The results also exhibit substantial group-level heterogeneity. Figure 5 (left panel) estimates the average adaptation ratio via random effects for each subgroup—firms, households, and farmers. Among firms, adaptation recoups 72 percent [CI: 0.43, 1.01] of climate damages, with a relatively tight CI, even though this group only contains 13 estimates. But adaptive behaviors are less effective for other agents: households (n=56) only recoup 49 percent [CI: 0.36, 0.61] of climate losses while farmer adaptations (n=59) offset 38 percent [CI: 0.25, 0.51] of the impact of climate shocks. The firm effect is significantly different from the household and agriculture effects.

There are many reasons why firm studies may generate larger adaptation ratios, but the most important one may be that firms have access to more effective adaptation strategies. The larger adaptation ratios in firms may reflect compositional effects: firms are studied in different regions and climate shocks (see Figures 2 and 3), as well as potentially with different methods. However, the key factor behind this finding may be that firms have access to more effective adaptation strategies, such as technology adoption.

Consider the right panel of Figure 5, which estimates group-specific aggregate effects for different adaptation mechanisms.<sup>7</sup> In general, the results indicate substantial variation in the effectiveness of adaptation mechanisms. The most effective ones are those that leverage either government policy or technology. Public goods such as infrastructure (Burgess and Donaldson 2010; Brooks and Donovan 2020), effective health systems (Abiona and Ajefu 2023), and piped water ( Costa, Sant’Anna, and Young 2023) are the most effective methods of blunting the costs of climate change, with an adaptation ratio of 0.64 [CI: 0.27, 1.00]. Next are technological solutions such as climate control (Barreca et al. 2016; Goodman et al. 2020; Somanathan et al. 2021), improved seeds ( Dar et al. 2013; Lee et al. 2022), and management practices ( Adhvaryu, Kala, and Nyshadham 2022), which offset 62 percent [CI: 0.41, 0.83] of the losses from climate shocks. Somewhat less effective, though still above average at 53 percent [CI: 0.39, 0.68], are transfers, which are particularly important in supporting resiliency following disasters ( Kosec and Mo 2017; Premand and Stoeffler 2022). Many of these constitute government-supported social protection programs, which have the benefit of ameliorating climate losses for the poorest ( Arouri 2015; Macours 2022; Premand and Stoeffler 2022).

The least effective mechanisms, in contrast, are private adjustments without the aid of finance, technology, or government assistance. In particular, labor market adjustments, most commonly migration ( Giles 2006) and off-farm work ( Gao and Bradford 2018), recover only 14 percent [CI: 0.06, 0.22] of climate losses. Similarly, climate-smart agriculture (CSA)—typically the adoption of improved farming practices (Michler et al. 2019; Alfani 2021; McCarthy 2021)—has belowaverage effectiveness, with an average adaptation ratio of 0.42 [CI: 0.21, 0.63].

> 7 Note that these categories are defined slightly differently than those in Figure 4 because of the smaller sample of articles. Climate smart agriculture (CSA) now forms its own category (previously it was under either reallocation or technology), while public goods now combines both public policy and infrastructure categories.

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