How trade barriers can hinder climate change adaptation

There are many evidences that global warming could have significant impacts on agricultural productivity all over the globe. Analysis suggests that each degree of daily temperature exposure above 30°C sharply reduces the yield of crops such as corn, soybeans, and wheat (Schlenker and Roberts 2009). Rising temperatures are predicted to cause severe damage to vulnerable crops and areas as the world heats up. 

The changing climate may allow farmers to reduce some of the agricultural damage caused by global warming. This could be done by optimizing their production decisions in response. Arnaud costinot and co. (2016) uses granular, global projections at field level from the UN Food and Agricultural Organization to calculate crop-specific yields with and without climate changes. This allows farmers to assess how they could reallocate planting decisions due to temperature and precipitation change. Their research shows large projected benefits from shifting production away the most affected crops. Some losses could be offset by gradual changes to the crop mix by local producers as the world warms.  

Some crops are more affected by global warming than others. Even the most optimized planting decisions may not be enough to protect agricultural production from future extremes in the hottest regions of the globe. For example, Costinot et al. Costinot et al. (2010) find that climate change will decrease agricultural productivity in Malawi by approximately 50% in a high-emissions environment. This is even if farmers re-optimise future crop allocations. Schlenker (2010) and Lobell (2010) also found severe impacts on a wide variety of crops in sub-Saharan Africa. The outlook for agricultural production looks grim as temperatures rise in the poorest and hottest parts of the globe. 

Could the most vulnerable countries, which are also the hottest and most affected by climate change, adapt by shifting their economies away entirely from agriculture? Research that shows rising temperatures could destroy agriculture in poor countries could also suggest that farmers in more temperate areas, such as Canada and Russia, could reap the benefits of rising temperatures. This suggests that countries in hot regions could adapt to global warming if they could shift labour into non-agricultural areas and increase imports of food. There is also the possibility that agricultural specialisation will shift away from the equator. If regions that are hit hard by extreme heat such as South Asia and sub Saharan Africa continue to be heavily focused on farming, their economies will suffer. My research (Nath 2021), quantifies the potential adaptation benefits from reallocating global agriculture specialisation, and examines how likely such gains are to be realized in practice. 

In order for hot countries to adapt to global warming by shifting production away from agriculture, the first requirement is for non-agricultural production to be less vulnerable than farming to extreme heat, such that comparative advantage in agriculture – not just absolute advantage – shifts away from the equator. There is a lot of research (e.g. Somanathan et al. 2021, Zhang et al. 2018) found that temperature has an effect on manufacturing productivity. However, it is not clear if hot areas have any potential to benefit from moving away from agriculture. 

This is the subject of my analysis. I used panel data at the firm level from 17 countries to estimate the impact of future temperature extremes in manufacturing and services. This was done to find that warming is less likely to affect productivity in non-agricultural areas than in agriculture. While some firms in poorer countries can suffer large productivity losses from exposure to extreme heat – up to 0.4 percentage point reductions in annual revenue per worker from each exposure to a day above 100°F – firms in richer countries and places that experience heat more frequently appear to have adapted such that they are much less vulnerable. Figure 1 shows the estimated impact of extreme temperatures on manufacturing productivity in a variety of local contexts. 

Figure 1 Impact of extreme temperatures on labour productivity in manufacturing across global contexts

My paper projects that global manufacturing productivity would decline by around 1.7% in the high emission scenario. According to previous studies, the decline in agricultural production will be about 20%. Cline 2007, Iglesias, and Rosenzweig 2010. In the hardest hit countries, future temperature extremes reduce manufacturing productivity by about 5–14% in manufacturing, as compared to 40–60% in agriculture. This means that countries with higher temperatures and poorer economies could reap large adaptation benefits if production was moved away from agriculture to more productive manufacturing sectors as the climate warms. 

There is another condition that must be met for global reallocation of agricultural resources to help with climate change adaptation. Specialization in agriculture must respond to shifting comparative advantages. In practice, patterns of agricultural specialty we observe around the globe today don’t appear to follow traditional definitions for comparative advantage. The simplest Ricardian model would suggest that countries should specialize in the sector with the highest relative productivity. However, the data shows the opposite. Lagakos & Waugh (2013) find that the 90th-percentile wealthiest countries in the world have a price-adjusted average value-added per worker that is four times higher then the 10th-percentile least wealthy countries in manufacturing but 45 times more in agriculture. In other words, if relative productivities predicted specialisation, we would already expect most of Canada’s economy to be in farming and for there to be very few farmers in Malawi, even without climate change. And yet, agriculture’s share of employment averages 65% in 10th-percentile countries, and only 3% in 90th-percentile countries. 

Why is agriculture so popular in poor countries despite its low productivity? Gollin et al. (2007), among others in the macro-development literature, refer to this phenomenon as “the food problem”. The basic idea is that food is a vital subsistence item, so people with low incomes living in poor countries must spend more money to eat enough food to live. These high food expenditures require high agricultural production to ensure that there is enough food supply. While it may seem that poor countries with unproductive farmlands could import food to meet domestic demand, the reality is that this mechanism is weak in most developing countries. My paper shows that the average person living in the poorest quarter of the world consumes 91% of its food, compared to 45% for those living in the wealthiest quarter. High production shares in agriculture are a result of the need for domestic populations and their subsistence food needs. 

The extremely low trade levels in poor countries are a major barrier to climate change adaptation. Instead of agricultural specialty shifting away from the hardest hit regions as the world heats upwards, my model projections indicate that warming will keep more people stuck on farms in hotter, less productive countries. This is because falling agricultural productivity in these areas will only exacerbate the food crisis. Climate change will make people poorer, and food more expensive. It will also raise the budget share and, consequently, the production share for agriculture. People in these areas are likely to suffer greatly as production remains concentrated in the sectors experiencing dramatic drops in productivity. Figure 2 shows how climate damages are projected to reach or exceed 10% in many poor countries due to rising temperatures and productivity. This excludes other climate harms like hurricane damages or health effects. Figure 3 shows the large projected increases in food costs in poor countries. This is because domestic food production is becoming increasingly fragile.

Figure 2 Willingness-to-pay to avoid the productivity effects of future extreme temperatures

Figure 3 Projected impact of global warming on domestic food price index

My paper presents model projections that show that trade does little to offset climate impacts. This is because the most vulnerable places to global warming are also the most open to trade. So warming causes only small adjustments in trade flows. Another scenario is where poor countries can trade as freely as richer members of the OECD. In this scenario, the developing world moves rapidly toward importing food and shifting specialty towards less vulnerable non-agricultural sector. The cost of rising temperatures is nearly 70% lower for those in the lowest quartile. Although the exact magnitude of these model projections should not be taken as a guideline, they do suggest that greater global trade openness could significantly reduce the effects of a warming planet. There is more research needed to understand the causes of low trade levels in poor countries. These include tariffs, poor infrastructure and red tape barriers like processing delays, fees and bribe payments. My analysis suggests that climate change adaptation could be aided by better understanding of the mechanisms and possible policy instruments that promote greater global openness to trade. 

In a larger sense, as climate-change economics literature develops, spatial economics plays an increasing role in analysing possible mechanisms of adaptation. Cruz and Rossi Hansberg (2021) examine the role played by international migration. Desmet et.al. Rudik et.al. (2021) examines the effects of sea level rise on coastal investment and coastal populations. The 2021 report focuses on the US’ spatial dynamics. While reducing carbon emissions is the best and most reliable way to avoid global warming, as long as global climate policies fail to reverse rising emissions, there will be an increasing need to research how to reduce vulnerability to any temperature changes that occur in the next century.

References

Cline, W. (2007). Global Warming and Agriculture: End of Century Estimates for Each CountryPeterson Institute.

Costinot, A, D Donaldson and C Smith (2016), “Evolving comparative advantage and the impact of climate change in agricultural markets: Evidence from 1.7 million fields around the world”, Journal of Political Economy 124(1): 205–248.

Cruz, J-L and E Rossi-Hansberg (2021), “The Economic Geography of Global Warming”, NBER Working Paper 28466.

Desmet, K, R Kopp, S Kulp, D Nagy, M Oppenheimer, E Rossi-Hansberg and B Strauss (2021), “Evaluating the Economic Cost of Coastal Flooding”, American Economic Journal: Macroeconomics 13(2): 444–486.

Gollin, D, S Parente and R Rogerson (2007), “The food problem and the evolution of international income levels”, Journal of Monetary Economics 54(4): 1230–1255.

Iglesias, A and C Rosenzweig (2010), “Effects of Climate Change on Global Food Production under Special Report on Emissions Scenarios and Socioeconomic Scenarios (SRES): Data from a Crop Modeling Study”, Technical Report, Columbia University.

Lagakos, D and M E Waugh (2013), “Selection, agriculture, and cross-country productivity differences”, American Economic Review 103(2): 948–80.

Nath, I (2021), “Climate Change, the Food Problem, and the Challenge of Adaptation through Sectoral Reallocation”, Working Paper. 

Rudik, I, G Lyn, W Tan and A Ortiz-Bobea (2021), “The economic effects of climate change in dynamic spatial equilibrium”, Working Paper. 

Schlenker, W and D Lobell (2010), “Robust negative impacts of climate change on African agriculture”, Environmental Research Letters 5(1): 014010.

Schlenker, W and M Roberts (2009), “Nonlinear temperature effects indicate severe damages to US crop yields under climate change”,Proceedings of the National Academy of Sciences 106(37): 15594–15598. 

Somanathan, E, R Somanathan, A Sudarshan and M Tewari (2021), “The impact of temperature on productivity and labor supply: Evidence from Indian manufacturing,” Journal of Political Economy 129(6): 1797–1827. 

Zhang, P, O Deschenes, K Meng and J Zhang (2018), “Temperature effects on productivity and factor reallocation: Evidence from a half million Chinese manufacturing plants”, Journal of Environmental Economics and Management 88: 1–17.