A meta-analysis of country-level studies on environmental change and migration

Hoffmann, Roman; Dimitrova, Anna; Muttarak, Raya; Cuaresma, Jesús Crespo; Peisker, Jonas

doi:10.1038/s41558-020-0898-6

Cited by 230 publications

(209 citation statements)

References 98 publications

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“…Quantifying the number of people who migrate at least partly due to climate- and weather-related events is inherently challenging, due to conceptual ambiguity, lack of robust methodologies, and poor data 5 , 9 . In general, there is more evidence that climatic conditions influence short-distance temporary displacement than international migration 8 , 10 . However, several recent studies have linked adverse climatic conditions in sending countries to refugee and asylum migration, for which statistics are more complete 11 – 13 .…”

Section: Introductionmentioning

confidence: 99%

Climatic conditions are weak predictors of asylum migration

et al. 2021

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Recent research suggests that climate variability and change significantly affect forced migration, within and across borders. Yet, migration is also informed by a range of non-climatic factors, and current assessments are impeded by a poor understanding of the relative importance of these determinants. Here, we evaluate the eligibility of climatic conditions relative to economic, political, and contextual factors for predicting bilateral asylum migration to the European Union—form of forced migration that has been causally linked to climate variability. Results from a machine-learning prediction framework reveal that drought and temperature anomalies are weak predictors of asylum migration, challenging simplistic notions of climate-driven refugee flows. Instead, core contextual characteristics shape latent migration potential whereas political violence and repression are the most powerful predictors of time-varying migration flows. Future asylum migration flows are likely to respond much more to political changes in vulnerable societies than to climate change.

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Section: Introductionmentioning

confidence: 99%

Climatic conditions are weak predictors of asylum migration

et al. 2021

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“…The complex interactions between climate risk, community risk aversion, and financial restrictions can serve as further explanatory factors for divergent migration patterns in the face of climate risk [12], particularly when there are multiple adaptation options with different risk-reward profiles. On the other hand, the robust effects of risk aversion and financial limitations on reducing community migration and average income suggest a role for risk transfer policies and interventions such as cash transfers that help households overcome financial restrictions.…”

Section: Risk Aversion and Financial Restrictions Mediate Climate Adamentioning

confidence: 99%

“…Climate change is likely to impact the livelihoods of many of the world's 500 million smallholder farming households [1,2], particularly with projected increases in drylands populations [3]. Migration represents one of several adaptation strategies that farmers could deploy in the face of climate stress [4], and there is mixed evidence on the extent to which climate change may positively or negatively impact migration flows [5][6][7][8][9][10][11][12]. While some studies warn that climate impacts could displace over 100 million people worldwide [13,14], scholarship from more traditional migration disciplines emphasizes that climate change may constrain various forms of resources needed to migrate, including financial and social resources [8,15,16].…”

Section: Introductionmentioning

confidence: 99%

“…While previous econometric studies have built our understanding of the conditions under which climatic factors have influenced migration patterns [5,6,11,12,21], they typically have limited ability to account for dynamic interactions between changing climatic and societal variables [22]. Recently, experimental economics has elucidated some causal factors of climate migration decisions [23], but under a limited set of conditions.…”

Section: Introductionmentioning

confidence: 99%

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Risk Transfer Policies Facilitate Smallholder Farmer Climate Adaptation

Choquette-Levy

Wildemeersch

Oppenheimer

et al. 2021

Preprint

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Increasing climate stress is likely to significantly impact smallholder farmer livelihoods, and can lead to divergent adaptation pathways. However, empirical evidence is inconclusive regarding how climate affects smallholder farmers’ deployment of various livelihood strategies, including rural-urban migration, especially as these impacts become more severe. Here we use an agent-based model to show that in a South Asian-type agricultural community experiencing a 1.5oC temperature increase by 2050, climate impacts are likely to decrease household income in 2050 by an average of 28 percent relative to the same income under a stationary climate, with fewer households engaging in economic migration and investing in cash crops. Pairing a small cash transfer with risk transfer mechanisms significantly increases the adoption of alternative livelihood strategies, improves community incomes, and reduces community inequality. While specific results depend on contextual factors such as risk preferences and climate risk exposure, these interventions are robust in improving adaptation outcomes by addressing the intersection of risk aversion, financial restrictions, and climate impacts.

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“…Systematic reviews and meta-analyses have been a popular tool for synthesizing evidence in many fields, including evidence-based medicine, public health, and environmental research [ 1 , 2 , 3 ]. Through systematic reviews and meta-analyses, researchers can combine findings from independent studies on common research topics, with one goal being to produce overall results that may be more precise than individual studies.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Methods for Meta-Analyses of Binary Outcomes: Implementations, Examples, and Impact of Priors

Amer

Thompson

Lin

2021

IJERPH

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Bayesian methods are an important set of tools for performing meta-analyses. They avoid some potentially unrealistic assumptions that are required by conventional frequentist methods. More importantly, meta-analysts can incorporate prior information from many sources, including experts’ opinions and prior meta-analyses. Nevertheless, Bayesian methods are used less frequently than conventional frequentist methods, primarily because of the need for nontrivial statistical coding, while frequentist approaches can be implemented via many user-friendly software packages. This article aims at providing a practical review of implementations for Bayesian meta-analyses with various prior distributions. We present Bayesian methods for meta-analyses with the focus on odds ratio for binary outcomes. We summarize various commonly used prior distribution choices for the between-studies heterogeneity variance, a critical parameter in meta-analyses. They include the inverse-gamma, uniform, and half-normal distributions, as well as evidence-based informative log-normal priors. Five real-world examples are presented to illustrate their performance. We provide all of the statistical code for future use by practitioners. Under certain circumstances, Bayesian methods can produce markedly different results from those by frequentist methods, including a change in decision on statistical significance. When data information is limited, the choice of priors may have a large impact on meta-analytic results, in which case sensitivity analyses are recommended. Moreover, the algorithm for implementing Bayesian analyses may not converge for extremely sparse data; caution is needed in interpreting respective results. As such, convergence should be routinely examined. When select statistical assumptions that are made by conventional frequentist methods are violated, Bayesian methods provide a reliable alternative to perform a meta-analysis.

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A meta-analysis of country-level studies on environmental change and migration

Cited by 230 publications

References 98 publications

Climatic conditions are weak predictors of asylum migration

Climatic conditions are weak predictors of asylum migration

Risk Transfer Policies Facilitate Smallholder Farmer Climate Adaptation

Bayesian Methods for Meta-Analyses of Binary Outcomes: Implementations, Examples, and Impact of Priors

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