Search results

This paper aims to assess the economic effects of climate change on the Mediterranean’s irrigated agriculture and how the adoption of alternative crop varieties adapted to the expected length of the growing season can be an effective adaptation measure.

A case study of two irrigation areas in Southern Portugal is used to assess the response to climate change impacts on crop yields and irrigation requirements, and an agricultural supply model is calibrated using a positive mathematical programming (PMP) approach was developed.

Climate change reduces crop yields and causes a slight decrease in irrigation requirements, which could allow an increase in the irrigated area. However, positive impacts on rural areas regarding employment and investment are not expected. The adoption of adaptation measures based on alternative crop varieties, which could maintain crop yields at current levels, increases dramatically the economic value of water and mitigates losses in farm income.

The impacts on output and input market prices, as well as other biophysical impacts (for instance, CO₂ and water availability), are important in understanding the effects of climate change on irrigated agriculture, but they were not considered in this study. While this may be a limitation, it can also be a stimulus for further research.

This is an empirical paper, whose results contribute to improving knowledge about the effects of climate change on irrigated agriculture in Mediterranean areas, namely, its economic impacts on returns and the use of agricultural resources (land, water, labour and capital). Other practical implications of the paper are associated with the methodological approach, which provides a framework able to deal with the complexity and multidimensional effects of climate change.

The results of the paper provide important information for scientists, politicians and other stakeholders about the design of more effective adaptation measures able to mitigate the effects of climate change.

Crop yields and irrigation requirements were previously calculated based on data generated by the regional climate models. This is the first time that an application is developed for Portugal. Two distinct profiles of irrigation areas were studied and a large set of crops was considered, which is not common in the existing studies. To specify the PMP approach used to calibrate the agricultural supply model, exogenous crop-specific supply elasticities were estimated through a least square model, which is not common in previous studies.

Estimating parameters of constrained optimization models in a consistent way requires a different set of methods than what is available in a typical econometric toolkit. We identify three complications likely to arise in this context, and suggest solutions to those complications: (i) the bi-level programming character, (ii) ill-posedness, and (iii) derivation of estimator properties. The solutions suggested involve a combination of numerical techniques and utilization of out-of-sample information through Bayesian techniques. The proposed framework is also suitable for typical empirical problems arising in trade analysis such as the estimation of trade equilibrium models and data balancing exercises.

The main aim of this study is to investigate the impact of climate change and water salinity on farmer’s income risk with future outlook mitigation. Salinity and climate change are a threat to agricultural productivity worldwide. However, the combined effects of climate change and salinity impacts on farmers' income are not well understood, particularly in developing countries.

The response-yield function and general maximum entropy methods were used to predict the impact of temperature, precipitation and salinity on crop yield. The target minimization of total absolute deviations (MOTAD)-positive mathematical programming model was used to simulate the impact of climate change and salinity on socioeconomic and environmental indicators. In the end, a multicriteria decision-making model was used, aiming at the selection of suitable climate scenarios.

The results revealed that precipitation shows a significantly decreasing trend, while temperature and groundwater salinity (EC) illustrate a significantly increasing trend. Climate change and EC negatively impact the farmer's income and water shadow prices. Maximum reduction in income and water shadow prices was observed for A2 scenario (−12.4% and 19.4%) during 2050. The environmental index was the most important, with priority of 43.4% compared to socioeconomic indicators. Subindex amount of water used was also significant in study area, with 28.1% priority. The technique for order preference by similarity to ideal solution ranking system found that B1 was the best climatic scenario for adopting climate change adaptation in the research region.

In this study, farmers' income threats were assessed with the aspects of different climate scenario (A1, A1B and B1) over the horizons of 2030, 2040 and 2050 and three different indicators (economic, social and environmental) in Northwestern region of Pakistan. Only in arid and semiarid regions has climate change raised temperature and reduced rainfall, which are preliminary symptoms of growing salinity.

The purpose of this paper is to contribute to land redistribution policy which is presently not only one of the most defining political and development issues, but also perhaps the most difficult in South Africa.

The paper develops a programming model for farm‐level land‐use changes and output supply response to estimate the effects of agricultural land tax in South Africa. The modeling approach is based on baseline statistics from a descriptive analysis.

The results indicate that changes in land use and output supply response are marginal. The highest effects are observed on irrigated areas of sunflower seed (0.23 percent) and wheat (0.17 percent). This results to declines in supply of 0.07 percent for sunflower seeds; 0.06 percent for wheat; 0.04 percent for soya beans; 0.03 percent for each of white maize and sorghum; and 0.02 percent for yellow maize production. Therefore, levying a land tax may discourage investment on irrigation facilities and consequently irrigated farming.

The programming modeling approach captures the significant differences in the farm characteristics and the overarching profit‐maximizing behaviour of farmers, which an econometric approach may not easily capture.

The purpose of this paper is to test the impact of the soybean rejuvenation plan and the subsidy on farmers' land allocation decisions, which may reference policy adjustment from a micro perspective.

The paper develops a multi-objective optimized programming model on farm-level, which simulated the land-use changes, as well as the resulting changes in benefits of the rational “typical farm”. The simulation scenarios include changes in subsidy policy and production efficiency, and the baseline scenario was the production status in 2018.

The results show that an increase in soybean producer subsidy will encourage farmers to allocate more land for soybean planting, which can be considered as a policy tool in promoting soybean production in China. Besides, the effect of subsidy in adjusting soybean acreage for farms is further affected by external conditions such as production technology (such as breeding technology, pesticide and fertilizer application efficiency). Meanwhile, large-scale farms show more significant land adjustments when facing changes in policies and external conditions.

The value of this paper is to simulate the effects of soybean policy and subsidy change on farmers' land-allocation decisions through a multi-objective farmer decision-making model, which provides a micro perspective to understand the implementation effect of the soybean revitalization plan.

The purpose of this paper is to examine the grain production implications of alternative designs for China’s grain subsidy policy. In particular, the authors examine three subsidy designs including area-based subsidy, quantity-based subsidy and production-cost-based subsidy.

To carry out the analysis, the authors develop a Chinese agricultural sector model (CASM) and an econometric, policy action–farmer response summary model. The CASM is used under a wide variety of subsidy level and basis experiments to generate pseudo data on farmer reactions to subsidies. Then a summary function model was estimated over those pseudo data that quantitatively summarized modeled farmer responses to different grain subsidy schemes. In turn, the summary functions were used to optimize the subsidy level such that it maximized grain production both within and across the area-based, quantity-based and cost-based subsidies. Regional implications were also developed.

The authors found that the production-quantity-based subsidy is the most cost-effective in stimulating grain production among the subsidy schemes. The authors also argue that scheme complies with WTO regulations regarding product-specific support. The authors found that the areas where grain production was most affected were the traditional grain-producing regions.

To the authors’ knowledge the authors have not seen a study of the Chinese grain subsidy program context that examined the effects of alternative subsidy schemes, nor one that developed estimates of the optimal subsidy level. In addition, the methodology is unique employing bottom-up, regionally disaggregated, sector modeling coupled with an aggregate pseudo data based summary function approach providing a new, original approach for analyzing agricultural policy design.

Increasing environmental concerns have placed the need for an enhanced water resources management on the policy agenda. In this context, a restrictive regulation of water withdrawals for irrigation has gained in importance. The purpose of this paper is to investigate how a reduction in water quotas and increased water prices affect risk‐efficient crop choices and the related economic implications for northern German farmers.

The authors apply a whole‐farm risk programming approach to a typical arable farm in northern Germany. By using irrigation field trials, production activities with varying irrigation intensities and inherently incorporated crop yield uncertainty are defined.

In contrast to increased water prices, a reduction in water quotas leads to higher water savings and lower economic disadvantages for farmers. Due to an adjusted portfolio crop choice, as well as irrigation intensity, the reduction in the expected total gross margin is partially offset.

This example ensures volumetric water monitoring at the farm level which, however, remains a major pitfall in many other countries. From a methodological perspective, the crop yield distribution choice might affect the findings. Likewise, the consideration of downside risk in an irrigation context appears to be interesting for future research.

This is the first paper to compare the implications of differentiated water quotas and water pricing schemes suggested by the European Water Framework Directive, while taking risk‐efficient crop portfolio considerations into account. This approach facilitates water reallocation not only between crops, but also in terms of the crop‐specific irrigation intensity. Crop yields are based on a unique panel of micro data rather than expert opinions or simulations.

An interdisciplinary model network consisting of the regional agricultural economic model RAUMIS and the hydro(geo)logical models GROWA/WEKU is used to analyze the effect of different scenarios of maximum agricultural nitrogen balance surplus on water quality. The study area is the federal state of Lower Saxony, Germany, which features heterogeneous natural site conditions as well as agricultural production structures. A focus of the study is the modeling of supra-regional manure transports that, according to the model's results, considerably increase due to a lowering of maximum nitrogen balance surpluses. The assessment of the examined nitrogen reduction measures reveals that adequate indicators have to be applied. In this regard, the model results show that even though the analyzed measure leads to a substantial overall reduction of agricultural nitrogen surpluses, nitrogen discharges into surface and groundwater can regionally increase.

The authors aim to provide here an opinion on the state‐of‐the‐art of integrated ecological‐economic assessments of bioenergy under climate change, as well as the challenges along with their implications faced in planning adaptation at local scale.

Investments to reduce emissions must be made in the coming decades to avoid the risks posed by climate change. If these investments are made wisely, then costs will be manageable, stability in markets as well as energy security will be achieved, and even rural development and economic growth may be stimulated. The authors call attention to the need for modeling of climate change impacts by combining the outputs from appropriately designed crop simulation models with economic analyses. Combining natural science and economics in a compatible fashion at local scale will play an essential role in advancing communication and information exchange.

There are key differences in drivers or determinants of mitigation and adaptation potential and decisions at different scales, which means that different actors, different timescales and different spatial scales of decision making must be specifically considered. Understanding of the potential impacts of climate change requires disaggregation of the agricultural sector with appropriate detail. A critical trade‐off exists between area‐wide spatial coverage and an explicit consideration of local peculiarities.

The authors suggest that a much stronger effort must be made to meld natural science crop modeling approaches with economic analyses, to include spatially explicit consideration of conventional crop production along with 1st and 2nd generation bioenergy crops, and the evaluation not only of “best guess” scenarios of change, but also potential system impacts of extreme scenarios.