RESPONSE DYNAMICS IN BUSINESS TENDENCY SURVEYS: EVIDENCE FROM POLAND

Main Article Content

Emilia Tomczyk

Abstrakt
In this paper, trends, business cycle correlates and macroeconomic patterns in response rates are explored. Two groups of respondents taking part in the RIED (Research Institute for Economic Development of the Warsaw School of Economics) economic tendency survey are taken into consideration: industrial enterprises and households. Empirical analysis indicates that household response rates rise slightly with consumer price index, and decline during current expansion phase of the economy. Gender, geographical location and city / country residence are not factors in determining household response rate dynamics. In case of industrial enterprises, willingness to answer seems to rise when business conditions deteriorate, and vice versa, although this effect is small in terms of absolute values of correlation coefficients. Non-response is found to be higher when economy expands but the relationship is weak.

Article Details

Jak cytować
Tomczyk, E. (2019). RESPONSE DYNAMICS IN BUSINESS TENDENCY SURVEYS: EVIDENCE FROM POLAND. Metody Ilościowe W Badaniach Ekonomicznych, 20(3), 230–239. https://doi.org/10.22630/MIBE.2019.20.3.22
Bibliografia

Adamowicz E., Walczyk K. (2018) Koniunktura w przemyśle. Luty 2018. Badanie okresowe nr 353. Instytut Rozwoju Gospodarczego (RIED), SGH Warsaw School of Economics (in Polish).

Bańkowska K., Osiewicz M., Pérez-Duarte S. (2015) Measuring Non-Response Bias in a Cross-Country Enterprise Survey. European Central Bank Statistics Paper Series, 12. (Crossref)

Białowolski P., Dudek S., Kowalczyk B. (2005) Analiza zwrotności w badaniach konsumenckich oraz próby poprawiania reprezentatywności na przykładzie badania kondycji gospodarstw domowych. Prace i Materiały Instytutu Rozwoju Gospodarczego (RIED), 76, SGH Warsaw School of Economics (in Polish).

Brick J. M., Tourangeau R. (2017) Responsive Survey Designs for Reducing Nonresponse Bias. Journal of Official Statistics, 33(3), 735-752 [http://dx.doi.org/10.1515/JOS-2017-0034]. (Crossref)

Calinescu M., Schouten B. (2016) Adaptive Survey Designs for Nonresponse and Measurement Error in Multi-Purpose Surveys. Survey Research Methods, 10(1) [https://ojs.ub.uni-konstanz.de/srm/article/view/6157].

Cobben F. (2009) Nonresponse in Sample Surveys: Methods for Analysis and Adjustment. Statistics Netherlands, The Hague [www.cbs.nl].

Curtin R., Presser S., Singer E. (2005) Changes In Telephone Survey Nonresponse Over The Past Quarter Century. The Public Opinion Quarterly, 69, 87-98. (Crossref)

Czajka J. L., Beyler A. (2016) Declining Response Rates in Federal Surveys: Trends and Implications. Mathematica Policy Research, Final Report, 1.

Drozdowicz-Bieć M. (2012) Cykle i wskaźniki koniunktury. Wydawnictwo Poltext, Warszawa (in Polish).

Dudek S. (2017) Kondycja gospodarstw domowych. IV kwartał 2017. Badanie okresowe nr 101. Instytut Rozwoju Gospodarczego (RIED), SGH Warsaw School of Economics (in Polish).

Dudek S., Zając T. (2012) Zastosowanie modeli czynnikowych do konstrukcji barometru koniunktury na podstawie badań ankietowych. Prace i Materiały Instytutu Rozwoju Gospodarczego (RIED), 90, SGH Warsaw School of Economics (in Polish).

Gradzewicz M., Growiec J., Hagemejer J., Popowski P. (2010) Cykl koniunkturalny w Polsce – wnioski z analizy spektralnej. Bank i Kredyt, 41(5), 41-76 (in Polish).

Kowalczyk B., Tomczyk E. (2009) Survey Non-Response and Properties of Expectations of Industrial Enterprises – Analysis Based on Business Tendency Surveys. [in:] Wywiał K., Żądło T. (Eds.) Survey Sampling in Economic and Social Research. 4, 42-59.

Lynn P. (2017) From Standardised to Targeted Survey Procedures for Tackling Non-Response and Attrition. Survey Research Methods, 11(1), 93-103 [doi:10.18148 /srm/2017.v11i1.6734].

Phillips A. W., Reddy S., Durning S. J. (2016) Improving Response Rates and Evaluating Nonresponse Bias in Surveys: AMEE Guide No. 102. Medical Teacher, 38(3), 217-228. (Crossref)

Platek R. (1977) Some Factors Affecting Non-Response. Paper Presented at the 41st Session of the International Statistical Institute, New Delhi, 5-15.

Rassmusen K., Thimm H. (2009) Fact-Based Understanding of Business Survey Non-Response. The Electronic Journal of Business Research Methods, 7(1), 83-92.

Seiler C. (2010): Dynamic Modelling of Nonresponse in Business Surveys. IFO Working Paper 93 [www.cesifo-group.de].

Thompson K., Oliver B. (2012) Response Rates in Business Surveys: Going Beyond the Usual Performance Measure. Journal of Official Statistics, 28(2), 221-237.

Toepoel V., Schonlau M. (2017) Dealing with Nonresponse: Strategies to Increase Participation and Methods for Postsurvey Adjustments. Mathematical Population Studies, 24(2), 79-83 [https://doi.org/10.1080/08898480.2017.1299988]. (Crossref)

Tomczyk E. (2018) To be (Accounted for) or not to be: Factors Influencing Probability of Non-Response in Economic Tendency Surveys. Prace i Materiały Instytutu Rozwoju Gospodarczego (RIED), 100, SGH Warsaw School of Economics.

Wittwer R., Hubrich S. (2015) Nonresponse in Household Surveys: A Survey of Nonrespondents from the Repeated Cross-Sectional Study ”Mobility in Cities – SrV” in Germany. Transportation Research Procedia, 11, 66-84. (Crossref)

Statystyki

Downloads

Download data is not yet available.