Climate Change and the Economics of Farm Management in the Face of Land Degradation: Dryland Salinity in Western Australia

Projected changes in climate would affect not only the profitability of agriculture, but also the way it is managed, including the way issues of land conservation are managed. This study provides a detailed analysis of these effects for an extensive dryland farming system in south-west Australia. Using a whole-farm linear programming model, with discrete stochastic programming to represent climate risk, we explore the consequences of several climate scenarios. Climate change may reduce farm profitability in the study region by 50% or more compared to historical climate. Results suggest a decline in the area of crop on farms, due to greater probability of poor seasons and lower probability of very good seasons. The reduced profitability of farms would likely affect the capacity of farmers to adopt some practices that have been recommended to farmers to prevent land degradation through dryland salinization. In particular, establishment of perennial pastures (lucerne or alfalfa, Medicago sativa ), woody perennials ("oil mallees", Eucalyptus spp.), and salt-tolerant shrubs for grazing ("saltland pastures", Atriplex spp.) may become slightly more attractive in the long run (i.e., relative to other enterprises) but harder to adopt due to their high establishment costs in the context of lower disposable income.     

Representing climatic uncertainty in agricultural models – an application of state‐contingent theory

The state‐contingent approach to production uncertainty presents a more general model than the conventional stochastic production approach. Here we investigate whether the state‐contingent approach offers a tractable framework for representing climatic uncertainty at a farm level. We developed a discrete stochastic programming (DSP) model of a representative wheat–sheep (mixed) farm in the Central West of NSW. More explicit recognition of climatic states, and associated state‐contingent responses, led to optimal farm plans that were more profitable on average and less prone to the effects of variations in climate than comparable farm plans based on the expected value framework. The solutions from the DSP model also appeared to more closely resemble farm land use than the equivalent expected value model using the same data. We conclude that there are benefits of adopting a state‐contingent view of uncertainty, giving support to its more widespread application to other problems.     

Modeling producer responses with dynamic programming: a case for adaptive crop management

Past research found agricultural producers’ conditional responses during the growing season are important adaptations to weather and other stochastic events. Failing to recognize these responses overstates the risks confronting producers and understates their ability to respond to adverse circumstances. Dynamic programming (DP) provides a means for determining optimal long‐term crop management plans. However, most applications in the literature base their analysis on annual time steps with fixed strategies within the year, effectively ignoring conditional responses during the year. We suggest an alternative approach that captures the strategic responses within a cropping season to random weather variables as they unfold, reflecting farmers’ ability to adapt to weather realizations. We illustrate our approach by applying it to a typical cereal farm in Karak, Jordan. The results show that including conditional within‐year responses to weather reduces the frequency of fallowing by 23% and increases expected income by 9%.     

Effect of yield and price risk on conversion from conventional to organic farming*

Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility‐efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer’s risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk‐neutral farmer it is optimal to convert to organic farming. However, for a more risk‐averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable.     

Valuing seasonal climate forecasts in a state‐contingent manner

We applied state‐contingent theory to climate uncertainty at a farm level to assess the value of seasonal climate forecasts in the Central West region of NSW. We find that modelling uncertainty in a state‐contingent manner results in a lower estimate of forecast value than the typical expected value approach. We attribute this finding to a more conservative long‐term farm plan in the discrete stochastic programming (DSP) model, which is better balanced for climate uncertainty. Hence, a climate forecast, even though it still revises probabilities held by farmers, does not call forth such large changes in farm plans and associated farm incomes. We then use the DSP model to assess how attributes of a hypothetical forecasting system, particularly its skill and timeliness, as well as attributes of the decision environment, influence its value. Lastly, we assess the value of current operational forecast systems and show that the value derived from seasonal climate forecasts is relatively limited in the case study region largely because of low skill embodied in forecasts at the time when major farm decisions are being made.     

The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management

Seasonal variability is an important source of risk faced by farmers and, regardless of an individual's attitude to risk, there are options to tactically adjust production strategies as the outcomes of risk become known. The objective of this article is to measure the economic benefits of alternative approaches to managing weeds, one of the most serious production problems in Australian cropping systems. A bioeconomic model that combines weed biology, crop growth and economics is developed to value the effects of seasonal variability and the role of tactical responses and sequential decision making in determining an optimal integrated weed management strategy. This shows that there are substantial differences in the measured long‐term benefits from deterministic and stochastic simulations. It is concluded that, for research evaluation of technologies that involve complex biological and dynamic systems, ignoring the impacts of seasonal variability, responses to risk and sequential decision making can lead to an incorrect estimate of the economic benefits of a technology. In this case study of optimal weed management strategies in Australia, the size of the error is high.     

Tactical Opportunities,Risk Attitude and Choice of Farming Strategy: an Application of the Distribution Method

When assessing farming strategies, it is important to account for the opportunities provided for tactically adjusting to outcomes of risk. The hypothesis that accounting for tactical adjustment is more important than accounting for risk attitude was supported in this study with regard to identifying the optimal drainage recirculation strategy for an irrigated dairy farm. Failing to account for tactical adjustment would lead to a sub-optimal choice, costing the farmer about A$3 100 in present value terms. In contrast, failing to account for risk aversion would not affect the strategy chosen. The distribution method was found to be well suited to modelling tactical adjustment.     

Farm‐level impacts of prolonged drought: is a multiyear event more than the sum of its parts?

A multiyear discrete stochastic programming model with uncertain water supplies and inter-year crop dynamics is developed to determine: (i) whether a multiyear drought's impact can be more than the sum of its parts, and (ii) whether optimal response to 1 year of drought can increase a producer's vulnerability in subsequent years of drought. A farm system that has inter-year crop dynamics, but lacks inter-annual water storage capabilities, is used as a case study to demonstrate that dynamics unrelated to large reservoirs or groundwater can necessitate a multiyear model to estimate drought's impact. Results demonstrate the importance of analysing individual years of drought in the context of previous and future years of drought.     

Farm demand for quality potato seed in Indonesia

Seed is the one of the most costly components of potato production in developing countries. Since potato is a vegetatively reproduced crop, diseases such as viruses build up and yield declines as tubers are saved from one harvest for use as seed the next season. Replacing farm‐saved seed with clean seed is one means to increase yield, but information asymmetry between buyers and sellers on seed quality may restrict market supply of this input. In this article we develop a model of the seed market in which clean seed is treated as a capital good providing benefits over several seasons. To determine farm demand for clean seed, we conducted a survey of 182 potato farmers in the major potato growing areas of Indonesia to elicit their perceptions of seed quality from different sources, and derive farmers' “willingness‐to‐pay” for quality potato seed. Results indicate that the effects of information asymmetry on seed supply may be partially offset by the “reputation” of specialized seed producers. Nevertheless, marginal returns to disease‐free seed appear to significantly exceed marginal costs, indicating that improving supply of quality seed will contribute strongly to productivity growth in potato. We discuss several policy options to encourage supply and utilization of quality potato seed.     

RISK ATTITUDE,PLANTING CONDITIONS AND THE VALUE OF SEASONAL FORECASTS TO A DRYLAND WHEAT GROWER*

The value of a seasonal forecasting system based on phases of the Southern Oscillation was estimated for a representative dryland wheat grower in the vicinity of Goondiwindi. In particular the effects on this estimate of risk attitude and planting conditions were examined. A recursive stochastic programming approach was used to identify the grower's utility-maximising action set in the event of each of the climate patterns over the period 1894-1991 recurring in the imminent season. The approach was repeated with and without use of the forecasts. The choices examined were, at planting, nitrogen application rate and cultivar and, later in the season, choices of proceeding with or abandoning each wheat activity. The value of the forecasting system was estimated as the maximum amount the grower could afford to pay for its use without expected utility being lowered relative to its non-use.     

A decision support system for strategic planning on pig farms

This paper reported on a decision support system (DSS) for strategic planning on pig farms. The DSS was based on a stochastic simulation model of investment decisions (ISM). ISM described a farm with one loan and one building using 23 variables. The simulation model calculated the results of a strategic plan for an individual pig farm over a time horizon of a maximum of 20 years for a given scenario. For six distinct replacement strategies, regression metamodels were specified to describe the outcome of the response variable as a function of the farm variables. The regression results indicated that a linear function with only nine or ten farm variables gave a reasonable estimate of the results of the simulation model. Turnover ratio, feed conversion ratio, percentage of meat, farm size, family expenses, and experience were the main parameters determining future relative farm position. For farms with high levels of family expenditures and/or financial leverage an economic replacement strategy was optimal. Risk attitudes played a minor role in the choice of the optimal strategy, because one strategy was preferred to another regardless of risk preference. To analyze the attractiveness of a chosen strategic plan for different ‘what-if’ scenarios, the visual method using graphical representations offered sufficient information. The number of years ahead for which the decision maker evaluated the consequences of simulated strategic plans influenced which strategy was preferred.     

Effect of changes in population density and crop productivity on farm households in Malawi

This study examines the ex‐ante farm‐household effects of changes in family size, yield potential, and yield gaps using a farm‐household simulation model that reflects the economic and biophysical conditions of central Malawi. Disparities between growth in human population and crop yields present challenges for farm‐household crop production and income in sub‐Saharan Africa. We focus on the effect of growth in yield potential and a more efficient use of livestock manure as approaches to improving crop production and incomes in the face of looming population pressures. Our results suggest that, even without considering climate change, expected changes in population density and crop prices in 2050 mean that per person crop production and income may fall by 21% compared to 2013 values if yield potential and yield gaps remain constant. However, per person crop production and income could increase in 2050 by 8% compared to 2013 values if (1) growth rates of yield potential rise for maize by 1.13% each year and for legumes rise by at least 0.4% each year, and (2) farmers use livestock manure more efficiently. Our foresight approach to considering crop production at the farm‐household scale supplements macro‐scale analyses of the production dimension of food security.     

An economic analysis of farm forestry as a means of controlling dryland salinity

Large areas of agricultural land under conventional crops and pastures are at risk of dryland salinisation in Australia. The salinisation problem can be controlled by strategic and large-scale planting of trees; however, farm forestry enterprises evaluated with conventional discounting techniques do not generally rank as an attractive alternative to annual crops on productive land. In this article, an optimal control model that explicitly accounts for decline or improvement in land quality over a period of 40 years is presented. The optimal area planted to trees and the optimal groundwater-table trajectory through time are determined under a variety of scenarios. Implications of the results for policy design are discussed.     

Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002

English and Welsh farm‐level survey data are employed to estimate stochastic frontier production functions for eight different farm types (cereal, dairy, sheep, beef, poultry, pigs, general cropping and mixed) for the period 1982 to 2002. Differences in the relative efficiency of farms are explored by the simultaneous estimation of a model of technical inefficiency effects. The analysis shows that, generally, farms of all types are relatively efficient with a large proportion of farms operating close to the production frontier. However, whilst the frontier farms of all types are becoming more efficient through time because of technical change, it is also the case that the efficiency of the average farm for most farm types is increasing at a slower rate. In addition, annual mean levels of efficiency for most farm types have declined between 1982 and 2002. The factors that consistently appear to have a statistically significant effect on differences in efficiency between farms are: farm or herd size, farm debt ratios, farmer age, levels of specialisation and ownership status.     

Impacts of changing water inflow distributions on irrigation and farm income along the Drâa River in Morocco

Irrigation water is essential for agriculture in the arid Drâa River basin in Morocco but climate change leads to increasingly unreliable water supply in the area. This article analyzes impacts of changing water inflow distributions on irrigation and farm income extending a conjunctive river basin model toward a stochastic modeling approach. Regional climate scenarios are used to derive a maximum likelihood density estimate of current and future water supplies. Based on these distributions, Monte Carlo simulations are performed to obtain stochastic model results on surface and groundwater irrigation as well as economic indicators for six oases along the river. The probability of farmers to receive revenues below the subsistence level is around 2% under current conditions, but this is likely to rise to rates of 6% to 15% depending on the underlying climate change scenario. The composition of water sources for irrigation will shift to more groundwater use. The river basin model is able to represent complex spatial interactions between oases as well as a partial complementarity between groundwater and surface water irrigation due to salinity management effects. Interestingly, the value of groundwater is not necessarily increasing under future climatic conditions as salinity problems are aggravated with expanded groundwater use.     

An Empirical Analysis of the Relative Efficiency of Policy Instruments to Reduce Nitrate Water Pollution in the U.S. Southern High Plains

This paper develops a modeling framework for evaluating alternative water quality protection policies. The framework integrates the EPIC-PST crop growth/chemical transport model and a mathematical programming model. The framework is applied to the evaluation of four water quality policies in the southern high plains of the United States:
• restrictions on per-acre nitrogen use,
• taxes on nitrogen use,
• taxes on irrigation water use, and
• incentives to convert conventional irrigation systems to modem irrigation technology. The results indicate that producers would make a variety of adjustments in responding to these policies. Important responses might include reductions in nitrogen and water use, crop substitution, removal of land from crop production and conversion from irrigated to dryland production. These four policies are evaluated based on changes in farm income and social welfare. The irrigation system conversion incentive clearly outperforms other policies from both society's and producers points of view. Producers would prefer nitrogen use restrictions to nitrogen or water use taxes because farm income would be reduced less under the restrictions than under the taxes. Nitrogen use taxes, however, are more desirable than nitrogen use restrictions from society's point of view.     

Crop Selection and Implications for Profits and Wind Erosion in a Semi-Arid Environment

A daily crop growth simulation model was applied to four dryland cropping systems to estimate the profit distributions for each of four price series under stochastic weather conditions on the Southern High Plains of Texas. Stochastic dominance with respect to a function was utilized to rank each crop rotation for different risk-averse intervals. Solutions from the model indicate that long-term average annual soil loss due to wind erosion was a function of the producer's risk aversion, price expectation, and discount rate which affect the optimal crop rotation selection.     

The economic impact of bean disease resistance research in Honduras

This paper presents evidence of recent adoption rates of disease resistant bean varieties (RVs), the farm‐level benefits of RV adoption, and the ex post rate of return to disease resistant bean research in Honduras. Results from a farm‐level survey in 2001 in the two principal bean‐producing regions of the country show that 41–46% of bean farmers (depending upon the season) have adopted an RV, and that adoption is neutral with respect to farm‐size and market orientation. An expected utility framework was used to estimate the farm‐level benefits of RV adoption, using a combination of experimental trial and farm‐level survey data. Adopters gain the equivalent of 7–16% (depending on the variety) in bean income from the yield loss averted through RV use. The ex post rate of return to disease resistant bean research in Honduras from 1984 to 2010 is 41.2%.     

Broadacre farm productivity and profitability in south‐western Australia

This paper examines broadacre farm performance in south‐western Australia. This region has experienced pronounced climate variability and volatile commodity prices since the late 1990s. Relationships between productivity and profitability are explored using panel data from 47 farms in the study region. The data are analysed using nonparametric methods. By applying the Fare‐Primont index method, components of farm productivity and profitability are measured over the period 1998–2008. Growth in productivity is found to be the main contributor of profitability. Gains in efficiency and technical change are identified as jointly and similarly important in their contribution to total factor productivity for the farm sample in the region from 1998 to 2008. However, across environments, efficiency gains play an increasingly important role in influencing productivity as growing season rainfall increases. We conclude that R,D&E that delivers further improvement in technical efficiency and technical change is needed to support the profitability of farms across the study region.     

Adaptation and Climate Change Impacts: A Structural Ricardian Analysis of Farm Types in Germany

Based on farm census data, we explore the climate‐dependent incidence of six farm types and the climate‐induced impacts on land rental prices in Germany. We apply a structural Ricardian approach by modeling the dominant farm type at 9,684 communities as depending on temperature, precipitation and other geographic variables. Rents per farm type are then modeled as depending on climate and other conditioning variables. These results allow the projection of the consequences of climate change as changes in our climate variables. Our results indicate that permanent‐crop farms are more likely to dominate in higher temperatures, whereas forage or mixed farms dominate in areas of higher precipitation levels. Land rental prices display a concave response to increases in annual precipitation, and appear to increase linearly with rising annual temperature. Moderate‐warming simulation results for future decades benefit most farm types but seem to penalise forage farms. Rental prices are projected to increase, ceteris paribus, for all farm types.