Methodology for Modelling Distributional Impacts of Emissions Budgets on Employment in New Zealand

Efforts to reduce emissions to counter climate change are expected to have both costs and benefits, and these effects are likely to be unevenly distributed across the population. Hence, we developed the Distributional Impacts Microsimulation for Employment (DIM-E) to examine the potential distributional employment impacts for different mitigation options to reduce greenhouse gas emissions. DIM-E is comprised of two main components: the first component estimates industry-level employment effects, and the second simulates the characteristics of impacted workers and jobs. We based DIM-E on results from a computable general equilibrium (CGE) model, C-PLAN, and applied them to more detailed employment information in order to better understand the extent to which industries, jobs and workers are likely to be impacted by the different pathways. It is possible, however, for DIM-E to be used to analyse any policy scenario and its baseline using employment indices and similar employment information. In this paper, we describe DIM-E in the context of the initial case for which it was developed – to analyse emissions budgets for greenhouse gasses to be set by the New Zealand government for three time periods (2022-2025, 2026-2030, and 2031-2035). We also provide a sampling of results from this initial case in order to put the methodology into context. Hence, we show that DIM-E can be used to examine changes in employment trends due to policy changes as well as the different types of workers that are most likely to be affected by the reallocation of employment across industries. We found that the DIM-E results produced for the initial case were in line with previous research in this area – the overall net industry employment effects were predicted to be relatively small, though some industries will be more affected than others especially in the short- and medium-term. Moreover, very few worker groups would be negatively affected (in terms of the number of jobs) by any of the proposed mitigation options especially over the long term.