REDD in the Carbon Market: A General Equilibrium Analysis

Abstract

Deforestation is a major source of CO2 emissions, accounting for around 17 % of annual anthropogenic carbon release. While costs estimates of reducing deforestation vary depending on model assumptions, it is widely accepted that emissions reductions from avoided deforestation consist of a relatively low cost mitigation option. Halting deforestation is therefore not only a major ecological challenge, but a great opportunity to cost effectively reduce climate change impacts. In this paper, we analyze the impact of introducing avoided deforestation credits into the European carbon market using a multiregional Computable General Equilibrium model. Taking into account political concerns over possible “flooding” of credits from reduced emissions from deforestation and forest degradation (REDD), limits to the number of these allowances are considered. Finally, we account for both direct and indirect effects occurring on land and timber markets resulting from lower deforestation rates. We conclude that avoided deforestation notably reduces climate change policy costs—approximately by 80 % with unlimited availability of REDD credits—and may drastically reduce carbon prices. Policy makers may effectively control for this imposing limits to REDD credits use. Moreover, avoided deforestation has the additional positive effect of reducing carbon leakage of a unilateral European climate change policy. This is good news for the EU, but not necessarily for REDD regions. We show that REDD revenues are not sufficient to compensate REDD regions for a less leakage-affected and more competitive EU in international markets. In fact, REDD regions would prefer to free ride on the EU unilateral mitigation policy.

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Notes

  1. 1.

    There are in fact other studies using a CGE approach, analyzing the economic implications of deforestation (Rainer and Wiebelt [16] and Cattaneo [17]), but their focus is not on climate policies, nor on REDD credits in an emission trading scheme in particular.

  2. 2.

    In the AEZ approach, cropland is diversified into 18 different types. Imperfect land substitutability is allowed within, but not between AEZs. Accordingly, a crop cannot be grown everywhere within a country, but only in those AEZs where the land is geographically and biochemically suitable to its cultivation. AEZs allow also for land competition between crops and forest activity.

  3. 3.

    This possibility allows Hertel et al. [11] to create a new production structure for the forest sector in which land and forest inputs substitute in production responding to carbon taxes to produce carbon sequestration. This is both through converting non forestland to forest (extensification) or increasing the biomass of existing forest (intensification).

  4. 4.

    For detailed information please refer to Tables 3, and 14 of Annex 3 in UN FAO (2006) [25].

  5. 5.

    See page 41 of Brown (2000) [26].

  6. 6.

    These figures are consistent with the existing literature. As a comparison, we just quote the 2008 EC staff working documents on the cost of meeting the 20-20-20 EU target which estimate for the EU27 a cost ranging from 0.54 to 0.66 % of GDP with a price ranging from 30 to 47€/t CO2 [30, 31].

  7. 7.

    High estimates for the leakage rate are not uncommon. For example, in a similar 20 % carbon dioxide emission reduction policy for EU, Bednar-Friedl et al. [32] estimate a leakage rate of 38 % when industrial processes emissions are also accounted for in the final estimation, and a rate of 29 % when considering combustion emissions only. In addition, the fact that only the European region implements the policy is an important element for a high leakage rate.

  8. 8.

    Note, however, that in our analysis, we are not considering any targeted use of the revenues from REDD credits that could entail higher pro-growth potential.

  9. 9.

    The ICES model was developed at the Fondazione Eni Enrico Mattei (FEEM), more information is available at the following website:

    http://www.feem.it/getpage.aspx?id=138&sez=Research&padre=18&sub=75&idsub=102.

    Additional technical documentation on the GTAP model and GTAP database are available at https://www.gtap.agecon.purdue.edu/

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Correspondence to Ramiro Parrado.

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This paper is part of the research of the Climate Change and Sustainable Development Programme of the Fondazione Eni Enrico Mattei.

Annex I: ICES Technical Appendix

Annex I: ICES Technical Appendix

ICES is a recursive-dynamic CGE model for the world economy that builds upon the original GTAP model structure, for which a detailed description is available at [20].Footnote 9 ICES solves recursively a sequence of static equilibria linked by endogenous investment determining the growth of capital stock from 2001 to 2050. For a more detailed description of the model, the reader can refer to [33] and [34].

Fig. 7
figure7

Nested tree structure for industrial production processes of the ICES model

Industries are modeled through a representative firm, minimizing costs while taking prices as given. In turn, output prices are given by average production costs. The production functions are specified via a series of nested CES functions. Domestic and foreign inputs are not perfect substitutes, according to the so-called “Armington” assumption. The production tree is reported in Fig. 7.

A representative consumer in each region receives income, defined as the service value of national primary factors (natural resources, land, labor, capital, see Fig. 8). Capital and labor are perfectly mobile domestically but immobile internationally. Land and natural resources, on the other hand, are industry-specific.

This income is used to finance three classes of expenditure: aggregate household consumption, public consumption, and savings. The expenditure shares are generally fixed, which amounts to saying that the top-level utility function has a Cobb-Douglas specification.

Public consumption is split in a series of alternative consumption items, again according to a Cobb-Douglas specification. However, almost all expenditure is actually concentrated in one specific industry: non-market services.

Private consumption is analogously split in a series of alternative composite Armington aggregates. However, the functional specification used at this level is the Constant Difference in Elasticities form: a non-homothetic function, which is used to account for possible differences in income elasticities for the various consumption goods.

Investment is internationally mobile: savings from all regions are pooled and then investment is allocated so as to achieve equality of expected rates of return to capital.

In this way, savings and investments are equalized at the world, but not at the regional level. Because of accounting identities, any financial imbalance mirrors a trade deficit or surplus in each region.

Fig. 8
figure8

Nested tree structure for final demand of the ICES model

The regional and sectoral detail of the model used for this study are represented in Tables 4 and 5. The use of land is only required by the agricultural sectors. Natural resources are divided into forestry, fishing, and fossil fuels, and are employed respectively by the forestry, fishing, and fossil energy industries (see Table 5).

The business as usual scenario was calibrated to reproduce the GDP growth rates according to the IPCC A2 scenario and is reported in Table 6. Assumptions on the evolution of population (taken from UNPD [35]), energy efficiency (taken from Bosetti et. al. [36]), CO2 emissions and major fossil fuel prices (based on EIA [37] and EIA [38]) are also incorporated and reported in Table 7.

Table 4 Regional disaggregation of the ICES model
Table 5 Sectoral disaggregation of the ICES model
Table 6 GDP growth rates for the BAU (% 2001–2020)
Table 7 Major exogenous variables growth rates for the BAU (% 2001–2020)

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Bosello, F., Parrado, R., Rosa, R. et al. REDD in the Carbon Market: A General Equilibrium Analysis. Environ Model Assess 20, 103–115 (2015). https://doi.org/10.1007/s10666-014-9419-1

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Keywords

  • Forestry
  • Avoided deforestation
  • Climate change
  • Emission trading
  • General equilibrium modeling

JEL Classification

  • D58
  • Q23
  • Q54