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Nowcasting LSM Growth in Pakistan

Author

Listed:
  • Fida Hussain

    (State Bank of Pakistan)

  • Kalim Hayder

    (State Bank of Pakistan)

  • Muhammad Rehman

    (State Bank of Pakistan)

Abstract

This paper attempts to Nowcast Large-scale Manufacturing (LSM) growth in Pakistan, which is generally used as a potential proxy for economic activity in Pakistan. For this purpose, the dynamic factor and penalize regression models are used to extract the unique information set from a range of variables having close association with LSM. Given high seasonality induced volatility in LSM growth, we have also attempted to nowcast the trend and cycles separately. The estimation results show that the predicted LSM series is fairly tracking the actual LSM series. Penalize regression models perform remarkably well in tracing cycles in LSM growth. Whereas, dynamic factor model is more successful in tracing the underlying trend in LSM growth.

Suggested Citation

  • Fida Hussain & Kalim Hayder & Muhammad Rehman, 2018. "Nowcasting LSM Growth in Pakistan," SBP Working Paper Series 98, State Bank of Pakistan, Research Department.
  • Handle: RePEc:sbp:wpaper:98
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    File URL: http://www.sbp.org.pk/publications/wpapers/2018/wp98.pdf
    File Function: First version, 2018
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    More about this item

    Keywords

    Nowcasting; Large-scale Manufacturing; Factor Model; Rigged Regressions;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

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