Xinjiang Agricultural Sciences ›› 2024, Vol. 61 ›› Issue (S1): 196-205.DOI: 10.6048/j.issn.1001-4330.2024.S1.031
• Agriculture·Economy·Agricultural and Industrial Information • Previous Articles Next Articles
HOU Xianzheng(), XIAO Tong, CHEN Yulan(
), WEI Jiyu
Received:
2024-07-05
Online:
2024-10-10
Published:
2024-11-15
Correspondence author:
CHEN Yulan
Supported by:
通讯作者:
陈玉兰
作者简介:
侯先正(2002-),男,硕士研究生,研究方向农业管理,(E-mail)2625212815@qq.com
基金资助:
CLC Number:
HOU Xianzheng, XIAO Tong, CHEN Yulan, WEI Jiyu. The spatial effects and mechanism of digital technology innovation on agricultural economic resilience[J]. Xinjiang Agricultural Sciences, 2024, 61(S1): 196-205.
侯先正, 肖彤, 陈玉兰, 魏积愚. 数字新质生产力、土地经营效率与新疆农业绿色全要素生产率的关系分析[J]. 新疆农业科学, 2024, 61(S1): 196-205.
地州市 Dizhou City | 2013年 | 2014年 | 2015年 | 2017年 | 2018年 | 2019年 | 2020年 | 2021年 |
---|---|---|---|---|---|---|---|---|
乌鲁木齐市 Urumqi City | 1.286 | 0.642 | 0.787 | 1.036 | 0.879 | 1.096 | 0.918 | 1.046 |
克拉玛依市 Karamay City | 1.225 | 1.103 | 1.022 | 1.008 | 0.876 | 1.063 | 1.282 | 1.02 |
吐鲁番市 Turpan City | 1.141 | 1.039 | 0.999 | 0.999 | 0.954 | 1.076 | 0.978 | 1.022 |
哈密市 Hami region | 1.182 | 0.986 | 1.011 | 1.008 | 0.998 | 1.075 | 0.968 | 1.009 |
昌吉回族自治州 Changji Hui Autonomous Prefecture | 1.088 | 0.993 | 0.988 | 1.001 | 1.055 | 1.007 | 0.974 | 0.997 |
博尔塔拉蒙古自治州 Prefecture | 1.002 | 1.026 | 0.99 | 0.987 | 1.021 | 1.02 | 1.007 | 0.997 |
巴音郭楞蒙古自治州 Bortala Mongol Autonomous Prefecture | 1.118 | 1.041 | 0.982 | 1 | 1.031 | 1.011 | 0.978 | 1.036 |
阿克苏地区 Aksu region | 1.092 | 1.062 | 0.996 | 0.975 | 0.93 | 0.997 | 0.999 | 1.049 |
克孜勒苏柯尔克孜自治州 Kizilsu kirghiz Autonomous Prefecture | 0.925 | 0.987 | 0.995 | 0.995 | 0.98 | 1.028 | 0.902 | 0.972 |
喀什地区 Kashgar region | 0.925 | 1.108 | 0.918 | 0.944 | 0.868 | 0.875 | 0.988 | 1.003 |
和田地区 Hetan region | 1.112 | 1.052 | 0.994 | 0.967 | 1.395 | 0.969 | 1.08 | 1.224 |
伊犁哈萨克自治州 Ili Kazak Autonomous Prefecturse | 1.108 | 1.046 | 0.977 | 0.978 | 0.777 | 1.331 | 1.002 | 1.013 |
塔城地区 Tacheng area | 0.913 | 1.026 | 0.969 | 0.991 | 1.012 | 0.997 | 0.986 | 1.014 |
阿勒泰地区 Altay region | 0.96 | 0.978 | 0.98 | 0.951 | 0.998 | 0.987 | 1.065 | 0.96 |
Tab.1 Changes of agricultural green total factor productivity in 14 regions and prefectures (cities) of Xinjiang from 2013 to 2021
地州市 Dizhou City | 2013年 | 2014年 | 2015年 | 2017年 | 2018年 | 2019年 | 2020年 | 2021年 |
---|---|---|---|---|---|---|---|---|
乌鲁木齐市 Urumqi City | 1.286 | 0.642 | 0.787 | 1.036 | 0.879 | 1.096 | 0.918 | 1.046 |
克拉玛依市 Karamay City | 1.225 | 1.103 | 1.022 | 1.008 | 0.876 | 1.063 | 1.282 | 1.02 |
吐鲁番市 Turpan City | 1.141 | 1.039 | 0.999 | 0.999 | 0.954 | 1.076 | 0.978 | 1.022 |
哈密市 Hami region | 1.182 | 0.986 | 1.011 | 1.008 | 0.998 | 1.075 | 0.968 | 1.009 |
昌吉回族自治州 Changji Hui Autonomous Prefecture | 1.088 | 0.993 | 0.988 | 1.001 | 1.055 | 1.007 | 0.974 | 0.997 |
博尔塔拉蒙古自治州 Prefecture | 1.002 | 1.026 | 0.99 | 0.987 | 1.021 | 1.02 | 1.007 | 0.997 |
巴音郭楞蒙古自治州 Bortala Mongol Autonomous Prefecture | 1.118 | 1.041 | 0.982 | 1 | 1.031 | 1.011 | 0.978 | 1.036 |
阿克苏地区 Aksu region | 1.092 | 1.062 | 0.996 | 0.975 | 0.93 | 0.997 | 0.999 | 1.049 |
克孜勒苏柯尔克孜自治州 Kizilsu kirghiz Autonomous Prefecture | 0.925 | 0.987 | 0.995 | 0.995 | 0.98 | 1.028 | 0.902 | 0.972 |
喀什地区 Kashgar region | 0.925 | 1.108 | 0.918 | 0.944 | 0.868 | 0.875 | 0.988 | 1.003 |
和田地区 Hetan region | 1.112 | 1.052 | 0.994 | 0.967 | 1.395 | 0.969 | 1.08 | 1.224 |
伊犁哈萨克自治州 Ili Kazak Autonomous Prefecturse | 1.108 | 1.046 | 0.977 | 0.978 | 0.777 | 1.331 | 1.002 | 1.013 |
塔城地区 Tacheng area | 0.913 | 1.026 | 0.969 | 0.991 | 1.012 | 0.997 | 0.986 | 1.014 |
阿勒泰地区 Altay region | 0.96 | 0.978 | 0.98 | 0.951 | 0.998 | 0.987 | 1.065 | 0.96 |
一级指标 First level indicator | 三级指标 Third level indicator | 指标衡量方式 Indicator measurement method | 指标属性 Indicator attribute |
---|---|---|---|
数字劳动者 Worker | 数字服务业从业人数占比 | 计算机服务和软件从业人员占总就业人数比值(%) | 正向 |
高等教育人数占比 | 高等教育人数占总人口人数的比值(%) | 正向 | |
数字劳动对象 Digital labor objects | 第三产业增加值占比 | 第三产业增加值占地区GDP的比值(%) | 正向 |
电信业务占比 | 电信业务总量与地区总人口比值(%) | 正向 | |
邮政业务占比 | 邮政业务总量与地区总人口比值(%) | 正向 | |
数字生产资料 Digital means of production | 互联网普及率 | 每百互联网用户数(户) | 正向 |
移动电话普及率 | 每百人移动电话用户数(人) | 正向 | |
邮局密度 | 邮局个数占地区土地总面积的比值(个/×104hm2) | 正向 | |
人均规模以上工业企业 专利申请数 | 规模以上工业企业专利申请数与地区 总人口的比值(件/人) | 正向 | |
R&D投入 | R&D经费支出占地区GDP的比值(×104元) | 正向 | |
数字金融水平 | 数字普惠金融指数 | 正向 |
Tab.2 Measurement index system of digital new quality productivity
一级指标 First level indicator | 三级指标 Third level indicator | 指标衡量方式 Indicator measurement method | 指标属性 Indicator attribute |
---|---|---|---|
数字劳动者 Worker | 数字服务业从业人数占比 | 计算机服务和软件从业人员占总就业人数比值(%) | 正向 |
高等教育人数占比 | 高等教育人数占总人口人数的比值(%) | 正向 | |
数字劳动对象 Digital labor objects | 第三产业增加值占比 | 第三产业增加值占地区GDP的比值(%) | 正向 |
电信业务占比 | 电信业务总量与地区总人口比值(%) | 正向 | |
邮政业务占比 | 邮政业务总量与地区总人口比值(%) | 正向 | |
数字生产资料 Digital means of production | 互联网普及率 | 每百互联网用户数(户) | 正向 |
移动电话普及率 | 每百人移动电话用户数(人) | 正向 | |
邮局密度 | 邮局个数占地区土地总面积的比值(个/×104hm2) | 正向 | |
人均规模以上工业企业 专利申请数 | 规模以上工业企业专利申请数与地区 总人口的比值(件/人) | 正向 | |
R&D投入 | R&D经费支出占地区GDP的比值(×104元) | 正向 | |
数字金融水平 | 数字普惠金融指数 | 正向 |
一级指标 First level indicator | 一级指标 Two level indicator | 三级指标 Third level indicator | 指标衡量方式 Indicator measurement method (%) | 指标属性 Indicator attribute |
---|---|---|---|---|
土地集约经营效率 Effciency of intensive land management | 土地投入水平 | 人口密度 | 人口总数/土地总面积 | 正向 |
地均固定资产投资 | 固定资产投资额/土地总面积 | 正向 | ||
地均从业人员 | 第一产业从业人员/土地总面积 | 正向 | ||
地均财政支出 | 公共财政预算支出/土地总面积 | 正向 | ||
土地产出效益 | 森林覆盖率 | 森林覆盖面积/土地总面积 | 正向 | |
地均财政收入 | 公共财政预算收入/土地总面积 | 正向 | ||
地均GDP | 地区GDP/土地总面积 | 正向 | ||
土地农业利用率 | 农业用地/土地总面积 | 正向 |
Tab.3 Index system of land intensive management efficiency measurement
一级指标 First level indicator | 一级指标 Two level indicator | 三级指标 Third level indicator | 指标衡量方式 Indicator measurement method (%) | 指标属性 Indicator attribute |
---|---|---|---|---|
土地集约经营效率 Effciency of intensive land management | 土地投入水平 | 人口密度 | 人口总数/土地总面积 | 正向 |
地均固定资产投资 | 固定资产投资额/土地总面积 | 正向 | ||
地均从业人员 | 第一产业从业人员/土地总面积 | 正向 | ||
地均财政支出 | 公共财政预算支出/土地总面积 | 正向 | ||
土地产出效益 | 森林覆盖率 | 森林覆盖面积/土地总面积 | 正向 | |
地均财政收入 | 公共财政预算收入/土地总面积 | 正向 | ||
地均GDP | 地区GDP/土地总面积 | 正向 | ||
土地农业利用率 | 农业用地/土地总面积 | 正向 |
变量 Variable | 符号 Symbol | 均值 Mean value | 标准差 Standard deviation | 最小值 Minimum value | 最大值 Maximum value |
---|---|---|---|---|---|
农业绿色全要素生产率 Agricultural green total factor productivity | Agtfp | 1.013 | 0.084 | 0.642 | 1.395 |
数字新质生产力 Digital new quality productivity | Dignqp | 0.186 | 0.134 | 0.029 | 0.592 |
财政支农水平 Financial support for agriculture | Fin | 0.165 | 0.081 | 0.021 | 0.359 |
农村居民收入 Rural residents income | Rrl | 1.509 | 0.6 | 0.427 | 3.411 |
地区资源禀赋 Regional resource endowment | Rre | 34.262 | 49.367 | 0.36 | 264.795 |
城镇化水平 Urbanization level | Urb | 0.522 | 0.226 | 0.151 | 1 |
农业劳动力质量 Quality of agricultural labor force | Alq | 2.751 | 3.343 | 0.172 | 14.845 |
土地集约经营效率 Effciency of land infensive management | Intensity | 0.13 | 0.167 | 0.006 | 0.826 |
土地规模经营效率 Efficiency of land scale management | Landtr | 0.988 | 0.416 | 0.241 | 2.258 |
Tab.4 Descriptive statistical characteristics of variables
变量 Variable | 符号 Symbol | 均值 Mean value | 标准差 Standard deviation | 最小值 Minimum value | 最大值 Maximum value |
---|---|---|---|---|---|
农业绿色全要素生产率 Agricultural green total factor productivity | Agtfp | 1.013 | 0.084 | 0.642 | 1.395 |
数字新质生产力 Digital new quality productivity | Dignqp | 0.186 | 0.134 | 0.029 | 0.592 |
财政支农水平 Financial support for agriculture | Fin | 0.165 | 0.081 | 0.021 | 0.359 |
农村居民收入 Rural residents income | Rrl | 1.509 | 0.6 | 0.427 | 3.411 |
地区资源禀赋 Regional resource endowment | Rre | 34.262 | 49.367 | 0.36 | 264.795 |
城镇化水平 Urbanization level | Urb | 0.522 | 0.226 | 0.151 | 1 |
农业劳动力质量 Quality of agricultural labor force | Alq | 2.751 | 3.343 | 0.172 | 14.845 |
土地集约经营效率 Effciency of land infensive management | Intensity | 0.13 | 0.167 | 0.006 | 0.826 |
土地规模经营效率 Efficiency of land scale management | Landtr | 0.988 | 0.416 | 0.241 | 2.258 |
(1) Agtfp | (2) Agtfp | (3) Agtfp | (4) Agtfp | (5) Agtfp | (6) Agtfp | |
---|---|---|---|---|---|---|
Dignqp | 0.498 4*** (0.17) | 0.460 6*** (0.17) | 0.486 1*** (0.16) | 0.438 6*** (0.16) | 0.417 9*** (0.16) | 0.418 1*** (0.16) |
Fin | 0.964 9*** (0.31) | 0.942 2*** (0.30) | 0.817 0 *** (0.30) | 0.729 1*** (0.29) | 0.727 2*** (0.29) | |
Rrl | 0.058 5** (0.02) | 0.061 0** (0.02) | 0.051 9** (0.02) | 0.052 7** (0.02) | ||
Rre | 0.001 0** (0.00) | 0.000 8* (0.00) | 0.000 8* (0.00) | |||
Urb | 0.210 3*** (0.07) | 0.214 3*** (0.07) | ||||
Alq | 0.002 3 (0.00) | |||||
个体固定效应 Individual fixed effects | YES | YES | YES | YES | YES | YES |
年份固定效应 Fixed year effect | YES | YES | YES | YES | YES | YES |
N | 126 | 126 | 126 | 126 | 126 | 126 |
R2 | 0.142 2 | 0.218 6 | 0.262 1 | 0.300 8 | 0.354 5 | 0.300 8 |
Tab.5 Baseline regression results
(1) Agtfp | (2) Agtfp | (3) Agtfp | (4) Agtfp | (5) Agtfp | (6) Agtfp | |
---|---|---|---|---|---|---|
Dignqp | 0.498 4*** (0.17) | 0.460 6*** (0.17) | 0.486 1*** (0.16) | 0.438 6*** (0.16) | 0.417 9*** (0.16) | 0.418 1*** (0.16) |
Fin | 0.964 9*** (0.31) | 0.942 2*** (0.30) | 0.817 0 *** (0.30) | 0.729 1*** (0.29) | 0.727 2*** (0.29) | |
Rrl | 0.058 5** (0.02) | 0.061 0** (0.02) | 0.051 9** (0.02) | 0.052 7** (0.02) | ||
Rre | 0.001 0** (0.00) | 0.000 8* (0.00) | 0.000 8* (0.00) | |||
Urb | 0.210 3*** (0.07) | 0.214 3*** (0.07) | ||||
Alq | 0.002 3 (0.00) | |||||
个体固定效应 Individual fixed effects | YES | YES | YES | YES | YES | YES |
年份固定效应 Fixed year effect | YES | YES | YES | YES | YES | YES |
N | 126 | 126 | 126 | 126 | 126 | 126 |
R2 | 0.142 2 | 0.218 6 | 0.262 1 | 0.300 8 | 0.354 5 | 0.300 8 |
变量 Variable | (1) 更换被 解释变量 (新测算方法) | (2) 工具 变量法 | (3) GMM 估计法 |
---|---|---|---|
Dignqp | 0.5279** (0.27) | 1.0863*** (0.58) | 0.3313** (0.16) |
AR(1) | -3.51 | ||
AR(2) | -0.03 | ||
Cragg - Donald Wald F statistic | 10.25*** | ||
Kleibergen - Paap Wald rk F statistic | 11.11*** | ||
控制变量 Control variable | YES | YES | YES |
个体固定效应 Individual fixed effects | YES | YES | YES |
年份固定效应 Fixed year effect | YES | NO | NO |
N | 126 | 126 | 126 |
R2 | 0.222 9 | 0.303 4 |
Tab.6 Robustness test
变量 Variable | (1) 更换被 解释变量 (新测算方法) | (2) 工具 变量法 | (3) GMM 估计法 |
---|---|---|---|
Dignqp | 0.5279** (0.27) | 1.0863*** (0.58) | 0.3313** (0.16) |
AR(1) | -3.51 | ||
AR(2) | -0.03 | ||
Cragg - Donald Wald F statistic | 10.25*** | ||
Kleibergen - Paap Wald rk F statistic | 11.11*** | ||
控制变量 Control variable | YES | YES | YES |
个体固定效应 Individual fixed effects | YES | YES | YES |
年份固定效应 Fixed year effect | YES | NO | NO |
N | 126 | 126 | 126 |
R2 | 0.222 9 | 0.303 4 |
变量 Variable | (1)北疆 (1)Northern Xinjiang | (2)南疆 (2)South Xinjiang | (3)东疆 (3)Eastern Xinjiang |
---|---|---|---|
Dignqp | 0.480 3*** (0.18) | 0.449 3* (0.28) | 0.161 0 (0.17) |
控制变量 Control variable | YES | YES | YES |
个体固定效应 Individual fixed effects | YES | YES | YES |
年份固定效应 Fixed year effect | NO | NO | NO |
N | 63 | 45 | 18 |
R2 | 0.239 3 | 0.311 6 | 0.058 9 |
Tab.7 Heterogeneity test
变量 Variable | (1)北疆 (1)Northern Xinjiang | (2)南疆 (2)South Xinjiang | (3)东疆 (3)Eastern Xinjiang |
---|---|---|---|
Dignqp | 0.480 3*** (0.18) | 0.449 3* (0.28) | 0.161 0 (0.17) |
控制变量 Control variable | YES | YES | YES |
个体固定效应 Individual fixed effects | YES | YES | YES |
年份固定效应 Fixed year effect | NO | NO | NO |
N | 63 | 45 | 18 |
R2 | 0.239 3 | 0.311 6 | 0.058 9 |
变量 Variable | (1) Intensity | (2) Landtr | (3) Agtfp | (4) Agtfp |
---|---|---|---|---|
Dignqp | 0.141 8** (0.06) | 0.880 9** (0.35) | 0.396 7** (0.17) | 0.380 0** (0.17) |
Intensity | 0.717 0*** (0.27) | |||
Landtr | 0.134 3*** (0.05) | |||
控制变量 Control variable | YES | YES | YES | YES |
个体 固定效应 Individual fixed effects | YES | YES | YES | YES |
年份 固定效应 Fixed year effect | YES | YES | YES | YES |
N | 126 | 126 | 126 | 126 |
R2 | 0.709 5 | 0.560 0 | 0.296 5 | 0.203 7 |
Tab.8 Test results of influence mechanism
变量 Variable | (1) Intensity | (2) Landtr | (3) Agtfp | (4) Agtfp |
---|---|---|---|---|
Dignqp | 0.141 8** (0.06) | 0.880 9** (0.35) | 0.396 7** (0.17) | 0.380 0** (0.17) |
Intensity | 0.717 0*** (0.27) | |||
Landtr | 0.134 3*** (0.05) | |||
控制变量 Control variable | YES | YES | YES | YES |
个体 固定效应 Individual fixed effects | YES | YES | YES | YES |
年份 固定效应 Fixed year effect | YES | YES | YES | YES |
N | 126 | 126 | 126 | 126 |
R2 | 0.709 5 | 0.560 0 | 0.296 5 | 0.203 7 |
变量Variable | Ins |
---|---|
Dignqp(Intensity<0.032) | 0.3440*** (0.13) |
Dignqp(Intensity≥0.032) | 0.7125*** (0.14) |
控制变量 Control variable | YES |
个体固定效应 Individual fixed effects | YES |
年份固定效应 Fixed year effect | YES |
Constant | 0.6236*** (0.06) |
N | 126 |
R2 | 0.3818 |
Tab.9 Results of the existence test of threshold values
变量Variable | Ins |
---|---|
Dignqp(Intensity<0.032) | 0.3440*** (0.13) |
Dignqp(Intensity≥0.032) | 0.7125*** (0.14) |
控制变量 Control variable | YES |
个体固定效应 Individual fixed effects | YES |
年份固定效应 Fixed year effect | YES |
Constant | 0.6236*** (0.06) |
N | 126 |
R2 | 0.3818 |
门槛变量 Threshold variable | 门槛类型 Threshold type | P值 | 门槛值 Threshold | BS次数 BS Number of times | 1% | 5% | 10% |
---|---|---|---|---|---|---|---|
土地集约 经营效率 Effciency of intensive land management | 单一门槛 | 0.00 | 0.032 | 300 | 13.685 | 10.143 | 8.413 |
双重门槛 | 0.17 | 0.301 | 300 | 17.569 | 13.156 | 11.773 | |
三重门槛 | 0.27 | 0.688 | 300 | 21.641 8 | 15.438 2 | 11.769 6 |
Tab.10 Threshold regression test results
门槛变量 Threshold variable | 门槛类型 Threshold type | P值 | 门槛值 Threshold | BS次数 BS Number of times | 1% | 5% | 10% |
---|---|---|---|---|---|---|---|
土地集约 经营效率 Effciency of intensive land management | 单一门槛 | 0.00 | 0.032 | 300 | 13.685 | 10.143 | 8.413 |
双重门槛 | 0.17 | 0.301 | 300 | 17.569 | 13.156 | 11.773 | |
三重门槛 | 0.27 | 0.688 | 300 | 21.641 8 | 15.438 2 | 11.769 6 |
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