The Climate PoLicy ANalysis (C-PLAN) Model, Version 1.0

Winchester, Niven; White, Dominic

doi:10.1016/j.eneco.2022.105896

Cited by 8 publications

(9 citation statements)

References 35 publications

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“…The amount of land that changes from production to permanent forests is a function of the maximum amount of land that can change use and a series of sigmoid function calculations (one for each productivity-farm size category). In each year, there are potentially six S-curves operating, each using a different 'breakeven' carbon 3 The 2050 carbon price with no forestry land use change calculated in this study differs from what is reported by Winchester and White (2022) due to an update in the projected carbon sequestration from forestry in the ENZ model.…”

Section: Productivitymentioning

confidence: 85%

“…The CGE model used for this analysis is an augmented version of the C‐PLAN model (Winchester & White, 2022), a global, recursive dynamic model built for the New Zealand Climate Change Commission (CCC). The C‐PLAN model provides a representation of the New Zealand economy including climate change mitigation policies such as the NZ ETS.…”

Section: Methodsmentioning

confidence: 99%

“…In the baseline scenario, the carbon price is imposed as an exogenous carbon tax. Details on each scenario and more information on the model are available in Winchester & White (2022).…”

Section: The Cge Model: Climate Policy Analysis (C-plan)mentioning

confidence: 99%

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Logs or permits? Forestry land use decisions in an emissions trading scheme

White,

Winchester

2023

Aus J Agri & Res Econ

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Negative carbon emissions options are required to meet long‐term climate goals in many countries. One way to incentivise these options is by paying farmers for carbon sequestered by forests through an emissions trading scheme (ETS). New Zealand has a comprehensive ETS, which includes incentives for farmers to plant permanent exotic forests. This research uses an economy‐wide model, a forestry model and land use change functions to measure the expected proportion of farmers with trees at harvesting age that will change land use from production to permanent forests in New Zealand from 2014 to 2050. We also estimate the impacts on carbon sequestration, the carbon price, gross emissions, GDP and welfare. When there is forestry land use change, the results indicate that the responsiveness of land owners to the carbon price has a measured impact on carbon sequestration. For example, under the fastest land use change scenario, carbon sequestration reaches 29.93 Mt CO2e by 2050 compared to 23.41 Mt CO2e in the no land use change scenario (a 28% increase). Even under the slowest land use change scenario, carbon sequestration is 25.89 Mt CO2e by 2050 (an 11% increase compared with no land use change). This is because, if foresters decide not to switch to permanent forests in 1 year, carbon prices and ultimately incentives to convert to permanent forests will be higher in future years.

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Section: Productivitymentioning

confidence: 85%

Section: Methodsmentioning

confidence: 99%

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Logs or permits? Forestry land use decisions in an emissions trading scheme

White,

Winchester

2023

Aus J Agri & Res Econ

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“…24 This measure is based on worker's earnings in the month relative to the minimum wage as described in Fabling and Maré (2015). 25 More details about C-PLAN are provided in Winchester & White (2021) 26 From the CGE model, the relevant parameter for employment is Employment (f,i,r,t) where f represents production factors, i represents industries, r represents regions (New Zealand or the rest of the world), and t represents time (annual). This parameter reports an employment index (EI) for each sector equal to one in the base year (2014) for each sector.…”

Section: Downscaling Cge Model Resultsmentioning

confidence: 99%

“…2 The C-PLAN model is a global, recursive, dynamic CGE model tailored to the economic and emissions characteristics of New Zealand. (Winchester & White, 2021) 3 This article categorises jobs into two groups: low-risk and high-risk. Low-risk jobs are defined as those where workers are minimally exposed to outdoor temperatures, and high-risk jobs are defined as those who are heavily exposed (construction, mining, agriculture, and manufacturing).…”

Section: Introductionmentioning

confidence: 99%

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

Riggs¹,

Mitchell²

2021

Motu Working Paper

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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.

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