Climate Change Economics

Following the release of the IPCC Fifth Assessment Report, and realizing the likely impact on California water and agricultural sectors, we review key concepts in the climate change lexicon in the context of California agriculture. There are a range of modeling approaches used to study the benefits of water basin- and/or farm-level adaptations, including hydrological, crop simulation, economic programming, and econometric models. Given the central role of farmer and institutional responsiveness, how do recent agro-economic assessments suggest that specific adaptations may improve economic welfare and reduce vulnerability? What is economically efficient adaptation in the short and long-run? What are the limits to the agricultural sector’s adaptive capacity?

The paper reviews progress in understanding the economics of climate change with an emphasis on identifying promising advances that are both significant and nonmarginal, as well as areas in which there are key gaps in our knowledge. We highlight several important areas in which important policy-relevant research questions remain: improving estimates of climate damage used for determining the social cost of carbon, refining integrated assessment models, and designing better climate policies. As the world moves to understand and implement country emissions reduction pledges in the context of the UNFCCC, understanding the economics of the problem will become even more important. The hope is that the paper is not only informative for existing economists already working in climate change economics, but that it also serves as an inspiration for economists in other areas, or even those in other disciplines, on ways in which to contribute to solving the problem at hand.

The climate sensitivity of electricity demand in India is likely to be highly sensitive to growth in income. Thus, both intensive and extensive adjustments in cooling and heating will play an important role in determining future climate change impacts on electricity demand. This paper utilizes a national level panel dataset of 28 Indian states for the period 2005–2009. The preferred estimates indicate that climate change will increase electricity demand by 6.7% with 4% p.a. GDP growth and 8.5% with 6% p.a. GDP growth in 2030 over the reference scenario of no climate change. This reflects the fact that the estimated marginal effect of a hotter climate is greater when income is higher. Over 50% of the climate change impacts will be due to extensive adjustments as the current penetration of space conditioning equipments such as air conditioners is very low.

A major impact of climate change is expected to materialize on energy demand for space heating and cooling needs in the residential sector. To quantify this impact, a set of regression models were tested to study the relation between residential energy demand for space heating in Iceland and explanatory variables such as Heating Degree Days and GDP per capita. Considering the nonstationarity of the time-series, three methods were studied to cope with this condition: Cointegration, differencing and detrending.

The evaluation statistics of the three models for the validation period showed that the modified detrending approach is the most reliable method. It became obvious that including the seasonal dummy variables and AR component significantly improve the power of the model to predict monthly energy demand for residential space heating in Iceland. The developed model can be used to project climate related changes in demand for low-geothermal heat.