Efficiency of PPP Investment in Infrastructure

Sixiang Wu () and Xuemeng Guo ()
Additional contact information
Sixiang Wu: Beijing Jiaotong University
Xuemeng Guo: Beijing Jiaotong University

A chapter in IEIS 2020, 2021, pp 339-354 from Springer

Abstract: Abstract In recent years, the Public–Private Partnership (PPP), as a new channel for providing public services, has received strong support from the Chinese government. This paper establishes a relatively objective evaluation index by combining the super-efficiency DEA method with the Malmquist index. It measures the investment efficiency of PPP projects in 18 provinces in North China, East China, South China and Central China from 2006 to 2018. The results show that, on the whole, the investment efficiency of PPP projects in China’s infrastructure sector is not high. And the trend is declining year by year. Meanwhile, with the continuous advancement of PPP mode, the influencing factor of investment efficiency has changed from technological progress to efficiency change. In addition, the investment efficiency of PPP projects has the problem of uneven regional development. For example, compared with the other three regions, central China may be relatively weak in technological progress, which drags down the investment efficiency.

Keywords: PPP; Investment efficiency; Super-efficiency DEA; Malmquist (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4363-4_26

Ordering information: This item can be ordered from
http://www.springer.com/9789813343634

DOI: 10.1007/978-981-33-4363-4_26

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().