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Beschreibung:
In its Global Risks Report 2017, the World Economic Forum identifies rising income and wealth disparity as one of the top five global development trends that potentially causes unemployment, underemployment, and profound social instability. To counteract this development, it is necessary to quantify inequality and to analyze the distribution of income and wealth. In order to measure inequality and identify factors that significantly impact income or wealth, governments and statistical offices collect data by conducting surveys and censuses. However, collecting data on rather private topics such as income can lead to high item non-response rates. Therefore, it is tempting for survey designers to collect information on income using income bands as opposed to detailed income. This kind of data is commonly known as interval-censored data, grouped data or banded data. It is defined as observing only the lower and upper bound of an income variable with its exact value remaining unknown. Collecting only the interval information instead of continuous data offers a higher degree of data privacy protection to survey respondents, which lowers response burdens and thus leads to lower item non-response rates and higher data quality. This kind of data is already being collected by a number of surveys and censuses. Among them is the biggest annually survey in Europe, the German Microcensus, and the censuses of Australia, Colombia, and New Zealand. While data quality is increased, analyzing interval-censored data requires more advanced statistical methods. This is due to the fact that only the interval information is observed and the underlying data distribution within each interval remains unobserved. For instance, well-established and widely used statistical methods, such as linear and linear mixed regression, require a continuous response variable. Furthermore, formulas to estimate statistical indicators, such as the mean, rely on metric data. While regression models are commonly applied to analyze income and wage, the ...