|Seiler, Christian (2010): Dynamic modelling of Nonresponse in Business Surveys. Department of Statistics: Technical Reports, No.93|
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.
|Item Type:||Paper (Technical Report)|
|Keywords:||Business survey, Logistic regression, Nonresponse, Panel survey, Varying-coefficient model|
|Collections:||Mathematics, Computer Science and Statistics > Statistics > Technical Reports|
|Subjects:||500 Science > 510 Mathematics|
|JEL Classification:||C33, C44, C81, C83|
|Deposited On:||11. Nov 2010 09:00|
|Last Modified:||11. Feb 2015 19:48|
Abberger, K., Birnbrich, M., and Seiler, C. (2009). Der ’Test des Tests’ im Handel - Eine Metaumfrage zum ifo Konjunkturtest. ifo Schnelldienst, 62(21):34–41.
Becker, S. O. and Wohlrabe, K. (2008). Micro Data at the Ifo Institute for Economic Research - The "Ifo Business Survey", Usage and Access. Journal of Applied Social Science Studies, 128(2):307–319.
Brehm, J. (1994). Stubbing out Toes for a Foot in the Door? Prior Contacts, Incentives and Survey Response. International Journal of Public Opinion Research, 6(1):45–63.
de Leeuw, E. and de Heer, W. (2002). Trends in Household Survey Nonresponse: A Longitudinal and International Comparison. In Groves, R. M., Dillman, D. A., Eltinge, J. L., and Little, R. J., editors, Survey Nonresponse, chapter 3, pages 41–54.Wiley.
Eilers, P. H. C. and Marx, B. D. (1996). Flexible smoothing using B-splines and penalized likelihood. Statistical Science, 11:89–121.
Goldrian, G., editor (2007). Handbook of Survey-Based Business Cycle Analysis. Edward Elgar Publishing.
Groves, R. M., Fowler, J. F., Couper, M. P., Lepkowski, J. M., Singer, E., and Tourangeau, R. (2004). Survey Methodology. Wiley and Sons.
Harris-Kojetin, B. and Tucker, C. (1999). Exploring the Relation of Economical and Political Conditions with Refusal Rates to a Government Survey. Journal of Official Statistics, 15(2):167–184.
Hastie, T. and Tibshirani, R. (1993). Varying-coefficient Models. Journal of the Royal Statistical Society, Series B, 55(4):757–796.
Hawkes, D. and Plewis, I. (2006). Modelling non-response in the National Child Development Study. Journal of the Royal Statistical Society, Series A, 169(3):479–491.
Hönig, A. (2009). The New EBDC Dataset: An Innovative Combination of Survey and Financial Statement Data. CESifo Forum, 10(4):62–63.
Janik, F. and Kohaut, S. (2009). Why Don’t They Answer? – Unit Non-Response in the IAB Establishment Panel. FDZ Methodenreport 7/2009, Bundesagentur für Arbeit.
Kalsbeek,W. D., Yang, J., and Agans, R. P. (2002). Predictors of nonresponse in a longitudinal survey of adolescents. In ASA Proceedings of the Joint Statistical Meetings, pages 1740–1745.
Kwak, N. and Radler, B. (2002). A Comparison Between Mail and Web Surveys: Response Pattern, Respondent Profile, and Data Quality. Journal of Official Statistics, 18(2):257–273.
Laurie, H., Smith, R., and Scott, L. (1999). Strategies for Reducing Nonresponse in a Longitudinal Panel Survey. Journal of Official Statistics, 15(2):269–282.
Lepkowski, J. M. and Couper, M. P. (2002). Nonresponse in the Second Wave of Longitudinal Household Surveys. In Groves, R. M., Dillman, D. A., Eltinge, J. L., and Little, R. J., editors, Survey Nonresponse, chapter 17, pages 259–272.Wiley.
Schräpler, J. P. (2004). Respondent Behavior in Panel Studies - A Case Study for Income-Nonresponse by means of the German Socio-Economic Panel (SOEP). Sociological Methods and Research, 33(1):118–156.
Steel, D. G., Holt, D., and Tranmer, M. (1996). Making Unit-Level Inferences from Aggregated Data. Survey Methodology, 22:3–15.
Tomaskovic-Devey, D., Leiter, J., and Thompson, S. (1994). Organizational Survey Nonresponse. Administrative Science Quarterly, 39:439–457.
Tomaskovic-Devey, D., Leiter, J., and Thompson, S. (1995). Item Nonresponse in Organizational Surveys. Sociological Methodology, 25:77–100.
Tutz, G. and Binder, H. (2004). Flexible modelling of discrete failure time including time-varying smooth effects. Statistics in Medicine, 23:2445–2461.
Willimack, D. K., Nichols, E., and Sudman, S. (2002). Understanding Unit and Item Nonresponse in Business Surveys. In Groves, R. M., Dillman, D. A., Eltinge, J. L., and Little, R. J., editors, Survey Nonresponse, chapter 14, pages 213–227.Wiley.
Wood, S. N. (2006). Generalized Additive Models: An Introduction with R. Chapman and Hall, CRC.
Available Versions of this Item
- Dynamic modelling of Nonresponse in Business Surveys. (deposited 11. Nov 2010 09:00) [Currently Displayed]