Nowcasting LSM Growth in Pakistan

Fida Hussain (), Kalim Hayder () and Muhammad Rehman ()
Additional contact information
Fida Hussain: State Bank of Pakistan
Kalim Hayder: State Bank of Pakistan
Muhammad Rehman: State Bank of Pakistan
Authors registered in the RePEc Author Service: Syed Kalim Hyder Bukhari

No 98, SBP Working Paper Series from State Bank of Pakistan, Research Department

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.

Keywords: Nowcasting; Large-scale Manufacturing; Factor Model; Rigged Regressions (search for similar items in EconPapers)
JEL-codes: C53 E43 E44 O53 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2018-05
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (2)

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