (in Chinese)
[16]	薛建良, 李秉龙. 基于环境修正的中国农业全要素生产率度量[J]. 中国人口·资源与环境, 2011, 21(5): 113-118.
	XUE J L, LI B L. Environmentlly-adjusted measurement of China’s agricultural total factor productivity[J]. China Population, Resources and Environment, 2011, 21(5): 113-118. (in Chinese with English abstract)
[17]	FAN S G, ZHANG X B. Production and productivity growth in Chinese agriculture: new national and regional measures[J]. Economic Development and Cultural Change, 2002, 50(4): 819-838.
[18]	FAN S G, PARDEY P G. Research, productivity, and output growth in Chinese agriculture[J]. Journal of Development Economics, 1997, 53(1): 115-137.
[19]	赵芝俊, 袁开智. 中国农业技术进步贡献率测算及分解: 1985—2005[J]. 农业经济问题, 2009, 30(3): 28-36.
	ZHAO Z J, YUAN K Z. Calculation and decomposition of contribution rate of agricultural technological progress in China: 1985—2005[J]. Issues in Agricultural Economy, 2009, 30(3): 28-36. (in Chinese)
[20]	匡远凤. 技术效率、技术进步、要素积累与中国农业经济增长: 基于SFA的经验分析[J]. 数量经济技术经济研究, 2012, 29(1): 3-18.
	KUANG Y F. Technology efficiency, technology progress, factor accumulation and China’s agricultural economic growth[J]. The Journal of Quantitative & Technical Economics, 2012, 29(1): 3-18. (in Chinese with English abstract)
[21]	张乐, 曹静. 中国农业全要素生产率增长: 配置效率变化的引入: 基于随机前沿生产函数法的实证分析[J]. 中国农村经济, 2013(3): 4-15.
	ZHANG L, CAO J. Growth of agricultural total factor productivity in China: introduction of allocation efficiency change: an empirical analysis based on stochastic frontier production function method[J]. Chinese Rural Economy, 2013(3): 4-15. (in Chinese)
[22]	COELLI T J, PRASADA RAO D S. Total factor productivity growth in agriculture: a Malmquist index analysis of 93 countries, 1980-2000[J]. Agricultural Economics, 2005, 32: 115-134.
[23]	杜江, 王锐, 王新华. 环境全要素生产率与农业增长: 基于DEA-GML指数与面板Tobit模型的两阶段分析[J]. 中国农村经济, 2016(3): 65-81.
	DU J, WANG R, WANG X H. Environmental total factor productivity and agricultural growth: a two-stage analysis based on DEA-GML index and panel Tobit model[J]. Chinese Rural Economy, 2016(3): 65-81. (in Chinese)
[24]	李晓阳, 许属琴. 经营规模、金融驱动与农业全要素生产率[J]. 软科学, 2017, 31(8): 5-8.
	LI X Y, XU S Q. Operational scale, financial drive and agricultural TFP[J]. Soft Science, 2017, 31(8): 5-8. (in Chinese with English abstract)
[25]	史常亮, 张益. 中国农业全要素生产率增长收敛吗?: 基于空间视角的分析[J]. 内蒙古社会科学, 2021, 42(1): 137-146.
	SHI C L, ZHANG Y. Are China’s agricultural total factor productivity growth convergence?: an analysis from a spatial perspective[J]. Inner Mongolia Social Sciences, 2021, 42(1): 137-146. (in Chinese with English abstract)
[26]	王珏, 宋文飞, 韩先锋. 中国地区农业全要素生产率及其影响因素的空间计量分析: 基于1992—2007年省域空间面板数据[J]. 中国农村经济, 2010(8): 24-35.
	WANG J, SONG W F, HAN X F. Spatial econometric analysis of agricultural total factor productivity and its influencing factors in China: based on provincial spatial panel data from 1992 to 2007[J]. Chinese Rural Economy, 2010(8): 24-35. (in Chinese)
[27]	王兵, 杨华, 朱宁. 中国各省份农业效率和全要素生产率增长: 基于SBM方向性距离函数的实证分析[J]. 南方经济, 2011(10): 12-26.
	WANG B, YANG H, ZHU N. Agricultural efficiency and total factor productivity growth in China’s provincial economies: an empirical analysis based on SBM directional distance function[J]. South China Journal of Economics, 2011(10): 12-26. (in Chinese with English abstract)
[28]	徐现祥, 周吉梅, 舒元. 中国省区三次产业资本存量估计[J]. 统计研究, 2007, 24(5): 6-13.
	XU X X, ZHOU J M, SHU Y. Estimates of fixed capital stock by sector and region: 1978-2002[J]. Statistical Research, 2007, 24(5): 6-13. (in Chinese with English abstract)
[29]	李谷成, 范丽霞, 冯中朝. 资本积累、制度变迁与农业增长: 对1978—2011年中国农业增长与资本存量的实证估计[J]. 管理世界, 2014(5): 67-79.
	LI G C, FAN L X, FENG Z C. Capital accumulation, institutional change and agricultural growth: an empirical estimation of agricultural growth and capital stock in China from 1978 to 2011[J]. Management World, 2014(5): 67-79. (in Chinese)
[30]	MA H Y, HUANG J K, OXLEY L. Capital formation and agricultural growth in China[J]. Asian Economic Papers, 2013, 12(1): 166-190.
[31]	黄勇峰, 任若恩, 刘晓生. 中国制造业资本存量永续盘存法估计[J]. 经济学(季刊), 2002, 1(2): 377-396.
	HUANG Y F, REN R E, LIU X. Capital stock estimates in Chinese manufacturing by perpetual inventory approach[J]. China Economic Quarterly, 2002, 1(2): 377-396. (in Chinese with English abstract)
[32]	张军, 吴桂英, 张吉鹏. 中国省际物质资本存量估算: 1952—2000[J]. 经济研究, 2004, 39(10): 35-44.
	ZHANG J, WU G Y, ZHANG J P. The estimation of China’s provincial capital stock: 1952-2000[J]. Economic Research Journal, 2004, 39(10): 35-44. (in Chinese with English abstract)
[33]	冯海发. 中国农业总生产率的计算与分析[J]. 统计研究, 1988, 5(3): 44-49.
	FENG H F. Calculation and analysis of total agricultural productivity in China[J]. Statistical Research, 1988, 5(3): 44-49. (in Chinese)
[34]	FARRELL M J. The measurement of productive efficiency[J]. Journal of the Royal Statistical Society: Series A(General), 1957, 120(3): 253-281.
[35]	AIGNER D, KNOX LOVELL C A, SCHMIDT P. Formulation and estimation of stochastic frontier production function models[J]. Journal of Econometrics, 1977, 6(1): 21-37.
[36]	MEEUSEN W, VAN DEN BROECK J. Technical efficiency and dimension of the firm: some results on the use of frontier production functions[J]. Empirical Economics, 1977, 2(2): 109-122.
[37]	KUMBHAKAR S C, LIEN G, HARDAKER J B. Technical efficiency in competing panel data models: a study of Norwegian grain farming[J]. Journal of Productivity Analysis, 2014, 41(2): 321-337.
[38]	彭国华. 中国地区收入差距、全要素生产率及其收敛分析[J]. 经济研究, 2005, 40(9): 19-29.
	PENG G H. The disparity of income, TFP and the convergence hypothesis in Chinese provinces[J]. Economic Research Journal, 2005, 40(9): 19-29. (in Chinese with English abstract)
[39]	CARTER C A, CHEN J, CHU B J. Agricultural productivity growth in China: farm level versus aggregate measurement[J]. China Economic Review, 2003, 14(1): 53-71.
[40]	李谷成, 冯中朝, 范丽霞. 农户家庭经营技术效率与全要素生产率增长分解(1999—2003年): 基于随机前沿生产函数与来自湖北省农户的微观证据[J]. 数量经济技术经济研究, 2007, 24(8): 25-34.
	LI G C, FENG Z C, FAN L X. An empirical analysis on the technical efficiencies and the decomposition of TFP of farmer’s household management[J]. The Journal of Quantitative & Technical Economics, 2007, 24(8): 25-34. (in Chinese with English abstract)
[41]	朱喜, 史清华, 盖庆恩. 要素配置扭曲与农业全要素生产率[J]. 经济研究, 2011, 46(5): 86-98.
	ZHU X, SHI Q H, GAI Q E. Misallocation and TFP in rural China[J]. Economic Research Journal, 2011, 46(5): 86-98. (in Chinese with English abstract)
[42]	CAO K H, BIRCHENALL J A. Agricultural productivity, structural change, and economic growth in post-reform China[J]. Journal of Development Economics, 2013, 104: 165-180.

Temporal and spatial changes of China’s agricultural total factor productivity based on the framework of input-output unity

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 42

Related Articles 12

Recommended Articles

Metrics

Comments

[1]	YE Han, WU Bowen, XU Hongwei, GAN Muye, ZHANG Jing, WANG Ke. Analysis on influencing factors and spatial distribution of leisure agriculture at provincial level based on geographic big data: a case study of Zhejiang Province, China [J]. Acta Agriculturae Zhejiangensis, 2021, 33(7): 1264-1274.
[2]	ZHANG Xiongyi, XU Xinliang, ZHANG Zheng, ZHUANG Dachun, ZENG Qin, BI Rengui, YAN Can. Spatial evolution characteristics of total agricultural machinery power in China from 2000 to 2017 [J]. , 2020, 32(4): 714-722.
[3]	ZHANG Han, ZHAO Xiaomin, KUANG Lihua, GUO Xi, LI Weifeng, OUYANG Zhencheng, HUANG Cong, WANG Xiaoyan, YE Yingcong. Spatial distribution features of cultivated land quality based on spatial autocorrelation: A case study of Nanchang County, Jiangxi Province [J]. , 2017, 29(8): 1365-1374.
[4]	SU Zhen\\|guo， LIU Yong\\|hui， LIU Jian\\|bo， ZHU Hong\\|tao. Spatial distribution pattern and sampling technique of overwintering larvae of Apriona germari Hope [J]. , 2016, 28(2): 302-.
[5]	ZHENG Yong\\|li1， WANG En\\|guo2， CAI Jian\\|jun2，LI Guo\\|jun1，YAO Xiao\\|ming1. The spatial distribution pattern and sampling technique of Bemisia tabaci in leafy mustard fields [J]. , 2015, 27(4): 589-.
[6]	XU Yue\\|qi， ZHAO Ming\\|qin， TAO Jin\\|jiang， LI Hui. Pollution assessment and spatial distribution of soil heavy metals in the tobacco production area in southern Shanxi [J]. , 2015, 27(3): 423-.
[7]	ZHU Zhen\\|ling1，2， MA Wan\\|zhu2， LONG Wen\\|li2， REN Zhou\\|qiao2， DENG Xun\\|fei2， CHEN Xiao\\|jia2， SHEN Jian\\|guo3， LYU Xiao\\|nan1，2，*. Spatial distribution characteristics of topsoil organic carbon in farmland and its influencing factors in Yuhang District， Hangzhou City [J]. , 2015, 27(11): 1990-.
[8]	LIU Zhanwei. Growth and decomposition of agricultural total factor productivity in Henan Province under carbon emissions constraint#br# [J]. , 2014, 26(4): 1031-.
[9]	CHEN Jiang;CHANG Yan-chun;TONG Li-hua. Analysis on spatial distribution and correlation of soil organic matter in surface soils of Huzhou [J]. , 2012, 24(4): 0-685.
[10]	ZHU Jin-liang;CHEN Yue;WANG Guang-hua;WANG Hua-di;ZHU Zeng-rong;*. Spatial distribution pattern and sampling technique of Sclerotinia stem rot of oilseed rape in low incidence [J]. , 2012, 24(3): 0-468.
[11]	WANG Li-juan;HU Bao;*;LIU Yu;LI Yu-rui;CAO Jun;TANG Xiao-lu. Changes in the spatial distribution of county economy in Zhejiang in recent three decades [J]. , 2011, 23(4): 0-839.
[12]	LI Gang;WU Yong-han;CHEN Wen-hua;DU Lin-na;XU Fang-cheng;. Spatial distribution patterns of Tomato leaf curl virus* and its vector Bemisia tabaci [J]. , 2010, 22(6): 779-783.