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Measuring the Socioeconomic Impacts of Climate Policies to Guide NDC Enhancement and a Just Transition

Published on 10 June 2022

The preamble of the Paris Agreement on climate change, adopted in 2015, underscores close links between climate action, sustainable development and a just transition, with Parties to the Agreement “taking into account the imperatives of a just transition of the workforce and the creation of decent work and quality jobs in accordance with nationally defined development priorities." Ideally, any NDC process should be informed by an assessment of the employment impacts—positive and negative—as well as an indication of the measures that will be taken to ensure a Just Transition for workers, as indicated in the Paris Agreement.

Against this background, UNDP and ILO (International Labour Organisation) supported a number of countries to measure how green and climate policies affect job creation, for women and youth, income distribution, skills development and economic growth, using the Green Jobs Assessment Model. Countries develop a national Green Jobs Assessment Model which provides quantitative and qualitative employment estimates for evidence based NDC making. These findings from the modelling provide insights for policy makers to understand co-benefits and distributional impact of proposed policies, and ultimately to choose those which reduce greenhouse emissions and bring considerable economic and social benefits.

The dashboard demonstrates results of the green jobs assessment undertaken in Nigeria and Zimbabwe. Using a green jobs assessment model, both countries measured  how climate and green economy policies would affect job creation, including for women and youth, income distribution, skills development and economic growth in their context.

The process has yielded some interesting and instructive results, with the modelling revealing very different medium- and long-term job growth implications.

In Zimbabwe, of the dozen climate investments and policy scenarios modelled – covering energy, industrial processes, agriculture and forestry – investments in conservation agriculture created up to 30,000 jobs for every million US dollars invested. This number stands in high contrast to only 100 jobs created for each million invested in a hydro dam and 25 in commercial solar.

Nigeria found similar positives for green policies. Some 25,000 jobs stand to be created through public transport initiatives, and 12 million through a massive increase in renewable energy. Agriculture and forest-related policies were found to have the highest value for money, with water efficiency initiatives seeming to create more jobs for women in the long run.

The results of the modelling, together with policy recommendations on leveraging job opportunities and achieving just transition of the workforce, were reflected in the updated NDCs of Zimbabwe and Nigeria.

What is the Green Jobs Assessment Model?

The Green Jobs Assessment Model or GJAM is a macro-economic modelling framework. It is based on Input-Output Tables (IOT) or Social Accounting Matrix (SAM) to assess and guide policy making.

If you are interested in this modeling and other impact assessments, please contact sangji.lee@undp.org.

UNDP’s Climate Promise is the largest global offer on NDC support, covering over 120 countries and territories, representing 80 percent of all developing countries globally – including 40 least developed countries, 28 small island developing states, and 14 high emitters – to enhance their Nationally Determined Contributions under the global Paris Agreement. Delivered in collaboration with a wide variety of partners, it is the world’s largest offer of support for the enhancement of climate pledges. Learn more at climatepromise.undp.org and follow at @UNDPClimate. UNDP is the leading United Nations organization fighting to end the injustice of poverty, inequality, and climate change. Working with our broad network of experts and partners in 170 countries, we help nations to build integrated, lasting solutions for people and planet. 

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