The aim of this study is to examine the sectoral effects on firm performance. At sectoral level Dynamism, munificence and HHI also have explanatory factors. The internal factor like liquidity of the firms and at external level the GDP are included. Other factors like munificence, dynamism and HHI shows the sectoral influence on firm performance. The data set use in this study consist of 2005-2017. The major data sources are State Bank of Pakistan, World Bank and Statistical Bureau etc. The financial statements including Balance sheets and Income statements are also sources of data. Study also makes a pre and post analysis of financial crises to examine the impact in different fiscal collapses. The major tools are used in this study to check the sectoral and sensitivity analysis of firm performance include diagnostic testing like descriptive summary and correlation. However, study also used the OLS regression to check the case and effects relationship among the variables. The study also used the fixed affects model to make the analysis. The study is limited to non-financial listed firms from the Pakistan stock exchange. The unlisted firms as well firms in the form of merger and acquisition are not included in the study. The population of study consist on non-financial including major sectors textile, sugar, energy and chemical etc. The sample are selected on the base of listed and highly capitalized firms. The findings of study argue that risk at internal and external levels have significant impact on firm performance. The findings supported by high risk high return phenomena. Same like some factors at sectoral level also have significant impact on firm performance. However, in pre and post analysis the impact is quite different in different economic collapses. The current study has various implications for the users in market. Study is useful for the students, researchers and other investor who take decision before investment. The study is also useful for financial institutions to plaid the threat influence in different periods. It is recommended that in future researchers can make addition by using latest data across the sectors like financial and non-financial. However, the study can be extended applying GMM dynamic modeling etc.
Key words: Sectoral Analysis, Pre and post analysis, Liquidity Risk, Munificence, Dynamism
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