Abstract:
It is essential that policymakers consider cyclical changes in output.
Monthly industrial production is one of the most important and commonly used
macroeconomic indicators for this purpose. However, monthly estimates of
industrial production are not available for Pakistan. Instead, policymakers rely on a
large-scale manufacturing (LSM) index that accounts for only 10 percent of GDP.
Another limitation of this index is that it accounts primarily for private sector
industry, leaving out the direct public sector presence in industrial production.
Economic policymakers rely heavily on the LSM index to gauge economic activity
in Pakistan. In this study, we compute a new industrial production index (IPI) that
extends to the whole industrial sector in Pakistan, incorporating additional
information that the LSM index misses. Post-estimation, we build seven econometric
models reflecting conditions in the real, financial, and external sectors to estimate
year-on-year changes in the new IPI. Our results show that the root mean square
error of the ARDL model reflecting financial conditions is lowest of the models
tested, which included AR, VAR, and BVAR, across all horizons.
