“双碳”目标下新疆粮食绿色全要素生产率的时空分异及驱动因素分析

doi:10.12118/j.issn.1000-6060.2023.169

Abstract

Abstract:

Xinjiang plays a crucial role as a significant grain production area and a key reservoir of arable land resources in China. Evaluating the green total factor productivity (GTFP) of grain in Xinjiang within the context of the carbon peaking and carbon neutrality goals holds substantial importance for advancing the green transformation of agriculture and ensuring food security in the region. This study incorporates carbon emissions from nondesired output in grain production into a framework for measuring grain GTFP. Using the SBM-GML model, we assessed the grain GTFP for 14 prefectures and municipalities in Xinjiang spanning the years 2000 to 2020. The analysis includes an examination of the spatial and temporal evolution of grain GTFP in each Xinjiang region (the North Xinjiang, East Xinjiang and South Xinjiang) using the kernel density estimation method and Dagum’s Gini coefficient decomposition. Moreover, we employ a fixed effects model to identify the impacts on the total factor productivity of Xinjiang’s agriculture. Subsequently, the fixed effects model is used to pinpoint the driving factors influencing grain GTFP in Xinjiang. The findings reveal several key insights: (1) Xinjiang’s grain GTFP exhibits an upward trajectory from 2000 to 2020, with an average annual growth rate of 0.7%. This growth is primarily attributed to advancements in grain green technology efficiency (GEC), while progress in grain green technology (GTC) acts as a constraining factor. (2) Notable regional heterogeneity characterizes the growth of Xinjiang’s grain GTFP, with the North Xinjiang region surpassing East Xinjiang and South Xinjiang in this regard. (3) Temporal regional disparities demonstrate a pattern of initial narrowing followed by an expansion, with intra-regional distinctions being the primary source of spatial differences. In addition, changes in the structure of grain cultivation significantly contribute to the growth of grain GTFP in Xinjiang, whereas urbanization levels and rural electricity consumption exert a notable dampening effect.

Key words: grain GTFP, dynamic evolution, drivers, carbon emissions, Xinjiang

MA Wenjiang, BAI Miaoqin, Adili AIHEMAITI, ZHANG Deping, YANG Zhongna. Spatial-temporal differentiation and driving factors analysis of green total factor productivity of Xinjiang grain under the carbon peaking and carbon neutrality goals[J].Arid Land Geography, 2023, 46(12): 2029-2041.

Figures/Tables 9

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碳源	碳排放系数	参考来源
化肥	0.8956 kg C·kg^-1	美国橡树岭国家实验室（OPNL）
柴油	0.5927 kg C·kg^-1	政府间气候变化专门委员会（IPCC）^[30]
翻耕	312.6 kg C·hm^-2	中国农业大学农学与生物技术学院（IABCAU）
灌溉	266.48 kg C·hm^-2	段华平等^[31]

年度	绿色技术效率（GEC）	绿色技术进步（GTC）	绿色全要素生产率（GTFP）
2000—2001	0.994	0.906	0.901
2001—2002	0.997	0.985	0.981
2002—2003	1.012	0.982	0.994
2003—2004	1.005	0.986	0.989
2004—2005	1.040	0.906	0.936
2005—2006	0.996	1.047	1.044
2006—2007	1.030	0.938	0.962
2007—2008	0.996	1.061	1.056
2008—2009	0.991	0.971	0.962
2009—2010	1.009	0.969	0.977
2010—2011	1.019	0.972	0.989
2011—2012	1.004	0.980	0.984
2012—2013	1.001	1.022	1.024
2013—2014	1.010	0.951	0.967
2014—2015	1.040	1.009	1.042
2015—2016	0.976	1.131	1.099
2016—2017	1.026	0.881	0.902
2017—2018	1.062	1.397	1.506
2018—2019	0.986	0.967	0.953
2019—2020	1.006	0.853	0.866
均值	1.010	0.996	1.007

变量	全疆	北疆	东疆	南疆
ln(PGDP_it)	-0.063（-0.88）	0.186^**（2.53）	0.420（0.90）	0.0575（0.53）
ln(URB_it)	-0.133^**（-2.34）	0.101（1.00）	-0.659^*（-2.06）	0.210^**（2.16）
ln(MACH_it)	0.015（0.30）	-0.136^**（-2.44）	1.365^**（2.23）	-0.198^**（-2.14）
ln(CPS_it)	0.123^***（4.30）	0.0603^*（1.75）	-0.109（-0.64）	0.208^**（2.01）
ln(ST_it)	-0.073（-0.51）	-0.125（-0.85）	-2.271（-1.07）	0.444（1.40）
ln(ELE_it)	-0.048^*（-1.86）	-0.0325（-1.40）	0.268（0.67）	-0.075（-1.40）
Constant	1.045（1.32）	-0.205（-0.23）	-19.26^*（-1.84）	2.218^**（2.17）
时间固定	YES	YES	YES	YES
地区固定	YES	YES	YES	YES
Obs.	294	147	42	105
R²	0.465	0.585	0.528	0.708

Spatial-temporal differentiation and driving factors analysis of green total factor productivity of Xinjiang grain under the carbon peaking and carbon neutrality goals

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