对非农业援助能否“以农兴工”——基于援非农技示范中心的准自然实验Can China's Agricultural Assistance to African Countries Improve the Level of Industrial Development——Quasi natural experiment based on African Agricultural Technology Demonstration Center
高杨,王亚琦,王寿彭
摘要(Abstract):
农业现代化的推进是工业发展的基石与动力源泉。本文基于2000—2019年非洲54个国家的面板数据,以援非农技示范中心开始运营作为外生冲击事件,采用多时点双重差分法就对非农业援助带给受援国工业发展水平的影响予以考察,并对其作用路径进行探析。研究发现,对非农业援助的实施显著提升了受援国工业发展水平,作用路径为产品贡献(粮食和原材料供给)、市场贡献(生活消费和生产消费扩容)和要素贡献(劳动力转移和资本积累)。对非农业援助对经济发展水平低、政治和投资风险程度低、农业自然条件良好的受援国工业发展水平提升作用更强。拓展性分析表明,对非农业援助对受援国产生了“污染光环”效应。本文在丰富对非援助相关研究的同时,也为非洲各国通过重视农业进步进而推动“以农兴工”,最终实现工农联动发展,初步提供了依据。
关键词(KeyWords): 农业技术示范中心;援非;以农兴工;污染光环;多时点双重差分法
基金项目(Foundation): 国家社科基金一般项目:“有为‘链长’赋能绿色低碳农业产业链研究”(22BGL164)的资助
作者(Author): 高杨,王亚琦,王寿彭
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- (1)2006年提出的第一批援非农技示范中心的实际开工建设数增加到14个。
- (2)详见附表1。
- (3)工业增加值占GDP的比重取对数,可反映工业GDP增速和GDP增速的差异。
- (4)佩恩表上提供了两种统计口径的全要素生产率:—种是以各国2005年全要素生产率水平为基准的纵向可比数据;另一种是以美国全要素生产率水平为基准的横向可比数据。为得到时序层面与截面层面同时可比的全要素生产率,本文将以美国为基准的横向全要素生产率与各国纵向可比全要素生产率相乘。
- (5)文中,除政治和制度数据来自WGI和FH、技术水平数据来自GGDC公布的佩恩表(PWT9.1)外,其他变量数据均来自于WDI。
- (6)北非国家包含埃及、突尼斯、利比亚、阿尔及利亚、摩洛哥。
- (7)本文选用NOAA所提供数据中的稳定灯光数据(stable lights)进行分析。需要指出的是,夜间灯光存在饱和度、同一年度不同卫星的数据和同一卫星不同年度的数据具有不可比性等问题。为提高数据准确性,本文参考Liu et al.(2012)的做法,对灯光数据进行校准、合并和修复。
- (8)高收入水平国家包括阿尔及利亚、安哥拉、博茨瓦纳、赤道几内亚、加蓬、利比亚、毛里求斯、纳米比亚、塞舌尔、南非;中等收入水平国家包括喀麦隆、佛得角、吉布提共和国、埃及、加纳、科特迪瓦、毛里塔尼亚、摩洛哥、莱索托、尼日利亚、刚果共和国、苏丹、南苏丹、坦桑尼亚、突尼斯、赞比亚、圣多美和普林西比、斯威士兰;低收入水平国家包括贝宁、布基纳法索、布隆迪、中非、乍得、科摩罗、刚果民主共和国、埃塞俄比亚、厄立特里亚、几内亚、几内亚比绍、肯尼亚、冈比亚、利比里亚、马达加斯加、马拉维、马里、莫桑比克、尼日尔、卢旺达、塞内加尔、塞拉利昂、索马里、多哥、乌干达和津巴布韦。
- (9)以各国政府稳定性指标是否处于中位数以上作为划分标准,若高于中位数为高风险国家,低于中位数为低风险国家。
- (10)以各国投资风险性指标是否处于中位数以上作为划分标准,若高于中位数为高风险国家,低于中位数为低风险国家。
- (11)以平均降水深度是否处于中位数以上作为划分标准,若高于中位数为农业自然良好的国家,低于中位数为农业自然条件恶劣的国家。
- (12)以远低于世界平均水平的单位面积化肥消费量来对非洲各国农业发展中的污染水平加以反映,严谨性存在欠缺,因此排除该指标。