Even though much has been written about climate change, and about poverty, as distinct and complex problems, the link between them has received little attention. This is odd for two reasons:
- The majority of the poor live in rural areas where agriculture is the predominant form of economic activity, and agriculture – particularly in the tropics – is one of the sectors most vulnerable to climate change (see World Bank 2010).
- At the same time, these regions offer some of the greatest potential to contribute to mitigation – particularly for forest carbon sequestration, but also for agricultural practices.
As a result of the 2010 UN Climate Change Conference in Cancun, governments are looking to increase their support for developing countries to mitigate climate change through programs such as reducing emissions through deforestation and degradation.
Economic incidence of climate shocks
In a recent paper (Hertel and Rosch 2010), we explore the literature linking climate change to poverty through agriculture. We find that the poverty consequences of climate change are more nuanced than has been suggested in most discussions to date. It is not simply a question of how climate change’s impacts on food prices affect low income consumers. The poor will also be affected through changes in factor markets and the availability of environmental resources. In addition, we hypothesise that, in the near term, in many parts of the tropics, the world’s efforts to mitigate climate change may have more important effects on the poor than will climate change itself.
The adverse consequences of food prices spikes have been well documented and will affect the poor in both rural and urban areas (see for example De Hoyos and Medvedev 2009 and Ivanic and Martin 2008). However, rural households may actually benefit from increased agricultural revenues – a point which is often overlooked in partial equilibrium analyses. In cases where agriculture is a major employer in the economy – particularly for unskilled workers – it is also possible that the earnings of poor, nonfarm households might be significantly affected through changes in unskilled wages. For example, depending on the timing, severity, and duration of floods in Bangladesh, these severe climate events have been shown to either depress or boost unskilled wages nationwide.1
The aggregate national poverty impact of an adverse climate change event will depend on the cumulative effect across all low income households in the economy. While we generally expect an adverse climate event to increase poverty, there are circumstances under which the national poverty head count could actually fall (Hertel et al. 2010). Such an eventuality is most likely when the following four conditions hold jointly.
- First, the adverse climate change is not localised and farm level demand is relatively inelastic, leading to a sharp rise in agricultural prices and farm factor returns.
- Second, poverty is concentrated in agriculture so that the majority of the poor are favourably affected due to the first condition.
- Third, the adverse climate shocks result in a sustained increase in labour demand.
- Lastly, if the farm sector represents a large share of the unskilled labour demand in the economy, then the indirect wage effects can mitigate the adverse food price impacts on the non-farm poor.
In addition to these market-mediated impacts on the poor, however, climate change can significantly alter the quantity and quality of natural resources available to low-income households. Empirical estimates from Zimbabwe, Peru, the Democratic Republic of Congo, and Brazil suggest that poor households derive significant portions of their household incomes – as much as 40% or more – from consumption and cash earnings associated with environmental goods such as forest products, bush meat, fish, and wild plants (see Hertel and Rosch 2010). Such non-market adverse impacts have been largely ignored in climate change impact studies and could potentially offset the gains described above.
The impact of climate change on poverty depends critically on the time frame over which it occurs. Low income households are better able to adapt to gradual changes; short-run climate shocks do not allow sufficient time for adaptation and may have severe implications for long-run wellbeing. Surveying all sources of external shocks to rural households in Ethiopia, Dercon (2005) finds that drought is the predominant cause of loss of assets, income and consumption. Furthermore, he estimates that it takes households ten years to rebuild livestock holdings. The slow rate of household recovery means that successive droughts can have a devastating impact on low income households. This is a particular concern as recent evidence suggests increased frequency and intensity of extreme climate events under global warming (see for example IPCC 2007 and Ahmed et al. 2009).
In light of these challenges, farm households adopt a variety of risk minimisation techniques – such as planting a multiple crops or staggering planting dates – in order to diversify against climate risks. However, these strategies often result in reduced long-run expected profits. Farmers in Andhra Pradesh who plant a mix of crops that hedge climate risks saw reduced variability of agricultural revenue but also lower average incomes (Gine et al. 2007).
A recent case study of South African farmers found a similar pattern. Wealthier households made planting decisions that were less diversified for climate risks than poor ones in order to better target market demand and maximise profits (see Ziervogel et al. 2006). Estimates of farmer behaviour in India by Rosenzweig and Binswanger (1993) found that increasing the coefficient of variation of rainfall by one standard deviation reduced estimated farm profits for the poorest wealth quartile by 35% while the richest quartile was virtually unaffected by more uncertain rainfall.
Farm households choose an array of adaptation strategies such as insurance, temporary migration and investment in human capital, depending on how these strategies are supported by institutions and public policies environments. However, in many areas today, farmers still prefer to rely on traditional knowledge and methods of forecasting climate for their planting decisions, although this may not persist as climate signals become noisier. As Quiggin and Horowitz (2003) have pointed out, climate change effectively destroys information by rendering more diffuse the historical knowledge held by producers. Many policies which can improve livelihoods today – such as improving insurance markets, investing in relevant climate forecasting capabilities, establishing water management institutions, and facilitating migration – also have the potential to aid farmers in adapting to climate change.
There are two channels through which climate change mitigation policies can affect poverty. The first of these is through payments for environmental services. When the poor are involved in efforts to sequester carbon, the payments to these households may directly serve to alleviate poverty. This idea has worked well in parts of the Amazon basin where indigenous households receive a monthly payment on their debit card when aerial surveillance shows that no deforestation has occurred. Insecure land tenure, credit constraints, and high fixed costs, however, tend to the bias the benefits of such programs towards large landowners.
The second channel by which mitigation policies affect poverty is indirectly through commodity and factor markets. Large-scale, global initiatives to reduce greenhouse-gas emissions through agriculture and forestry are likely to increase global land demand and commodity prices. The poverty impacts of higher commodity prices induced by mitigation efforts are ambiguous. Higher prices hurt consumers everywhere but also have the potential to benefit households of rural agricultural producers where many of the world’s poor reside.
A key avenue through which climate change affects the poor is via the agriculture sector, since poverty tends to be concentrated in rural areas, the poor spend a large share of their income on food, and their income from farm production and wages is tied to climate patterns.
Given the length of time required for households to recover from adverse climate shocks, the prospect of increasingly frequent and intense extreme events is of great concern. Policymakers should consider undertaking measures to facilitate adaptation by the poor to such events, including improvement of credit and insurance markets and better governance of natural resources. Given our hypothesis that the near-term poverty impacts of climate mitigation policies could be more significant than the poverty impacts of climate change itself, policymakers have a duty to design such mitigation projects to maximise their poverty-reducing potential.
Ahmed, S, N Diffenbaugh, and T Hertel (2009), “Climate volatility deepens poverty vulnerability in developing countries”, Environmental Research Letters.
Banerjee, L (2007), “Effect of flood on agricultural wages in Bangladesh: An empirical analysis”, World Development, 35(11):1989–2009.
De Hoyos, RE and D Medvedev (2009), “Poverty Effects Of Higher Food Prices”, World Bank Policy Research Working Paper 4887, 1-34.
Dercon, S (2005) “Vulnerability: a micro perspective, presented at the Annual Bank Conference on Development Economics Conference, Amsterdam.
Gine, X, RM Townsend, and J Vickery (2007), “Rational expectations? Evidence from planting decisions in semi-arid India”, World Bank Policy Research Working Paper.
Hertel, Thomas W and Stephanie D Rosch (2010), “Climate, Agriculture and Poverty”, Applied Economics Perspectives and Policies.
Hertel, T, D Lobell, and M Burke (2010), “The poverty implications of climate-induced crop yield changes by 2030”, Global Environmental Change.
IPCC (2007), Climate Change 2007: The Physical Science Basis: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
Ivanic, M and W Martin (2008), “Implications of Higher Global Food Prices for Poverty in Low-income Countries”, Agricultural Economics, 39(1):405-416.
Quiggin, J and J Horowitz (2003), “Costs of adjustment to climate change”, The Australian Journal of Agricultural and Resource Economics, 47(4):429-446.
Rosenzweig, MR and HP Binswanger (1993), “Wealth, weather risk and the composition and profitability of agricultural investments”, Economic Journal, 56-78.
World Bank (2010), World Development Report.
Ziervogel, G, S Bharwani, and TE Downing (2006), “Adapting to climate variability: Pumpkins, people and policy”, Natural Resources Forum, 30:294-305.
1 For example, if the flood requires replanting of the fields, the demand for labor may rise as a consequence. On the other hand, massive flooding has a dampening effect on wages as the demand for labor is reduced (see Banerjee 2007).