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Time-Frequency Relationship between U.S. Output with Commodity and Asset Prices

Author

Listed:
  • Aviral K. Tiwari

    (Faculty of Management, IBS Hyderabad, IFHE University, Dontanpalli, India)

  • Claudiu T. Albulescu

    (Management Department, Politehnica University of Timisoara, Timisoara, Romania)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

Abstract

Commodity and asset prices have a well-documented effect on economic growth, manifested through various channels. At the same time, the business cycle influences the commodity and asset prices. Whereas empirical evidence on the effect of commodity and asset prices on the long-run economic growth is ambiguous, most of the previous researches highlight a positive correlation in the short-run. The aim of this paper is to disentangle the short- and long-run co-movements between U.S. historical business cycles and commodity and asset prices, over the period 1859-2013. For this purpose we use a time-frequency approach and we test the historical influence of oil, gold, housing and stock prices, over the output growth. Different from other studies, we control for the effect of other prices and monetary conditions, using the wavelet partial coherency. In line with the previous works, we discover that co-movements between economic growth and commodity and assets prices manifest especially in the short-run. We also find that stock returns and housing prices have a more powerful effect on the U.S. economic growth rate than the oil and gold prices. The long-run co-movements are documented especially around the World War II. Finally, when controlling for the influence of the interest rate, inflation and other commodity and asset prices, co-movements become weaker in the short-run. In general the oil and housing prices lead the GDP growth, the U.S. output lead the gold prices, while there is no clear causality direction between business cycle and stock prices.

Suggested Citation

  • Aviral K. Tiwari & Claudiu T. Albulescu & Rangan Gupta, 2015. "Time-Frequency Relationship between U.S. Output with Commodity and Asset Prices," Working Papers 201523, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201523
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    Cited by:

    1. Białkowski, Jędrzej & Dang, Huong Dieu & Wei, Xiaopeng, 2022. "High policy uncertainty and low implied market volatility: An academic puzzle?," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1185-1208.
    2. Oscar V. De la Torre-Torres & José Álvarez-García & María de la Cruz del Río-Rama, 2024. "An EM/MCMC Markov-Switching GARCH Behavioral Algorithm for Random-Length Lumber Futures Trading," Mathematics, MDPI, vol. 12(3), pages 1-20, February.
    3. Zhu, Huiming & Xia, Xiling & Hau, Liya & Zeng, Tian & Deng, Xi, 2024. "Time-frequency higher-order moment Co-movement and connectedness between Chinese stock and commodity markets," International Review of Economics & Finance, Elsevier, vol. 96(PA).
    4. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    5. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    6. Nikolaos Antonakakis & Rangan Gupta & John W. Muteba Mwamba, 2016. "Dynamic Comovements Between Housing and Oil Markets in the US over 1859 to 2013: a Note," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(3), pages 377-386, September.
    7. Thomas Conlon & Brian M. Lucey & Gazi Salah Uddin, 2018. "Is gold a hedge against inflation? A wavelet time-scale perspective," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 317-345, August.
    8. Sharma, Gagan Deep & Tiwari, Aviral Kumar & Talan, Gaurav & Jain, Mansi, 2021. "Revisiting the sustainable versus conventional investment dilemma in COVID-19 times," Energy Policy, Elsevier, vol. 156(C).
    9. Xu Zhang & Xiaoxing Liu & Jianqin Hang & Dengbao Yao, 2018. "The dynamic causality between commodity prices, inflation and output in China: a bootstrap rolling window approach," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 407-425, January.
    10. Funashima, Yoshito, 2016. "Governmentally amplified output volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 469-478.

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    Keywords

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • N11 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - U.S.; Canada: Pre-1913
    • N12 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - U.S.; Canada: 1913-

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