Dynamic modelling of Nonresponse in Business Surveys

It is well-known that nonresponse affects the results of surveys and can even cause bias due to selectivities if it cannot be regarded as missing at random. In contrast to household surveys, response behaviour in business surveys has been examined rarely in the literature. This paper is one of the first which analyses a large business survey on micro data level for unit nonresponse. The data base is the Ifo Business Tendency Survey, which was established in 1949 and has more than 5,000 responding firms each month. The panel structure allows to use statistical modelling including time-varying effects to check for the existence of a panel fatigue. The results show that there are huge differences in business characteristics such as size or subsector and that nonresponse is more frequent in economically good times