of non-Annex B countries where CDM projects are carried out, however, it may be viewed as funds directed at domestic energy efficiency and technology development, thus item c.

Most interesting for our discussion is the scope for future financing, where great uncertainties persist. In this section we will try to conceptualize the major flow types, with an indication of their future likely magnitudes.

# **2.2 Financing related to adaptation**

Future financial flows related to adaptation are hard to predict. One reason is that adaptation costs are elusive, and will in part, perhaps mostly, be borne by the private sector. Private and public adaptation cost are likely to be broad substitutes, as more public adaptation investment is likely to reduce the private sector’s need to incur such costs. There are also various ways of assessing adaptation costs, various time frames to consider, and different ways in which costs can be split and categorized: by foreign and domestic, and by private and public, sources.

Different approaches exist for assessing future adaptation cost. It is here useful to distinguish between “bottom-up” and “top-down” procedures. “Bottom-up” cost assessments start with the adaptation needs in individual sectors or even projects, and aggregate these up to a national and international level. Typically, such assessments will give adaptation finance need numbers at national levels. “Topdown” assessments start with considerations of likely total needs e g for adaptation investments as share of GDP, and in most cases consider global adaptation finance needs, or alternatively, regional needs, but will as a rule not give national numbers.

For our purposes, the “top-down” assessments appear to be the most useful, in particular, as our scope is largely macroeconomic, with an emphasis on macroeconomic effects. OECD (2008) provides a useful and fairly comprehensive survey of such studies to date. Table 2.1 below sums up these studies. While the table lists 6 studies, they are all based on only two fully independent estimates, namely the World Bank (2006) (WB) and the UNFCCC (2007) studies. The Stern (2007), Oxfam (2007) and UNDP (2007) studies all represent modifications of the WB study. The WB study accounts for three major types of financial flows or expenditures: official development aid (ODA) assessed at US$100 billion annually; foreign direct investment (FDI) in lower-income countries, assessed at US$160 billion, and gross domestic investment (GDI) in the same countries, assessed at US$1500 billion. 40 percent of ODA, 10 percent of FDI, and 2-10 percent of GDI are assumed to be “climate-sensitive” thus giving rise to a potential need for adaptation expenditure, and with a need for “climate-proofing”; which in turn is assumed to represent 10-20 percent of the financial exposure to potential climate effects for each of the three categories.

The Stern, Oxfam and UNDP studies represent relatively simple refinements of the WB study, with updated and more refined numbers. In particular, the UNDP study makes predictions up to 2015, for ODA (US$106 billion per year), FDI (US$281 billion) and GDI (US$2724 billion). Note that the UNDP study gives substantially higher numbers than the other studies, and has a much higher lower bound for adaptation costs. This is due to two factors: first, that a “target”, rather than a lower bound, is set for climate-proofing; and secondly, that a specific cost estimate is here included for additional assistance for climate-related disaster response.

The main purpose of the WB study, and the follow-up studies discussed, was to get a hand on the need for public support to adaptation activity and replacement of damage caused by climate change, mainly from the public sector point of view, rather than as a comprehensive measure of adaptation costs for both the public and private sector. It should still be noted that the “climate-proofing” notion, used in all the above studies, is a very imprecise way of identifying adaptation costs.

The UNFCCC (2007) study deals with individual sectors in more depth, and in that sense is not a pure “top-down” study but rather one that combines both “top-down” and “bottom-up” elements. A 5