Acta academica karviniensia 2020, 20(1):47-57 | DOI: 10.25142/aak.2020.004
Úprava váhového schématu výpočtu konjunkturálních průzkumů
- Prague University of Economics and Business, Faculty of Informatics and Statistics
The Business and Consumer Survey is a commonly used and easy-to-follow tool for describing the current and near-future situation in the national economy. A lot of countries use leading indicators for economic predictions. The computations of the indicators are generally based on weighting schemes considering the importance of each survey questions groups. The European Commission harmonizes the weighting schemes for those calculations. In this article, we adjust the weighting scheme of the Economic Sentiment Indicator as the main result of the Business and Consumer Survey and design a new weighting structure of the calculation. To find a new weighting scheme, we use a combination of a penalty method which measures L3-based-norm distance between all original weights and the proposed ones, adapting the weight system to the Czech economic data. Applying the penalty functions is a method of respecting the original, empirically estimated weights used for the indicator's calculations on a long-term basis. The modified weighting scheme for the Economic Sentiment Indicator construction is supposed to ensure better predictions and, eventually, provide early warnings about any unexpected changes in the business cycle in the national economy.
Klíčová slova: business and consumer survey, optimization, prediction ability, weighting scheme.
JEL classification: C10, C22
Vloženo: 2. říjen 2020; Revidováno: 4. prosinec 2020; Přijato: 16. prosinec 2020; Zveřejněno: 17. prosinec 2020 Zobrazit citaci
Reference
- ANCUSA, V., R. BOGDAN and O. CAUS, 2015, June. A Complex Network-Based Visual Analysis of Business Tendency and Consumer Opinion Surveys. In ECRM2015-Proceedings of the 14th European Conference on Research Methods 2015: ECRM 2015 (p. 10). Academic Conferences Limited.
- BRAND D. A., M. SAISANA, L. A. RYNN, F. PENNONI and A. B. LOWENFELS, 2007. Comparative Analysis of Alcohol Control Policies in 30 Countries, PLoS Medicine, 0759 April 2007, Vol. 4, 4, e151:0752-0759, www.plosmedicine.org
Přejít k původnímu zdroji...
- CZECH STATISTICAL OFFICE, 2020. Business cycle surveys. Available at: https://www.czso.cz/csu/czso/business_cycle_surveys
- DIBIASI, A., K. ABBERGER, M. SIEGENTHALER and J. E. STURM, 2018. The effects of policy uncertainty on investment: Evidence from the unexpected acceptance of a far-reaching referendum in Switzerland. European Economic Review, 104, pp. 38-67.
Přejít k původnímu zdroji...
- EMERSON, R. A. and D. F. HENDRY, 1996. An evaluation of forecasting using leading indicators. Journal of Forecasting, 15(4), pp. 271-291
Přejít k původnímu zdroji...
- EUROPEAN COMMISSION, 2020. User guide. Available: https://ec.europa.eu/info/sites/info/files/bcs_user_guide_en_0.pdf
- EUROSTAT, 2020. Glossary: Leading indicator. Available: https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Leading_indicator
- GOGGIN, J., 2008. An analysis of the potential of the European Commission business and consumer surveys for macroeconomic forecasting. Quarterly Economic Commentary: Special Articles, 2008(4-Winter), pp. 46-67.
- HÖLZL, W., S. KANIOVSKI and Y. KANIOVSKI, 2019. Exploring the dynamics of business survey data using Markov models. Computational Management Science, 16(4), 621-649.
Přejít k původnímu zdroji...
- KAUFMANN, D. and R. SCHEUFELE, 2017. Business tendency surveys and macroeconomic fluctuations. International Journal of Forecasting, 33(4), 878-893.
Přejít k původnímu zdroji...
- LEHMANN, R., 2020. Forecasting exports across Europe: What are the superior survey indicators?. Empirical Economics, 1-25.
Přejít k původnímu zdroji...
- KEARNEY, I., 1991. A Preliminary Analysis of the CII/ESRI Business Survey Data. ESRI, mimeo.
- MEĻIHOVS, A. and S. RUSAKOVA, 2005. Short-Term Forecasting of Economic Development in Latvia Using Business and Consumer Survey Data (No. 2005/04). Latvijas Banka.
- OECD, European Commission, 2008. Handbook on Constructing Composite Indicators. Methodology and user guide. Available: https://www.oecd.org/sdd/42495745.pdf
- PTÁČKOVÁ, V., L. ŠTĚPÁNEK and V. HANZAL. Business and Consumer Surveys: the Weighting Scheme. In Löster, T., Pavelka, T. (ed.). International Days of Statistics and Economics 2019. Slaný: Melandrium, Libuše Macáková, 2019, s. 1234 - 1243. ISBN 978-80-87990-18-6. URL: https://msed.vse.cz/msed_2019/article/182-Ptackova-Veronika-paper.pdf
- R CORE TEAM, 2014. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org.
- SAISANA, M. and S. TARANTOLA, 2002. State-of-the-art report on current methodologies and practices for composite indicator development, EUR 20408 EN, European Commission-JRC: Italy.
- SAMMUT, C. and G. I. WEBB, 2011. Mean Squared Error. Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_528
Přejít k původnímu zdroji...
- SHARMA, A. K., 2005. Text Book of Correlations and Regression. Discovery Publishing Pvt. Ltd. ISBN: 8171419356