Joined-up approaches to economic development and climate
Macroeconomic models from the IKI provide a perspective on the benefits of adaptation measures for the economy as a whole.
The report Climate Change 2022 – Impacts, Adaptation and Vulnerability from the Intergovernmental Panel on Climate Change (IPCC) shows that a livable future on our planet is possible only if state-level long-term planning includes a greater focus on adaptation to the impacts of climate change. In particular, economic development and climate adaptation must be considered as parts of a whole. However, this meshing of economic policy and adaptation measures still remains the exception in most countries to date. As a result, climate risks continue to manifest their devastating potential largely unhindered and cause economic losses that could otherwise be avoided.
This is where the IKI´s Policy Advice for Climate Resilient Economic Development project (CRED) comes in. Macroeconomic modelling in particular aims to improve the basis of information available for policymaking decisions. The key advantage of macroeconomic modelling is that it can present synergistic benefits and thereby enable a long-term perspective for planning.
The results of such modelling can highlight areas where investment in an adaptation measure can affect macroeconomic indicators – such as the country’s gross domestic product or its employment rate – over the medium to long term. Climate risk and adaptation measures can then be integrated into national economic policy in order to put climate-resilient economic development theory into practice.
Macroeconomic modelling in the adaptation policy cycle
The policy brief ‘Macroeconomic Models for Climate Resilience’ published by the IKI’s CRED project utilises adaptation policy to illustrate the benefits of macroeconomic modelling.
This adaptation policy cycle can itself be subdivided into three phases:
The first phase lays the foundations for macroeconomic modelling work. As a first step, it is important to establish the needs and political mandates for adaptation measures within a ministry. Ideally, this should produce a policy leadership role that is then of use when implementing the subsequent steps and ensuring coordination between the participating stakeholders.
The next step is to analyse the country’s climate risks and vulnerabilities, and give these an economic weighting. This work involves considering future climate scenarios while analysing past and current economic losses resulting from climate-related hazards. This leads to a prognosis of the long-term development of economic losses.
As a final step, adaptation measures for macroeconomic modelling are then identified; these can be concrete investments in climate-resilient roads, drip irrigation in agriculture, protection from strong winds by hedges and much more. As this kind of analysis requires a lot of data, only the most relevant measures should be selected.
The second phase in the policy cycle involves the actual modelling itself, which extends over a longer period of time covering at least 30 years. The development of economic key indicators is mapped out over this timespan: these key indicators include gross domestic product, sectoral productivity and the employment rate.
To obtain a better idea of the economic impact of individual adaptation measures, the modelling approach utilises a hypothetical comparison scenario in which climate change does not take place. As a first step, the climate risks analysed beforehand are then integrated into this comparison scenario. This has the effect of highlighting the long-term impact from climate change on the economy.
The next step is then to incorporate the adaptation measures. The macroeconomic consequences of individual adaptation measures can be estimated by comparing the two scenarios, ‘Climate change with no adaptation’ and ‘Climate change with adaptation’.
Examples of such modelling work can be found in the policy briefs produced by the CRED project, such as in the publications Agriculture in Kazakhstan and Tourism and Infrastructure in Georgia.
In the third phase of the policy cycle, the adaptation measures are selected and implemented. Suitable adaptation measures are chosen based on the results of macroeconomic modelling. The necessary budget decisions are justified by the prior assessment of the economic impacts of the various adaptation measures. Modelling results can also improve the monitoring and evaluation of adaptation measures, since these results already include indicators such as the employment rate, which can be used to assess the measures.
Benefits and challenges at a glance
One of the greatest benefits of macroeconomic modelling is also the most obvious: the economic impact of climate risks and adaptation measures is made visible, and can then be used as input for national economic policy. Macroeconomic models also facilitate comprehensive risk assessments, which provide a more detailed overview of the social and economic impacts of climate-related risk.
One should be aware, however, that such a model is typically unable to portray the non-economic impacts of climate change – which include the loss of biodiversity, for example. The sheer amount of data involved presents another difficulty with macroeconomic modelling. Comprehensive data sets are required on economic indicators and climate risks/losses, as well as cost-benefit analyses for the adaptation measures planned.
Despite the challenges involved in macroeconomic modelling, it must nonetheless be acknowledged that the continuous fine-tuning of the original model is a major strength of this approach. For example, economists are in constant exchange with business and academia as well as government decision-makers about which are the most effective adaptation approaches for a resilient economy.
These dialogue processes are just as important as the actual results of modelling, since they help to promote a ‘joined-up’ approach to climate and the economy.
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Zukunft – Umwelt – Gesellschaft (ZUG) gGmbH
Publications to the news article
03/ 2023 | Educational material
Strengthening Decision-Making for Risk-Informed DevelopmentEnglish (PDF, 581 KB)