Simulations and Results

A baseline scenario from 2004–2080 was constructed under the assumption that there would be no climate change impacts on economic activities. The baseline scenario provided a reference growth trajectory for examining the effects of climate change-induced agricultural damages. In the baseline, GDP growth up to 2013 was exogenous, derived from the International Monetary Fund's (IMF) medium baseline projection. For each region, an economy-wide, labor-augmented productivity grew endogenously over the simulation period of 2005–2013 to match the pre-specified GDP growth path. After 2013, the productivity growth rate was held fixed at the level of 2013 up to 2040, and then declined by 1% per year afterwards. The supply of agricultural land was assumed to be fixed in high-income countries and to grow by 0.12% annually in Asia and 0.2% annually in Latin America, Africa and other regions.

The baseline scenario projected a high rate of world economic growth over the next seven decades, with global GDP growing by an average of 3.1% per year over the period of 2010– 2050, and slowing down to 2.5% per year between 2050 and 2080. The average annual growth of Southeast Asia over 2010-2080 was 1.1 percentage points higher than that of the world average, and its share in global GDP increased from less than 2% in 2004 to 4.1% in 2080. Growth was accompanied by rapid structural change in developing countries. The share of agricultural value added, in volume terms, would decline from nearly 10% in 2004 to 3.8% in 2080 in Southeast Asia. Even though some Asian countries like India and Viet Nam had trade surpluses in agricultural products in the base year, they would become net importers in the next decade because of the combined effects of economic growth, industrialization, and land constraints. However, Thailand, the Philippines and Central Asia were expected to maintain surpluses in agricultural trade over the projection period.

In the counterfactual scenario with agricultural damages, it was assumed that productivity in four crop agricultural sectors (paddy rice, wheat, other grains, and other crops) would be lower than that in the baseline scenario because of the projected changes in climate. Crop productivity shocks, which were Cline's estimates without carbon fertilization effect as reported in the first column of Table 2, were imposed gradually over 2009–2080. The crop productivity shocks were assumed to be uniform across sectors. The impacts of climate change were assessed by a comparison of the counterfactual scenario with the baseline scenario.

4.1 Global Impacts

Table 3 [ PDF 13.7KB | 1 page ] presents the simulated impacts on global welfare, GDP, and agricultural production, which are reported as percentage deviation from the “no damage” baseline. The table indicates that global real GDP would decline by 1.4% by 2080 as a result of the predicted impacts of climate change on agricultural productivity. India would suffer the largest GDP loss of 6.2%, followed by Sub-Sahara Africa, other South Asian countries, and Central Asia. Although the estimated productivity losses from Cline's study were modest for the overall Central Asia region, high agricultural shares in some of the region's national economies account for the relatively large loss of GDP in Central Asia. Southeast Asia would see a drop in real GDP of 1.4%, similar to that of the world's average. New Zealand is the only region in the model that would experience a real GDP increase in response to the climate changeinduced global agricultural adjustment.

Aggregate welfare effects, which were measured by the sum of equivalent variation of the households and real investment, generally followed the changes in real GDP. However, international price adjustment played a role in determining the distribution of global welfare losses. After incorporating agricultural damage, international prices of crop products were expected to increase by 16–22% relative to the price of manufacturing exports of highincome countries, reflecting the inelastic demand structure of agricultural products (Figure 1 [ PDF 15.6KB | 1 page ]). The resulting changes in terms of trade would benefit net agricultural exporting countries, but damage net agricultural importing countries. As shown in the second column of Table 3, New Zealand's welfare gained as much as 1.5% of GDP, much higher than its GDP expansion, due to its improved terms of trade. In Canada and the European Union (EU), improvements in terms of trade more than offset the direct losses from agricultural productivity reduction, leading to slight welfare gains. Central Asia would benefit from changes in terms of trade. However, for other regions the deterioration of their terms of trade would amplify the effects of agricultural damage. Generally, the resulting welfare losses would be larger than GDP decline.

The detailed world agricultural production simulation results suggest that global crop production would shrink by 7.4% by 2080, which is less than half of Cline's estimate. This is partly due to the declining weight of developing countries, which would be more adversely impacted by climate change than developed countries, in global agricultural production over 2004–2080. In Cline's original estimate, agricultural output values in 2003 were used as weights to obtain the estimate for global impact. The reallocation of resources across sectors also partially offset the direct impact of agricultural productivity slowdown, contributing to the smaller magnitude of crops output contraction. In regions where the impacts on agricultural productivity are small or positive, crop production would expand. New Zealand's crop output would increase the most, by 141%, because of its higher agricultural productivity under climate change and relatively small crop share in its economy. Central Asia, the EU, US, and Japan, would see crop production rise by 5–50% in response to the crop price hikes. In general, the crop production expansion would come at the expense of the livestock sector, with land and other production resources being diverted toward crops sectors.

Crop production in South Asia, Latin America and Sub-Sahara Africa would be the most adversely affected by climate change. The decline of crop output in Southeast Asia would be more moderate, but still significant at 17.3% by 2080. The negative impact of climate change on crop production in East Asian countries would be modest, ranging from 0.1% for the People's Republic of China (PRC) and 5.1% for the Republic of Korea.

As downstream sectors of crop agriculture, the production of livestock and processed food would also decline with rising input costs. World output of livestock and processed food would shrink by 5.9% and 4.6%, respectively. Again, cross-region variation exists. The production of these two sectors would drop significantly in India, but rise in Japan. Australia and the EU would also see output expansion of livestock and processed food, respectively, reflecting their stronger comparative advantage in these products as a result of climate change. The shifting comparative advantage induced by climate change would have important implications for international patterns in agricultural commodities. Global trade in crop agriculture would increase, but trade in livestock and processed food would shrink (Figure 1).

4.2 Impacts on Southeast Asian Countries

Table 4 [ PDF 13.4KB | 1 page ] reports the macroeconomic effects of the projected slowdown in agricultural productivity on six Southeast Asian countries. It is not surprising that the impact on real GDP was very modest for Singapore, given the small agricultural sector in its economy. However, the GDP contractions in Thailand, Viet Nam, and the Philippines were much more significant, ranging from 1.7% to 2.4%. The welfare losses were generally larger than GDP reductions, except for Viet Nam, which would experience a slight improvement in terms of trade. Both consumption and investment would decline compared to the baseline scenario. The incorporation of agricultural productivity damage would hamper agricultural exports of Southeast Asian countries, leading to a reduction of their aggregate exports. Consequently, aggregate imports would also decline to maintain the current account balance.

To get a sense of the contribution of agricultural production slowdown in other regions to welfare losses in Southeast Asia, we ran two additional scenarios in which the climate change-induced agricultural productivity shocks were applied to Southeast Asia and other regions separately. The welfare effects of these two scenarios are presented in Figure 2 [ PDF 14.2KB | 1 page ]. It is clear that that domestic productivity reduction would be the major source of welfare losses of Indonesia, Philippines, Thailand, and Viet Nam. Actually, Indonesia, Thailand, and Viet Nam would benefit slightly from the agricultural production contraction in rest of the world. However, in Malaysia and Singapore the shocks from rest of the world would dominate total welfare effects because of their small agricultural sectors and their high dependence on imports for agricultural supply.

The pattern of changes in production factor gains and losses is specific to each country. In general, following negative agricultural productivity shocks, the average return to agricultural factors of production would rise relative to non-agricultural production factors, because of the inelastic demand of agricultural products. This is evident from the smaller wage decline received by unskilled labor than skilled labor, and the rising rate of return to agricultural land in most Southeast Asian countries. Singapore and Thailand are two exceptions with declining rates of return to land, mainly due to their high use of intermediate crop inputs in their crop production.

The impact on agricultural and food production and trade is shown for each Southeast Asian country in Table 5 [ PDF 11.8KB | 1 page ]. All countries would see output losses in all crops sectors, except for rice production in Malaysia. Livestock output would increase in Thailand and Singapore, partly because declining land returns in the crops sectors would lead to the conversion of some arable lands to pastures. The production of the processed food sector would expand in Malaysia and Singapore, reflecting their relatively higher efficiency in the use of crop inputs in production.

As a result of the rising producer prices relative to other regions in the world, the crop exports would shrink significantly for all Southeast Asian countries except Viet Nam. Viet Nam would experience export expansion in rice and other crop products due to its stronger comparative advantage in crop production and smaller reduction in agricultural productivity relative to other Southeast Asia countries. Similarly, the imports of crop agricultural products would rise for Southeast Asian economies. As a consequence, the import dependence of Southeast Asia's crops sector in 2080 would rise from 23.3% of baseline to 25.8% under the climate change scenario. Southeast Asia's grain self-sufficiency ratio in 2080 would decrease by 2.4 percentage points to 84.1% (Figure 3 [ PDF 16KB | 1 page ] and Figure 4 [ PDF 16KB | 1 page ]).

4.3 Sensitivity to the Assumption About Baseline Agricultural Productivity Growth

In the baseline scenario, agricultural productivity was assumed to grow at the same rate as the manufacturing and services sectors. However, in recent decades, there has been significant slowdown in agricultural technological progress. In the 1960s and 1970s, world grain yields rose at an annual rate of 2.7%. This rate has slowed to 1.6% in the past quarter century. The languishing agricultural productivity growth is especially evident in Southeast Asia. A recent global estimate of agricultural productivity by Ludena et al. (2007) shows that total factor productivity (TFP) growth rates in the crops sector in East and Southeast Asia have lowered from 0.99% in 1970s to -0.67% in 1980s and -0.48% in 1990s. This negative productivity growth pattern is expected to continue for the next two decades as a result of low levels of expenditure on research and development. For example, Anderson, Pardey, and Roseboom (1994) report an agricultural research intensity (research expenditures as a share of agricultural GDP) for the Asia and Pacific region outside of the PRC and India in the early 1980s of 0.32. This is about one sixth the research intensity in developed countries and only half that in Sub-Saharan Africa (Hertel et al. 2008).

Given the considerable downside uncertainty to our assumed baseline agricultural productivity growth for Southeast Asia, we developed an alternative baseline scenario with slower productivity growth in Southeast Asia's agricultural sectors—specifically, one percentage point lower on annual average than the original baseline, thereupon repeating the scenario of incorporating agricultural damages. The key simulation results are presented in Table 6 [ PDF 13.2KB | 1 page ]. Since the results for non-Southeast Asia regions are little changed from our original results, only revised results on GDP and welfare of Southeast Asian countries are reported.

Because of the slower agricultural productivity growth in Southeast Asia, its agricultural share of GDP in 2080 was smaller under the alternative baseline in comparison with the original baseline. This lead to more muted impacts on aggregate output, as shown in the first column of Table 6. However, because long-term agricultural import dependence was larger as a result of slower agricultural productivity improvement in the alternative baseline, most Southeast Asian economies were more vulnerable to the rise in world prices of agricultural products. Southeast Asian economies' losses in terms of trade, and thusly welfare, were generally larger. Therefore, the results from the alternative simulations suggested that agricultural technological progress would be important for Southeast Asia to cope with the potential risks from global climate change.

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