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Should Transportation Output be Included as Part of the Coincident Indicators System?

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  • Kajal Lahiri
  • Wenxiong Yao

Abstract

With the increasing importance of the service-providing sectors, information from these sectors has become essential to the understanding of contemporary business cycles. This paper explores the usefulness of the transportation services output index (TSI) as an additional coincident indicator in determining the peaks and troughs of U.S. economy. The index represents a service sector that plays a central role in facilitating economic activities between sectors and across regions, and can be useful in monitoring the current state of the economy. We evaluate the marginal contribution of the TSI in identifying cyclical turning points in the context of four currently used NBER indicators. The TSI is found to have advantages over the composite index of coincident indicators in identifying turning points, and has been of critical importance in recent recessions.

Suggested Citation

  • Kajal Lahiri & Wenxiong Yao, 2011. "Should Transportation Output be Included as Part of the Coincident Indicators System?," CESifo Working Paper Series 3477, CESifo.
    • Handle: RePEc:ces:ceswps:_3477
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    References listed on IDEAS

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    1. Thor Hultgren, 1948. "American Transportation in Prosperity and Depression," NBER Books, National Bureau of Economic Research, Inc, number hult48-1, September.
    2. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
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    Cited by:

    1. Zhang, Lili & Zhong, Juandan, 2024. "Transportation sector and Chinese stock volatility forecasting: Evidence from freight and passenger traffic," Finance Research Letters, Elsevier, vol. 60(C).
    2. Arora, Vipin & Lieskovsky, Jozef, 2016. "Electricity Use as an Indicator of U.S. Economic Activity," EconStor Research Reports 126147, ZBW - Leibniz Information Centre for Economics.
    3. Boriss Siliverstovs, 2015. "Dissecting the purchasing managers' index," KOF Working papers 15-376, KOF Swiss Economic Institute, ETH Zurich.
    4. Lourenço, Nuno & Rua, António, 2021. "The Daily Economic Indicator: tracking economic activity daily during the lockdown," Economic Modelling, Elsevier, vol. 100(C).
    5. Chew Lian Chua & Sarantis Tsiaplias & Ruining Zhou, 2024. "Constructing a high‐frequency World Economic Gauge using a mixed‐frequency dynamic factor model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2212-2227, September.
    6. Eduardo A. Haddad & Renato S. Vieira & Inácio F. Araújo & Silvio M. Ichihara & Fernando S. Perobelli & Karina S. S. Bugarin, 2022. "COVID-19 crisis monitor: assessing the effectiveness of exit strategies in the State of São Paulo, Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(2), pages 501-525, April.
    7. Galina Ševčenko-Kozlovska & Kristina Čižiūnienė, 2022. "The Impact of Economic Sustainability in the Transport Sector on GDP of Neighbouring Countries: Following the Example of the Baltic States," Sustainability, MDPI, vol. 14(6), pages 1-26, March.
    8. Liudmila Kitrar & Tamara Lipkind & Georgy Ostapkovich, 2020. "Information Content of Russian Services Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(1), pages 59-74, April.
    9. António Rua & Nuno Lourenço, 2020. "The DEI: tracking economic activity daily during the lockdown," Working Papers w202013, Banco de Portugal, Economics and Research Department.

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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