On the reverse causality between output and infrastructure: The case of China

C-Tier
Journal: Economic Modeling
Year: 2018
Volume: 74
Issue: C
Pages: 97-104

Score contribution per author:

0.503 = (α=2.01 / 2 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

After the 2008 global financial crisis, promoting public infrastructure investment as a growth engine has been revived by economists. China has been considered as such a successful example of enhancing economic growth by massive infrastructure investments in the past decades. However, the literature has provided conflicting empirical results on the productivity effect of public infrastructure using aggregate data, mainly due to reverse causality. Thus, the estimated productivity effect could be either upward or downward biased. In this paper we rely on the institutional background of infrastructure investment in China, and explore several alternative ways to mitigate the reverse causality. Using China's provincial-level data over 1996–2015 and within the framework of an aggregate production function estimation, we find that an upward bias dominates when estimating output elasticity of public infrastructure, and that weak evidence is found on the productivity effect of public infrastructure. This finding highlights the necessity of using alternative identification strategies or data types.

Technical Details

RePEc Handle
repec:eee:ecmode:v:74:y:2018:i:c:p:97-104
Journal Field
General
Author Count
2
Added to Database
2026-01-25