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The Level of Economic Development and the Savings Rate of Households

Author

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  • Malgorzata Grzywinska-Rapca
  • Aleksandra A. Olejarz

Abstract

Purpose: The aim of this article was to present the G7 household savings rate models, including the extraction and identification of time series components that determine the formation of the studied phenomenon. Design/Methodology/Approach: The research was carried by a detailed analysis of the savings rates of G7 households in individual quarters in the years 2000-2018. Time series decomposition and identification of time series components, including the seasonal component, trend and outliers were made using econometric tools. The analyses used the automatic seasonal adjustment procedures TRAMO-SEATS and ARIMA-X-12. The obtained models were formally verified empirically. Findings: The decomposition of the time series of the G7 household savings rate provided information on the shaping of the analysed phenomenon. Using the Tramo-Seats procedure, it was shown that the savings rate of the United States, Canada and France is not subject to seasonal fluctuations, and the visible fluctuations are the result of the moving average process and outliers. Seasonal savings occurred in the case of Japan, Germany, Italy, and Great Britain. This seasonality was of a different nature, with the largest seasonal deviations recorded for Germany and Italy. Practical implications: In this paper the components of the time series of savings rates of G7 households were analysed and distinguished, showing differences in the development of the analysed phenomenon in individual countries, providing the appropriate economic justification for the differences. Originality/Value: In macroeconomic scale, households play an important role in the economy, creating the conditions for the sustainable development of the economy. They are an important source of financing for business investment and budget deficits. In a microeconomic perspective, a low savings rate can reduce the living conditions of the population, which has many negative effects. Taking this into account the above, learning about the development of the phenomenon under study, which is the household savings rate, allows to predict and adjust economic programs to optimize the desired effects.

Suggested Citation

  • Malgorzata Grzywinska-Rapca & Aleksandra A. Olejarz, 2021. "The Level of Economic Development and the Savings Rate of Households," European Research Studies Journal, European Research Studies Journal, vol. 0(2 - Part ), pages 430-442.
    • Handle: RePEc:ers:journl:v:xxiv:y:2021:i:2-part2:p:430-442
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    References listed on IDEAS

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    1. John Y. Campbell & N. Gregory Mankiw, 1989. "Consumption, Income, and Interest Rates: Reinterpreting the Time Series Evidence," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 185-246, National Bureau of Economic Research, Inc.
    2. Ramesh Mohan, 2006. "Causal Relationship Between Savings And Economic Growth In Countries With Different Income Levels," Economics Bulletin, AccessEcon, vol. 5(3), pages 1-12.
    3. William S. Cleveland & Douglas M. Dunn & Irma J. Terpenning, 1979. "SABL: A Resistant Seasonal Adjustment Procedure with Graphical Methods for Interpretation and Diagnosis," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 201-241, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    Savings rate; households; TRAMO-SEATS procedure.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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