Backward assessments or expectations: what determines the consumer confidence index more strongly? Panel model based on the CCI of European countries

Małgorzata Grzywińska-Rąpca; Aneta Ptak-Chmielewska

doi:10.59139/ws.2023.02.1

Małgorzata Grzywińska-Rąpca Uniwersytet Warmińsko-Mazurski w Olsztynie, Wydział Nauk Ekonomicznych, Polska / University of Warmia and Mazury in Olsztyn, Faculty of Economic Sciences, Poland ORCID: https://orcid.org/0000-0003-2088-2795 , Aneta Ptak-Chmielewska Szkoła Główna Handlowa w Warszawie, Kolegium Analiz Ekonomicznych, Polska / SGH Warsaw School of Economics, Collegium of Economic Analysis, Poland ORCID: https://orcid.org/0000-0002-9896-4240 Wiadomości Statystyczne. The Polish Statistician, vol. 68, 2023, 2, s. 1-15 Opublikowano online: 28 lutego 2023 DOI 10.59139/ws.2023.02.1 Sposób cytowania: Grzywińska-Rąpca, M., Ptak-Chmielewska, A. (2023). Backward assessments or expectations: what determines the consumer confidence index more strongly? Panel model based on the CCI of European countries. Wiadomości Statystyczne. The Polish Statistician, 68(2), 1–15. https://doi.org/10.59139/ws.2023.02.1.

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ARTYKUŁ

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STRESZCZENIE

The consumer confidence index (CCI) is an index constructed on the basis of subjective assessments of the economic situation (retroactive and future), in many studies used as a variable supplementing the forecasting of consumer behaviour. Its significance is evidenced by the literature on consumer sentiment. Research on developed, economically stable countries focuses on assessments of the economic situation in the preceding period. On the other hand, according to many authors, the analysis of economically unstable states should focus on the expectations of respondents. The aim of the study is to check which respondent assessments (retroactive or expectations for the future) have a statistically significant impact on the level of the CCI and to examine the differences in respondent assessments between countries (cross-sectionally), as well as the time differences (time series effects). The panel modelling was carried out using data for the CCI as a dependent variable and a set of independent variables for all European Union countries and five non-member states. The data were collected from the Eurostat database. The analysis period of seven years and five months (January 2015–May 2022) results from the availability of data. The SAS 9.4 software was used in this research.
The results of the survey showed that higher expectations of respondents result in a higher CCI, and that they have a statistically significant impact on the level of the index. The modelling also demonstrated that the differences in respondent’ assessments between countries are significant, whereas the time differences are not.

SŁOWA KLUCZOWE

consumer confidence index, CCI, subjective assessment, panel model, European countries

JEL

C22, C33, D14, E21, G50

BIBLIOGRAFIA

Abaidoo, R. (2012). Macroeconomic uncertainty, consumer sentiments, consumption expenditures and US fixed private investment growth. Journal of Applied Business Research, 28(1), 133–144. https://doi.org/10.19030/jabr.v28i1.6690.

Bai, J. (2009). Panel data models with interactive fixed effects. Econometrica, 77(4), 1229–1279. https://doi.org/10.3982/ECTA6135.

Baltagi, B. H. (2013). Econometric Analysis of Panel Data. John Wiley & Sons.

Batchelor, R., & Dua, P. (1998). Improving Macroeconomic Forecasts: The Role of Consumer Confidence. International Journal of Forecasting, 14(1), 71–81. https://doi.org/10.1016/S0169-2070(97)00052-6.

Białowolski, P. (2014). Consumer confidence, durable goods purchase and unemployment forecast. Ekonometria. Econometrics, (3), 42–55. https://doi.org/10.15611/ekt.2014.3.04.

Boneva, L., & Linton, O. (2017). A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issurance (Bank of England Staff Working Paper No. 640). http://dx.doi.org/10.2139/ssrn.2904941.

Bram, J., & Ludvigson, S. (1998). Does Consumer Confidence Forecast Household Expenditure? A Sentiment Index Horse Race. Federal Reserve Bank of New York Economic Policy Review, 4(2), 59–78. https://www.newyorkfed.org/medialibrary/media/research/epr/98v04n2/9806bram.pdf.

Carroll, C. D., Fuhrer, J. C., & Wilcox, D. W. (1994). Does Consumer Sentiment Forecast Household Spending? If So, Why?. The American Economic Review, 84(5), 1397–1408.

Çelik, S. (2010). An unconventional analysis of consumer confidence index for the Turkish economy. International Journal of Economics and Finance Studies, 2(1), 121–129.

Çelik, S., Aslanoglu, E., & Uzun, S. (2010). Determinants of Consumer Confidence in Emerging Economies: A Panel Cointegration Analysis. Topics in Middle Eastern and North African Economies, 12, 1–20. https://ecommons.luc.edu/cgi/viewcontent.cgi?article=1124&context=meea.

Çelik, S., & Özerkek, Y. (2009). Panel cointegration analysis of consumer confidence and personal consumption in the European Union. Journal of Business Economics and Management, 10(2), 161–168. https://doi.org/10.3846/1611-1699.2009.10.161-168.

Cotsomitis, J. A., & Kwan, A. C. (2006). Can Consumer Confidence Forecast Household Spending? Evidence from the European Commission Business and Consumer Surveys. Southern Economic Journal, 72(3), 597–610. https://doi.org/10.2307/20111835.

Daskalopoulou, I. (2014). Consumer Confidence Index. In A. C. Michalos (Ed.), Encyclopedia of Quality of Life and Well-Being Research (pp. 1214–1216). Springer. https://doi.org/10.1007/978-94-007-0753-5_542.

Desroches, B., & Gosselin, M.-A. (2002). The usefulness of consumer confidence indexes in the United States (Working Paper 2002-22). https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp02-22.pdf.

Eurostat. (n.d). Business and consumer surveys. https://ec.europa.eu/eurostat/cache/metadata/en/ei_bcs_esms.htm#unit_measure1675328008110.

Fan, J., Hu, J., Kong, L., & Zhang, X. (2017). Relationship between energy production and water resource utilization: A panel data analysis of 31 provinces in China. Journal of Cleaner Production, 167, 88–96. https://doi.org/10.1016/j.jclepro.2017.08.167.

Feng, G., Peng, B., Su, L., & Tao Yang, T. (2019). Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice. Journal of Econometrics, 212(2), 607–622. https://doi.org/10.1016/j.jeconom.2019.05.018.

Fisher, K. L., & Statman, M. (2003). Consumer confidence and stock returns. The Journal of Portfolio Management, 30(1), 115–127. https://doi.org/10.3905/jpm.2003.319925.

Floro, D., & van Roye, B. (2017). Threshold effects of financial stress on monetary policy rules. A panel data analysis (European Central Bank Working Paper Series No. 2042). https://doi.org/10.2866/419677.

Garrett, T. A., Hernández-Murillo, R., & Owyang, M. T. (2005). Does Consumer Sentiment Predict Regional Consumption. Federal Reserve Bank of St. Louis Review, 87(2), 123–135. https://files.stlouisfed.org/files/htdocs/publications/review/05/03/part1/GarrHernOwy.pdf.

Golinelli, R., & Parigi, G. (2003). What is this thing called confidence? A comparative analysis of consumer confidence indices in eight major countries (Economic Working Paper No. 484). https://www.bancaditalia.it/pubblicazioni/temi-discussione/2003/2003-0484/tema_484_03.pdf.

Görmüş, Ş., & Güneş, S. (2010). Consumer confidence, stock prices and exchange rates: The case of Turkey. Applied Econometrics and International Development, 10(2), 103–114. https://www.usc.es/economet/reviews/aeid1029.pdf.

Grzywińska-Rąpca, M. (2019). Regional differentiation of households in the context of a subjective assessment of the level of income. Nierówności Społeczne a Wzrost Gospodarczy, 60(4), 227–241. http://dx.doi.org/10.15584/nsawg.2019.4.15.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate Data Analysis (8th edition). Cengage.

Hsiao, C. (2014). Analysis of Panel Data (3rd edition). Cambridge University Press. https://doi.org/10.1017/CBO9781139839327.

Hu, J., Liu, F., & You, J. (2014). Panel data partially linear model with fixed effects, spatial autoregressive error components and unspecified intertemporal correlation. Journal of Multivariate Analysis, 130, 64–89. https://doi.org/10.1016/j.jmva.2014.05.002.

Islam, T. U., & Mumtaz, M. N. (2016). Consumer Confidence Index and Economic Growth: An Empirical Analysis of EU Countries. Euro Economica, 35(2), 17–21. https://journals.univ-danubius.ro/index.php/euroeconomica/article/view/3541/3685.

Jansen, W. J., & Nahuis, N. J. (2003). The stock market and consumer confidence: European evidence. Economics letters, 79(1), 89–98. https://doi.org/10.1016/S0165-1765(02)00292-6.

Leeper, E. M. (1992). Consumer Attitudes: King for a Day. Economic Review, 77(4), 1–15. https://fraser.stlouisfed.org/files/docs/publications/frbatlreview/rev_frbatl_199207.pdf?utm_source=direct_download.

Lemmon, M., & Portniaguina, E. (2006). Consumer Confidence and Asset Prices: Some Empirical Evidence. The Review of Financial Studies, 19(4), 1499–1529. https://doi.org/10.1093/rfs/hhj038.

Lopez, H. B., & Durré, A. (2003, July 1). The determinants of consumer confidence: the case of United States and Belgium. http://webdoc.sub.gwdg.de/ebook/serien/e/CORE/dp2003-53.pdf.

Loría, E., & Brito, L. (2004). Is the Consumer Confidence Index a Sound Predictor of the Private Demand in the United States?. Estudios de Economía Aplicada, 22(3), 795–809. https://www.redalyc.org/pdf/301/30122317.pdf.

Ludvigson, S. C. (2004). Consumer Confidence and Consumer Spending. The Journal of Economic Perspectives, 18(2), 29–50. https://doi.org/10.1257/0895330041371222.

Matsusaka, J. G., & Sbordone, A. M. (1995). Consumer Confidence and Economic Fluctuation. Economic Inquiry, 33(2), 296–318. https://doi.org/10.1111/j.1465-7295.1995.tb01864.x.

Qiu, J., Ma, Q., & Wu, L. (2019). A moving blocks empirical likelihood method for panel linear fixed effects models with serial correlations and cross-sectional dependences. Economic Modelling, 83, 394–405. https://doi.org/10.1016/j.econmod.2019.09.029.

Utaka, A. (2014). Consumer Confidence and the Japanese Economy-Comparison of Pre- and Post- Bubble Period. Economics Bulletin, 34(2), 1165–1173.

Wałęga, A. (2012). Zróżnicowanie poziomu i źródeł dochodów gospodarstw pracowniczych w Polsce. Acta Universitatis Lodziensis. Folia Oeconomica, 271. Statystyka w praktyce społecznogospodarczej, 219–232.

Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. MIT Press.

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