Identifying Structural Changes in Austrian Social Insurance Data ★

摘要

Testing for structural changes is a well studied field. Classical tests for breakpoint detection utilize F-statistics which depend on independent and identically normal distributed residuals. In general, this condition is not satisfied which leads to distorted test results when the p-values of classical tests are close to the significance level. Thus, permutation tests are used to properly estimate the critical values.Based on the accounting data of Austrian hospitals, collected by the Austrian social insurance institutions, specific observations (hospital stays) which are connected to pre-defined diseases are analysed. For those groups of observations we use characteristic factors, to test for structural changes from different perspectives. The first test analyses the temporal trend and identifies breakpoints, caused by changes in the underlying system between years. The second analysis focuses on identifying differences between hospitals. Both implemented tests ensure the often ignored aspect of a homogeneous data base for further analysis.