Suchergebnisse

18. Editing a Survey Data: How Much Is Enough? / Leopold Granquist and John G. Kovar -- 19. The Quality of Occupational Coding in the United Kingdom / Pamela Campanelli, Katarina Thomson and Nick Moon [and others] -- 20. Survey Measurement and Process Improvement: Concepts and Integration / Cathryn S. Dippo -- 21. Continuous Quality Improvement in Statistical Agencies / David Morganstein and David A. Marker -- 22. Quality Policies, Standards, Guidelines, and Recommended Practices at National Statistical Agencies / Michael Colledge and Mary March -- 23. Improving the Comparability of Estimates Across Business Surveys / Bill Gross and Susan Linacre -- 24. Evaluating Survey Data: Making the Transition from Pretesting to Quality Assessment / James L. Esposito and Jennifer M. Rothgeb -- 25. CATI Site Management in a Survey of Service Quality / Mary Batcher and Fritz Scheuren -- 26. Using Statistical Methods Applicable to Autocorrelated Processes to Analyze Survey Process Quality Data / Piyasena Hapuarachchi, Mary March and Adam Wronski -- 27. A Review of Measurement Error Effects on the Analysis of Survey Data / Paul P. Biemer and Dennis Trewin -- 28. Categorical Data Analysis and Misclassification / Jouni Kuha and Chris Skinner -- 29. Separating Change and Measurement Error in Panel Surveys with an Application to Labor Market Data / Frank van de Pol and Rolf Langeheine -- 30. Estimating Usual Dietary Intake Distributions: Adjusting for Measurement Error and Nonnormality in 24-Hour Food Intake Data / Sarah M. Nusser, Wayne A. Fuller and Patricia M. Guenther -- 31. Identifying and Adjusting for Recall Error with Application to Fertility Surveys / Thomas W. Pullum and S. Lynne Stokes -- 32. Estimators of Nonsampling Errors in Interview-Reinterview Supervised Surveys with Interpenetrated Assignments / Francesca Bassi and Luigi Fabbris -- 33. Variance Estimation Under Stratified Two-Phase Sampling with Applications to Measurement Bias / J.N.K. Rao and R.R. Sitter

During the past 20 years, survey methodology has undergone a paradigm shift. The old paradigm was based on a statistical model that focused on the effects of survey errors on the estimates derived from survey data. The new paradigm is based on a social scientific model that focuses on the causes of survey errors. Several developments have helped bring about this shift -- the application of methods & concepts from cognitive psychology to the reduction of survey measurement error, the development of new computerized methods of data collection, & the increase in concern about measurement & nonresponse as sources of error in survey estimates. The new paradigm has little to say about the topics, such as sampling error, that were central to the old one; similarly, the old paradigm had little to say about how to reduce or prevent errors, a major concern for the new one. Thus, the two paradigms do not clash so much as complement each other. 17 References. Adapted from the source document.

Der Arbeitsbericht diskutiert Auswirkungen unterschiedlicher Datenerhebungsmethoden auf die Antwortausprägungen der Befragten. Im Mittelpunkt der Erörterungen stehen die direkte Kommunikation in face-to-face-Situationen, Telefoninterviews und schriftliche Befragungen. Die jeweiligen Effekte werden durchgängig daraufhin reflektiert, inwieweit sie kognitiven und/ oder kommunikativen Prozessen zuzuordnen sind. Hingewiesen wird in diesem Zusammenhang auch darauf, daß ein komplexes Geflecht von Bedingungsfaktoren anzutreffen ist, weil nicht nur die Form der Präsentation von Fragen die Antwortausprägungen bestimmt, sondern gleichzeitig die Organisation der Befragung selbst die Anordnung und Formulierung der Untersuchungsfragen ein Stück weit determiniert, so daß unterschiedliche Antwortausprägungen durch die Anlage der Untersuchung selbst bestimmt sein können. (GF)

Umfragen zur contingent valuation (CV) werden als methodisches Instrumentarium dazu eingesetzt, den Wert von Dienstleistungen oder Gütern ohne Marktwert zu bestimmen. Im wesentlichen werden Befragte aufgefordert, aufgrund einer detaillierten Beschreibung eines Gutes oder einer Dienstleistung eine Kostenbewertung durchzuführen, d.h. anzugeben, wieviel sie für dieses Gut bezahlen würden. Fragebogen solcher Art werden vor allem eingesetzt, um den passiven Wert natürlicher Ressourcen zu bestimmen, mit dem Ziel, Kosten-Nutzen-Analysen bzw. Schadensersatzberechnungen bei Umweltschäden wie sie etwa im Zusammenhang mit der Exxon Valdez-Ölkatastrophe aufgetreten sind, anzustellen. Im Rahmen der intensiven Diskussion um Kosten-Nutzen-Analysen z.B. innerhalb der amerikanischen Umweltpolitik, befaßt sich der Beitrag mit einigen kognitionspsychologischen Implikationen im Zusammenhang mit der CV. In Anlehnung an Ergebnisse der Einstellungsforschung berücksichtigen diese den Stellenwert von inneren Wahrnehmungsprozessen bei der Bewertung sowie die Abhängigkeit der Befragungsergebnisse von der Methode der Datensammlung. (ICH)

Previous research has documented effects of the order in which response choices are offered to Rs, using closed-ended survey items, but no theory of the psychological sources of these effects has yet been proposed. Such a theory, drawn from a variety of psychological research, is offered. Using data from a split-ballot experiment in the 1984 General Social Survey involving a variant of M. L. Kohn's parental values measure (Class and Conformity: A Study in Values, Homewood, Ill: Dorsey, 1969), some predictions are made about what kind of response order effect would be expected (a primacy effect), & among which Rs it should be strongest (those low in cognitive sophistication). These predictions are confirmed. The "form-resistant correlation" hypothesis is also tested. Although correlations between items are altered by changes in response order, the presence & nature of the latent value dimension underlying these responses is essentially unaffected. 5 Tables, 51 References. AA

An introduction to survey errors -- An introduction to survey costs -- Costs and errors of covering the population -- Nonresponse in sample surveys -- Probing the causes of nonresponse and efforts to reduce nonresponse -- Costs and errors arising from sampling -- Empirical estimation of survey measurement error -- The interviewer as a source of survey measurement error -- The respondent as a source of measurement error -- Measurement errors associated with the questionnaire -- Response effects of the mode of data collection.

A person has nonseparable preferences when her preference on an issue depends on the outcome of other issues. A model of survey responses in which preferences are measured with error implies that responses will change depending on the order of questions and vary over time when respondents have nonseparable preferences. Results from two survey experiments confirm that changes in survey responses due to question order are explained by nonseparable preferences but not by the respondent's level of political information, partisanship, or ideology.

State departments of transportation are investing suabstantial time and effort in developing performance measurement systems to help manage more effectively in a period of unprecedented change. Based on information obtained from a mail survey, review of documents, and follow-up telephone interviews, this article examines conventional and leading-edge approaches to performance measurement in these large public works agencies, which have often been characterized as being "data rich/information poor." Compared with the traditional operations-oriented management information systems, the new generation of performance measures emerging in departments of transportation tend to be more outcome-oriented and more strategically focused, with much greater emphasis on quality and customer service.

Empirical analysis of rural credit market failure has been of key scientific and political interest in recent years. The aim of this paper is to give an overview of various methods for measuring credit rationing of farms employed in the literature. Furthermore, based on a common analytical framework entailing a formal model of a credit rationed farm household, the methods are subjected to a comparative evaluation of their specific strengths or shortcomings. Six approaches are distinguished: measurement of loan transaction costs, analysis of qualitative information collected in interviews, analysis of quantitative information collected in interviews by using the credit limit concept, analysis of spill-over effects with regard to secondary credit sources, econometric household modelling, and the econometric analysis of dynamic investment decisions. The first approach defines credit rationing as the impossibility to take a loan due to prohibitively high, measurable transaction costs on loan markets, which is a price rationing mechanism. All other approaches at least implicitly define credit rationing as a persistent private excess demand in terms of a quantity restriction. The six approaches are more or less closely linked to the neo-classical efficiency concept. An explicit comparison with a first-best solution is impossible in the first three approaches, since they essentially rely on a subjective assessment of borrowers' access to credit, based on qualitative or quantitative indicators. The fifth and sixth approach allow a rigorous interpretation in the framework of neo-classical equilibrium theory. The fourth approach takes an intermediate position, since spill-over on segmented loan markets reveals a willingness to pay with regard to the supposedly less expensive but rationed primary source. Approaches are fairly data demanding in general, usually requiring specific data on loan transactions. Even so, most approaches are applicable to cross-sectional household data. Only dynamic modelling of investment decisions necessitates the availability of panel data, therefore restricting the applicability in low-income and transition countries. With the exception of the first, all methods surveyed might plausibly be used to empirically detect credit rationing. ; Die empirische Analyse von Marktversagen auf ländlichen Kreditmärkten ist in den vergangenen Jahren von hohem wissenschaftlichen und politischen Interesse gewesen. Ziel dieses Beitrags ist es, einen Überblick über verschiedene in der Literatur angewandte Methoden zur Messung von Kreditrationierung zu geben. Auf der Grundlage eines gemeinsamen analytischen Bezugsrahmens werden die Methoden darüber hinaus einer vergleichenden Bewertung im Hinblick auf ihre Stärken und Schwächen unterzogen. Es werden sechs Vorgehensweisen unterschieden: die Messung von Kredittransaktionskosten, die Analyse von in Interviews gewonnenen qualitativen Informationen, die Analyse von in Interviews erhobenen quantitativen Information unter Rückgriff auf das Konzept des credit limits, die Analyse von Überschusseffekten im Hinblick auf sekundäre Kreditquellen, ökonometrische Haushaltsmodellierung sowie die ökonometrische Analyse von dynamischen Investitionsentscheidungen. Die erste Vorgehensweise versteht unter Kreditrationierung die Unmöglichkeit, einen Kredit zu erhalten aufgrund von prohibitiv hohen, messbaren Transaktionskosten auf Kreditmärkten. Es handelt sich hierbei um einen Mechanismus der Preisrationierung. Alle anderen Vorgehensweisen definieren Kreditrationierung zumindest implizit als andauernde Überschussnachfrage, folglich eine Mengenbeschränkung. Die sechs Vorgehensweisen sind mehr oder weniger eng mit dem neoklassischen Effizienzkonzept verbunden. Ein expliziter Vergleich mit einer first-best Lösung ist in den ersten drei Vorgehensweisen jedoch unmöglich, da sie auf einer subjektiven Einschätzung des Kreditzugangs beruhen. Die fünfte und sechste Methode erlauben hingegen eine strikte Interpretation im Rahmen der neoklassischen Gleichgewichtstheorie. Die vierte Vorgehensweise nimmt eine Zwischenstellung ein, da Überschusseffekte auf segmentierten Kreditmärkten eine Zahlungsbereitschaft im Hinblick auf die primäre, rationierte Kreditquelle implizieren. Die Methoden erfordern die Verfügbarkeit von geeigneten Datensätzen über Kredittransaktionen. Die meisten Ansätze können allerdings auf Querschnittsdaten angewendet werden. Lediglich die dynamische Modellierung von Investitionsentscheidungen erfordert Paneldaten und beschränkt daher die Einsatzmöglichkeit in Entwicklungs- und Transformationsländern. Mit Ausnahme des ersten können alle Ansätze auf plausible Weise für die empirische Untersuchung von Kreditrationierung eingesetzt werden.

Empirical analysis of rural credit market failure has been of key scientific and political interest in recent years. The aim of this paper is to give an overview of various methods for measuring credit rationing of farms employed in the literature. Furthermore, based on a common analytical framework entailing a formal model of a credit rationed farm household, the methods are subjected to a comparativeevaluation of their specific strengths or shortcomings. Six approaches are distinguished: measurement of loan transaction costs, analysis of qualitative information collected in interviews, analysis of quantitative information collected in interviews by using the credit limit concept, analysis of spill-over effects with regard to secondary credit sources, econometric household modelling, and the econometric analysis of dynamic investment decisions. The first approach defines credit rationing as the impossibility to take a loan due to prohibitively high, measurable transaction costs on loan markets, which is a price rationing mechanism. All other approaches at least implicitly define credit rationing as a persistent private excess demand in terms of a quantity restriction. The six approaches are more or less closely linked to the neo-classical efficiency concept. An explicit comparison with a first-best solution is impossible in the first three approaches, since they essentially rely on a subjective assessment of borrowers' access to credit, based on qualitative or quantitative indicators. The fifth and sixth approach allow a rigorous interpretation in the framework of neo-classical equilibrium theory. The fourth approach takes an intermediate position, since spill-over on segmented loan markets reveals a willingness to pay with regard to the supposedly less expensive but rationed primary source. Approaches are fairly data demanding in general, usually requiring specific data on loan transactions. Even so, most approaches are applicable to cross-sectional household data. Only dynamic modelling of investment decisions necessitates the availability of panel data, therefore restricting the applicability in low-income and transition countries. With the exception of the first, all methods surveyed might plausibly be used to empirically detect credit rationing.