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A FARMer's View of the Ricardian Approach to Measuring Agricultural Effects of Climatic Change
Abstract
During the past few years two new methods, each based on the analogous region concept, have been developed to account for farmer adaptation in response to global climatic change. The first, called ''Ricardian'' by Mendelsohn, Nordhaus, and Shaw (1994), econometrically estimates the impact of climatic and other variables on the value of farm real estate. Under some conditions, estimates of climate-induced changes in farm real estate capture first-round adaptations by farmers and represent the economic value of climatic change on agriculture. The second method, promulgated by Darwin et al. (1994) in the Future Agricultural Resources Model (FARM), uses a geographic information system to empirically link climatically derived land classes with other inputs and agricultural outputs in an economic model of the world. FARM provides estimates of economic impacts that fully account for all responses by economic agents under global climate change as well as estimates of Ricardian rents. The primary objective of this analysis is to evaluate how well changes in Ricardian rents measure agricultural or other effects of climatic change after all economic agents around the world have responded. Results indicate that changes in Ricardian rents on agricultural land are poor quantitative, but good qualitative, measures of how global climatic change is likely to affect the welfare of agricultural landowners, if one recognizes that increases in Ricardian rents actually indicate losses in landowner welfare and vice versa. Results also indicate that regional changes in Ricardian rents on all land are good qualitative measures of changes in regional welfare. They are poor quantitative welfare measures because they systematically overestimate both benefits and losses and are on average upwardly biased because inflated benefits are larger than exaggerated losses. Results also indicate that, when based on existing land-use patterns, changes in Ricardian rents on all the world''s land are poor quantitative and qualitative measures of changes in world welfare. Despite these shortcomings, changes in Ricardian rents can provide useful information when other measures are not available. In this analysis, for example, estimated changes in Ricardian rents on all land indicate that climatic change would likely have detrimental effects in Latin America and Africa, beneficial effects in the former Soviet Union, and either detrimental or beneficial impacts in eastern and northern Europe and western and southern Asia. This is consistent with previous studies showing that climatic change would likely have detrimental, beneficial, and mixed effects on economic welfare in, respectively, equatorial, high latitude, and temperate areas. Estimated changes in Ricardian rents also indicate that aggregating Africa, Latin America, the former Soviet Union, eastern and northern Europe, and western and southern Asia into one region causes FARM''s economic model to generate upwardly biased changes in world welfare. Modified results from scenarios with moderately flexible land-use change and which account for current land-use patterns indicate that world welfare may increase if the average surface land temperature does not increase by more than 1.0 or 2.0C. If the average surface land temperature increases by 3.0C or more, however, then world welfare may decline.
... FARM results indicate that climate change will have adverse effects on the health and integrity of tropical forests in Southeast Asia, Latin WorId Resource Revjew Vol. 14 No. 4 America and Africa; decreased forest land areas were a result of climateinduced effects and competition from crop production (Darwin et a]., 1996). In addition, estimated changes in Ricardian rents indcate likely detrimental effects in Latin America and Africa, beneficial effects in the former Soviet Union, and mixed impacts on eastern and northern Europe and western and southern Asia (Darwin, 1999). Benefits and losses associated with these changes are passed on to consumers. ...
... Wbr/d Rmource Review Val. 14 No. 4 America and Africa; decreased forest land areas were a result of climateinduced effects and competition from crop production (Darwin et al., 1996). In addition, estimated changes in Ricardian rents indicate likely detrimental effects in Latin America and Africa, beneficial effects in the former Soviet Union, and mixed impacts on eastern and northern Europe and western and southern Asia (Darwin, 1999). Benefits and losses associated with these changes are passed on to consumers. ...
The linkage between global climate change and forests have assumed political prominence as forest sinks are now acknowledged as a means for offsetting carbon dioxide (CO,) emissions under the Kyoto Protocol targets. As such, policies to stimulate forest carbon sequestration in an open economy will require varying levels of economic information to allow for decisions that are both eficient and sustainable. This paper reviews the various economic approaches that have been recently used to examine the impacts of climate-forest policies, and discusses their usefulness for policy analysis. A suite of integrated economic-ecologic models is also reviewed to contrast with the shortcomings of static single sector studies, and a series of guidelines for future integrated research in this area are highlighted.
... Finally, technology improvements and climate change factors are explicitly not included in the simulation, and therefore, the generated farmland prices across the four scenarios are relatively stable. However, technological improvements will increase long-run farmland prices because of increases in net income (Klinefelter 1973) and it is also highly likely climate change consequences will also generate effects on farmland values through the simulated era (Darwin 1999). These issues will have to be addressed in future research on farm level modeling. ...
With deep agricultural roots, Western Canada is a major farmland market. Historically, farmland was retained within families by succession. But with strong personal and economic linkages, succession can create a difficult situation for retiring farmers trying to make objective decisions about the future of their (land) assets. Some offer that increased farmland ownership by external investors has the potential to negatively affect farm structure. Yet there are sound financial reasons for institutional investors to want farmland as an investment, including diversification benefits for investment portfolios. Due to the complexity and heterogeneity of individual agricultural land market decisions, we build upon prior related models to develop an agent-based simulation framework designed to highlight the interplay between these potentially conflicting factors. To this end, we endogenize both farm succession and the presence of institutional investors who desire to purchase regional farmland as a financial asset. Under conservative assumptions, we find that the presence of institutional investors elevates farmland prices in the study region by approximately 15% to 40%, depending on scenario. With the presence of investors, farmers tend to lease more land over time to support their arable land base. Through the duration of our simulation, the total number of farms in the study region drops over time, while larger individual farms emerge. We conclude that institutional investors will affect future farming structure in the region, but their presence could manifest in very subtle ways. Most critically, farming success with institutional investors operating in this land market is contingent on future farmers being willing to rely on land rental rather than ownership in the process of farm maintenance or expansion.
... Although Wang Chen (2018) used the Nerlove model and GMM to analyze the impact of price and climate factors on soybean production, the data used in this study are all inter-provincial data, which are too macroscopic for variables such as precipitation and temperature [17]. To consider variables such as price and climate simultaneously, some scholars have used the Ricardian approach [39,40]; however, the Ricardian approach uses cross-sectional data, which assumes that input and output price variables will not change over time while changing has certain limitations [39,41]. In addition, some scholars have used econometric methods when studying the factors affecting crop production but were limited by the level of econometrics development at that time. ...
This paper uses panel data from 116 prefecture-level cities in China from 2003 to 2019 to study the impact of price and climate factors on soybean planting area and yield per unit area in China. We adopt the panel instrumental variable method to control the endogeneity of the price in the regression and allow possible spatial autocorrelation errors. According to the research results, price is the primary factor affecting soybean production. For every 1% increase in soybean prices, the soybean planting area increases by 1.650%, and the per unit yield decreases by 0.898%. As for fertilizer prices, for every 1% increase in fertilizer prices, the soybean planting area will decrease by 2.616%, and the yield per unit area will increase by 0.819%. At the same time, climate change will also significantly affect soybean production. For every 1 cm increase in precipitation in April and May, the soybean planting area will increase by 0.233% and decrease by 0.172%, respectively. The precipitation increase in June and July can also significantly promote soybean yield. The results demonstrate that because soybean is a shade-loving crop, the increase of growing degree days will hinder the progress of soybean yield.
... Moreover, some studies found that crop yield and climatic conditions are influenced by ocean-related phenomena in China (Shuai et al. 2016;Tao et al. 2004). Furthermore, a few studies used the Ricardian model to calculate the effect of climate on the land rent while enabling adaptation (Darwin 1999;DARwin 2017;Kurukulasuriya and Ajwad 2007). This approach also addresses the direct and indirect impact of climate, crops, alterations in inputs, and supplementary practices on agricultural sectors as a whole. ...
Evidence revealed that climate change has a significant impact on grain production in China. Northeast China has abundant agricultural resources which can make the maximum contribution to national food security. This study examines the effects of
climate variability and price anomalies on grain yield and land use in Northeast China. The analysis showed that different climate variability phase combinations based on Pacific Decadal Oscillation and North Atlantic Oscillation present variations in signals and different magnitude of effects over the study area. The results revealed that land use by total grain crop negatively responds to the increase in price anomalies in Heilongjiang and Jilin Provinces. To assess the impact of climate change on crop yield model, the yield models under dynamically downscaled regional climate models revealed that climate variables significantly contribute to total grain yields. In the near future, minimum temperature (− 0.26 °C under CanESM2-4.5, − 4.42 °C under HadGEM2-ES), maximum temperature (− 2.82 °C under CanESM2-4.5, − 0.84 under HadGEM2-ES), and precipitation (ranged from 3.59 to 11.10%) positively contribute to total grain yields under both models. Overall, analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.
... Scientific research community have used various methods such as production function model, Ricardian cross-sectional model, Crop simulation model, Future agricultural resources model, Agro-ecological zone model or Agroeconomic zone model, and Computable general equilibrium model to estimate the climate change impact on crop yield, agricultural productivity, agricultural GDP and other sectors using primary and secondary data in different countries (Mendelsohn et al., 1994;Darwin, 1999;Quiggin and Horowitz, 2003;Eid et al., 2006;Zhai et al., 2009;Singh et al., 2017). Cobb-Douglas production function approach produce the better regression coefficient of explanatory variables in magnitude in agriculture production analysis (Chen et al., 2004;Kumar et al., 2016;Kumar et al., 2017;Singh et al., 2017;Jyoti and Singh, 2020). ...
Purpose : This study examines the impact of climatic change on food-grain production and yield using state-wise panel data during 1977-2014 in fifteen Indian states. Accordingly, it estimates the projected food-grain production and yield by the years of 2040, 2040, 2060, 2080 and 2100. Finally, it provides the effective practical and effective policy suggestions to reduce the climate change impact on food-grain farming based on existing studies. Research Method : Regression coefficients of food-grain production and yield with climatic and non-climatic factors are estimated using Cobb-Douglas production function model. Marginal impact analysis method is used to examine the projected food-grain production and yield. Findings : Empirical results infer that most climatic factors have a negative impact on food-grain production and yield in different weather seasons. Projected results are suggested that food-grain production is expected to be declined by 5.25%, 6.64%, 8.03% and 9.57% by 2040, 2060, 2080 and 2100 respectively. Food-grain yield is likely to be decreased by 1.05%, 1.96%, 2.87% and 5.07% by the aforesaid years. Research Limitations : This study could not capture impact of inter-states disparities in socioeconomic condition of farmers, geographical conditions, agriculture policies and public spending on agriculture and rural development on food-grain production and yield. It also could not include factors such as solar radiation, sun intensity, wind speed and heat wave in empirical investigation. Originality/ Value : It compiles state-wise panel of food-grain production and yield as dependent variables, and climatic variables and non-climatic factors as explanatory variables during 1977-2014. It examines the projected food-grain production and yield.
... Cela permet en particulier de proposer une approche complémentaire aux études agronomiques qui doivent modéliser explicitement l'adaptation (Carleton and Hsiang, 2016). La dépendance de l'agriculture mondiale au climat peut être ainsi caractérisée sur la base de données relativement parcimonieuses, ce qui a permis de nombreuses applications (Darwin, 1999 ;Fezzi and Bateman, 2015 ;Reinsborough, 2003 ;Sanghi and Mendelsohn, 2008 ;Van Passel et al., 2016 ;Wang et al., 2009). En France, des travaux couplent l'influence du climat sur le prix de la terre agricole et sur les choix d'usage du sol dans une analyse en termes de scénarios d'évolution à l'horizon 2050 (Ay et al., 2014). ...
... In order to empirically verify the possible impact of natural shocks on the agricultural sector, researchers have used several methods such as the Ricardian cross-sectional approach, agro-economic modeling, and the production function approach in the literature. The Ricardian approach has been widely used to examine the impact of weather variables on land prices and farm revenue generation studies (as in Mendelsohn, andDinar, 1999 andDarwin, 1999;Gbetibouo and Hassan, 2005;Mendelsohn and Reinsborough, 2007;Sanghi and Mendelsohn, 2008;Kavikumar, 2009;Palanisami et al., 2009). However, this approach has been severely criticised for not providing information on agricultural production and ignoring price variation and carbon fertilisation effects (Mendelsohn, 2000). ...
This paper examines the impact of climate variables such as temperature and rainfall on the yields of
selected major crops in Odisha during the period 1980-81 to 2014-15. Rice, gram, groundnut, maize,
potato and sugarcane are major crops included in the study along with total cereals, total foodgrains, total
oilseeds and total pulses. The study has used the Random Effect Method, Panel Corrected Standard Error,
and Arellano-Bond estimation to identify the crucial determinants of crop yields on panel data of 13
districts. The regression results have reinforced that crop yields of the selected crops are susceptible to
climate change. The study has shown that almost all the principal crops grown in the state are highly
sensitive to changes in rainfall and temperature. Both these variables have some effects (+/-) on the yield
of all crops. It is also observed that the rainfall has significant positive effects on the yields of all the
selected crops under study. In case of temperature, we observed mixed results for the selected crops under
study. But the extent of increase in the temperature appears to be more harmful for the crop yields. Both
irrigation intensity and time trend variable appear to have significant effect on crop y6ield across districts
of Odisha. Thus, the findings of the study have important policy implications.
Keywords: Agriculture, Climatic Shocks, Vulnerability, Climate Change, Odisha
JEL: D10, D81, G22, Q54, Q10
... In order to empirically verify the possible impact of natural shocks on the agricultural sector, researchers have used several methods such as the Ricardian cross-sectional approach, agro-economic modeling, and the production function approach in the literature. The Ricardian approach has been widely used to examine the impact of weather variables on land prices and farm revenue generation studies (as in Mendelsohn, andDinar, 1999 andDarwin, 1999;Gbetibouo and Hassan, 2005;Mendelsohn and Reinsborough, 2007;Sanghi and Mendelsohn, 2008;Kavikumar, 2009;Palanisami et al., 2009). However, this approach has been severely criticised for not providing information on agricultural production and ignoring price variation and carbon fertilisation effects (Mendelsohn, 2000). ...
This paper examines the impact of climate variables such as temperature and rainfall on the yields of selected major crops in Odisha during the period 1980-81 to 2014-15. Rice, gram, groundnut, maize, potato and sugarcane are major crops included in the study along with total cereals, total foodgrains, total oilseeds and total pulses. The study has used the Random Effect Method, Panel Corrected Standard Error and Arellano-Bond Estimation to identify the crucial determinants of crop yields on panel data of 13 districts. The regression results have reinforced that crop yields of the selected crops are susceptible to climate change. The study has shown that almost all the principal crops grown in the state are highly sensitive to changes in rainfall and temperature. Both these variables have some effects (+/-) on the yield of all crops. It is also observed that the rainfall has significant positive effect on the yields of all the selected crops under study. In case of temperature, we have observed mixed results for the selected crops under study. But the extent of increase in the temperature appears to be harmful for the crop yields across districts of Odisha. Thus, findings of the study have important policy implications.
... When it comes to real estate adaptation, there is still a shortage of studies, cost and benefit analyses, adaptation efforts, identification of directions, and cooperation opportunities between the public and private sector. Literature analyses revealed that research studies deal mostly with: 1) adaptation strategies pursued by investors and developers vis-á-vis coastal properties, the actors' awareness, cost of adaptation, demand and supply of coastal properties, 2) identification of factors and barriers that determine the decision-making factors and determinants of the implementation of adaptation efforts in real estate, 3) the role of real estate in climate change adaptation, 4) the need to create and absorb innovation that helps climate change adaptation, 5) tourist real estate and winter tourism in the context of reduced snowfall (Rutty et al., 2015;Scott, Dawson & Jones, 2008), 6) agricultural real estate in the face of climate change (Darwin, 1999). For ages, cities have been located in highly attractive locations in the proximity of water. ...
This paper aims to review subject-matter literature and analyse the development policy documents of major Polish cities addressing the issue of climate change adaptation (urban adaptation plans, Polish abbr. MPA) and concerning the real estate sector; it is also an attempt to draw conclusions and identify potential benefits and challenges that the construction sector is currently facing. The literature focuses on coastal real estate, costs, benefits and barriers in the adaptation of buildings. MPAs point to the significant role of the real estate sector in adapting to climate change. Soft and hard instruments are becoming increasingly important in MPA. These are spatial planning (building restrictions in hazardous areas, use of green roofs in investments), a system of incentives for investors to promote adaptation activities, ecological education, investments in improving the energy efficiency of buildings. Also identified are the benefits to the real estate sector, e.g. the growing importance of occupations on the real estate market, the development of innovations and increased access to cheaper services and technologies. In Polish cities, high-intensity residential areas are characterized by high sensitivity. MPAs will strengthen the resilience of the city’s technical infrastructure and public space, as well as develop blue and green infrastructure, which may translate into the increased resilience of real estate.
... The approach posits that the value of land represents the capitalized values of expected future earnings from the best use of land. That land values are correlated with local climate conditions such as rainfall, temperature, soil quality and that knowing the variation across farms provides information on how farmers have adjusted to a changing climate and the implication on farmland (Darwin, 1999, Reinsborough, 2003. ...
Abstract
Climate change is expected to affect land area farmers cultivate as well as induce responses that are both beneficial and detrimental. Hence, the need to advance sustainable pathways for Nigeria's agricultural growth. To support policy action, the net effect of climate change impact on cropland was modelled using the Ricardian econometric framework. The data set for empirical application was sourced from the National Bureau of Statistics of the Federal Government of Nigeria. Specifically, the study used the socio economic data set of small farms collected in 2010 together with baseline historical climate observations for 40 years average and climate projections for 2050 sourced from World Climate Data Base. Complementary data on population, soil and altitude were sourced from National Population Commission (NPC) and Food and Agriculture Organization (FAO). Climate change reduced land value by 62.79% for the whole country. The distribution across zones revealed reduction by 8.24%, 41.95%, 7.19% and 44.96% for guinea savannah, Sahel, Sudan Sahel and Savannah and increased marginally by 3.36% for forest agroecology.This raises policy imperatives for programmes that seek to improve on the quality of farm land using best practices that are sustainable.
... With respect to rural livelihood and agricultural activities, climate change/variability seems to be the most discussed issue about environmental change adaptation. Quality and quantity of land and water resources available for production in agriculture and other climate-dependent sectors such as forestry and fisheries are affected by the changing climate (Darwin, 1999;Kankam-Yeboah et al., 2011;Yaro, 2013). Climate change is adding more stress to already threatened habitats, ecosystems and species in Africa. ...
This study investigated the local level impacts of climatic and non-climatic factors on the agricultural land-use dynamic in rural northern Ghana. Data was collected by means of household questionnaires and interview. The data collected relates to farmer's knowledge about climate change, response to the impact of climate change, dynamics in the area cultivated for crops, and the climatic and non-climatic factors that affect agricultural land-use dynamics. The data collected was subjected to simple descriptive statistics and chi-square tests. Farmers indicated that the weather patterns have affected their cropping activities. Delay in the start of rainfall, fluctuation and cessation before the growing season ends have affected them. Also, inadequate access to farm inputs has affected them. In the face of unfavourable conditions, the farmers may respond by increasing or decreasing the land area cultivated for some crops, they may continue to cultivate their crops, or they may abandon the crop(s) for the season. Jobs outside of the farm are being taken up to support household needs. Climate change has been interacting with non-climatic (socio-economic) factors, and a holistic approach would be the best to address the local or regional change. Intensification of research within the study region and nearby regions would improve preparedness for future local/regional change.
... Contrary to building land differences within the model, another method is to get it done outside the model such that autonomous modules which account for differences in land characteristics and uses are developed (e.g. [63]. Finally, a more complicated method- ology is one which combines both the output and economic infor- mation with a land use framework. ...
... Here, possible adaptations are embedded in the information collected regarding the farmer's behaviour, which is the main difference between this approach and the structural approach. We found two methods amongst the spatial-analogue, the Ricardian approach that estimates adaptations using cross-sectional statistics and econometric techniques (e.g., Mendelsohn et al., 1994Mendelsohn et al., , 1996, and the duality-based model that uses geographic information systems combined with an economic model (e.g., Darwin et al., 1995;Darwin, 1999) 1 . Regardless of the method used, both methods assume that variations in land values reflect the welfare implication of the impacts of climate change. ...
The economic effects of climate change on agriculture have been widely assessed in the last two decades. Many of these assessments are based on the integration of biophysical and agroeconomic models, allowing to understand the physical and socio-economic responses of the agricultural sector to future climate change scenarios. The evolution of the bio-economic approach has gone through different stages. This review analyses its evolution: firstly, framing the bio-economic approach into the context of the assessments of climate change impacts, and secondly, by reviewing empirical studies at the global and European level. Based on this review, common findings emerge in both global and regional assessments. Among them, the
authors show that overall results tend to hide significant disparities on smaller spatial scales. Furthermore, due to the effects of crop prices over yield changes, several authors highlight the need to consider endogenous price models to assess production impacts of climate change. Further, major developments are discussed: the progress made since the last two decades and the recent methods used to provide insights into modeling uncertainties. However, there are still challenges to be met. On this matter, the authors take these unresolved challenges as guidelines for future research.
... This feature of CGE models, coupled with their flexibility, has led recently to their increased application to the economic assessment of climate change impacts. A growing CGE literature assesses the costs of single impact categories, e.g., Deke et al. (2002), Darwin and Tol (2001), Bosello et al. (2007) on sea-level rise; Bosello et al. (2006) on health;Tzigas et al. (1997), Darwin (1999), Ronneberger et al. (2009) on agriculture; and Calzadilla et al. (2008) on water scarcity. CGE models have been also used to investigate the interactions of multiple impacts, although the techniques are still in their infancy. ...
The present study integrates Computable General Equilibrium (CGE) modelling with biodiversity services, proposing a possible methodology for assessing climate-change impacts on ecosystems. The assessment focuses on climate change impacts on carbon sequestration services provided by European forest, cropland and grassland ecosystems and on provisioning services, but provided by forest and cropland ecosystems only. To do this via a CGE model it is necessary to identify first the role that these ecosystem services play in marketable transactions; then how climate change can impact these services; and finally how the economic system reacts to those changes by adjusting demand and supply across sectors, domestically and internationally.
... Adams, et al. (1989Adams, et al. ( , 1990Adams, et al. ( , 1993Adams, et al. ( , & 1999,Parry (1990),Tobey et al. (1992),Easterling et al. (1993),Kaiser et al. (1993),Rosengweig and Parry (1994),Darwin et al. (1995),Darwin (1999),Watson et al. (1997),Bruce et al. (1996),Reilly (1994Reilly ( & 1995,Cline (1996),Mendelsohn et al. (1994),Mendelsohn & Nordhaus (1996),Mendelsohn and Dinar (1999),Iglesias and Minguez (1997),Iglesias et al. (1999),Maddison (2000), etc., were among the first researchers to initially assessed CC impacts on agriculture in the industrial countries. ...
... As for any conceptual model, Ricardian analysis has caveats and cannot replace other kinds of analyses but rather complements other studies. In previous literature concerning Ricardian models, the absence of irrigation variables was criticized (Darwin, 1999); however, since then this question has been carefully addressed (Seo & Mendelsohn, 2008a). For example, Kurukulasuriya and Mendelsohn (2006) considered irrigation as endogenous and used a modified Heckman selection model. ...
We apply the Ricardian approach to analyse the economic impact of climate change on agriculture using the 2007World Bank
Tajikistan Living Standards Survey. The study analyses data of 2557 farm households in 166 villages across the 10 agroecological
country zones. In general, the results indicated that increasing temperature and precipitation will both be
damaging to Tajikistan agriculture and consequently to the net revenue (NR) of farmers in the medium and long term.
Regressing NR on climate parameters, household and soil variables showed that these variables have a significant impact
on the farmers’ NR per hectare. We examined the impact of the current climate on farmers’ NR per hectare, and how that
is affected by future climate scenarios: one +2.9°C warming and one 4.6°C warming scenarios. Although the analysis did
not incorporate variables such as the carbon fertilization effect, the role of technology or the change in prices in the
future, significant information for policy-making can be extracted. Tajikistan has very diverse regions in terms of
geography, population density and socio-economic situation; our results will help policy-makers to anticipate the
adaptation effort needed in different locations of the country.
... The economic data by region, sector, and commodity are from version 4E (with upgraded energy content) of the GTAP database (McDougall et al., 1998). Economic values of inputs and outputs were distributed to the land classes based on their respective shares in 1990 as derived by FARM's geographic information system (Darwin et al., 1995(Darwin et al., , 1996Darwin, 1999). These GTAP data have been enriched with financial data required by the investment theory in D-FARM (Ianchovichina, 1998). ...
Introduction The world's rate of population growth is slowing, but total population is still increasing at about 80 million per year and is expected to reach 10 billion by the middle of the 21st century (World Bank 1999). Most of this growth will take place in developing countries, particularly in Asia and Africa. These projected increases in population, along with growth in per capita incomes and associated changes in demand for agricultural commodities, are expected to increase pressures on natural resources both through the expansion of land under cultivation and through more intense use of resources already employed in agricultural production. In support of these expectations, a recent study by Evenson et al. (1999) estimates that without the development of high-yielding varieties of crops, prices for developing country consumers would likely be much higher than they are today. For example, technological advances in the cultivation of rice have reduced costly food imports by 8% and have eliminated the need to convert millions of hectares of forestland to agricultural uses, as would have been required had yields remained at 1960 levels. This evidence and the rise of food and resource prices in 2008 highlight the central role of agricultural research in ensuring sustainable rural development and food security in high-growth developing countries and in reducing the strain on forest ecosystems.
... Climate change is adding more stress to already threatened habitats, ecosystems, and species in Africa (UNDP 2004). It has affected the quality and amount of land and water resources accessible for agriculture production and other climatedependent sectors such as forestry and fisheries (Darwin 1999;Fischer et al. 2002). It is also responsible for changes in the spatial distribution of agroecological zones, habitats, and patterns of plant diseases and pests, which can have notable impacts on agriculture and food production (FAO 2007). ...
Climate change is a serious challenge for the future development of Africa, particularly the drier regions. Knowledge and awareness about climatic patterns are important for adaptation planning. Although there are many studies on farmers’ perceptions about climate change, the views of heterogeneous farm households also need to be addressed. This paper investigates the variations and similarities in the views of heterogeneous farm households about climate change. We employed a household survey (186) and interviews for data collection. Using principal component analysis and K-mean cluster analysis, we identified two household types that differ in terms of assets (human, natural and financial) and we compared their perceptions about climate change. Household-1 farmers are better off than household- 2 in terms of land area cultivated and income generated from rain fed rice. On the other hand, household-2 farmers are better off than household-1 in terms of area cultivated for maize and income generated from maize. In addition, household-2 farmers are better off than household-1 in terms of land area cultivated and income generated from irrigated rice. The findings from this study show that the two household types shared similar views with respect to rainfall and temperature patterns, as well as in the ranking of climate change drivers. However, variation was observed in the perceptions of the household types of adaptation constraints. More household-1 farmers (60%) compared to household-2 (43%) saw access to dry season farmland as a barrier for adaptation. This may be due to the fact that household-2 farmers are better off with respect to irrigated farming. Heterogeneous household perceptions about climate change reveal similarities, but differences still exist in some aspects. From a similar environment, we can see that farm household heterogeneity shows a relationship with climate change perception. Therefore, it will be important to account for diversities within our local environments when planning for climate change adaptation.
... Erratic rainfall is a major challenge facing agricultural practice in the semi-arid regions of West Africa. The quality as well as the amount of land and water resources accessible for agriculture and other climate-dependent sectors such as forestry and fisheries are affected by climate change [1,2]. Farmers are changing their agricultural practices and devising ways to modify livelihoods in light of the changing climate and other multiple stresses. ...
Soil loss is not limited to change from forest or woodland to other land uses/covers. It may occur when there is agricultural land-use/cover modification or conversion. Soil loss may influence loss of carbon from the soil, hence implication on greenhouse gas emission. Changing land use could be considered actually or potentially successful in adapting to climate change, or may be considered maladaptation if it creates environmental degradation. In semi-arid northern Ghana, changing agricultural practices have been identified amongst other climate variability and climate change adaptation measures. Similarly, some of the policies aimed at improving farm household resilience toward climate change impact might necessitate land use change. The heterogeneity of farm household (agents) cannot be ignored when addressing land use/cover change issues, especially when livelihood is dependent on land. This paper therefore presents an approach for simulating soil loss from an agro-ecosystem using multi-agent simulation (MAS). We adapted a universal soil loss equation as a soil loss sub-model in the Vea-LUDAS model (a MAS model). Furthermore, for a 20-year simulation period, we presented the impact of agricultural land-use adaptation OPEN ACCESS Land 2015, 4 608 strategy (maize cultivation credit i.e., maize credit scenario) on soil loss and compared it with the baseline scenario i.e., business-as-usual. Adoption of maize as influenced by maize cultivation credit significantly influenced agricultural land-use change in the study area. Although there was no significant difference in the soil loss under the tested scenarios, the incorporation of human decision-making in a temporal manner allowed us to view patterns that cannot be seen in single step modeling. The study shows that opening up cropland on soil with a high erosion risk has implications for soil loss. Hence, effective measures should be put in place to prevent the opening up of lands that have high erosion risk.
... The Ricardian approach also accounts for the impact of climate on the agricultural sector as a whole by including both the direct impact of climate on yields and indirect impact due to changes in inputs, crops, and other practices. It relies on cross-sectional data and inherently assumes that input and output prices remain constant over time even with climate change (Darwin 1999;Schlenker, Hanemann, and Fisher 2005;Schlenker and Roberts 2009). However, as Deschênes and Greenstone (2007) and Schlenker and Roberts (2009) note, climate change may affect crop prices by affecting world crop production. ...
We investigate the effect of crop price and climate variables on rainfed corn and soybean yields and acreage in the United States using a large panel dataset for the 1977-2007 period. Instrumental variables are used to control for endogeneity of prices in yield and acreage regressions, while allowing for spatially auto-correlated errors. We find that an increase in corn price has a statistically significant positive impact on corn yield, but the effect of soybean price on soybean yields is not statistically significant. The estimated price elasticities of corn yield and acreage are 0.23 and 0.45, respectively. Of the increase in corn supply caused by an increase in corn price, we find that 33.8% is due to price-induced yield enhancement and 66.2% is due to price-induced acreage expansion. We also find that the impact of climate change on corn production ranges from $-$7% to $-$41% and on soybean ranges from $-$8% to $-$45%, depending on the climate change scenarios, time horizon, and global climate models used to predict climate change. We show that the aggregate net impact of omitting price variables is an overestimation of the effect of climate change on corn yield by up to 9% and on soybean yield by up to 15%.
... Here, possible adaptations are embedded in the information collected regarding the farmer's behaviour, which is the main difference between this approach and the structural approach. We found two methods amongst the spatial-analogue, the Ricardian approach that estimates adaptations using cross-sectional statistics and econometric techniques (e.g., Mendelsohn et al., 1994Mendelsohn et al., , 1996, and the duality-based model that uses geographic information systems combined with an economic model (e.g., Darwin et al., 1995;Darwin, 1999) 1 . Regardless of the method used, both methods assume that variations in land values reflect the welfare implication of the impacts of climate change. ...
The economic effects of climate change on agriculture have been widely assessed in the last two decades. Many of these assessments are based on the integration of biophysical and agro-economic models, allowing to understand the physical and socio-economic responses of the agricultural sector to future climate change scenarios. The evolution of the bio-economic approach has gone through different stages. This review analyses its evolution: firstly, framing the bio-economic approach into the context of the assessments of climate change impacts, and secondly, by reviewing empirical studies at the global and European level. Based on this review, common findings emerge in both global and regional assessments. Among them, the authors show that overall results tend to hide significant disparities on smaller spatial scales. Furthermore, due to the effects of crop prices over yield changes, several authors highlight the need to consider endogenous price models to assess production impacts of climate change. Further, major developments are discussed: the progress made since the last two decades and the recent methods used to provide insights into modeling uncertainties. However, there are still challenges to be met. On this matter, the authors take these unresolved challenges as guidelines for future research.
... As for any conceptual model, Ricardian analysis has caveats and cannot replace other kinds of analyses but rather complements other studies. In previous literature concerning Ricardian models, the absence of irrigation variables was criticized (Darwin, 1999); however, since then this question has been carefully addressed (Seo & Mendelsohn, 2008a). For example, Kurukulasuriya and Mendelsohn (2006) considered irrigation as endogenous and used a modified Heckman selection model. ...
We apply the Ricardian approach to analyse the economic impact of climate change on agriculture using the 2007 World Bank Tajikistan Living Standards Survey. The study analyses data of 2557 farm households in 166 villages across the 10 agro-ecological country zones. In general, the results indicated that increasing temperature and precipitation will both be damaging to Tajikistan agriculture and consequently to the net revenue (NR) of farmers in the medium and long term. Regressing NR on climate parameters, household and soil variables showed that these variables have a significant impact on the farmers' NR per hectare. We examined the impact of the current climate on farmers' NR per hectare, and how that is affected by future climate scenarios: one +2.9°C warming and one 4.6°C warming scenarios. Although the analysis did not incorporate variables such as the carbon fertilization effect, the role of technology or the change in prices in the future, significant information for policy-making can be extracted. Tajikistan has very diverse regions in terms of geography, population density and socio-economic situation; our results will help policy-makers to anticipate the adaptation effort needed in different locations of the country.
... The United States is the world's largest producer and exporter of agricultural produce (Ashenfelter & Storchmann, 2006;Auffhammer, Ramanathan, & Vincent, 2006;Darwin, 1999;Dechenes & Greenstone, 2007;Kelly, Kolstad, & Mitchell, 2006;Mendelsohn, Nordhaus, & Shaw, 1994;Schlenker, Hanemann, & Fisher, 2006;Schlenker & Roberts, 2009;Timmins, 2006). In the 2007 Agricultural Census, over 2.2 million farms were reported in the United States (Vilsack, 2009). ...
The effects of climate change and other stressors on the agricultural sector provide proof that the need to achieve agricultural sustainability is a legitimate issue that should be addressed immediately. The ultimate financial benefits to achieving sustainability are immense. This study investigated the causes of climate change and reported how it directly and indirectly affects the agricultural sector of the Southeastern Region of the United States. We concluded that crops vary with the different adaptation strategies and with the predicted rise in temperature and fluctuation in precipitation. It is essential for producers to monitor closely their previous growing seasons. Long term investments include plant breeding, rotating crops, building infrastructure, and mitigation systems. Climate awareness and its impacts on agriculture by consumers, producers, and policymakers are essential to develop adaptation strategies to mitigate the effects of climate change.
... Global (11 regions) Agriculture, Sea-level rise Uses DART model (Klepper et al., 2003) Darwin (1999 Global (8 regions Uses GEM-E3 model (Capros et al, 1997) Literature Surveys Agrawala and Fankhauser (2008) Multiple Block et al. (2008) Ethiopia Water, Agriculture Uses IMPACT model ) Nelson et al. (2010 Global (281 regions) Water, Agriculture Butt et al. (2005Butt et al. ( , 2006 Mali Agriculture Uses MASM model Atwood et al. (2000) U.S. regional Agriculture Uses ASM model (McCarl et al., 1998 U.S. Forestry Uses FASOM model (Adams et al., 1996) Sohngen et al. (2001 Global (9 regions) Forestry Uses an optimal control model (Adams et al., 1996) Other Simulation Studies Tol (2008) Global (16 regions) Health ...
This paper offers a critical review of modeling practice in the field of integrated assessment of climate change and ways forward. Past efforts in integrated assessment have concentrated on developing baseline trajectories of emissions and mitigation scenario analyses. A key missing component in IAMs is the representation of climate impacts and adaptation responses. Through the examination of conceptual, theoretical and empirical frameworks for the analysis of climate impacts and adaptation, we identify five characteristics of an ideal IAM: regional and sectoral detail for impacts and adaptation strategies; distinct representation of the three types of adaptation—adaptation through market adjustments, protective/defensive expenditures, and adaptive/coping expenditures; intertemporal decision making under uncertainty; induced innovation in adaptation-related technologies; and connection with empirical work on impacts and adaptation. Our review of existing IAMs finds that most models are severely lacking in most of these modeling features.
... However, the preparedness requires evolving adaptive strategies to change the cropping patterns, change the farm operation timing, use of traditional crop varieties, improve water use efficiency, improve soil fertility, flexible institutional and governmental policies to suite diverse farming systems [96]. Likewise, agro-biodiversity hotspots must receive increased attention to conserve and safeguard the species of local origin [97,98]. Thus, the preparedness for the projected climate change requires building social capital at farm level. ...
In the recent past there has been concern to address the declining trends and deteriorating ecological elements and their functions in pro-ductive agricultural landscapes. The efforts to revive the ecological functions needs multiple scale approach, which include scientific under-standing, time dependent restorative activities and incorporation of wisdom of the stakeholders. Conservation initiatives linked to precision farm-ing is an apt mechanism to minimize the loss of natural resources of agricultural landscapes to maintain the complex stabilizers of ecological functions. Such an effort must address the sci-entific evaluation of the farm as "ecologically sustainable unit" with due consideration to so-cial construct at local to regional level. Sustaina-bility indices can be useful tools for evaluating the farms to isolate degradative factors and iden-tify ecologically conservative practices. This re-view will analyze certain inter-linked concepts relevant to address the sustainability issues in agro-ecology at the interface of socio-ecological perspective.
... This feature of CGE models, coupled with their flexibility, has led recently to their increased application to the economic assessment of climate change impacts. A growing CGE literature assesses the costs of single impact categories, e.g., Deke et al. (2002), Darwin and Tol (2001), Bosello et al. (2007) on sea-level rise; Bosello et al. (2006) on health;Tzigas et al. (1997), Darwin (1999), Ronneberger et al. (2009) on agriculture; and Calzadilla et al. (2008) on water scarcity. CGE models have been also used to investigate the interactions of multiple impacts, although the techniques are still in their infancy. ...
This paper contributes to the ongoing debate by addressing the economic valuation of the induced climate change impacts on European biodiversity and ecosystem services. Firstly, we evaluate the impacts of climate change on biodiversity and ecosystem services, building upon the Millennium Ecosystem Assessment (MA) conceptual framework, and encompasses the determination of the role of biodiversity in the creation of provisioning, regulating and cultural services. Secondly, we develop an integrated, hybrid valuation approach to assess the economic magnitude of the involved impacts. Finally, we extend state-of-the-art general equilibrium model by introducing a new 'ecosystem' sector into the underlying "market-based" general equilibrium assessment. The estimation results show that induced climate change impacts on biodiversity and ecosystem services involve significant welfare losses, of about 145-170 billion US$ and therefore autonomous adaptation cannot be invoked as the solution to climate change. Furthermore, the distribution of the impacts varies widely according to the nature of the ecosystem service under consideration and to the geo-climatic region. Thus, the decision of including biodiversity and ecosystem services is expected to be a key component of the future climate policy framework, along with the evaluation of exisiting mitigation and planned adaptation strategies.
... 최근 지난 한 세기간의 급격한 지구온난화로 유발 되는 이상기후징후에 대한 위급성을 깨닫고 수자원, 농업, 생명다양성, 연안, 에너지소비 등 다양한 영역에 서 그 취약성과 영향평가 연구가 진행되고 있다 (IPCC, 2001a(IPCC, , 2001bUKCIP, 2000UKCIP, , 2001Parson et al., 2003) Downing et al. (1995Downing et al. ( , 1996 (Sonka et al., 1989;Mendelsohn et al., 1994;Darwin, 1999;Thomson et al., 2005;Deschenes and Greenstone, 2006;Mendelsohn and Reinsborough, 2007 etc.). 농업분야에서 기후영향평 가의 가장 대표적인 접근법은 소위 "production func- (Tol, 2002;Joel and Sam, 2003). ...
This study provides an impact assesment of climate change on energy consumption, based on active-deal scenario. This approach assumes that the amount of electric energy consumption depends on human spontaneous acts against local (REC) has ben developed by using monthly mean temperature and monthly amount of electric energy consumption in the 6 major cities over the 19-205 period. The statistical model is utilized to estimate the past and future REEC, and to assess the economic benefits and damage in energy consumption sector. For an estimation of the future REEC, climate change scenario, which is generated by National Institute of Meteorological Research, is utilized in this study. According to the model, it is estimated that over the standard period (1999~2005), there might be economic benefits of about 31 bilion Won/year in Seoul due to increasing temperature than in the 1980s. The REC is also predicted to be gradually reduced across the Korean peninsula since the 2020s. These results suggest that Korea will gain economic benefits in the REC sector during the 21st century as temperature increases under global warming scenarios.
This chapter presents a review of the literature on land use models structured according to disaggregation of space, time and decision-makers and representing the process of land use mosaic and change. Geographical models relate land use to the properties of the land supply, its suitability for different types of use and its location. Economic models assume that land use is determined by the demand for land, influenced by a system of preferences, motivations, markets, accessibility, and population. Agronomic models do not include spatial interaction and have as a fundamental reference each plot of soil, apt to different types of culture, conditioned both by the markets and by the aptitudes of each territory unit to a certain type of culture. Spatial interaction models focus mainly the movement of flows across space constrained by the attrition of distance between origins and destinations. Finally, integrated models, join spatial interaction with land use explicitly including human behaviour in the decision-making processes and diversified land properties.
Geoenvironmentally, the northeastern Himalayan region of India is highly susceptible to geohydrological hazards due to heavy annual rainfall (varies from 236 to 324 cm), active seismotectonics, young fragmented geology, reshaping dissected geomorphology, high drainage density, and dynamic hydrological process. Apart from this, anthropogenic activities such as unplanned rapid urbanization, deforestation, and shifting agricultural practices have been increasing the rate of climate change and its adverse geohydrological impacts in terms of increasing events of cloud burst, extreme rainfall, floods, erosion, landslides, etc., during rainy season, cause great loss of environment, infrastructure, economy, lives, etc. Addressing this burning environmental problem, a geospatial technology–based case study is presented here of Kohima district, Nagaland, in the northeast Himalaya region (India). Through the development and integration of multiple geospatial modules, this reconnaissance study analyzed the climatic and monsoon hazard data catalog for the last three decades (1991–2022). Results show that the average temperature and extreme rainfall events have been increasing at the rate of 0.13 °C/year and 3 events/year, respectively, whereas the average rainfall and rainy days have been decreasing at the rate of 9.55 cm/year and 2 days/year, respectively. These rates of climate change increase with mounting elevations and are found to be relatively higher than the global average. Consequently, the existing climatic zones (comprised of humid tropical, humid subtropical, humid temperate, and humid sub-temperate) have been shifting towards higher altitudes with an average rate of 175 m/year. This trend of climate change affects the region’s ecological and hydro-meteorological processes and results in increased geohydrological hazard events during the monsoon rainy season at the rate of 8.94%/year (nine events). This rate varies at a minimum of 0.16%/year (one event) for cloud burst to a maximum of 2.58%/year (three events) for landslides, whereas floods, land creeping, and land subsidence have been increasing with a rate of 1.84%/year (two events), 2.26%/year (two events), and 2.58%/year (two events), respectively. Subsequently, the area of very high hazard zone sprawls out at 1.68% annual rate and poses great environmental concern for sustainable socioeconomic development of the region.
As a part of the Himalayan mountains, the North East Hill (NEH) region of India is geophysically dynamic and seismotectonically active since its formation about 55 million years ago with a head-on collision of the Indian plate and the Eurasian plate. The region still has been underthrusting at a rate of 4.5–5 cm/year causing the reshaping and changing of its geophysical characteristics (geology, geomorphology, relief, slope gradient, drainage system, etc.), whereas anthropogenic activities, particularly shifting cultivation and technological intervention, have caused changes or degradation of the ecological environment (air, land, water, vegetation, crop pattern, climate, wildlife, etc.). Addressing this burning geoecological problem, a geospatial technology-based case study from the Kohima district of Nagaland in the North East Hill region of India is presented here. Through the development and integration of multiple GIS modules, this reconnaissance study suggests that continuous seismic activities (about 27 seismic events/year) along tectonic faults, thrusts, and lithological shear zones have been reshaping and changing the geophysical environment, whereas the ecological environment has been changing or degrading due to decreasing natural landscape and habitats (forest area, water bodies, and shrubs) at an annual rate of 5.91 km2 (0.60%), increasing built-up area, agricultural land, and wasteland at an annual rate of 2.73 km2 (0.28%), 2.69 km2 (0.27%), and 0.49 km2 (0.05%) respectively. Results also suggest that environmental degradation results in accelerated trends of climate change (rising temperature at the rate of 0.13 °C/year, decreasing annual rainy days at the rate of 2 days/year, decreasing annual rainfall at the rate of 9.55 cm/year, mounting climatic zones at the rate of 175 m/year) and its adverse impacts (increasing extreme rainfall events at the rate of 3 events/year and causing cloud burst, erosion, landslides, and floods) in the region.
The Vietnamese government is concerned with long‐term food security due to the rising demand for food and potential climate‐induced conversion of areas under food production. This article is among the first studies which examine the climate‐induced uptake of crop substitution and its likely impact on the national target of maintaining food areas to sustain food security. In contrast to most crop choice analyses which obtain cross‐household evidence using a Multinomial Logit model, we model within household competition across alternative uses of land using a Fractional Multinomial Logit model. Our empirical findings suggest that Vietnamese farmers have adapted to the changing climate by selecting different crops. Increases in winter and summer temperatures mean that farmers are more likely to substitute cereals for others. Farmers choose annual industrial crops in locations with warmer springs and autumns. The choice of perennial industrial crops is sensitive to spring and autumn temperatures. Precipitation has small impacts on land use choice. The projected climate changes are not likely to jeopardize the national target of maintaining 40 percent of farmland under food production. However, we expect projected climate changes to result in large shifts from cereals to annual industrial crops in the main rice bowl of Vietnam.
A sequel to Global Trade Analysis: Modeling and Applications (Cambridge University Press, 1996, edited by Thomas W. Hertel), this new volume presents the technical aspects of the Global Trade Analysis Program's global dynamic framework (GDyn) and its applications within important global policy issues. The book covers a diverse set of topics including trade reform, growth, investment, technology, demographic change and the environment. Environmental issues are particularly well-suited for analysis with GDyn, and this volume covers its uses with climate change, resource use and technological progress in agriculture. Other applications presented in the book focus on integration issues such as rules governing foreign investment, e-commerce regulations, trade in services, harmonization of technical standards, sanitary and photo-sanitary regulations, streamlining of customs procedures, and demographic change and migration.
A sequel to Global Trade Analysis: Modeling and Applications (Cambridge University Press, 1996, edited by Thomas W. Hertel), this new volume presents the technical aspects of the Global Trade Analysis Program's global dynamic framework (GDyn) and its applications within important global policy issues. The book covers a diverse set of topics including trade reform, growth, investment, technology, demographic change and the environment. Environmental issues are particularly well-suited for analysis with GDyn, and this volume covers its uses with climate change, resource use and technological progress in agriculture. Other applications presented in the book focus on integration issues such as rules governing foreign investment, e-commerce regulations, trade in services, harmonization of technical standards, sanitary and photo-sanitary regulations, streamlining of customs procedures, and demographic change and migration.
Most environmental statutes passed since 1970 have endorsed a pragmatic or 'precautionary' principle under which the existence of a significant risk is enough to trigger regulation. At the same time, targets of such regulation have often argued on grounds of inefficiency that the associated costs outweigh any potential benefits. In this work, Jason Johnston unpacks and critiques the legal, economic, and scientific basis for precautionary climate policies pursued in the United States and in doing so sheds light on why the global warming policy debate has become increasingly bitter and disconnected from both climate science and economics. Johnston analyzes the most influential international climate science assessment organizations, the US electric power industry, and land management and renewable energy policies. Bridging sound economics and climate science, this pathbreaking book shows how the United States can efficiently adapt to a changing climate while radically reducing greenhouse gas emissions.
This study used the Ricardian analytical framework to examine the relative importance of climate normals (average long-term temperature and precipitation) in explaining net revenue per hectare (NRh) for cocoa farms in Nigeria under supplementary irrigated
and rainfed conditions. A farm-household survey involving 280 cocoa farmers across seven cocoa-producing states in Nigeria was carried out. Net revenue per cocoa hectare was regressed on climate, household socioeconomic characteristics and other control
variables. The results indicate high sensitivity of NRh to climate normals in Nigeria, depending on whether cocoa farms are supplementary irrigated or not. On the average,
annual increases in temperature and decreasing precipitations are associated with NRh losses for rainfed farms, whereas it increases for irrigated cocoa farms. Projections of future climate change impacts using different climate scenarios (i.e., 6 CORDEX Regional Climate Models [RCMs] Ensemble between 2036-2065 and 2071-2100, and
a 2.50 C increase in temperature only, a 5% decrease in rainfall only, and a uniform 2.50 C increase in temperature and a 5% reduction in precipitation from 2050-2100), suggest a wide range of outcomes on NRh for both rainfed and supplementary irrigated cocoa farms. Specifically, the various climate scenarios predict a fall in NRh for rainfed farms, compared to net gains for irrigated cocoa farms. This clearly shows irrigation as an important adaptation strategy by farmers in Nigeria to reduce the harmful effects of climate change.
This study analyzes the economic impact of climatic variations on rice cultivation in Côte d'Ivoire. It attempts to respond to the lack of academic study at the national level and then to introduce a new approach that corrects the bias of the traditional Ricardian approach. We estimate an endogenous switching regression model to control for the effect of irrigation using a survey data from a national sample of 895 rice farmers. The results of our estimates show that Ivorian rice cultivation is significantly affected by variations and dispersion of rainfall. The elasticity of farmers’ net income in relation to rainfall is 0.47 in rain-fed systems and 2.89 in irrigated systems. A decrease in the annual rainfall volume affects negatively the yield of farms both in rain-fed and irrigated systems. However, irregular rainfall or greater annual dispersion of precipitation has a negative impact only on the yield of rain-fed farms. Indeed, irrigation practices make it possible to respond effectively to highly dispersed precipitation during the year. The results suggest that farmer training, support services, and irrigation practices are the relevant options to better adapt rice farming to climatic variations.
Considerable progress in understanding how global climate change is likely to affect agricultural production and forest resources has been made in recent years. In the recent Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change’s (IPCC) Working Group (WG) II (IPCC, 2001), agriculture was combined in a chapter with other, less managed terrestrial and aquatic ecosystems in order to assess its response to climate change. This was intended to facilitate comparison of the impacts of climate change on basic biological and ecological processes across ecosystems (including agroecosystems and forest ecosystems) in a consistent manner. However, agroecosystems are fundamentally different from less managed ecosystems such as wetlands, tundra, and savannas: they produce economically valuable goods and services within a system of clear and enforceable property rights. Such greatly complicates understanding of their response to climate change because of intense human intervention into climate-ecosystem interactions and because responses of these ecosystems to climate change can have direct and immediate economic impacts. Hence, I focus on agriculture in this chapter.
For most of human history, agriculture accounted for the dominant share of GDP and employed most labor. Johnson (1997) estimates that in 1800 about 75–80 percent of the labor force in developed nations were engaged in farming, and only 11 percent of the population lived in urban settings (cities with more than 5000 inhabitants). For some of the world, the industrial revolution changed everything. During the 19th century, labor productivity in agriculture (and everything else) increased sharply. By 1980 a unit of labor produced 50–100 times as much wheat or corn as compared to 1800. Productivity growth initially came from machinery replacing human and animal work effort. Since 1930, productivity gains came mostly from development of high-yielding crop species and adoption of intensive farming practices, including use of commercial fertilizers and pesticides. Crop yields (output per unit of land area) increased roughly threefold in the second half of the 19th century, both in the developed and in the developing world. This “Green Revolution” has been attributed more to the efforts of a single man, Norman Borlaug, than to the entrepreneurial efforts of all the world’s farmers.
Glossary
Definition of the Subject
Introduction
Issues
Total Costs
Marginal Costs
Policy Implications
Future Directions
Acknowledgments
Bibliography
Following the release of the IPCC Fifth Assessment Report, and realizing the likely impact on California water and agricultural sectors, we review key concepts in the climate change lexicon in the context of California agriculture. There are a range of modeling approaches used to study the benefits of water basin- and/or farm-level adaptations, including hydrological, crop simulation, economic programming, and econometric models. Given the central role of farmer and institutional responsiveness, how do recent agro-economic assessments suggest that specific adaptations may improve economic welfare and reduce vulnerability? What is economically efficient adaptation in the short and long-run? What are the limits to the agricultural sector’s adaptive capacity?
Climate change is likely to have significant impacts on the agricultural sector to which farmers will have to adapt. While agriculture is a significant contributor to greenhouse gas emissions, it is also a source of carbon storage in soils. This report examines the economic and policy issues related to the impacts of climate change on agriculture and adaptation responses and to the mitigation of greenhouse gases from agriculture. It outlines research undertaken and underway in other national and international research agencies. It also highlights some of the knowledge gaps on the impacts of climate change on food production and the uncertainties of those impacts in a global context that warrant further research efforts. In particular, the report analyses marginal abatement cost curves, which show the relative costs of achieving reductions in greenhouse gas emission through the implementation of different actions in the agricultural sector. The aim of the report is to help guide policy makers in the design of policies to address climate change issues in agriculture.
This section introduces the main methodologies used by the climate change impact science to assess economically the consequences of climate change. Furthermore it presents the main findings of this literature focusing specifically on possible future economic consequences of climate change in the Mediterranean area emphasizing the new knowledge in this field brought by the CIRCE project. The robust finding of the literature points out a low economic vulnerability of Euro-Mediterranean countries (with losses ranging from −0.25 to −1.4% of GDP for extreme temperature scenarios or even slight gains), and a higher vulnerability of North African and Eastern-Mediterranean countries (of roughly 2% of GDP by the mid of the century). Against this background the CIRCE project proposes one of the first attempts to perform a detailed integrated impact assessment exercise focusing on the Mediterranean area. With the IPCC A1B SRES scenario as reference, impacts related to energy demand, sea-level rise and tourism, have been economically assessed by a general equilibrium model. The Mediterranean as a whole loses 1.2% of GDP with the Northern-Mediterranean countries clearly less vulnerable than the Southern-Mediterranean ones. Among the former the average loss in 2050 is 0.5% of GDP, while among the latter this more than doubles. Particularly adversely affected are Cyprus, Albania and the Eastern Mediterranean region (−1.6, −2.4, −1.5% of GDP respectively in 2050). In terms of impact types, tourism and sea-level rise are clearly the most threatening, while GDP impacts induced by demand re-composition of energy use is less of an issue and often positive.
Estimates of the marginal damage costs of carbon dioxide emissions suggest that, although climate change is a problem and some emission reduction is justified, very stringent abatement does not pass the cost-benefit test. However, current estimates of the economic impact of climate change are incomplete. Some of the missing impacts are likely to be positive and others negative, but overall the uncertainty seems to concentrate on the downside risks and current estimates of the damage costs may have a negative bias. The research effort on the economic impacts of climate change is minute and lacks diversity. This field of study should be strengthened, with a particular focus on the quantification of uncertainties; estimating missing impacts, estimating impacts in developing countries; interactions between impacts and higher-order effects; the valuation of biodiversity loss; the implications of extreme climate scenarios and violent conflict; and climate change in the very long term. I discuss these particular gaps in research, and speculate on possible sign and size of the impacts of climate change.
The ability to test dynamic interactions between agroclimatic factors and field management is critical for policy makers assessing economically efficient investment options. This study produced a robust set of linked modeling tools and a coherent set of linked databases to facilitate the evaluation of dynamic interactions of high-resolution agroclimatic and field management factors affecting crop growth and development. It allowed interactions with a detailed general equilibrium model to include and test the constraints of realistic socioeconomic factors on production and welfare.
For Latin America and the Caribbean the projected yield shocks on wheat, maize, and soybean generated by the AZS platform could result in substantial negative economic impacts in the aggregate—particularly for Argentina and Brazil, which are heavily invested in the focus crops of this study.
The findings have several major policy implications.
1. The estimated negative impacts could be significantly larger than what has previously been predicted for Latin America and the Caribbean—and for precisely the two major agricultural producers (Brazil and Argentina) expected to play a major role in the global food supply chain. This should be a red flag for policy makers deciding on both mitigation and adaptation investments to combat global warming via greenhouse gas emissions reductions in the LCR countries and globally.
2. Despite the projected severity of climate change impacts for maize, soybean, and wheat, some findings were encouraging. For example, the study simulated the response to the use of simple adaptation strategies such as the use of improved varieties, change of sowing dates, and modest irrigation and found that although these strategies did not overcome the projected damages from climate change, they did reduce the yield shocks to a significant degree for some crops. Policy-relevant interventions related to adaptation strategies include:
a. Allocating adequate research and development (R&D) resources to generate improved and adapted plant varieties—currently estimated to take at least a decade and to cost US$5–7 million for each new variety).
b. Expanding high-efficiency irrigation to overcome moisture limitation during grain-filling, a major yield-limiting factor in the region for maize, soybean, and wheat. Less than 6% of Brazil‗s agriculture and less than 2% of Argentina‗s are irrigated yet these are the two countries projected to be hit most severely by climate change and moisture limitations for their major commodity crops.
3. One surprise from the study is the estimated positive impact of climate change on rice productivity in the region, which highlights to the potential for increasing rice production, especially since rice now feeds about 3 billion people worldwide, and global supplies expected to tighten significantly in coming years. The key policy-relevant issues for rice futures in LCR include:
a. Raising the current low yield levels of irrigated rice in LCR. Most of the region‗s rice is produced in the rainy season to ensure adequate supplies of water for most of the growing season. The yield plateau for rainy season rice is about 5 tons per hectare because sunlight is often reduced by clouds. If the rice could be produced during the dry season with adequate water capture and irrigation, the rice yield plateau could rise to between 8 and 12 tons per hectare.
b. Ensuring adequate water supplies and water control in the landscape. Most of the region‗s countries have plans to expand hydroenergy as a part of national low-carbon growth strategies. Ensuring that new hydroenergy programs also include irrigation would enhance the adaptation capacity for agriculture. Policies that promote multipurpose hydro would also permit relocating rice and other agriculture in coastal and low-lying areas to areas less vulnerable to major floods and rising sea levels—an adaptation-mitigation win-win.
c. Reducing the environmental footprint of rice. Because flooded rice is a major source of methane (a powerful greenhouse gas), adequate R&D funding and policy instruments will be needed to catalyze public-private partnerships to develop and extend rice field management strategies and the use of improved biological and new-generation ―high efficiency-low emissions‖ synthetic fertilizers.
4. The study finding that moisture limitations are likely to strongly influence the reduction of future crop yields further emphasizes the importance of current discussions at the global level to include soil carbon sequestration in any post-2012 climate agreement. The available empirical evidence for a wide variety of soil and agroecosystem types confirms that an increase in soil carbon can also result in significant improvements in soil moisture holding capacity and thereby reduce the need for irrigation. Appropriate policy and market signals are urgently needed to encourage land-based carbon sequestration to facilitate better soil and water use and result in more resilient agroecosystems. Sequestration above and below ground could also increase rural income opportunities through more diverse ecosystem services.
5. The AZS estimates of climate impacts on agricultural productivity at relatively high spatial resolution could provide key information to reduce uncertainty for risk-reducing insurance and microfinance instruments. Insurance (risk-sharing) is likely to be important in future adaptation decisions, whether through traditional indemnity-based insurance or through other options that may be more suitable for climate-based insurance, such as index-based schemes, weather derivatives, and catastrophe bonds.
6. If a large share of world agriculture faces similar impacts to the AZS projections for the region and the four crops studied, initial economic simulations project higher food prices than the baseline. So, investments and grants are urgently needed to expand the current portfolio of crops in the AZS platform to include subsistence crops, biofuels crops, and horticultural crops beyond wheat, soybean, maize, and rice. This will allow more robust assessments of the intrasectoral impacts and economic implications in the region and across regions.
The impacts of climate change on agriculture are projected to be significant in coming decades, so response strategies and their likely costs should be evaluated now. Robust crop models are needed to estimate those impacts on agricultural productivity regionally, nationally, and even sub- nationally. But existing crop–climate change modeling platforms are not easily accessible to most stakeholders in developing countries. So there is less testing of those models than there might be, and there are fewer opportunities for further improvements based on local tests and emerging data.
That is why this study produced an open-access crop-climate-economic impact modeling platform for Latin America and the Caribbean that can be extended to other regions—and modified and improved by users as new crop, climate, and economic datasets become available. The new platform projects the likely impacts of agroclimatic factors on crop productivity on the basis of climate projections from two general circulation models and couples it with an economic model to derive and evaluate a range of climate-change scenarios and likely agricultural productivity and economic impacts over the next several decades.
The open-access modeling platform developed in this study, the agroecological zone simulator (AZS), provides biophysical representations of crop growth as a function of agroclimatology and crop-field management. It is based on the biophysical model applications (BioMA) approach used by the European Commission Joint Research Centre to investigate climate-change impacts in the EU. The AZS simulations used:
The baseline climate (1989 to today) re-sampled to 0.25 degree grid cells (25 kilometers at the horizon).
Two general circulation models—the U.K. Met Office‘s Hadley3 model and the National Center for Atmospheric Research (NCAR) model.
Two special report on emissions scenarios (SRES), A1b and B1, to represent respectively a high scenario (business as usual) and low scenario (near carbon dioxide stabilization at 550 parts per million).
Two time horizons for simulating risks to crop production, with little time for adaptation (2020) and with time for adaptation (2050).
The role of adaptation in impact assessment and integrated assessment of climate policy is briefly reviewed. Agriculture in the US is taken as exemplary of this issue. Historic studies in which no adaptation is assumed (so-called "dumb farmer") versus farmer-agents blessed with perfect foresight (so-called "clairvoyant farmer") are contrasted, and considered limiting cases as compared to "realistic farmers." What kinds of decision rules such realistic farmer-agents would adopt to deal with climate change involves a range of issues. These include degrees of belief the climate is actually changing, knowledge about how it will change, foresight on how technology is changing, estimation of what will happen in competitive granaries and assumptions about what governmental policies will be in various regions and over time. Clearly, a transparent specification of such agent-based decision rules is essential to model adaptation explicitly in any impact assessment. Moreover, open recognition of the limited set of assumptions contained in any one study of adaptation demands that authors clearly note that each individual study can represent only a fraction of plausible outcomes. A set of calculations using the Erosion Productivity Impact Calculator (EPIC) crop model is offered here as an example of explicit decision rules on adaptive behavior on climate impacts. The model is driven by a 2xCO_2 regional climate model scenario (from which a "mock" transient scenario was devised) to calculate yield changes for farmer-agents that practice no adaptation, perfect adaptation and 20-year-lagged adaptation, the latter designed to mimic the masking effects of natural variability on farmers' capacity to see how climate is changing. The results reinforce the expectation that the likely effects of natural variability, which would mask a farmer's capacity to detect climate change, is to place the calculated impacts of climate changes in two regions of the US in between that of perfect and no adaptation. Finally, the use of so-called "hedonic" methods (in which land prices in different regions with different current average climates are used to derive implicitly farmers' adaptive responses to hypothesized future climate changes) is briefly reviewed. It is noted that this procedure in which space and time are substituted, amounts to "ergodic economics." Such cross-sectional analyses are static, and thus neglect the dynamics of both climate and societal evolution. Furthermore, such static methods usually consider only a single measure of change (local mean annual temperature), rather than higher moments like climatic variability, diurnal temperature range, etc. These implicit assumptions in ergodic economics make use of such cross-sectional studies limited for applications to integrated assessments of the actual dynamics of adaptive capacity. While all such methods are appropriate for sensitivity analyses and help to define a plausible range of outcomes, none is by itself likely to define the range of plausible adaptive capacities that might emerge in response to climate change scenarios.
The main objective of the study was to assess climate change and its geohydrological impacts on non-monsoon crop pattern at watershed level through GIS development on climate informatics, land use informatics, hydro-informatics and agro-informatics. The Dabka watershed constitutes a part of the Kosi Basin in densely populated Lesser Himalaya, India in district Nainital has been selected for the case illustration. This reconnaissance study analyzed the climatic database for last three decades (1982–2012) and estimates that the average temperature and evaporation loss have been rising with the rate of 0.07 °C/year and 4.03 mm/year respectively whereas the average rainfall has been decreasing with the rate of 0.60 mm/year. These rates of climate change increasing with mounting elevations. Consequently the existing micro climatic zones (sub-tropical, temperate and moist temperate) shifting towards higher altitudes and affecting the favorable conditions of the land use pattern and decreased the eco-friendly forest and vegetation cover. The land use degradation and high rate of deforestation (0.22 km2 or 1.5%/year) leads to accelerate several hydrological problems during non-monsoon period (i.e. decreasing infiltration capacity of land surface, declining underground water level, drying up natural perennial springs and streams, decreasing irrigation water availability etc.). In order to that the non-monsoon crops yield has been decreasing with the rate of 0.60% each year as the results suggest that the average crop yield is just about 58 q/ha whereas twenty five to thirty year back it was recorded about 66 q/ha which is about 12% higher (8 q/ha) than existing yield. On the other hand the population increasing with the growth rate of 2% each year. Therefore, decreasing crop yield and increasing population raised food deficiency problem and the people adopting other occupations which ultimately affecting rural livelihood of the Himalaya.
The potential economic and agronomic impacts of gradual climate warming are examined at the farm level. Three models of the
relevant climatic, agronomic, and economic processes are developed and linked to address climate change impacts and agricultural
adaptability. Several climate warming scenarios are analyzed, which vary in severity. The results indicate that grain farmers
in southern Minnesota can effectively adapt to a gradually changing climate (warmer and either wetter or drier) by adopting
later maturing cultivars, changing crop mix, and altering the timing of field operations to take advantage of a longer growing
season resulting from climate warming.
Early evaluations of the effects of climate change on agriculture, which did not account for economic adjustments or consider the broader economic and environmental implications of such changes, overestimated the negative effects of climate change. This report, which highlights ERS research, focuses on economic adaptation and concludes there is considerably more sectoral flexibility and adaptability than found in other analyses. The report frames the discussion of economic adjustments within the context of global agricultural environmental sustainability.
Global climate change from increases in atmospheric carbon dioxide and other trace gases is an issue of international concern. Adverse climate conditions are expected to reduce crop yields and alter the demand for and supply of water. These potential adjustments imply economic costs to agriculture and its constituents. This paper explores possible economic implications for U.S. agriculture, with particular reference to the West. Results from a series of spatial equilibrium model analyses suggest that climate change is not a food security issue for the United States. However, regional adjustments in agricultural production and associated resource use are expected. This implies additional pressure in rural communities. Environmental quality reductions are also likely.
This paper challenges the hypothesis that negative yield effects in key temperate grain producing regions of the world resulting from global climate change would have a serious impact on world food production. Model results demonstrate that even with concurrent productivity losses in the major grain producing regions of the world, global warming will not seriously disrupt world agricultural markets. Country/regional crop yield changes induce interregional adjustments in production and consumption that serve to buffer the severity of climate change impacts on world agriculture and result in relatively modest impacts on world agricultural prices and domestic economies.
In this paper we investigate the potential production and implications of a global biofuels industry. We develop alternative approaches to consistently introduce land as an economic factor input and in physical terms into a computable general equilibrium framework. The approach allows us to parameterize biomass production consistent with agro-engineering information on yields and a "second generation" cellulosic biomass conversion technology. We explicitly model land conversion from natural areas to agricultural use in two different ways: in one approach we introduced a land supply elasticity based on observed land supply responses and in the other approach we considered only the direct cost of conversion. We estimate biofuels production at the end of the century could reach 221 to 267 EJ in a reference scenario and 319 to 368 EJ under a global effort to mitigate greenhouse gas emissions. The version with the land supply elasticity allowed much less conversion of land from natural areas, forcing intensification of production, especially on pasture and grazing land, whereas the pure conversion cost model led to significant deforestation. These different approaches emphasize the importance of somehow reflecting the non-market value of land more fully in the conversion decision. The observed land conversion response we estimate may be a short turn response that does not fully reflect the effect of long run pressure to convert land if rent differentials are sustained over 100 years.
The authors measure the economic impact of climate on land prices. Using cross-sectional data on climate, farmland prices, and other economic and geophysical data for almost 3,000 counties in the United States, they find that higher temperatures in all seasons except autumn reduce average farm values, while more precipitation outside of autumn increases farm values. Applying the model to a global-warming scenario shows a significantly lower estimated impact of global warming on U.S. agriculture than the traditional production-function approach and, in one case, suggests that, even without carbon dioxide fertilization, global warming may have economic benefits for agriculture. Copyright 1994 by American Economic Association.
The authors measure the economic impact of climate on land prices. Using cross-sectional data on climate, farmland prices, and other economic and geophysical data for almost 3,000 counties in the United States, they find that higher temperatures in all seasons except autumn reduce average farm values, while more precipitation outside of autumn increases farm values. Applying the model to a global-warming scenario shows a significantly lower estimated impact of global warming on U.S. agriculture than the traditional production-function approach and, in one case, suggests that, even without carbon dioxide fertilization, global warming may have economic benefits for agriculture. Copyright 1994 by American Economic Association.
A global assessment of the potential impact of climate change on world food supply suggests that doubling of the atmospheric carbon dioxide concentration will lead to only a small decrease in global crop production. But developing countries are likely to bear the brunt of the problem, and simulations of the effect of adaptive measures by farmers imply that these will do little to reduce the disparity between developed and developing countries.
Climate change could have far‐reaching effects on agriculture, trade patterns, development and food security. This article examines quantitatively the impact of climate change on food production and numbers at risk of hunger, allowing for factors such as latitude and farming practice. Globally, a doubling of atmospheric carbon dioxide (CO2) level may lead to a small to moderate decrease in food production, but developing countries would bear the brunt of the consequences. To prevent widespread hunger, the agricultural industry should develop management programmes for hot and dry conditions, in conjunction with measures to slow the growth of the human population and reduce emissions of greenhouse gases.
This study uses recent GCM forecasts, improved plant science and water supply data and refined economic modeling capabilities to reassess the economic consequences of long-term climate change on U.S. agriculture. Changes in crop yields, crop water demand and irrigation water arising from climate change result in changes in economic welfare. Economic consequences of the three GCM scenarios are mixed; GISS and GFDL-QFlux result in aggregate economic gains, UKMO implies losses. As in previous studies, the yield enhancing effects of atmospheric CO2 are an important determinant of potential economic consequences. Inclusion of changes in world food production and associated export changes generally have a positive affect on U.S. agriculture. As with previous studies, the magnitude of economic effects estimated here are a small percentage of U.S. agricultural value.
This paper explains a Ricardian method which compares actual farmer behavior across different climates. The method incorporates farmer's adaptation because it captures the outcome of each farmer matching his behavior to local climate conditions. This paper explores a new application of the Ricardian method capturing how climate effects both the per acre value of farms and how much land is farmed. These empirical relationships are used to predict the agricultural impacts of simple climate warming scenarios.
A basic premise of ecological economics is that the world economy is embedded in and dependent upon Earth's ecosystem. Because land is a basic source of mass and energy throughput in all terrestrial ecosystems, land use and cover represents an integrating element in ecological economics. We have developed a global model that captures this concept. We illustrate this concept's usefulness by showing how global changes in climate, human populations, and international trade policies might affect tropical forests. Results from our scenarios indicate that such changes would likely have adverse effects on the health and integrity of tropical forest ecosystems. Results from our scenarios also indicate that forest depletion in Southeast Asia can be correlated with numerous economic indicators. Whether the correlation with a particular economic variable is positive or negative depends on the global change scenario. This merely reflects the fact that interactions between economic and ecological phenomena are complex. Modeling capabilities can be expanded by adding economic and ecological detail, including more material on throughput, and developing methods for simulating dynamic analyses.
We present a high-resolution global data base of animal population densities and associated methane emission. Statistics on animal populations from the Food and Agriculture Organization and other sources have been compiled. Animals were distributed using a 1° resolution data base of countries of the world and a 1° resolution data base of land use. The animals included are cattle and dairy cows, water buffalo, sheep, goats, camels, pigs, horses and caribou. Published estimates of methane production from each type of animal have been applied to the animal populations to yield a global distribution of annual methane emission by animals. There is large spatial variability in the distribution of animal populations and their methane emissions. Emission rates greater than 5000 kg CH4 km−2 yr−1 are found in small regions such as Bangladesh, the Benelux countries, parts of northern India, and New Zealand. Of the global annual emission of 75.8 Tg CH4 for 1984, about 55% is concentrated between 25°N and 55°N, a significant contribution to the observed north-south gradient of atmospheric methane concentration. A magnetic tape of the global data bases is available from the authors.
GEMPACK is a suite of general-purpose economic modelling software especially suitable for general and partial equilibrium models. It can handle a wide range of economic behaviour and also contains a versatile method for solving intertemporal models. GEMPACK provides software for calculating accurate solutions of an economic model, starting from an algebraic representation of the equations of the model. These equations can be written as levels equations, linearized equations or a mixture of these two. The software provides a range of utility programs for handling the economic data base and the results of simulations, and is fully documented from a user's point of view. GEMPACK is used to implement and solve a number of economic models including several single-country models (of which the ORANI model of Australia is perhaps the best known), multi-country trade models, regional models and intertemporal (or dynamic) models. GEMPACK runs on a wide variety of computers including PCs, workstations and mainframes. This paper gives an overview of the current release of GEMPACK (Release 5.1, April 1994). Included are descriptions of
the algebra-like language used to describe and document the equations of an economic model
the operation of the pre-processor TABLO which converts the equations of the model to a form suitable for computing solutions of the model
the solution methods used for producing accurate solutions of the model
the facilities for specifying and carrying out simulations, including the options for varying the choice of endogenous and exogenous variables and the variables shocked
the condensation facility which makes it possible to solve very large models
the utility programs for assisting in managing the data bases on which models are based
the different versions of GEMPACK and the machines on which they run.
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