Ex-Ante Evaluation of Public-Private Partnerships: Macroeconomic Analysis

Henry Liu; Peter E.D. Love; Brad Carey; Jim Smith; Michael Regan

doi:10.1061/(asce)is.1943-555x.0000228

Ex-Ante Evaluation of Public-Private Partnerships: Macroeconomic Analysis

Henry Liu, Peter E.D. Love, Brad Carey, Jim Smith, Michael Regan

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

Public-private partnerships (PPPs) are currently a popular approach for governments to procure social and economic infrastructure. The macroeconomic environment plays a critical role and influences the factors that can lead to the successful delivery of a PPP project. Despite the importance of the macroeconomic environment, limited attention has been paid to ex-ante (that is, before the event, or forecast) evaluation. A review of the normative literature was undertaken, aiming to derive key performance indicators (KPIs) of PPP success. The KPIs were validated by using a vector error correction model. It is suggested that the developed KPIs can be used to evaluate the suitability of the macroeconomic conditions in which a PPP project will be implemented. These KPIs can provide governments and stakeholders with a platform to conduct an effective ex-ante evaluation of PPP projects that will be significant in policy and decision making.

Original language	English
Article number	04014038
Number of pages	8
Journal	Journal of Infrastructure Systems
Volume	21
Issue number	2
Early online date	30 Jun 2014
DOIs	https://doi.org/10.1061/(asce)is.1943-555x.0000228
Publication status	Published - 1 Jun 2015
Externally published	Yes

Keywords

Ex-ante evaluation
Public-private partnerships
key performance indicators
Macroeconomic environment

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10.1061/(asce)is.1943-555x.0000228

Cite this

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abstract = "Public-private partnerships (PPPs) are currently a popular approach for governments to procure social and economic infrastructure. The macroeconomic environment plays a critical role and influences the factors that can lead to the successful delivery of a PPP project. Despite the importance of the macroeconomic environment, limited attention has been paid to ex-ante (that is, before the event, or forecast) evaluation. A review of the normative literature was undertaken, aiming to derive key performance indicators (KPIs) of PPP success. The KPIs were validated by using a vector error correction model. It is suggested that the developed KPIs can be used to evaluate the suitability of the macroeconomic conditions in which a PPP project will be implemented. These KPIs can provide governments and stakeholders with a platform to conduct an effective ex-ante evaluation of PPP projects that will be significant in policy and decision making.",

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AU - Liu, Henry

AU - Love, Peter E.D.

AU - Carey, Brad

AU - Smith, Jim

AU - Regan, Michael

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AB - Public-private partnerships (PPPs) are currently a popular approach for governments to procure social and economic infrastructure. The macroeconomic environment plays a critical role and influences the factors that can lead to the successful delivery of a PPP project. Despite the importance of the macroeconomic environment, limited attention has been paid to ex-ante (that is, before the event, or forecast) evaluation. A review of the normative literature was undertaken, aiming to derive key performance indicators (KPIs) of PPP success. The KPIs were validated by using a vector error correction model. It is suggested that the developed KPIs can be used to evaluate the suitability of the macroeconomic conditions in which a PPP project will be implemented. These KPIs can provide governments and stakeholders with a platform to conduct an effective ex-ante evaluation of PPP projects that will be significant in policy and decision making.

KW - Ex-ante evaluation

KW - Public-private partnerships

KW - key performance indicators

KW - Macroeconomic environment

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DO - 10.1061/(asce)is.1943-555x.0000228

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JO - Journal of Infrastructure Systems

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Ex-Ante Evaluation of Public-Private Partnerships: Macroeconomic Analysis

Abstract

Keywords

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