Climate change–related labour productivity and income loss

Key messages

• The negative effects of heat stress on labour productivity are among the most clearly established channels by which climate change affects economies. Additional global warming of 1°C is expected to expose over 800 million people in tropical regions to unsafe levels of heat stress, potentially reducing working hours by as much as 50%.
• While direct impacts are concentrated in developing countries, the economic damages are amplified globally by supply chains and trade. Hence, global income losses are not limited to the regions where the heat stress occurs.
• In a low-emissions scenario, global annual GDP losses from labour impacts could be limited to 0.1%–0.8% compared to 1.4%–4.5% under high-emissions scenarios, providing a compelling economic justification for more ambitious climate action. While estimates of the aggregate economic costs vary depending on the methodological approach, there is consensus that global incomes will be negatively affected.

Estimates of the economic costs of climate change are crucial for informing decisions about mitigation and adaptation measures. They can reveal important channels through which climate change can impact the economy; identify risks across regions, sectors, and demographics; highlight issues related to justice and equity; and motivate emission mitigation.

One of the main ways climate change hurts the economy is in reducing worker productivity (Figures 7A & B), and there is consensus that large increases in future exposure to and impacts of unsafe heat stress will occur. Consistent definitions of heat stress that take into account variables beyond temperature, such as humidity, are a challenge. Additional warming of 1°C is set to expose over 800 million people in tropical regions to unsafe levels of heat stress which would reduce working hours by 50%, impacting productivity and labour supply to economic markets. Importantly, labour exposure is subject to great inequality, with developed countries able to benefit from imports produced in increasingly heat-exposed developing countries. A recent review concludes that 3°C of warming would cut labour effectiveness by 33% in Africa’s outdoor, high-exposure sectors and 25% in Asia’s, with substantial impacts in low-exposure sectors too. By 2060, indirect effects on global trade and supply chains are projected to account for 12–43% of heat stress–related global economic losses, with effects varying across regions and sectors. Recent studies have found that for a high-emissions scenario (RCP8.5), labour productivity loss from heat could result in annual global GDP losses of 1.4–2.6%, and when also accounting for health costs and supply chain disruptions due to climate impacts on labour, this could increase to 2.9–‍4.5%. Mitigation to RCP2.6 or RCP1.9 levels could reduce these annual GDP reductions to only 0.1–0.8%.

While understanding has improved and there is consensus about negative impacts on global incomes, estimates of the aggregate economic impacts of climate change from all possible channels remain wide (Figures 7C & D). First, it is increasingly clear that estimates vary based on the method employed, with a divergence between “structural” and “statistical” modelling approaches. Statistical approaches are able to capture the aggregate effects of a range of sectoral impact mechanisms and their interactions but provide less insight into the relative role of those mechanisms. Their sensitivities to model specification and extrapolation of historical relationships into different potential futures are sources of widespread debate. Structural models can offer greater mechanistic clarity by explicitly enumerating specific impact chains, but they rely on certain assumptions and struggle to capture all the relevant impact channels. These different approaches are not directly comparable and should be treated as different lines of evidence rather than as interchangeable substitutes. Ongoing research efforts are attempting to better understand and reconcile these differences to reduce uncertainties.

Statistical estimates of aggregate economic impacts have undergone major revisions in recent years, typically increasing cost estimates over time. New work has highlighted the role of climate hazards in addition to average temperatures, including extremes, temperature variability, and precipitation. A complementary research strand has highlighted the global nature of climate shocks, finding that incorporating metrics of global temperature into empirical work more than doubles estimates from prior findings. And advances in the way models capture the persistence of impacts on economic growth have found at least partially persistent effects, resolving a source of prior discrepancy and supporting estimates of larger overall impacts.

Persistent knowledge gaps remain. The largest gap is in the discrepancies between models, but there are others. While advances have highlighted key impact categories such as heat stress and labour, other climate impacts have yet to be widely included, such as drought, tropical storms, and wildfires. Similarly, the costs of impacts on “non-market” sectors (e.g., biodiversity, crime and conflict, migration) are difficult to monetise and are largely omitted, despite some advances in accounting for ecosystem services. More attention to the effects of compounding climate hazards and their cascading effects across systems is also needed. Finally, the role of adaptation remains a large source of uncertainty, as statistically observed responses to weather may change under fundamentally different future socio-economic and climate conditions. Evidence exists for successful adaptation against heat-related mortalities, but other sectors show much less clear evidence of adaptation occurring historically. To better predict the aggregate costs of climate change, understanding and integrating adaptive responses is needed in statistical and structural models.

The evidence on global labour productivity and income loss due to climate change strengthens the case for mitigation, can narrow the focus of adaptation efforts, and helps anticipate loss and damage. For example, heat impacts on labour are a critical impact channel, which can provide guidance for adaptation strategies. Advances in statistical approaches, particularly in accounting for further climate hazards and global effects, have increased estimates of the economic cost of climate change. These vary substantially by region, sector, and demographic, with lower-income countries facing the highest economic losses, due to their higher dependence on climate-sensitive industries, lower adaptive capacity, and location in more vulnerable regions. Recognising these vulnerabilities is essential for designing policies that not only mitigate economic losses, but also foster resilient, equitable systems capable of withstanding future climatic shocks. Finally, domestic economies are impacted by climate change directly as well as indirectly via global trade effects driven by climate impacts that occur elsewhere. In an interconnected world that is experiencing a growing number of extreme weather events, it is increasingly important to design policy and business strategies towards proactive supply chain resilience and international cooperation to mitigate the economic impacts and address transboundary risks.