Estimating Poverty and Inequality Indicators using Interval Censored Income Data from the German Microcensus

Rising poverty and inequality increases the risk of social instability in countries all around the world. For measuring poverty and inequality there exists a variety of statistical indicators. Estimating these indicators is trivial as long as the income variable is measured on a metric scale. However, estimation is not possible, using standard formulas, when the income variable is interval censored (or grouped), as in the German Microcensus. This is the case for numerous censuses due to confidentiality constraints or in order to decrease item non-response. To enable the estimation of statistical indicators in these scenarios, we propose an iterative kernel density algorithm that generates metric pseudo samples from the interval censored income variable. Based on these pseudo samples, poverty and inequality indicators are estimated. The standard errors of the indicators are estimated by a non-parametric bootstrap. Simulation results demonstrate that poverty and inequality indicators from interval censored data can be unbiasedly estimated by the proposed kernel density algorithm. Also the standard errors are correctly estimated by the non-parametric bootstrap. The kernel density algorithm is applied in this work to estimate regional poverty and inequality indicators from German Microcensus data. The results show the regional distribution of poverty and inequality in Germany

Psychologische Paradigmen für die Controllingforschung

Die Controllingforschung ist eine vergleichsweise junge Forschungsdisziplin und als solche noch auf der Suche nach ihrer Definition, Identität und Legitimität. Die Controllingpraxis hingegen besteht bedeutend länger. Dennoch hat sich über die Zeit keine einheitliche Controllingpraxis entwickelt. Stattdessen dominieren nationalspezifische und unternehmensspezifische Ausprägungen des Controllings. Dementsprechend heterogen ist auch die Controllingforschungslandschaft. Mit dem Wandel des in der ökonomie vorherrschenden Menschenbilds wandelt sich auch die Modellvorstellung vom Menschen in der Controllingforschung. Die im neoklassischen Homo oeconomicus zusammengefassten Annahmen werden durch verhaltenswissenschaftlich-psychologische Erkenntnisse ergänzt oder ersetzt. Die Berücksichtigung der Eigenschaften realer Entscheidungsträger ermöglicht eine wirkungsvolle Unterstützung dieser realen Entscheidungsträger durch das Controlling. Für eine solche wirkungsvolle Unterstützung genügt es nicht, die Controllinginstrumente selbst dahingehend zu verbessern, dass die verwendeten Methoden die eingehenden Fakten immer besser zu einem Output verarbeiten. Die Zuständigkeit der Controllingforschung endet nicht bei der Erstellung von Controllinginstrumenten, die Zustände valide und reliabel anhand von Zahlen ausdrücken, dokumentieren, prognostizieren und damit eine quantifizierte Bewertungsgrundlage liefern. Es muss auch sichergestellt werden, dass die Information, die ein Controllinginstrument liefert, von den beteiligten Personen verstanden und verwendet werden kann. Die Psychologie als Wissenschaft vom Erleben und Verhalten des Menschen bietet zwar keine umfassenden Menschenbilder, die den Menschen in seiner ganzen Komplexität beschreiben könnten, dennoch kennt sie empirisch belegte Zusammenhänge im Verhalten und Erleben des Menschen. Unter Einbeziehung psychologischer Erkenntnisse kann die Controllingforschung somit zu inhaltlich valideren Beschreibungen, Erklärungen und Vorhersagen über Forschungsgegenstände wie reale Entscheidungsträger gelangen. Der vorliegende Beitrag stellt psychologische Paradigmen vor, die durch ihre Berücksichtigung sowohl der anwendungsorientierten als auch der konzeptionellen Controllingforschung eine Weiterentwicklungsmöglichkeit bieten. Es wird vorgeschlagen, psychologische Paradigmen mit den ökonomischen Controllingansätzen zu etwas Neuem zu kombinieren. Dieser Beitrag ist somit im Bereich der Psychological Management Accounting Research angesiedelt. Der vorliegende Beitrag stellt psychologische Paradigmen vor, die vorrangig an der bounded rationality anknüpfen

Broadband Suzaku observations of IGR J16207-5129

An analysis of IGR J16207-5129 is presented based on observations taken with Suzaku. The data set represents ~80 ks of effective exposure time in a broad energy range between 0.5 and 60 keV, including unprecedented spectral sensitivity above 15 keV. The average source spectrum is well described by an absorbed power law in which we measured a large intrinsic absorption of nH = 16.2(-1.1/+0.9)x10^22 /cm2. This confirms that IGR J16207-5129 belongs to the class of absorbed HMXBs. We were able to constrain the cutoff energy at 19(-4/+8) keV which argues in favor of a neutron star as the primary. Our observation includes an epoch in which the source count rate is compatible with no flux suggesting a possible eclipse. We discuss the nature of this source in light of these and of other recent results.Comment: 12 pages, 6 figures, accepted for publication in Ap

Measuring vulnerability to poverty using long-term panel data

We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty

Measuring Vulnerability to Poverty Using Long-Term Panel Data

We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty

Heinrich Hoffmann und sein Struwwelpeter in der Universitätsbibliothek Johann Christian Senckenberg Frankfurt am Main

In der Frankfurter Universitätsbibliothek befindet sich eine Vielzahl an handschriftlichen und gedruckten Materialien von und über Heinrich Hoffmann. Hier eine Auswahl (Stand: April 2009)

Measuring Vulnerability to Poverty Using Long-Term Panel Data

We investigate the accuracy of ex ante assessments of vulnerability to poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility

Fit and Healthy in Middle Adulthood – Do Fitness Levels Make a Difference

Strong evidence exists that fitness is a physical health resource, which serves to protect one’s health. There is still uncertainty about which fitness level provides the best health outcome and which measurements can be used for analyzing this question. This cross-sectional study analyzed 462 (64.07% female) German middle-aged adults regarding their fitness status, physical activity (Non-Exercise test), body composition (Body Mass Index) and heart-related health status. Motor tests were used to measure the health-related fitness status. The heart-related health status was surveyed by questionnaire and diagnosis was done in part by a physician. Relationships between risk factors and fitness factors are visible during the correlative analysis. They are substantially more visible in the differentiation of people with and without risks. People with low fitness show noticeable risks in activity, Body Mass Index and heart-related health. People with high fitness show health resources for activity, Body Mass Index and heart-related health. This study points out that all fitness dimensions influence one’s heart-related health in a positive way. Fitness is measured objectively and includes all health-related fitness dimensions such as endurance, strength, coordination and flexibility. Apart from this standardization, we ask for more longitudinal studies and more objective health measurements