Search results

Valuation accuracy usually conjures up images of empirical studies of comparisons between sales and valuations and different valuations of the same properties, and a number of references to these studies are included in the paper. However, this paper concentrates on the institutional influences which impact on valuations and their accuracy. The overall aim of this paper is to examine the legal interpretation of valuation inaccuracy in the UK. This might seem a bit parochial in the context of a World Valuation Congress. However, cases in many countries in the Commonwealth form precedents for each other and therefore decisions in, for example, the UK and Australasia, are drawn on by others in reaching decisions. The paper also reaches conclusions which have wider implications for all jurisdictions which have valuation disputes settled in courts, tribunals and any other quasi‐judicial body.

This paper seeks to provide researchers and librarians with an overview of the US Census Bureau's American Community Survey (ACS), with a specific focus on practical issues that users must face when choosing and using ACS datasets.

Each of the following issues are explored subsequent to a general overview of the ACS: choosing among census datasets from different census programs, interpreting and choosing between the different ACS period estimates, selecting census geography, understanding and recalculating margins of error, and accessing the data. Samples of ACS tables and formulas for creating derived estimates are used to illustrate how to interpret and work with the data.

The ACS datasets are fundamentally different from the decennial census as they are period estimates created from rolling sample surveys. The ACS has a steeper learning curve; this complexity is due in part to the number of choices users must make between datasets, but the primary challenge is learning how to understand and work with estimates as opposed to population counts.

While other papers have discussed the benefits and challenges of the ACS, this paper is structured around the practical issues that researchers must face when using it. Special consideration is given to calculating derived estimates using spreadsheet formulas, as this is a key task that many users will need to perform and spreadsheets are the most likely tool users will employ to manipulate the data.

The purpose of this study is to assess the level and variability of Ghanaian property and liability insurer’s reserve estimates to examine its sources and ascertain if reserve errors are random or not (i.e. manipulated or not).

It uses information on insurer claim reserve provisions, claims outstanding, claims incurred and claims paid for the period of 2000-2010. Categorizing the sources of variation as endogenous and exogenous, the authors use the panel correlated standard error regression model to determine sources and magnitude of industry reserve error.

The study finds that size, age, lag of loss reserve error, inflation rate and real gross domestic product are significant in determining the degree of reserve error variation. Type of ownership (domestic or foreign) is, however, not a significant source of variation. Further, the authors found that industry reserve errors are random (not manipulated) across firms, suggesting that sampled insurers act independently on reserve error decision making and are not influenced by industry trends and competition.

The main research study limitation is the difficulty involved in obtaining annual statements from insurance companies in Ghana. Reluctance of companies to make statements available impeded on the smooth flow of the study during data collection.

Policy-wise, this suggest that regulatory bodies can uniquely set reserve error levels for existing firms with little influence on competition. Further, the Ghanaian insurance regulator does not to focus on the type of ownership (foreign or local) when setting regulatory standards. However, size of the company and age (length of operation) should be considered.

This paper is the first empirical study to examine the loss reserve error and loss reserve variability of Ghanaian property and liability insurance companies.

Ensuring the sufficient service level is essential for critical materials in industrial maintenance. This study aims to evaluate the use of statistically imperfect data in a stochastic simulation-based inventory optimization where items' failure characteristics are derived from historical consumption data, which represents a real-life situation in the implementation of such an optimization model.

The risks of undesired shortages were evaluated through a service-level sensitivity analysis. The service levels were simulated within the error of margin of the key input variables by using StockOptim optimization software and real data from a Finnish steel mill. A random sample of 100 inventory items was selected.

Service-level sensitivity is item specific, but, for many items, statistical imprecision in the input data causes significant uncertainty in the service level. On the other hand, some items seem to be more resistant to variations in the input data than others.

The case approach, with one simulation model, limits the generalization of the results. The possibility that the simulation model is not totally realistic exists, due to the model's normality assumptions.

Margin of error in input data estimation causes a significant risk of not achieving the required service level. It is proposed that managers work to improve the preciseness of the data, while the sensitivity analysis against statistical uncertainty, and a correction mechanism if necessary, should be integrated into optimization models.

The output limitations in the optimization, i.e. service level, are typically stated precisely, but the capabilities of the input data have not been addressed adequately. This study provides valuable insights into ensuring the availability of critical materials.

Investigates the extent and possible causes of variance in property investment valuations for commercial lending purposes within the UK. A literature review was undertaken and a questionnaire survey was circulated to individuals involved in the commercial property valuation process in order to gauge professional opinion. The survey revealed that the main cause of variance was found to be a result of the individual valuer’s “behavioural influences”. The survey also found that parties to a valuation instruction widely accept the margin of error principle, the legal manifestation of valuation variance, as a test of negligence.

One of the fundamental tenets of social studies education is preparing students to become knowledgeable and informed citizens. Especially in this era of increased communication and technology, one skill necessary for informed citizenship is the ability to critically understand polling data. Social studies educators, however, rarely provide their students with the mathematical framework required to move beyond face-value analysis of public opinion polls. This article outlines the basic statistical processes behind public opinion polls and provides social studies teachers with activities that encourage students to critically question political data presented in the media.

The purpose of this paper is to construct, for the first time, composite index for Egypt that measures the economic and social rights fulfillment (ESRF) based on socioeconomic surveys at the household/individual levels.

The paper highlights some of the statistical debatable issues about composite indices and focuses mainly on six of them. Those issues are indicators selection, handling missing data, identification of and dealing with outliers, scale of measurement, computing the margin of error, weights assigned for indicators and domains and aggregation method. Handling these problematic issues gave rise to a rigorous index.

The quality of economic and social rights fulfillment index (ESRFI) is judged by its bootstrap standard error. Based on these margin of errors, confidence intervals can be computed and rigorous comparisons across all disaggregation levels of the ESRFI can be made. The results shows that the overall index is accurate and representative in measuring the ESRF in Egypt. Comparisons between rural and urban regions indices show that the rural areas are always worse than the urban areas in all levels of dimensions, especially for the Right to Education and Adequate Housing.

The ESRFI is not very current because it is based on the 2010 Egyptian Household Conditions Observatory Survey (EHCOS), which is the latest published version of the survey with complete variables for the index data. When the next EHCOS becomes available, an updated ESRFI can be easily and quickly constructed.

The ESRFI could strengthen policy formulation that takes into account ESRF, especially by highlighting the situation in different regions and disaggregation levels.

The proposed ESRFI would strengthen policy formulation that takes into account ESRF, especially by highlighting the situation in different regions and different disaggregation levels.

The paper emphasizes the importance of recognizing and handling of the six problematic issues that arise when constructing composite indices. The paper presents the first ESRFI for Egypt and demonstrates the rigor of its construction.

The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

The current need for performance measurement and quality targets for services to users requires suitable performance indicators for libraries to use. This paper looks at the self‐assessment audit tool for catalogue quality developed by UKOLN in collaboration with Essex libraries. For the tool a checklist of errors was drawn up, which can then be used to assess the quality of records within a catalogue using a sample of library stock. The tool can be used to assess the quality of catalogue records for monographs and non‐book materials (but not serials), for complete collections or parts of collections and for records created at different periods. This paper describes the tool and the process of making the assessment and reports on the results of the pilot study carried out at the University of Bath library in 2000.

Possible approaches to the formulation of health indicators and the uncertainties that should be associated with such indicators are discussed. As an illustration, two health indicators are formulated, one reflecting the degree of premature mortality in a population, and one reflecting the impact of health on the ratio between the productive and the dependent age groups in a population. Illustrative values of these indicators are computed for various countries and are compared with the corresponding values of the customary health indicators of life expectancy and infant mortality. The indication of the margin of error that should be attached to such indicators if they are to be regarded as measures of population “health” is obtained by observing the extent to which these different indicators correlate with each other when their values for various countries are considered.