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On the Sources of the Feldstein–Horioka Puzzle across Time and Frequencies

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  • Jun‐Hyung Ko
  • Yoshito Funashima

Abstract

This study quantitatively assesses existing explanations for the Feldstein–Horioka puzzle using time–frequency domain analyses for nine countries for the period 1885–2010. The main findings are summarized as follows. First, large economies (e.g. the United States, Italy) show higher correlations between saving and investment than middle‐sized and small countries do. Second, countries can be grouped into two time‐changing patterns of correlations: inverted U‐shaped and increasing patterns. Third, the fiscal balance seems most related to a positive saving‐investment correlation in many countries. Fourth, a global common factor plays an important role in explaining the Feldstein–Horioka puzzle.

Suggested Citation

  • Jun‐Hyung Ko & Yoshito Funashima, 2019. "On the Sources of the Feldstein–Horioka Puzzle across Time and Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 889-910, August.
    • Handle: RePEc:bla:obuest:v:81:y:2019:i:4:p:889-910
    DOI: 10.1111/obes.12293
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    Cited by:

    1. Vasudeva N. R. Murthy & Natalya Ketenci, 2020. "Capital mobility in Latin American and Caribbean countries: new evidence from dynamic common correlated effects panel data modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-17, December.
    2. Makin, Anthony J. & Ratnasiri, Shyama, 2023. "New estimates of international capital mobility for select OECD economies," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 127-138.
    3. João Martins, 2022. "Bond Yields Movement Similarities and Synchronization in the G7: A Time–Frequency Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 189-214, July.
    4. Hakan Yetkiner & Gamze Öztürk & Bahar Taş, 2024. "Consumption convergence: theory and evidence," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 619-643, August.
    5. Bales, Stephan & Burghof, Hans-Peter, 2024. "Public attention, sentiment and the default of Silicon Valley Bank," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    6. Funashima, Yoshito, 2020. "Money stock versus monetary base in time–frequency exchange rate determination," Journal of International Money and Finance, Elsevier, vol. 104(C).
    7. Funashima Yoshito, 2021. "Time–Frequency Regression," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 21-32, January.
    8. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    9. Mustapha Olalekan Ojo & Luís Aguiar-Conraria & Maria Joana Soares, 2019. "A Time-Frequency Analysis of Sovereign Debt Contagion in Europe," NIPE Working Papers 11/2019, NIPE - Universidade do Minho.
    10. Mustapha Olalekan Ojo & Luís Aguiar‐Conraria & Maria Joana Soares, 2024. "The performance of OECD's composite leading indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2265-2277, April.
    11. Bales, Stephan, 2022. "Policy uncertainty and the sovereign-bank nexus: A time-frequency analysis using wavelet transformation," Finance Research Letters, Elsevier, vol. 44(C).

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F3 - International Economics - - International Finance

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