Regional Planning of Wastewater Reuse for Irrigation and River Rehabilitation

Subject to a few agri‐environmental restrictions, municipal wastewater can be utilised for agricultural irrigation and river rehabilitation. This paper develops a single‐year Planning Model for a region in Israel which consists of a city and three potential wastewater consumers. The model incorporates, in one endogenous system, the economic, physical and biological relationships in the water–soil–plant–environment system and its objective is to maximise the regional social welfare. The model determines the optimal crop mix and the optimal allocation of the limited water and land resources among all potential users. Then, different allocation approaches from the concept of transferable utility games are applied to determine a reasonable and fair allocation of the additional net benefits which will be acceptable to all the players. The results support the collaboration among the economic entities and indicate economic and environmental advantages which can serve the decision‐makers.     

The impact of perception and other factors on the adoption of agricultural technology in the Moret and Jiru Woreda (district) of Ethiopia

The objectives of this study arc to examine both the significance of the impact of farmers' perceptions regarding new technology for the adoption decision and how perceptions themselves are influenced by the decision to adopt new technology. The study is based on data from 96 wheat farms in the Moret and Jiru woreda (district) of Ethiopia. The probit approach is used to analyse the adoption decision, while the variables relevant to farmers' perceptions are modelled using the ordered probit methodology. A simultaneous equations model combining the probit and ordered probit approaches provides a useful approach to modelling the two-way relationship between perception and adoption. Variables such as farm size, farm income and soil type have a key role to play in the model. Perception is measured by eight different components and as there is a strong collinearity among these various measures, a principal components analysis is attempted to draw the best possible linear combination of variables.     

Understanding how participatory approaches foster innovation

Adapting through innovation is one way for rural communities to sustain and improve their livelihoods and environments. Since the 1980s research and development organizations have developed participatory approaches to foster rural innovation. This paper develops a model, called the Learning-to-Innovate (LTI) model, of four basic processes linked to decision making and learning which regulate rate and quality of innovation. The processes are: creating awareness of new opportunities; deciding to adopt; adapting and changing practice; and learning and selecting. The model is then used to analyse four participatory approaches and the model is evaluated through the quality of insights generated. It shows that, while outwardly very different, the four approaches are built from combinations of 11 strategies. Most of these strategies are aimed at providing information about new opportunities and deciding whether to adopt, and give less support to the other two processes, thus suggesting one way the four participatory approaches can be strengthened. Beyond analysing participatory approaches, the model could be used as a framework for diagnosing the health of local innovation systems and designing tailor-made approaches to strengthen them.     

Foreign Direct Investment and the Performance of European Agribusiness Firms

This article analyses the relationship between foreign direct investment and the performance of European agribusiness firms. Motivated by the role of heterogeneous firms in new trade theory and using a firm‐level dataset, statistical analyses identify key differences between firms investing in foreign economies and those that do not. A binary choice model quantifies the relationship between firm characteristics and the decision to engage in foreign investment. Size and – less strongly – productivity are greater for multinationals relative to domestic firms. Furthermore, European multinationals are characterised by a larger debt to equity ratio and show lower labour and input costs.     

A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L.

This paper develops a stochastic multi-period decision model to analyse a continuous wheat cropping system infested by wild oats (Avena fatua L.), in southern Australia. The multi-period solutions is obtained by employing a dynamic programming model in conjunction with a bioeconomic simulation model. An empirically estimated dose response function is used to derive the optimal herbicide rate. Uncertainties due to environmental effects on the performance of herbicide and crop yields are modelled and optimal decision rules derived. The results indicate that substantial economic gains can be realised if herbicide dose decisions are taken by considering future profit effects of current decisions, as opposed to the more common approach of only considering the current-period effect.     

Export Restrictions and Smooth Transition Cointegration: Export Quotas for Wheat in Ukraine

We extend previous modelling approaches to identify domestic price effects of export controls. We allow for smooth transition between free‐trade price transmission regimes and those under export restricting regimes, using a smooth transition cointegration (STC) approach, rather than the more common assumption that regime changes are abrupt. Our approach has the advantage that the switch in the price transmission regime may be induced not only by an actual but also by an expected policy change. Results confirm the gradual nature of the transition between the regimes, which reflect trader heterogeneity and wheat storage decisions. We find that the STC approach outperforms alternative model approaches in terms of both regime classification and goodness of fit, when explaining Ukrainian domestic wheat prices under export controls. In particular, application of the Markov‐switching error correction model (MSECM) to the same data generates results which do not reflect any identifiable economic reality (in contrast to Götz et al., 2013 ).     

Agriculture trade restrictiveness in Canada: How important are the cross effects?

A trade restrictiveness index (TRI) aggregates an entire protection structure into a single uniform measure that is consistent with trade theory and reflects the extent of policy interventions on trade or welfare. Although there are several variants of a TRI, all approaches aggregate protective measures using weights that depend on import demand and export supply elasticities; some studies ignore cross-price effects while others account for them. This study measures the degree of bias introduced by ignoring cross effects. It provides a practical approach to account for demand- and supply-side cross-price effects in a multi-commodity TRI setting. This approach is illustrated with a case study of distortions in the Canadian crop and livestock sector. Domestic demand and supply cross effects are approximated using a “constant differences of elasticities of substitution” functional form. On average, over the period 1996–2016, we find that cross-price effects do make a difference, and that including them makes the TRI 27% higher than an approach which ignores them. Furthermore, both TRI approaches produce indices that are higher and more variable than the OECD's percentage Producer Support Estimate (PSE) that measures policy transfers as a share of gross farm receipts. The fundamental differences between a TRI and PSE% is driven by market price support for milk.     

Soil-specific agro-ecological strategies for sustainable land use – A case study by using MicroLEIS DSS in Sevilla Province (Spain)

To reverse the negative environmental impacts of agriculture, a land evaluation decision support system (DSS) known as MicroLEIS-DSS was used to design the most sustainable land use and management practices for selected Mediterranean benchmark sites in Sevilla Province, Southern Spain. This DSS is based on the multifunctional evaluation of soil quality, using input data collected in standard soil surveys, and with particular reference to the peculiarities of the Mediterranean region. Specific agro-ecological strategies to prevent soil degradation in the benchmark sites were designed within two major topics: (i) strategies related to land use planning at a regional level: segregation of agricultural lands, restoration of marginal areas, diversification of crop rotation, and identification of vulnerability areas; and (ii) those related to land management planning at a farm level: organic matter restoration, formulation of tillage practices and workability timing, optimum machinery use, and input rationalization. The predicted results of applying the 12 agro-ecological land evaluation model constituents of MicroLEIS DSS are presented and discussed for each application site. The main conclusion of this paper is that using soil type information in decision-making is at the heart for sustainable use and management of agricultural land. This agro-ecological approach can be especially useful when formulating soil-specific agricultural practices to reverse environmental degradation, based on the spatial variability of soils and related resources.     

What is the Value of Agricultural Economics Research?

The output of agricultural economics research is information, much of it aimed at designing or improving institutions. Bayesian decision theory and economic surplus analysis have been suggested as possible approaches to evaluate that information. This article takes a critical look at the strengths and weaknesses of combining those approaches for empirical evaluation of agricultural economics research. It presents three case studies, utilizing prior and posterior probabilities elicited from key decision makers. Direct application of the probabilities to a simple set of states and actions is best suited to situations involving a single policy-making center, or a consensus decision-making process.     

Labour Migration as a Social Security Mechanism for Smallholder Households in Sub-Saharan Africa: The Case of Cameroon

Labour migration is traditionally considered to be a way of protecting household members at the migrant's place of origin from economic pitfalls by receipt of remittances. More recently, young urban migrants from rural regions have been observed to neglect their traditional obligations to support their elderly parents, especially if they do not intend to return to their native village, do not expect any sizeable inheritance and have no reciprocal insurance commitment with their parents. Under such circumstances, rural people are exposed to the risk of staying without support in times of economic crises or during their old age. This paper analyses the potential of migration with remittance strategies in stabilizing the income of rural households. The analytical results are based on a microeconomic survey from Cameroon in 1991/92. A Probit model is applied to analyse access to remittances and a Tobit model to look into their extent. A major result of this analysis is that migration with remittance strategies fails as a social security mechanism when the potential remitter does not expect any sizeable inheritance.     

Payments for environmental services to promote “climate‐smart agriculture”? Potential and challenges

Payments for environmental services (PES) have gained wide popularity as approaches to promote environmentally friendly land use or agricultural production practices. Yet academics have also voiced concerns against seeing PES as a panacea. This article discusses whether PES is an appropriate and promising approach to promote so‐called “climate‐smart agriculture” (CSA) practices, which we define as agricultural production practices that contribute to CO₂ emission reductions and/or removals and provide benefits to farmers via increased productivity and profits and reduced vulnerability to climate change. PES appears most promising for the promotion of CSA practices in small‐scale farming contexts with low incomes. Effective design, however, requires solid estimates of cost and benefit flows from CSA adoption over time, accounting for differences in socioeconomic and ecological conditions, and addressing the risk of leakage. Funding for such PES will likely have to come from public sources, and seems most promising where synergies with other objectives such as agricultural development, food security, and climate adaptation or other environmental services exist. The potential of alternative approaches for CSA support such as taxation with rebates for CSA practices, CSA‐related investment support such as microcredits, and hybrid approaches such as conditional microcredit should be further investigated.     

Using virtual environments and agent models in multi-criteria decision-making

Decision-making is often a complex task. There may be multiple criteria to be satisfied. The consequences of the available options will have different spatial and temporal distributions affecting different population groups and different generations. Decisions are also frequently made in a social context where perceptions can be as important as facts. In this complex environment, research into decision-making has two aspects: (a) understanding the decision process and (b) assisting the decision process. This paper is based on the premise that these are closely linked and that tools are possible which both help us to understand and provide support to decision-makers. A frequently requirement is determination of the trade-offs involved in complex decision situations. These are difficult to establish. Common approaches have used both stated preference and revealed preference techniques. The latter provides a better reflection of real decisions, primarily in market conditions, but does not have the level of experimental control available in hypothetical choice situations. Experimental economics has recently emerged to try to bridge this gap by providing for control of variables within a decision context made real by salient inducements. After review of these options, and the associated literature, we propose a series of linked developments in visualisation and modelling which will support: definition of non-dominated choice sets; interactive choice experiments which encompass spatial and temporal disaggregation; agent-based models to provide social context; and, visualisation to provide a greater sense of immersion in the decision context supported by more intuitive information. We have begun the integration of the necessary software into a virtual decision environment but this paper is focused on conceptual development.     

A trait-based model of the potential demand for a genetically engineered food crop in a developing economy

We predict the potential demand of smallholder farmers for genetically transformed varieties of a food crop, the cooking banana of the East African highlands. Farmer demand for planting material is derived in an agricultural household model that accounts for variety traits and missing markets. The demand for candidate host varieties is predicted using a Zero‐Inflated Poisson (ZIP) regression system. The fitted model is used to illustrate the sensitivity of farmer demand for improved planting material to (a) investments in research and development, represented by the effectiveness of gene insertion and expression, and (b) other public investments in education, extension, and market infrastructure that support diffusion. By comparing the characteristics of agricultural households we demonstrate that the choice of host variety can have social consequences, favoring one rural population compared with another. Clients for transgenic banana planting material are likely to be poorer, subsistence‐oriented farmers in areas greatly affected by biotic constraints. A model of this type might be useful in assessing the investments needed to support the systematic dissemination of improved planting material. The approach can be generalized to other crop biotechnologies for smallholder farming systems, particularly in developing economies.     

A TEST OF BAYESIAN LEARNING FROM FARMER TRIALS OF NEW WHEAT VARIETIES*

In this study, elicited estimates of farmers' subjective beliefs about the mean and variance of wheat variety yields were used to test propositions about Bayesian learning developed in the recent literature on innovation adoption. A series of empirical tests of the Bayesian adoption model were conducted using beliefs elicited from farm surveys conducted in 1982, 1983 and 1984. The results of the analysis neither confirm nor reject the Bayesian approach as a model of how farmers revise subjective beliefs, but do raise serious doubts about its realism, and suggest some issues requiring further investigation. Shortcomings in the elicitation techniques are discussed and the assumptions of the Bayesian model are reviewed.     

Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis

This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis (VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis (MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was characterised by an external input ≤12 kg/ha/yr inorganic fertilizer with/without the addition of manure in rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20, 50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows: (1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b) benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services) were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental performance of the scenarios are compared to maize production systems in other developing regions in order to put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and sustainability of agricultural production systems at farm and regional scales, as well as in connecting the management planning level and regional development considerations.     

Factors Influencing Retailers' Decision to Sell PDO/PGI Fresh Meat

Abstract

The objective of this paper is to analyze retailers' attitudes toward region of origin labeling in fresh meat and the factors influencing retailers' decision to sell these quality labeled meats. Data come from a survey conducted with retailers in Spain (Aragon) in 2002. Firstly, retailers' attitudes toward region-of-origin labeled meat are investigated. Secondly, factors affecting the probability to sell region-of-origin labeled for two meat products (beef and lamb) and the level of sales are determined. To do this, a probit model has been specified to analyze the probability to sell region-of-origin labeled beef/lamb and an ordered probit, to study the level of sales for beef/lamb.     

Risk,learning, and technology adoption

This article explores how decision makers learn and use information, with an application to the adoption of biotechnology in agriculture. The empirical analysis relies on experimental and survey data measuring risk preferences, learning processes, and the adoption of genetically modified (GM) seeds among U.S. grain farmers. While controlling for risk aversion, we link individual learning rules with the cognitive abilities of each decision maker and their actual GM adoption decisions. We find evidence that very few individuals are Bayesian learners, and that the population of farmers is quite heterogeneous in terms of learning rules. This suggests that Bayesian learning (as commonly assumed in the analysis of agricultural technology adoption) is not an appropriate characterization. In addition, we do not find a strong relationship between observed learning styles and the timing of GM seed adoption. To the extent that learning is a key part of the process of technology adoption, this suggests the presence of much unobserved heterogeneity in learning among farmers.     

Minimum‐data analysis of ecosystem service supply in semi‐subsistence agricultural systems

Antle and Valdivia (2006, Australian Journal of Agricultural and Resource Economics 50, 1–15) proposed a minimum‐data (MD) approach to simulate ecosystem service supply curves that can be implemented using readily available secondary data and validated the approach in a case study of soil carbon sequestration in a monoculture wheat system. However, many applications of the MD approach are in developing countries where semi‐subsistence systems with multiple production activities are being used and data availability is limited. This paper discusses how MD analysis can be applied to more complex production systems such as semi‐subsistence systems with multiple production activities and presents validation analysis for studies of soil carbon sequestration in semi‐subsistence farming systems in Kenya and Senegal. Results from these two studies confirm that ecosystem service supply curves based on the MD approach are close approximations to the curves derived from highly detailed data and models and are therefore sufficiently accurate and robust to be used to support policy decision making.     

Wheat and Maize Price Policies in Hungary: Tradeoffs between Foreign Exchange and Government Revenue

This paper reports on a methodology designed to examine the effects of selected agricultural policies in Hungary. The purpose of the paper is twofold. The first is to explain the methodology, dubbed multi-market analysis in previous work, which is implemented on personal computers to support discussions on policy reforms. The second is to examine wheat and maize policies in Hungary. While the model is constructed to focus on these policies, it will also be possible to outline ways to use the model to address other problems.     

Persistent Underinvestment in Public Agricultural Research

It is often argued that public support of agricultural research is inadequate. However, the empirical papers that support this hypothesis rarely reflect formal behavioral theory capable of explaining this phenomenon. This paper presents a theory that explains underfunding, namely, that funding agencies respond too slowly to secular changes in the value of research. A model of farmer and funding agency behavior is presented, and shown to imply that actual research funding will be consistently smaller than optimal funding. The assumptions and results of the model are explained in terms of the institutional literature on public agricultural research agencies.