Summary information

Study title

Adaptation and climate-resilient development 1980-2008

Creator

Fankhauser, S, London School of Economics

Study number / PID

853653 (UKDA)

10.5255/UKDA-SN-853653 (DOI)

Data access

Restricted

Series

Not available

Abstract

The main empirical paper (Fankhauser and McDermott 2014) uses panel data on natural disasters at the country-year level to estimate the degree of adaptation to disaster risks observed in countries with different income levels. This information is then used to explain the origin and nature of the so-called adaptation gap: the observation that low-income countries tend to have lower levels of adaptation than high-income countries.

This CCCEP project explored, from an economics angle, policy challenges related to climate-resilient development and adaptation to climate change. There were three main lines of enquiry. A first set of papers analysed the link between economic development, income growth and vulnerability to climate change. They explored to what extent economic development might increase or decrease the climate change risks faced by developing countries. A second set of papers analysed what the extra costs might be of climate-proofing economic development paths, in other words, what the costs of adaptation could be. The third strand of work was normative and developed recommendations for adaptation planning and the allocation of adaptation finance.

Methodology

Data collection period

01/01/1980 - 31/12/2008

Country

World Wide

Time dimension

Not available

Analysis unit

Other

Universe

Not available

Sampling procedure

Not available

Kind of data

Numeric

Data collection mode

The paper relied on the natural disaster data from the Munich Re NatCat database. The proprietary NatCat databaserecords all natural hazard events worldwide that result in property damage or personal injury. The paper used data for two disaster types over the period 1980 to 2008, floods and tropicalcyclones. The disaster data were converted into 2,274 country-year observationsthat formed the dependent variable.The control variables include economic data (GDP, GDP per capita, and government spending) from the World Bank’s World Development Indicators and estimates of countrysize (area in km2) from the Portland State University Country Geography data set. For more information, see the ReadMe file attached.

Funding information

Grant number

RES-599-28-0001

Access

Publisher

UK Data Service

Publication year

2019

Terms of data access

The Data Collection is available from an external repository. Access is available via Related Resources.

Related publications

Not available