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Forecasting Current-Quarter U.S.Exports Using Satellite Data

Author

Listed:
  • Jun Nie
  • Amy Oksol

Abstract

Forecasting export growth can be challenging. Export growth depends heavily on demand from foreign countries, which is difficult to directly measure. In practice, forecasters usually use growth in foreign gross domestic product. But GDP data are released with a significant delay, and in some economies, GDP is poorly measured. Nighttime lights data from satellites are able to overcome both of these challenges, making them potentially useful in forecasting U.S. exports. {{p}} Jun Nie and Amy Oksol use nighttime lights data to forecast current-quarter U.S. export growth and compare their forecasts to those generated using foreign GDP. They find that forecasts using monthly nighttime lights data outperform those using quarterly foreign GDP. Their results suggest the greater frequency of lights data could help provide increasingly accurate forecasts of export growth.

Suggested Citation

  • Jun Nie & Amy Oksol, 2018. "Forecasting Current-Quarter U.S.Exports Using Satellite Data," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 5-24.
  • Handle: RePEc:fip:fedker:00065
    DOI: 10.18651/ER/2q18nieoksol
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    Cited by:

    1. Sohrabpour, Vahid & Oghazi, Pejvak & Toorajipour, Reza & Nazarpour, Ali, 2021. "Export sales forecasting using artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 163(C).

    More about this item

    Keywords

    Exports; Forecasting;

    JEL classification:

    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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