Abstract:
The L.S.M (large-scale Manufacturing) industry is one of the three major components
of economic growth of a country, the other two being Agriculture and Services. Through
the course of time, Pakistan’s L.S.M industry has seen about its fair share of ups and
downs but so far, no concrete study has been performed to study this sector. This
thesis intends to investigate the behavior of the L.S.M industry of Pakistan for the
time periods 2006-07 to 2020-21 and to put light on this sector’s future. The study
highlights the factors (or variables) that are more significantly impacting the growth
of the L.S.M industry in Pakistan, and secondly which statistical model best describes
the relationship between the variables. For this study, time series data (setting the
base year 2005-06) was collected from the online archives/repositories of the Pakistan
Bureau of Statistics and State Bank of Pakistan. After stationarity checks and lag
selection, the data was estimated using the O.L.S (ordinary least squares), A.R.I.M.A
(autoregressive integrated moving average), V.E.C (vector error correction), V.A.R
(vector autoregression) and S.V.A.R (structural vector autoregression) models. Next,
we looked at the I.R.F (impulse response function) for the variables keeping L.S.M/QIM
(quantum index of manufacturing)as the response, and lastly, the data was also forecasted
for the next 36 months. This study can help policymakers as well as scientists in
future planning r
