Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure
Public-private partnerships (PPPs) in infrastructure provision have expanded around the world since the early 1990s. Well-structured PPPs can unleash efficiency gains, but PPPs create liabilities for governments, including contingent ones. This pap...
Main Authors: | , , |
---|---|
Format: | Working Paper |
Language: | English |
Published: |
Washington, DC: World Bank
2022
|
Subjects: | |
Online Access: | http://documents.worldbank.org/curated/en/750981647367854667/Fiscal-Risks-from-Early-Termination-of-Public-Private-Partnerships-in-Infrastructure http://hdl.handle.net/10986/37159 |
id |
okr-10986-37159 |
---|---|
recordtype |
oai_dc |
spelling |
okr-10986-371592022-03-18T05:10:43Z Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure Herrera Dappe, Matias Melecky, Martin Turkgulu, Burak PRIVATE PARTICIPATION IN INFRASTRUCTURE PER CAPITA GROWTH RATE JAPAN INTERNATIONAL COOPERATION AGENCY ORDINARY LEAST SQUARES REGRESSION BASELINE HAZARD FUNCTION ECONOMETRIC ESTIMATION Public-private partnerships (PPPs) in infrastructure provision have expanded around the world since the early 1990s. Well-structured PPPs can unleash efficiency gains, but PPPs create liabilities for governments, including contingent ones. This paper assesses the fiscal risks from contingent liabilities from early termination of PPPs in a sample of developing countries. It analyzes the drivers of early termination and identifies systematic contractual, institutional, and macroeconomic factors that can help predict the probability that a PPP project will be terminated early, using a flexible parametric hazard regression. Using the probability distributions from the regression analysis, it simulates scenarios of fiscal risks for governments from early termination of PPPs in the electricity and transport sectors, adopting a value-at-risk approach. The findings indicate that the rate of early terminations decreases with direct government support, greater constraints on executive power, and the award of the PPP by subnational governments; it increases with project size and macro-financial shocks. The simulations show that fiscal risks from infrastructure PPP portfolios are not negligible in some countries, reaching as high as 2.8 percent of GDP. A severe macro-financial shock substantially increases the estimates, with the value at risk the year after the shock 11–20 times larger. 2022-03-17T17:56:06Z 2022-03-17T17:56:06Z 2022-03-15 Working Paper http://documents.worldbank.org/curated/en/750981647367854667/Fiscal-Risks-from-Early-Termination-of-Public-Private-Partnerships-in-Infrastructure http://hdl.handle.net/10986/37159 English CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank Washington, DC: World Bank Policy Research Working Paper Publications & Research |
repository_type |
Digital Repository |
institution_category |
Foreign Institution |
institution |
Digital Repositories |
building |
World Bank Open Knowledge Repository |
collection |
World Bank |
language |
English |
topic |
PRIVATE PARTICIPATION IN INFRASTRUCTURE PER CAPITA GROWTH RATE JAPAN INTERNATIONAL COOPERATION AGENCY ORDINARY LEAST SQUARES REGRESSION BASELINE HAZARD FUNCTION ECONOMETRIC ESTIMATION |
spellingShingle |
PRIVATE PARTICIPATION IN INFRASTRUCTURE PER CAPITA GROWTH RATE JAPAN INTERNATIONAL COOPERATION AGENCY ORDINARY LEAST SQUARES REGRESSION BASELINE HAZARD FUNCTION ECONOMETRIC ESTIMATION Herrera Dappe, Matias Melecky, Martin Turkgulu, Burak Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure |
description |
Public-private partnerships (PPPs) in
infrastructure provision have expanded around the world
since the early 1990s. Well-structured PPPs can unleash
efficiency gains, but PPPs create liabilities for
governments, including contingent ones. This paper assesses
the fiscal risks from contingent liabilities from early
termination of PPPs in a sample of developing countries. It
analyzes the drivers of early termination and identifies
systematic contractual, institutional, and macroeconomic
factors that can help predict the probability that a PPP
project will be terminated early, using a flexible
parametric hazard regression. Using the probability
distributions from the regression analysis, it simulates
scenarios of fiscal risks for governments from early
termination of PPPs in the electricity and transport
sectors, adopting a value-at-risk approach. The findings
indicate that the rate of early terminations decreases with
direct government support, greater constraints on executive
power, and the award of the PPP by subnational governments;
it increases with project size and macro-financial shocks.
The simulations show that fiscal risks from infrastructure
PPP portfolios are not negligible in some countries,
reaching as high as 2.8 percent of GDP. A severe
macro-financial shock substantially increases the estimates,
with the value at risk the year after the shock 11–20 times larger. |
format |
Working Paper |
author |
Herrera Dappe, Matias Melecky, Martin Turkgulu, Burak |
author_facet |
Herrera Dappe, Matias Melecky, Martin Turkgulu, Burak |
author_sort |
Herrera Dappe, Matias |
title |
Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure |
title_short |
Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure |
title_full |
Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure |
title_fullStr |
Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure |
title_full_unstemmed |
Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure |
title_sort |
fiscal risks from early termination of public-private partnerships in infrastructure |
publisher |
Washington, DC: World Bank |
publishDate |
2022 |
url |
http://documents.worldbank.org/curated/en/750981647367854667/Fiscal-Risks-from-Early-Termination-of-Public-Private-Partnerships-in-Infrastructure http://hdl.handle.net/10986/37159 |
_version_ |
1764486640224436224 |