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Estimation and Forecasting of Industrial Production Index

Author

Listed:
  • Muhammad Ejaz

    (State Bank of Pakistan)

  • Javed Iqbal

    (State Bank of Pakistan)

Abstract

It is essential for policy makers to timely consider the cyclical changes in output. Monthly industrial production is one of the most important and commonly used macroeconomic indicators for this purpose. In Pakistan monthly estimates of industrial production are not available. Alternatively, policy makers rely on Large Scale Manufacturing (LSM) index which accounts for only 10% of the GDP. Another limitation of LSM is that it mainly accounts for private sector industry thus leaving out direct public sector presence in industrial production. LSM is relied upon heavily by economic policy makers to gauge economic activity in Pakistan. In this paper, we present a new Industrial Production Index (IPI), which covers whole of industrial sector in Pakistan. The advantage of this IPI index is that it provides additional information that LSM misses out. Post estimation, we built seven econometrics models reflecting conditions in real, financial and external sectors to estimate YoY changes in the proposed Instrial Production Index (IPI). Our results show that the root mean square error of the ARDL model reflecting financial conditions is lowest across all horizons

Suggested Citation

  • Muhammad Ejaz & Javed Iqbal, 2019. "Estimation and Forecasting of Industrial Production Index," SBP Working Paper Series 103, State Bank of Pakistan, Research Department.
    • Handle: RePEc:sbp:wpaper:103
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    References listed on IDEAS

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    Cited by:

    1. Bilge Pekçaglayan, 2021. "Determinants of Industrial Production in Turkey: ARDL Model," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 71(71-2), pages 435-456, December.

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    More about this item

    Keywords

    Economic Indicator; Industry Studies; Econometric Forecasting;
    All these keywords.

    JEL classification:

    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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