Table 3 reports average annual growth rates of real per capita absorption over the entire 2007-2050 simulation period. Changes in annual growth rates are small, with discernable reductions for only the HOT and DRY scenarios. However, even small reductions in growth rates accumulate over time. For example, by the end of the 2040s, national absorption is 0.77 and 1.7 percent below the baseline in the HOT and DRY scenarios, respectively. This is consistent with the larger and more widespread reductions in crop yields experienced under these two scenarios (see Table 2).

We measure the total economic damages caused by climate change via the agricultural sector as the cumulative loss or deviation in national absorption from the baseline using a five percent annual discount rate. The largest damages occur in the DRY scenario, where the total discounted loss throughout the 2007-2050 period amounts to US$13 billion (measured in 2007 prices). This amount is two-thirds of Tanzania’s GDP in 2007. By contrast, total discounted absorption rises in the WET scenario by US$3 billion suggesting possible gains from climate change for Tanzania.<sup>4</sup> Table 3 also decomposes economic damages across time periods. Despite the escalating biophysical effects of climate change on agricultural yields towards the end of our simulation period, applying a five percent discount rate means that a significant share of the economic costs or benefits of climate change will accrue over the next two decades. This is because crop yield reductions are often temporary during a bad year and can immediately rebound in the subsequent year if the season’s climate improves. In other words, crop yield losses in a given year are usually temporary, unlike damages to assets which may have lasting effects, such as roads damaged by flooding. This partly explains why agricultural damages are more evenly distributed across time periods. However, if we did not discount effects further into the future, then the costs or benefits of climate change would be larger and more heavily weighted towards the middle of the century. Moreover, it should be noted that most GCMs predict a pronounced aggravation of climate change impacts during the second half of the century. Were the time horizon of our analysis extended beyond 2050, then later periods would begin to exhibit progressively stronger impacts.

One of the advantages of CGE models is their ability to decompose national impacts to the sector and regional levels. Table 4 reports deviations in real GDP from the baseline in 20462050 for different sectors. Since agriculture is our only impact channel through which climate effects economic growth, it is not surprising that this sector exhibits the largest changes in our four scenarios. However, agriculture provides important inputs into downstream sectors, such as agro-processing. For example, agricultural GDP is 11.5 percent below the baseline in the DRY scenario by the end of the 2040s. This reduces the supply of raw inputs (e.g., grain) to

> 4 Other impacts, such as increased frequency and intensity of flooding events, were not modeled for the case of Tanzania. The impacts of these events are potentially large (Arndt et al., forthcoming) and could easily overwhelm the benefits of enhanced moisture to crops.

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