It is important to keep in mind that the approach of this paper is designed to capture the long-term effects of climate change, _after_ people have adjusted to the changed climate. The paper does not address transition costs and costs of normal climate variability. This is a reasonable approach if climate change takes place slowly and predictably, so that people can gradually adjust their behaviors (for example by sowing a different crop than their parents used to). It is assumed that people base their economic decisions on what their current climate is like, rather than on what the climate was like a generation ago, just as they should base their economic decisions on current market conditions rather than on market conditions 30 years earlier.

It is also assumed that for any given temperature-precipitation combination, climate has not become more unpredictable. At the aggregate level, however, predictability may have changed, since there are now more municipalities with lower temperatures. Places where temperatures oscillate close to the freezing point inherently have more unpredictable weather than places which are consistently hot and humid, and temperature variations close to zero have more severe consequences. Indeed we find that the two highland stations, Oruro and Charaña, have experienced increased variability in temperatures. But the rest of the stations have experienced no significant changes in variability or even reduced variability. With respect to precipitation, we found three stations (Cobija, Yacuiba, and San Javier) that had higher precipitation variability since 1991 compared to the reference period 1960-90. The rest had either lower or unchanged variability.

The modest impacts of climate _change_ (the slow, systematic changes in average temperature and precipitation) do not preclude large impacts from climate _variability_ . Indeed many studies have evaluated the costs of El Niño and La Niña events in Bolivia (causing extreme droughts and flooding) finding costs of up to 18% of annual GDP for the 1982-83 El Niño event; 7% for the 1997-98 El Niño; 4.2% from the 2006-2007 El Niño; and 3.4% from the 2007-2008 La Niña event (Bolivia 2004; CAF 2000; CEPAL 2007; CEPAL 2008).

_Predicting the effects of future climate change_ While recent climate change can be analyzed and documented using temperature and precipitation records from weather stations spread across the national territory, it is much more difficult to assess the impacts of future climate change, because there is very little scientific consensus about how the local climates in Bolivia are going to change in the future.

The Intergovernmental Panel on Climate Change uses a combination of different General Circulation Models to predict future climates. For some regions these models do a reasonably good job at replicating past climate change and current climatic conditions, and there is a high level of agreement between the many different models. This is not the case for South America in general, and even less the case for Bolivia. Not a single model has replicated the recent temperature reductions observed across most of Bolivia. According to the IPCC4, Working Group I chapter on Regional Climate Projections for Latin America: 17