IDEAS home Printed from https://ideas.repec.org/a/bla/manchs/v90y2022i2p122-143.html
   My bibliography  Save this article

A reappraisal of Katona’s adaptive theory of consumer behaviour using U.K. data

Author

Listed:
  • Robert Gausden
  • Mohammad Hasan

Abstract

The objective of this paper is to conduct a reappraisal of Katona's (1968) adaptive theory of consumer behaviour, which maintains that discretionary consumption is partly determined by attitudes and expectations of households. Initially, using UK data, we follow Katona by empirically examining whether changes in personal expenditure on durable goods are connected to earlier movements in consumer confidence. Evidence of a lack of a stable relationship between these two variables encourages us to perform a disaggregated analysis involving 111 components of four different forms of consumption, which enables construction of an aggregate measure of discretionary spending. We find that sufficient criteria are satisfied for the sentiment index to be accepted as a reliable predictor of the growth of gratuitous expenditure. In conclusion, then, it would seem that the validity of Katona's theory can be revived if we are prepared to discard the assumption that durable goods’ consumption is synonymous with discretionary spending.

Suggested Citation

  • Robert Gausden & Mohammad Hasan, 2022. "A reappraisal of Katona’s adaptive theory of consumer behaviour using U.K. data," Manchester School, University of Manchester, vol. 90(2), pages 122-143, March.
    • Handle: RePEc:bla:manchs:v:90:y:2022:i:2:p:122-143
    DOI: 10.1111/manc.12395
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/manc.12395
    Download Restriction: no
    File URL: https://libkey.io/10.1111/manc.12395?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Easaw, Joshy Z. & Garratt, Dean & Heravi, Saeed M., 2005. "Does consumer sentiment accurately forecast UK household consumption? Are there any comparisons to be made with the US?," Journal of Macroeconomics, Elsevier, vol. 27(3), pages 517-532, September.
    2. Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994. "Does Consumer Sentiment Forecast Household Spending? If So, Why?," American Economic Review, American Economic Association, vol. 84(5), pages 1397-1408, December.
    3. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    4. Robert Gausden & Mohammad S. Hasan, 2020. "Comparative performances of measures of consumer and economic sentiment in forecasting consumption: a multi-country analysis," Applied Economics, Taylor & Francis Journals, vol. 52(10), pages 1088-1104, February.
    5. Easaw, Joshy Z. & Heravi, Saeed M., 2004. "Evaluating consumer sentiments as predictors of UK household consumption behavior: Are they accurate and useful?," International Journal of Forecasting, Elsevier, vol. 20(4), pages 671-681.
    6. Ahmed, M. Iqbal & Cassou, Steven P., 2016. "Does consumer confidence affect durable goods spending during bad and good economic times equally?," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 86-97.
    7. Robert Gausden & Mohammad S. Hasan, 2016. "Would information on consumer confidence have helped to predict UK household expenditure during the recent economic crisis?," Applied Economics, Taylor & Francis Journals, vol. 48(18), pages 1695-1709, April.
    8. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. Francis X. Diebold, 2015. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 1-1, January.
    11. Jason Bram & Sydney C. Ludvigson, 1998. "Does consumer confidence forecast household expenditure? a sentiment index horse race," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Jun), pages 59-78.
    12. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Croushore, Dean, 2005. "Do consumer-confidence indexes help forecast consumer spending in real time?," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 435-450, December.
    2. Hector H. Sandoval & Anita N. Walsh, 2021. "The role of consumer confidence in forecasting consumption, evidence from Florida," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 757-788, October.
    3. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    4. Vosen, Simeon & Schmidt, Torsten, 2012. "A monthly consumption indicator for Germany based on Internet search query data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19(7), pages 683-687.
    5. McCracken,M.W. & West,K.D., 2001. "Inference about predictive ability," Working papers 14, Wisconsin Madison - Social Systems.
    6. Hinterlang, Natascha, 2019. "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203503, Verein für Socialpolitik / German Economic Association.
    7. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    8. Aneta M. Klopocka & Rumiana Gorska, 2021. "Forecasting Household Saving Rate with Consumer Confidence Indicator and its Components: Panel Data Analysis of 14 European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 874-898.
    9. Benjamin K. Johannsen & Elmar Mertens, 2021. "A Time‐Series Model of Interest Rates with the Effective Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(5), pages 1005-1046, August.
    10. Christos Kallandranis & Socrates Karidis, 2014. "Assessing the Effect of the Consumer-Voter Sentiment on Tiebout-Like Migration: The EU 27 Case," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 14(1), pages 31-55, April.
    11. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    12. Michelle L. Barnes & Giovanni P. Olivei, 2017. "Consumer Attitudes and Their Forecasting Power for Consumer Spending," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 1031-1058, August.
    13. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    14. Bahram Adrangi & Joseph Macri, 2011. "Consumer Confidence and Aggregate Consumption Expenditures in the United States," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 1-18, February.
    15. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    16. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
    17. Hinterlang, Natascha, 2020. "Predicting monetary policy using artificial neural networks," Discussion Papers 44/2020, Deutsche Bundesbank.
    18. Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis.
    19. repec:zbw:rwirep:0208 is not listed on IDEAS
    20. Dudek, Sławomir, 2008. "Consumer Survey Data and short-term forecasting of households consumption expenditures in Poland," MPRA Paper 19818, University Library of Munich, Germany.
    21. Torsten Schmidt & Simeon Vosen, 2010. "A monthly consumption indicator for Germany based on internet search query data," Ruhr Economic Papers 0208, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:manchs:v:90:y:2022:i:2:p:122-143. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/semanuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.