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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 em...
Context in source publication
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... These characteristics of AER highlight the need for a framework that captures (a) the im- pacts of AER on the subjective beliefs of pol- icy makers and private decision makers about the consequences of actions, (b) the economic efficiency or welfare effects of those actions, and (c) the political-economic interactions be- tween policy makers and interest groups that underpin policy decisions. A summary of the key elements of a Bayesian political-economy model, drawing on both Zusman (1995) and Hirshleifer and Riley, for assessing the contri- bution of AER is provided in figure 1. A va- riety of feasible actions are assumed open to a decision maker, x = (1, . . . ...
Citations
... The literature has begun to address the value of scientific research in the context of environmental and marine resource management (Lave 1963;Adams et al. 1995;Bernknopf et al. 1997;Schimmelpfennig and Norton 2003;Costello et al. 2010). Model. ...
The ocean's biological carbon pump (BCP) sequesters carbon from the surface to the deep ocean and seabed, constituting one of Earth's most valuable ecosystem services. Significant uncertainty exists surrounding the amounts and rates of organic carbon sequestered in the oceans, however. With improved understanding of BCP sequestration, especially its scale, world policymakers would be positioned to make more informed decisions regarding the mitigation of carbon emissions. Here, an analytical model of the economic effects of global carbon emissions—including scientific uncertainty about BCP sequestration—was developed to estimate the value of marine scientific research concerning sequestration. The discounted net economic benefit of a putative 20-year scientific research program to narrow the range of uncertainty around the amount of carbon sequestered in the ocean is on the order of $0.5 trillion (USD), depending upon the accuracy of predictions, the convexities of climate damage and economic output functions, and the initial range of uncertainty.
... This is due to the point that industrial and agricultural developments are not alternative but more complementary since they are mutually supporting in terms of inputs and outputs. Though the agricultural sector can be viewed at the macro-level perspective since it focuses on how agriculture affects domestic economies and how events that are occurring in other sectors affect these economies and the GDP (Schimmelpfennig and Norton, 2003). Therefore, the agricultural sector in South Africa makes its contribution to the country's economy through the supply of food, provision of employment, foreign currency earnings and supply of raw material to other sectors towards contributing to the growth of the GDP (Van Zyl, Nel, and Groenewald, 1988). ...
The South African government has shown a glut commitment in improving the growth of Gross Domestic Product (GDP). This is entrenched as the long term vision on the National Development Plan, which anticipates to accelerate the growth of the GDP through the industrial and agricultural sectors. This paper analyzes the performance of the South African agricultural economy towards the GDP from the financial year of 2018 and beyond. The case study assisted a researcher to go through the previous report including online data sources such as Statistics South Africa, the Global Economy, and the World Bank. The textual analysis assisted a researcher in critically analyzing the relevant reviewed literature and Microsoft Excel was used to present and analyze the graph to fulfill the quantitative part of this paper. The most important part of the findings reveals that the agricultural sector has shown to reach a recession in terms of contributing to the GDP in 2019 and that raises concerns about the future of the agricultural sector towards contributing to the growth of the GDP in South Africa. This is because the country is currently going through the issue of load shedding, which remains a threat to the growth of the agricultural economy. The government should develop the gas infrastructure by converting all diesel fired power plants to gas in order to back up the agricultural sectors during electricity shortage.
... A few studies (DFID, 2005) have attempted to quantify the efficiency, productivity, or rates of return of social science research, which has used esoteric methods such as the Bayesian decision theory and has reached estimates that cannot be considered robust (Gardner, 1999;Schimmelpfennig and Norton, 2003). The investigation of some databases (Eco-Link, ProQuest, Ektaband EBSCO) that revealed the need to conduct further research to assess the benefits of research no doubt constitutes a serious challenge. ...
This paper investigates the publication activity and the value of research funding in Saudi institutions of higher education. Our main question was what is the relationship between the efficiency of chair research funding and the productivity of faculty members? This interdisciplinary paper consists of applying econometric modeling to determine the profile of a faculty member involved in research and the Return on investment (ROI) methodology to assess the value of the funding in the case of SABIC chair. A survey using a questionnaire on perceptions of academic research productivity and documentary analysis of the profile of funding recipients showed that research funding has a positive impact on faculty productivity (2.66 published papers more) when the count considered is the number of published papers. However, there is no significant relationship between grants and publications in peer-reviewed journals with an impact factor. Furthermore, the results revealed that the estimated ROI was 37.2% more.
... A few studies (DFID, 2005) have attempted to quantify the efficiency, productivity, or rates of return of social science research, which has used esoteric methods such as the Bayesian decision theory and has reached estimates that cannot be considered robust (Gardner, 1999;Schimmelpfennig and Norton, 2003). The investigation of some databases (Eco-Link, ProQuest, Ektaband EBSCO) that revealed the need to conduct further research to assess the benefits of research no doubt constitutes a serious challenge. ...
This paper investigates the publication activity and the value of research funding in Saudi institutions of higher education. Our main question was what is the relationship between the efficiency of chair research funding and the productivity of faculty members? This interdisciplinary paper consists of applying econometric modeling to determine the profile of a faculty member involved in research and the Return on investment (ROI) methodology to assess the value of the funding in the case of SABIC chair. A survey using a questionnaire on perceptions of academic research productivity and documentary analysis of the profile of funding recipients showed that research funding has a positive impact on faculty productivity (2.66 published papers more) when the count considered is the number of published papers. However, there is no significant relationship between grants and publications in peer-reviewed journals with an impact factor. Furthermore, the results revealed that the estimated ROI was 37.2% more.
... Geospatial and spatiotemporal public data are integrated into current economic activities that have considerable economic benefits such as transportation route and communication facility planning. Economic models have been developed to estimate the benefits of geospatial data for a wide range of topics in industrial sectors such as agriculture [2][3][4][5], resource extraction [6], environmental hazards [7], wildfire management [8] and maritime shipping [9]. ...
... (4) Estimate the net benefit of regulatory mitigation and compare the results of expected outcomes with voluntary mitigation for census tracts identified in steps (1)- (3). If the four criteria are met, the cost minimizing regulation program could be made available for all multi-family buildings in a census tract to avoid any missed special circumstances. ...
Geospatial data inform decision makers. An economic model that involves application of spatial and temporal scientific, technical, and economic data in decision making is described. The value of information (VOI) contained in geospatial data is the difference between the net benefits (in present value terms) of a decision with and without the information. A range of technologies is used to collect and distribute geospatial data. These technical activities are linked to examples that show how the data can be applied in decision making, which is a cultural activity. The economic model for assessing the VOI in geospatial data for decision making is applied to three examples: (1) a retrospective model about environmental regulation of agrochemicals; (2) a prospective model about the impact and mitigation of earthquakes in urban areas; and (3) a prospective model about developing private-public geospatial information for an ecosystem services market. Each example demonstrates the potential value of geospatial information in a decision with uncertain information.
... One of the difficulties in using the VOI lies in how to assess the probabilities before and after receiving the new information. Some authors have tried to estimate them using knowledge elicitation methods by interviewing decision makers directly [see e.g., Bouma et al., 2009;Schimmelpfennig and Norton, 2003], while other authors have used empirical methods such as data from model outputs [see Dakins et al., 1996;Lin et al., 1999]. Yokota and Thompson [2004] offer a comprehensive review of various VOI applications in the field of management decisions concerning environmental health risk and the different approaches used to estimate these probabilities. ...
... [34] From the Bayesian viewpoint, the data used to estimate the prior P s should be independent to the data used to evaluate the likelihood P(m|s), so it is debatable to use the same data set to estimate the likelihoods (this issue is addressed in section 5). For the time being, let us assume that P s was obtained from some knowledge elicitation method [see e.g., Bouma et al., 2009;Schimmelpfennig and Norton, 2003]. Then, the probability of the joint occurrence of the messages produced at O and the states observed at R can be estimated using equation (8). ...
The role of decision-makers is to take the outputs from hydrological and
hydraulic analyses and, in some extent, use them as inputs to make
decisions that are related to planning, design and operation of water
systems. However, the use of these technical analyses is frequently
limited, since there are other non-hydrological issues that must be
considered, that may end up in very different solutions than those
envisaged by the purely technical ones. A possibility to account for
the nature of the human decisions under uncertainty is by exploring the
use of concepts from decision theory and behavioural economics, such as
Value of Information and Prospect Theory and embed them into the
methodologies we use in the hydrology practice. Three examples are
presented to illustrate these multidisciplinary interactions. The first
one, for monitoring network design, uses Value of Information within a
methodology to locate water level stations in a complex canal of
networks in the Netherlands. The second example, for operation, shows
how the Value of Information concept can be used to formulate
alternative methods to evaluate flood risk according to the set of
options available for decision-making during a flood event. The third
example, for planning, uses Prospect Theory concepts to understand how
the "losses hurt more than gains feel good" effect can determine the
final decision of urbanise or not a flood-prone area. It is
demonstrated that decision theory and behavioural economic principles
are promising to evaluate the complex decision-making process in
water-related issues.
... One of the difficulties in using the VOI lies in how to assess the probabilities before and after receiving the new information. Some authors have tried to estimate them using knowledge elicitation methods by interviewing decision makers directly [see e.g., Bouma et al., 2009;Schimmelpfennig and Norton, 2003], while other authors have used empirical methods such as data from model outputs [see Dakins et al., 1996;Lin et al., 1999]. Yokota and Thompson [2004] offer a comprehensive review of various VOI applications in the field of management decisions concerning environmental health risk and the different approaches used to estimate these probabilities. ...
... [34] From the Bayesian viewpoint, the data used to estimate the prior P s should be independent to the data used to evaluate the likelihood P(m|s), so it is debatable to use the same data set to estimate the likelihoods (this issue is addressed in section 5). For the time being, let us assume that P s was obtained from some knowledge elicitation method [see e.g., Bouma et al., 2009;Schimmelpfennig and Norton, 2003]. Then, the probability of the joint occurrence of the messages produced at O and the states observed at R can be estimated using equation (8). ...
Because the collection of data in water systems is important for making
informed decisions, monitoring networks are designed and installed in
such systems. Traditionally, the design of hydrometric monitoring
networks has been concentrated on measuring streamflow/precipitation at
particular key (gauged) sites so that streamflow/precipitation can be
estimated accurately at ungauged sites. Although many methods take into
account a set of final users of the information, there appears to be no
method that explicitly considers them in the mathematical formulation of
the decision-making process. This paper presents a novel approach for
designing monitoring networks in a water system using the concept of
value of information (VOI). This concept takes into account three main
factors: (1) the belief that the decision maker has about the state of
the water system before having any information; (2) the consequences
associated with the decision of having to choose among several possible
management actions given the state of the water system; and (3) the
evaluation and update of new information when it becomes available. The
methodology uses a water level time series generated by a hydrodynamic
model at every computational point, each one being a potential monitor
site. The method is tested in a polder system in the Netherlands, where
monitoring is required to make informed decisions about the operation of
a set of hydraulic structures to reduce flood impacts.
... Hence, the analysis in this paper will focus on the added value of EO river plume and sediment discharge information for better targeted run-off reduction measures in the catchments discharging into the GBR lagoon. The method we use for assessing the value of EO information is an expert elicitation method based on Bayesian Decision Theory, which measures the extent to which policy-makers are likely to actually use the information to change the decisions they make (Schimmelpfennig and Norton, 2003). Hirshleifer and Riley (1979) theoretically elaborate how this determines the economic value of information, concluding that information only has economic value when it causes real welfare impacts, which depends on the extent to which information is used to improve the decisions made. ...
... Inherent difficulties in the modeling of complex decision-making processes have limited the use of Bayesian Decision theory for empirical applications (Yokota and Thompson, 2004). The few studies that did apply Bayesian decision theory to estimate the value of information have done so by reducing the complexity of the decision-making problem by using discrete instead of continuous probability functions and by limiting the number of possible actions and states (see for example, Lybbert et al., 2006; Schimmelpfennig and Norton, 2003 and Bouma et al., 2009). Also in this study we will simplify the decision-making problem by using discrete probability functions, and by reducing the decision-making problem to two possible actions and two potential states. ...
... Inherent difficulties in the modeling of complex decision-making processes have limited the use of Bayesian Decision theory for empirical applications (Yokota and Thompson, 2004). The few studies that did apply Bayesian decision theory to estimate the value of information have done so by reducing the complexity of the decision-making problem by using discrete instead of continuous probability functions and by limiting the number of possible actions and states (see for example, Lybbert et al., 2006; Schimmelpfennig and Norton, 2003 and Bouma et al., 2009). Also in this study we will simplify the decision-making problem by using discrete probability functions, and by reducing the decision-making problem to two possible actions and two potential states. ...
The Integrated Global Observing Strategy (IGOS, 2003) argues that further investments in Earth Observation information are required to improve coral reef protection worldwide. The IGOS Strategy does not specify what levels of investments are needed nor does it quantify the benefits associated with better-protected reefs. Evaluating costs and benefits is important for determining optimal investment levels and for convincing policy-makers that investments are required indeed. Few studies have quantitatively assessed the economic benefits of Earth Observation information or evaluated the economic value of information for environmental management. This paper uses an expert elicitation approach based on Bayesian Decision Theory to estimate the possible contribution of global Earth Observation to the management of the Great Barrier Reef. The Great Barrier Reef including its lagoon is a World Heritage Area affected by anthropogenic changes in land-use as well as climate change resulting in increased flows of sediments, nutrients and carbon to the GBR lagoon. Since European settlement, nutrient and sediment loads having increased 5-10 times and the change in water quality is causing damages to the reef. Earth Observation information from ocean and coastal color satellite sensors can provide spatially and temporally dense information on sediment flows. We hypothesize that Earth Observation improves decision-making by enabling better-targeted run-off reduction measures and we assess the benefits (cost savings) of this improved targeting by optimizing run-off reductions under different states of the world. The analysis suggests that the benefits of Earth Observation can indeed be substantial, depending on the perceived accuracy of the information and on the prior beliefs of decision-makers. The results indicate that increasing informational accuracy is the most effective way for developers of Earth Observation information to increase the added value of Earth Observation for managing coral reefs.
... An approach that does solve the second through fourth problem is to take advantage of Bayesian statistics, which are complementary to the classical statistics employed in most aquacultural research (Robert 2001;Schimmelpfennig and Norton 2003;Carlin and Louis 1996;Press 1989;Winkler 1972). In contrast to classical statistics' focus on estimating a population parameter like a water-quality improvement rate, Bayesian statistics concentrates on the new information the water-quality study provides. ...
The ISTA conferences are the primary events to review and predict the direction of the global tilapia farming industry. Presentations on genetics, health, nutrition and feeds, national reports, processing innovations and development of commercial co-products from experts bring the latest information to the participants.
... Bayesian methods are a formal means to quantify the degree to which research uptake changes beliefs (Schimmelpfennig and Norton (2003) and Norton and Alwang (2004)). In this approach, there are two steps that analysts of impact assessment can usefully investigate: first, evidence that policymakers are paying attention, and second, evidence that after paying attention, their views and hence decisions are influenced by the research of interest. ...
Assessing the impact of policy-oriented research is fraught with methodological difficulties ranging from attributing influence on policy change to constructing an appropriate counterfactual. The six case studies in this special section address these challenges in the context of international agricultural research. Methodological and analytical lessons are drawn about the uptake and influence of policy-oriented research on policy change and about the conduct of cost–benefit analysis for such research. The authors of the studies effectively used a key-informant approach to document uptake and influence for policy reforms that were believed to have incorporated well-defined outputs from policy research.
