Dynamic Modelling of Nonresponse in Business Surveys

It is well-known that nonresponse affects the results of surveys and can even causebias due to selectivities if it cannot be regarded as missing at random. In contrast tohousehold surveys, response behaviour in business surveys has been examined rarely inthe literature. This paper is one of the first which analyses a large business survey onmicro data level for unit nonresponse. The data base is the Ifo Business TendencySurvey, which was established in 1949 and has more than 5,000 responding firms eachmonth. The panel structure allows to use statistical modelling including time-varyingeffects to check for the existence of a panel fatigue. The results show that there are hugedifferences in business characteristics such as size or sub-sector and that nonresponse ismore frequent in economically good times.