Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity.

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture–recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture–recapture models. Alternative methods, still under the capture–recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture–recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN)

Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.

Reductions in insecticide use from adoption of Bt cotton in South Africa: impacts on economic performance and toxic load to the environment

The study reported presents the findings relating to commercial growing of genetically-modified Bt cotton in South Africa by a large sample of smallholder farmers over three seasons (1998/99, 1999/2000, 2000/01) following adoption. The analysis presents constructs and compares groupwise differences for key variables in Bt v. non-Bt technology and uses regressions to further analyse the production and profit impacts of Bt adoption. Analysis of the distribution of benefits between farmers due to the technology is also presented. In parallel with these socio-economic measures, the toxic loads being presented to the environment following the introduction of Bt cotton are monitored in terms of insecticide active ingredient (ai) and the Biocide Index. The latter adjusts ai to allow for differing persistence and toxicity of insecticides. Results show substantial and significant financial benefits to smallholder cotton growers of adopting Bt cotton over three seasons in terms of increased yields, lower insecticide spray costs and higher gross margins. This includes one particularly wet, poor growing season. In addition, those with the smaller holdings appeared to benefit proportionately more from the technology (in terms of higher gross margins) than those with larger holdings. Analysis using the Gini-coefficient suggests that the Bt technology has helped to reduce inequality amongst smallholder cotton growers in Makhathini compared to what may have been the position if they had grown conventional cotton. However, while Bt growers applied lower amounts of insecticide and had lower Biocide Indices (per ha) than growers of non-Bt cotton, some of this advantage was due to a reduction in non-bollworm insecticide. Indeed, the Biocide Index for all farmers in the population actually increased with the introduction of Bt cotton. The results indicate the complexity of such studies on the socio-economic and environmental impacts of GM varieties in the developing world.

Reductions in insecticide use from adoption of Bt cotton in South Africa: impacts on economic performance and toxic load to the environment

The study reported presents the findings relating to commercial growing of genetically-modified Bt cotton in South Africa by a large sample of smallholder farmers over three seasons (1998/99, 1999/2000, 2000/01) following adoption. The analysis presents constructs and compares groupwise differences for key variables in Bt v. non-Bt technology and uses regressions to further analyse the production and profit impacts of Bt adoption. Analysis of the distribution of benefits between farmers due to the technology is also presented. In parallel with these socio-economic measures, the toxic loads being presented to the environment following the introduction of Bt cotton are monitored in terms of insecticide active ingredient (ai) and the Biocide Index. The latter adjusts ai to allow for differing persistence and toxicity of insecticides. Results show substantial and significant financial benefits to smallholder cotton growers of adopting Bt cotton over three seasons in terms of increased yields, lower insecticide spray costs and higher gross margins. This includes one particularly wet, poor growing season. In addition, those with the smaller holdings appeared to benefit proportionately more from the technology (in terms of higher gross margins) than those with larger holdings. Analysis using the Gini-coefficient suggests that the Bt technology has helped to reduce inequality amongst smallholder cotton growers in Makhathini compared to what may have been the position if they had grown conventional cotton. However, while Bt growers applied lower amounts of insecticide and had lower Biocide Indices (per ha) than growers of non-Bt cotton, some of this advantage was due to a reduction in non-bollworm insecticide. Indeed, the Biocide Index for all farmers in the population actually increased with the introduction of Bt cotton. The results indicate the complexity of such studies on the socio-economic and environmental impacts of GM varieties in the developing world.

On the question of proportionality of the count of observed Scrapie cases and the size of holding

Background: The present paper investigates the question of a suitable basic model for the number of scrapie cases in a holding and applications of this knowledge to the estimation of scrapie-ffected holding population sizes and adequacy of control measures within holding. Is the number of scrapie cases proportional to the size of the holding in which case it should be incorporated into the parameter of the error distribution for the scrapie counts? Or, is there a different - potentially more complex - relationship between case count and holding size in which case the information about the size of the holding should be better incorporated as a covariate in the modeling? Methods: We show that this question can be appropriately addressed via a simple zero-truncated Poisson model in which the hypothesis of proportionality enters as a special offset-model. Model comparisons can be achieved by means of likelihood ratio testing. The procedure is illustrated by means of surveillance data on classical scrapie in Great Britain. Furthermore, the model with the best fit is used to estimate the size of the scrapie-affected holding population in Great Britain by means of two capture-recapture estimators: the Poisson estimator and the generalized Zelterman estimator. Results: No evidence could be found for the hypothesis of proportionality. In fact, there is some evidence that this relationship follows a curved line which increases for small holdings up to a maximum after which it declines again. Furthermore, it is pointed out how crucial the correct model choice is when applied to capture-recapture estimation on the basis of zero-truncated Poisson models as well as on the basis of the generalized Zelterman estimator. Estimators based on the proportionality model return very different and unreasonable estimates for the population sizes. Conclusion: Our results stress the importance of an adequate modelling approach to the association between holding size and the number of cases of classical scrapie within holding. Reporting artefacts and speculative biological effects are hypothesized as the underlying causes of the observed curved relationship. The lack of adjustment for these artefacts might well render ineffective the current strategies for the control of the disease.

Application of one-list capture-recapture models to scrapie surveillance data in Great Britain

In this paper, we apply one-list capture-recapture models to estimate the number of scrapie-affected holdings in Great Britain. We applied this technique to the Compulsory Scrapie Flocks Scheme dataset where cases from all the surveillance sources monitoring the presence of scrapie in Great Britain, the abattoir survey, the fallen stock survey and the statutory reporting of clinical cases, are gathered. Consequently, the estimates of prevalence obtained from this scheme should be comprehensive and cover all the different presentations of the disease captured individually by the surveillance sources. Two estimators were applied under the one-list approach: the Zelterman estimator and Chao's lower bound estimator. Our results could only inform with confidence the scrapie-affected holding population with clinical disease; this moved around the figure of 350 holdings in Great Britain for the period under study, April 2005-April 2006. Our models allowed the stratification by surveillance source and the input of covariate information, holding size and country of origin. None of the covariates appear to inform the model significantly. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Regulation of plant growth in container-grown ornamentals through the use of controlled irrigation

The aim of this research was to determine whether shoot growth could be regulated and plant quality improved through two controlled irrigation techniques: Regulated Deficit Irrigation (RDI) or Partial Root Drying (PRD). An additional benefit of such techniques is that they would also improve the efficiency of irrigation application and reduce the volume of water used on commercial nurseries. Results from two ornamental woody plant species (Cotinus and Forsythia) demonstrated that plant quality could be significantly improved when RDI was applied at ≤ 60% of potential evapo-transpiration (ETp). Stomatal closure and reduced leaf and internode growth rates were associated with both the RDI and PRD techniques, but reduced leaf water potential was only recorded in the RDI system. Changes in xylem sap pH and ABA concentrations were correlated with changes in shoot physiology, and thought to be generated by those roots exposed to drying soil. By adopting such controlled irrigation systems on commercial holdings it is estimated that water consumption could be reduced by 50 to 90%.

A bagging-based correction for the mixture model estimator of population size

Estimation of a population size by means of capture-recapture techniques is an important problem occurring in many areas of life and social sciences. We consider the frequencies of frequencies situation, where a count variable is used to summarize how often a unit has been identified in the target population of interest. The distribution of this count variable is zero-truncated since zero identifications do not occur in the sample. As an application we consider the surveillance of scrapie in Great Britain. In this case study holdings with scrapie that are not identified (zero counts) do not enter the surveillance database. The count variable of interest is the number of scrapie cases per holding. For count distributions a common model is the Poisson distribution and, to adjust for potential heterogeneity, a discrete mixture of Poisson distributions is used. Mixtures of Poissons usually provide an excellent fit as will be demonstrated in the application of interest. However, as it has been recently demonstrated, mixtures also suffer under the so-called boundary problem, resulting in overestimation of population size. It is suggested here to select the mixture model on the basis of the Bayesian Information Criterion. This strategy is further refined by employing a bagging procedure leading to a series of estimates of population size. Using the median of this series, highly influential size estimates are avoided. In limited simulation studies it is shown that the procedure leads to estimates with remarkable small bias.

Geographical concentration in the institutional market for office property in England and Wales

This paper examines the regional investment practices of institutional investors in the commercial real estate office market in 1998 and 2003 in England and Wales. Consistent with previous studies in the US the findings show that investors concentrate their holdings in a few (urban) areas and that this concentration has become more pronounced as investors have rationalised their portfolio holdings. The findings also indicate that office investment does not fully correlate with the UK urban hierarchy, as measured by population, but is focused on urban areas with high service sector employment. Finally, the pre-eminence of the City of London and and West End office markets as the key focus of institutional investment is confirmed.

The impact of exchanges rates on international real estate portfolio allocation

This paper, examines whether the asset holdings and weights of an international real estate portfolio using exchange rate adjusted returns are essentially the same or radically different from those based on unadjusted returns. The results indicate that the portfolio compositions produced by exchange rate adjusted returns are markedly different from those based on unadjusted returns. However following the introduction of the single currency the differences in portfolio composition are much less pronounced. The findings have a practical consequence for the investor because they suggest that following the introduction of the single currency international investors can concentrate on the real estate fundamentals when making their portfolio choices, rather than worry about the implications of exchange rate risk.

The marginal benefit of diversification in commercial real estate portfolios

The number of properties to hold to achieve a well-diversified real estate property portfolio presents a puzzle, as the estimated number is considerably higher than that seen in actual portfolios. However, Statman (1987) argues that investors should only increase the number of holdings as long as the marginal benefits of diversification exceed their costs. Using this idea we find that the marginal benefits of diversification in real estate portfolios are so small that investors are probably rational in holding small portfolios, at least as far as the reduction in standard deviation is concerned.