International financial transfers in climate policy: blessing or curse? Brigitte Knopf, Michael Jakob, Jan Steckel, Christian Flachsland

Research Questions What financial flows can be expected from emission trading due to climate change mitigation? How does this relate to tranfers from FDI or Foreign Aid? What are appropriate mechanisms and governance structures to avoid (or at least minimize) outcomes that slow down economic development

Results from Integrated Assessment Models Data for financial flows from emission trading available from 2 model comparisons (with 3 models each): RECIPE (Edenhofer et al. 2009, Luderer et al. 2011) Different technology options Different allocation schemes for emission trading systems ADAM (Knopf et al. 2009, Edenhofer et al. 2010) Different mitigation targets Always assumed: fully implemented cap&trade system Relatively coarse regionalization (CHN, IND, Rest of non-Annex-I (RNAI), AFR)

Results from Integrated Assessment Models (IAM) RECIPE: Different technology options: nuclear fixed to baseline (fixNUC); renewbles fixed to baseline (fixREN); biomass use fixed to baseline (fixBIO); CCS not available (noCCS) Different allocation schemes for emission trading systems: Contraction and Convergence (C&C); Common but differentiated convergence (CDC); Per GDP shares ADAM: Different climate mitigation targets, i.e. different probabilities for 2°C 550ppm 450ppm 400ppm

Financial flow rel. to GDP [%] Financial flow [bln US$] Financial Flow in IAMs India Financial flow rel. to GDP [%] Financial flow [bln US$] Large spread between different models Steep increase in financial flow

Financial flows in IAMs India India Financial flow [bln $] China China Financial flow rel. to GDP [%] For IND always positive flow, for CHN partly negative

Resource Revenues, Foreign Aid, and Foreign Direct Investment Most recent data on Resource Exports and FDI are for 2009, on foreign aid for 2008. Source: UNCTAD (2010), WDI (2010) Relevant order of magnitude of financial flows from emissions trading

Financial Flows – Example for China 2030 Models Technology Allocation C&C / 550 Climate target

Financial Flows in DC – absolute numbers 2030 2050 Financial flow [bln $] RNAI and IND: net exporter, CHN: net importer of emission allowances Largest uncertainty is related to the different models

Influence of the CO2 Price in the models Financial flow = volume of emission permit exports * CO2 price

CO2 Price 2030 2050 Large spread due to different model-dependent CO2 prices

Financial Flows in DC – numbers rel. to GDP 2030 2050 Financial flow rel. to GDP [%] Large influence of allocation scheme, especially for „GDP shares“ Influence of technological availability and climate target is limited

Financial flows for AFR 2030 2050 Financial flow rel. to GDP [%] Largest financial transfers are reported for AFR

Types of financial transfers in climate policy related to known problems of resource revenues Dutch Disease Rent-seeking / corruption Volatility Full binding cap&trade Sectoral (non-binding) cap&trade Sectoral CDM Policy CDM Fund based approaches NAMAs

Conclusions Climate finance can be expected to amount to large sums, roughly comparable to foreign aid. Problems discussed in relation with aid and resource revenues (Dutch Disease, corruption, volatility) have to be taken into account with respect to climate finance. The size of financial flows – and hence the optimal policy regime – depends on the model, allocation scheme, technology and the climate target. The range of uncertainty is extremely large. Fund-based systems might be more appropriate than allowance trading when it comes to dealing with volatility.

Backup

Large uncertainties of financial transfers from emissions trading Conclusion Large uncertainties of financial transfers from emissions trading Tranfers depend on The model used (M) The allocation scheme (A) The climate target (C) The available technologies (T) Transfers are in the order of magnitude of FDI and larger Transfer (relative to GDP) are in the order of magnitude where negative growth effects can be expected (for >20%, Feeny and McGillivray (2011)

Financial flows in IAMs USA EUR Financial flow [bln $] Financial flow [bln $] Financial flow rel. to GDP [%] Financial flow rel. to GDP [%]

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