当前位置: X-MOL 学术Review of Development Economics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Biased FDI spillovers in incomplete datasets: An empirical examination
Review of Development Economics ( IF 2.0 ) Pub Date : 2020-12-20 , DOI: 10.1111/rode.12740
Dea Tusha 1 , Jacob A. Jordaan 2
Affiliation  

We examine biases in foreign direct investment (FDI) productivity spillovers that can arise when using incomplete datasets, by comparing estimates for Indonesia from the World Bank Enterprise Survey (WBES)—an incomplete dataset example—with estimates from the Indonesian Manufacturing Survey (MS). Furthermore, we conduct estimations on samples drawn from MS, following the sampling methodology of WBES. We find that estimates with this sampling framework are inaccurate, due to measurement error in industry-level horizontal and vertical FDI, strong presence of small firms, and small sample size. Relaxing the WBES sampling criteria and using FDI variables from MS produces substantially more reliable findings.

中文翻译:

不完整数据集中的有偏向的外国直接投资溢出:一项实证检验

通过比较世界银行企业调查(WBES)对印尼的估计(不完整的数据集示例)与印尼制造业调查(MS)的估计,我们研究了使用不完整数据集时可能出现的外国直接投资(FDI)生产率溢出偏差。 。此外,我们根据WBES的抽样方法,对从MS提取的样本进行估算。我们发现,由于行业水平和垂直外国直接投资中的计量误差,小企业的存在以及小样本规模,这种抽样框架的估计是不准确的。放宽WBES抽样标准,并使用MS的FDI变量会产生更为可靠的发现。
更新日期:2020-12-20
down
wechat
bug