This section reviews previous empirical evidences on the productivity impact of climate change. A brief summary of the channels through which climate change manifests its effect on productivity is presented. This will be followed by a brief summary of the disproportionate and heterogeneous nature of its impact. The sources of this heterogeneity and the different mechanisms that are included in the models used to estimate the impact and are found to have significant impact in minimizing the impact are discussed in sub sections three and four, respectively.
2.1. Channels of climate change impact
Climate change manifests itself in several forms. Among these are the rise in sea levels causing coastal flooding, higher temperature, reduction in precipitation and erratic and extreme climate events (IPCC, 2013). All of these have implications for agricultural productivity and hence the welfare of households (McGuigan et al., 2002). Climate change affects agricultural productivity through various channels. The rise in temperature along with the reduction in rainfall reduces agricultural productivity if both are beyond the threshold that is suitable for crop production (Cabral et al., 2007; McGuigan et al., 2002; Skoufias, 2014). Climate change could also result in a change in the length of seasons. In places where traditional agriculture dominates, the change in the length of the seasons makes it difficult to conduct the crop production process at the regular time unless some sort of adaptation mechanism is adopted (Cabral et al., 2007 and McGuigan et al., 2002). Climate change also increases the probability of extreme weather conditions such as drought and heavy precipitation (IPCC, 2013 and Skoufias, 2012). Such events could obliterate agricultural produce and household's productive assets. This would have a negative effect on both current and future food security status of households respectively (Cabral et al., 2007 and McGuigan et al., 2002). Lastly, the level of soil fertility is altered due to climate change (McGuigan et al., 2002). All of these factors work jointly to reduce agricultural productivity and, therefore, weaken the status of food security.
The reduction in agricultural productivity due to climate change has a strong welfare implication for many of the countries with majority of their population relying on agriculture for livelihood. The loss of agricultural productivity affects the income and consumption of households. It could either push or keep households below the poverty line. The ability of net consumers to purchase consumer products could be constrained due to the reduction in their income. Net producers could also face a decline in their consumption due to smaller crop yield (Karfakis et al., 2012).
Skoufias (2012) identifies three ways through which climate change could affect households. The first is the deterioration of households’ asset base. The advent of a climate change event would force households to sell their assets to mitigate the impact of these extreme climatic conditions. The fact that extreme climate events are of covariate nature rather than idiosyncratic make it difficult to access credit markets to mitigate this risk (McGuigan et al., 2002). This problem is further accentuated by the lack of efficient capital and insurance markets in developing countries (IPCC, 2014 and Skoufias, 2012). Furthermore, if households sell productive assets, the extreme climatic event may have a lasting impact by limiting the households’ future capacity to produce.
Secondly, there are various ways through which climate change may affect the health of household members. The increase in temperature which is a typical manifestation of climate change allows more disease vectors to survive (Majule and Mary, 2008; McGuigan et al., 2002; Skoufias, 2014). The reduction in water resources aggravated by the population pressure especially in urban areas prevents a hygienic lifestyle thereby worsening health (McGuigan et al., 2002 and IPCC, 2014). Extreme weather events also expose people to injuries which may have both short term and long term implication on their health (IPCC, 2014). In addition, the reduction in real income due to food price rise for net consumers and the decrease in crop production for net producers could have an impact on the nutrition of household members which in turn affects their health (Karfakis et al., 2012).
The third impact Skoufias (2012) identified is the reduction in access to water and infrastructure. The gradual decline in precipitation especially in tropical areas creates a constraint in water supply. Furthermore, extreme climatic events could destroy the infrastructure already in place. The decrease of agricultural productivity manifested in the reduction of crop yield not only creates loss of farm income but also has impact on the labor allocation of the households. The loss of income may force households to allocate their labor to non-farm income sources and may even result in migration (Gemenne, 2010). Female members of the households that normally engage in household activities may also be forced to leave the household to earn income (Karfakis et al., 2012). This leaves children without care which thereby affects their wellbeing both in terms of nutrition and education. Children may also be forced to work outside the household which comes at the expense of their education (McGuigan et al., 2002).
2.2. The disproportionate effect of climate change
Several studies have pointed out that there will be gain in agricultural productivity in higher latitudes and loss in tropical areas. The reason behind this gain is the existence of a threshold beyond which temperature starts contributing negatively (Cline, 2007). If temperature rises above its current average in tropical areas, it will bring about drought, pests and diseases thereby reducing agricultural productivity (Cabral, 2007). Food production would, therefore, decline. Moreover, precipitation has been rising in the temperate areas (IPCC, 2013). This further contributes to the improvement in agricultural productivity in higher latitudes.
The overall food supply at the international level may increase. However, the reduction in domestic supply of food is likely to create food price spikes in developing countries. The shortage of food supply could be filled through imports. Various groups are affected differently through these price hikes. One of the main explanations behind this is the net production and consumption position of households (Skoufias, 2014). Net producers are likely to benefit from the price rise in contrast to net consumers who would lose since they would need to purchase food to meet their consumption needs. The overall effect will depend on the net position of the households (Deaton, 1989). The net position in turn is determined by factors such as level of urbanization and access to land and technology. Climate change has a regressive impact on the poor - the poor are more likely to be affected than the rich. Moreover, the urban poor (wage laborers) are more likely to be affected with the increasing trend in urbanization and the fact that urban workers are net consumers. Food price hikes would, therefore, affect the urban poor more than any other group (Skoufias, 2012).
An important implication of the differential impact of climate change on agricultural productivity in high latitude and low latitude areas is that it sustains and exacerbates the existing inequality between developing and developed countries (Cabral, 2007 and McGuigan, 2002). Not only are developing countries more vulnerable to the impacts of climate change as they are more dependent on economic activities whose productivities depend on weather conditions, they also lack effective financial systems that can help cope with these risks (Skoufias, 2012). This problem is further intensified by the fact that 'weather shocks' are of covariate nature which makes it difficult to mitigate even with the existence of efficient credit and insurance markets (McGuigan, 2002).
Moreover, coping and adaptation with the effects of natural hazards depends on economic resources, infrastructure and technology which are lacking in developing countries. This constrains the ability of such countries to engage in ex-ante risk management mechanism such as early warning and ex-post shock coping mechanisms such as disaster response, victim relief and assistance (Karfakis et al., 2012 and McGuigan, 2002).
The role played by high population growth and rapid urbanization, both of which characterize developing countries, in aggravating the impact of climate change in developing countries is also pertinent to the analysis (IPCC, 2000 and McGuigan, 2002). Given the fact that the urban poor are the most affected by the food price hikes resulting from reduced crop yield, the unrestrained rapid urbanization process observed in many developing countries increases the group that loses from the rise in food price, i.e., the net consumers (Karfakis et al., 2012). Rapid population growth also creates pressure on natural resources and leaves less food per capita.
In summary, the process of climate change not only has a negative effect on the overall wellbeing of households in developing countries, but also plays a role in increasing the inequality between developing and developed countries. This implies that the burden of climate change is born disproportionately by the poor both within and cross country settings.
2.3. Sources of Heterogeneity of Impact
A crucial point to note when looking into the impact of climate change on all economic units is that it is heterogeneous. It is dependent on a myriad of factors among which are wealth, location, access to infrastructure and basic services, education, net production and consumption position, gender, access to land and modern agricultural inputs (IPCC, 2014 and Skoufias, 2014). The specific agro-ecological zone an economic unit is located in determines whether it will benefit or lose from climate change (Tol, 2009). In general, there is a possibility that temperate areas may benefit from climate change in terms of agricultural productivity since the temperature change may not have reached the threshold beyond which crop yield declines (Cabral et al., 2007 and Cline, 2007). The reverse is true in tropical areas. Not only does climate change increase susceptibility to drought but also increases the exposure to pests and diseases (IPCC, 2014; McGuigan et al., 2002; Skoufias, 2014). The location of the household also affects its access to infrastructure and markets which are important factors in determining the strength of the impact of climate change on the household (Skoufias et al., 2012).
The income, asset and expenditure structure of households also affects the strength of the impact of a climate related risk. If households have enough resources to rely on at the time of such events, climate related impacts can be mitigated relatively easily (Skoufias, 2014). Moreover, rich households with larger access to land could lose due to the loss in agricultural productivity. Wage earners, on the other hand, could be insulated from this impact if they are not engaged in agricultural activities. However, the wage earners could lose due to the food price rise caused by the reduction in food supply. The overall effect hence depends on whether the loss of return from land and labor outweigh the loss of real income due to price rises for the poor (Skoufias et al., 2012).
The education level of the household may also affect the extent of the damage inflicted by climate change by increasing its ability to diversify and come up with adaptation mechanisms to mitigate the climate related risk (IPCC, 2014). Greater human capital endowment of the household could also contribute the household by making it less dependent on agriculture for income. The argument of Skoufias et al. (2012) in determining the overall effect would apply for education as well.
The gender of the household head and the gender composition of the households also has implication on the size of the impact of the climate change. Karfakis et al. (2012) and Barrientos and Khanji (2002) argue that female headed households are more vulnerable to the impacts of climate change in comparison to their male counterparts because they have limited access to land and financial services which are important resources to mitigate the negative effects of climate change. Hence, female headed households are more likely to be affected by climate change than male headed households. Female members of the household will also be forced to leave the household to earn income mostly under dire working conditions as a result of reduction in income or agricultural produce due to climate change (Barrientos and Khanji, 2002). This implies that labor is reallocated from reproductive to productive labor. This reallocation deprives children of child care and weakens their status of nutrition and educational performance. This slows down the process of human capital accumulation of the households.
Households’ access to modern agricultural inputs also affects how well households can respond to climate change. The use of modern agricultural inputs helps households to circumvent the negative impacts of higher temperature and limited precipitation (IPCC, 2014). This is one of the ex-ante risk management mechanisms adopted by crop producers (Karfakis et al., 2012). It is also part of the recommended climate change adaptation mechanisms (IPCC, 2014). This argument is supported by Amaliah et al. (2012), which has shown that increased investment on agricultural research and development significantly reduces the impact of climate change on household consumption which is an important indicator of welfare.
To conclude, at the household and community levels, these factors result in a variation in the impact of climate change on households. Hence, it is crucial to take them into account in trying to explain the heterogeneity in the effects of climate change on agricultural production and household welfare.
2.4. Adaptation as means of reducing the impact
The extent of the effect of climate change on poverty depends on the effectiveness of the adaptation strategy adopted by households, if at all they have an adaptation strategy. If adaptation strategies are carefully planned, they can significantly reduce the negative impacts of climate change (Skoufias et al., 2011). Adaptation strategies must particularly target those that are vulnerable to this change given the resource constraints. Hence, it is necessary to equip this group with the necessary tools to mitigate the impact (Kyotalimye et al., 2010). Skoufias (2012) identifies four important factors that determine households’ ability to adapt to climate change events. Among these are autonomous adaptation strategies which are dependent on the ability to shift from the agricultural sector to a non-agricultural sector. The faster one can shift between the two, the lesser the damage inflicted will be.
Adaptation mechanisms can also be induced by governments through policy and direct intervention. Access to these interventions affects the ability of the household to mitigate climate related risks. Conditional cash transfer programs and safety net programs are examples of such intervention. Governments also intervene to improve households’ access to credit and insurance so that the climate related risks are effectively mitigated.
The third important factor that determines the ability of households to adapt to climate change events is the relative productive endowment of the households. The nature of land held by households, for example, whether or not it is irrigated, affects the ability of the household to adapt to these changes. Moreover, the skill composition of the households’ labor also has an implication on its adaptation capacity.
Lastly, as has been discussed in the earlier sections of this review, the net consumption and production position of the household determines its ability to adapt to climate change and which adaptation mechanism fits the household.
A crucial factor in ensuring the success of adaption strategies is the dissemination of information about climate related risks in the future. This allows one to take into account the expected patterns in temperature and precipitation and, hence, its resulting impact on agricultural productivity in designing adaptation strategies. This adds to the strength of the adaptation strategies in mitigating climate related risks (Skoufias et al., 2011).
There are various forms of adaptation strategies adopted by households to mitigate climate related risks particularly in the agriculture sector. Households adjust their consumption and production patterns in response to changing climate which affects their agricultural productivity (Skoufias et al., 2011). One form of response is changing their cropping pattern to deal with the timing of the seasons that is altered due to global climate change (Majule and Mary, 2008). Another form of adjustment in production patterns comes through the use of improved inputs and better production technology in agriculture. Migration is also used as an adaptation strategy to mitigate the risks of climate change (Gemenne, 2010).
At policy level, there are initiatives to establish governance systems for adaptation in many African countries. The efforts are exerted in different dimensions such as disaster risk management, adjustment in technologies and infrastructure, ecosystem-based approach and public health measures and livelihoods diversification. Although these initiatives have contributed to the alleviation of vulnerability, they are criticized for lacking coordination in deploying them (IPCC, 2014). Among the policy measures that can be adopted to help households and communities to adapt to climate change are well-targeted safety net programs that can be scaled up (Skoufias, 2012 and Skoufias et al. 2011). Given the lack of access to capital and insurance markets in developing counties, improving the access to such markets could also improve the capacity of the poor to adapt to climate change. Any climate related risk could be circumvented through credit or insurance without the need to sell productive assets or wipe out savings (McGuigan, 2002).
In terms of the management of natural resources, the improvement in the governance of common-pool natural resources and raising the investment on irrigation and improved water management could help maintain or increase agricultural productivity by dealing with events of extreme precipitation (Skoufias et al., 2011). However, it is argued that solely focusing on water management practices in dealing with the impacts of climate change without the consideration of social, institutional and ecosystem based measures limits the capacity of the measures to effectively tackle climate change events (IPCC, 2014).
Expansion of access to international markets is also one form of an adaptation strategy. Regional and country specific climate shocks are likely to cause food price hikes. In this case, ensuring trade openness could insulate net consumers from the impact by alleviating the increase in food prices. Hence, an intervention through the liberalization of trade could contribute to the mitigation of the impact of climate change (Cirera et al., 2002 and Skoufias et al.,2011). Another crucial factor to ensure the mitigation of the impact of climate change is occupational mobility. With the ability to shift between occupations, it is possible to escape the impact of climate change by switching jobs (IPCC, 2014 and Skoufias et al., 2011). This is similar to livelihood diversification which is also one sort of an adaptation strategy. Households diversify their risk by sourcing their income from different activities. This way, they can rely on an alternative source if one of their income sources is affected by a climate change event (IPCC, 2014).
Overall, adaptation strategies are necessary to reduce the impact of climate change on poor households. These strategies come both in terms of changes in consumption and production patterns, direct intervention by governments and policy induced. Although the importance of these strategies to protect the vulnerable cannot be debated, the success of such adaptation strategies, however, depends on the inclusion of social, institutional and ecosystem measures in designing the adaptation strategies.
2.5. Methodological review
A review of the literature on the welfare impact of climate change revealed that there are different approaches used to estimate the impact. These approaches range from use of economy-wide growth model to household model. One feature of the former model is that, using aggregated data, it incorporates consistent climate-change scenarios to show how climate change might affect the path of poverty. For instance, using aggregated data, one can estimate the percentage change in output due to a change in climate. The different studies that use such approach differ in their estimation of the impact depending on the type of information they use. Zhai et al (2009) used comparable general equilibrium (CGE) model in order to examine the impact of climate change on agriculture sector of China in 2080. Similarly, using a Social Accounting Matrix, a CGE model is used to estimate the macroeconomic effects of climate change in Uganda (Matovu and Buyinza, 2010). The authors argued that use of such model has a number of strengths. Firstly, the model simulates the functioning of the economy as a whole and track how changes in economic conditions are transmitted through price and quantity adjustments on a range of markets. Secondly, the structural nature of the CGE model allows us to analyse separately the impacts of multiple climate changes. Thirdly, since the basis of the CGE model is a Social Accounting Matrix, we are able to discern the effects of the changes in economic conditions on individual sectors of the economy. Fourthly, the link of the model to household survey data enables an assessment of the impacts on the welfare of households, which is particularly interesting since this is where the most important policy implications are likely to be found. Finally, the recursive dynamic nature of our model implies that the behaviour of its agents is based on adaptive expectations when faced with difficult circumstances, rather than on the forward looking expectations that underlie inter-temporal optimization models. A simulation model is also used in estimating the impact of climate change. For instance, Cerri et al (2007) used simulation model for Central South region of Brazil up to 2050. They revealed that 3oC to 5oC increase in temperature and 11% increase in precipitation would cause a decrease in the productivity of wheat to the level equal to one million ton by weight. Ayinde, et al. (2010) using time series data empirically analyzes trend climate change and agricultural production in Nigeria. Their Granger causality analysis indicates that there is a relationship between changes in rainfall and agricultural production in Nigeria. Deschênes and Greenstone (2007) propose a fixed-effect model that exploits the presumably year-to-year variation in temperature and precipitation to estimate the impacts of climate change on agricultural profits and yields. More specifically, the authors use a county-level panel data to estimate the effect of weather on US agricultural profits, conditional on county and state by year fixed effects. Hertel, Burke, and Lobell (2010) analyzed the impacts of climate change through a more careful modelling of the channels and heterogeneity of impacts in the context of economic growth. They use disaggregated data on household economic activity (stratified by primary source of income) within 15 developing countries and a general equilibrium global trade model (the Global Trade Analysis Project, or GTAP) to explore how changes in agricultural productivity will affect poverty in poor countries. Although their model allows only limited heterogeneity, a key feature is that it allows different types of households to be affected differently by the prices of agricultural goods. The authors use three scenarios of how climate change affects agricultural productivity (low, medium, or high productivity) to evaluate the resulting changes by 2030 in global commodity prices, national economic welfare, and poverty headcount rate.
These studies are informative as they provide the magnitude of the impact. However, general equilibrium models have tradeoffs between the tractability of the general equilibrium effects and the heterogeneity incorporated into the model. In addition, studies based on aggregated data may not provide clear channels through which climate change translates its impact on the welfare of households. In addressing such shortfalls, studies used a microeconomic approach, which helps to shed light on the channels through which climate change can affect household welfare. A production function approach, also called ‘agronomic model’, is one such approach that was also used in some studies to estimate the welfare impact of climate change. For instance, Decker et al. (1986), Adams (1989), among others adopted this approach. This approach takes an underlying production function and varies the relevant environmental input variables to estimate the impact of these inputs on production of different crops. Ricardian model is another method commonly used in estimating the impact of climate change. The model first captures the type of crop a farmer will select and then examines the conditional net revenue of that crop. Kurukulasuriya and Mendelsohn (2008) examine the impact of climate change on primary crops grown in Africa. Using sample of 5,000 farmers, they find that farmers use crop switching as a strategy for adapting to climate change using a ‘structural Ricardian model’. The main conclusion from this study is that farmers shift the crops they plant to match the climate they face. Studies that fail to account for crop switching will overestimate the damages from climate change and underestimate the benefits. The same approach is also used by Temesgen et al. (2009). Their study empirically analysed the farmer adaption techniques to varying climate change in Ethiopia using the Ricardian approach with household level data from different agro-ecological zones of the country. In their empirical analysis, net crop revenue per hectare was regressed on climate, household and soil variables. The findings from their study show that these variables have a significant impact on the net crop revenue per hectare of farmers under Ethiopian conditions. Baez and Mason (2008) and World Bank (2012) provided a thorough review of the Literature on the welfare impact of climate change. Though numerous studies have examined the welfare impacts of climate change, only few studies used actual weather data to analyse the general relationship between weather and the level of welfare. After a detailed review of the different literatures, this study used a microeconomic approach in which observed and projected climate variables are modelled along with non–climate drivers of vulnerability to estimate the productivity and welfare impact of climate change. This approach is discussed in the following section.