Domestic Private Investment, and Export on Output Growth of Large-Scale Manufacturing Sector in Pakistan: An Application of Bound Tests to Cointegration Approach

Abstract

The goal of this analysis is to explore the impact of domestic private investment in large-scale manufacturing sector on the output growth of the large-scale manufacturing in Pakistan. The investigation utilized yearly data for the year 1973-2020. By applying the autoregressive distributed lag (ARDL) technique, the study examines both short-term and long-run effects of domestic private investment (DPI) on output growth in large-scale manufacturing.However, the study affirms a positive and significant relationship among domestic private investment, exports and value-added, large-scale manufacturing (VAL) in both short-and long-run, while market size and inflation also have a negatively and significantly influence on the value-added, large-scale manufacturing sector. It is also confirmed that domestic private investment, export, inflation have a bidirectional causal relationships with large-scale manufacturing, value-added. Moreover, findings also implies that unidirectional causality is running between employment (EMP), market size (MS), and large-scale manufacturing growth output growth (VAL). Hence, numerous incentives with tax cuts or subsidizations must be sponsored by the supervision of government in a direction to foster private investment. Provided that political stability, better infrastructure, and management in industrial manufacturing zones empowers to attract transnational exports by improving law and order conditions in Pakistan.
 Keywords: Domestic private investment, value-added, large scale manufacturing, export, Pakistan.

Public Investment, Technological Innovations, and Environmental Degradation: Asymmetric ARDL Approach

“…Moreover, the coefficients of ICT_POS and ICT_NEG are (-0.925 and 0.508) and significant at a 5% level of significance which means a 1% increase in positive shock of ICT will decrease the 0.925% carbon emissions which means technology will mitigate the environmental pollution from the atmosphere and positive shock has inverse relationship while the negative shock also demonstrates if 1% decrease ICT will decrease 0.508% ED and has direct relationship but the positive shock is very effective rather than negative shock. These finding are aligned with (Khan, 2022;Rehman, Ali, Idrees, Ali, & Zulfiqar, 2022;Sarwar, Ali, Bhatti, & ur Rehman, 2021;Shahzadi, Sheikh, Sadiq, & Rahman, 2023;Zulfiqar et al, 2022). Further, EG_POS and EG_NEG have coefficients (0.086 and 0.088) almost the same and significant at 5% and 10% respectively which means a 1% increase in positive shock will increase 0.086% ED, while a 1% decrease in EG will decrease 0.088% ED from the environment so there is no any difference between the positive and negative shocks of EG.…”

Impact of Work Load and Stress in Call Center Employees: Evidence from Call Center Employees

“…Workplace environments differed amongst centers, with unpleasant or congested spaces making employees unhappy while airier settings and natural light were liked by staff at other sites. (Pierre & Tremblay, 2011;Rehman et al, 2022;Shahid et al, 2022). In actuality, research on contact centers typically emphasizes the drawbacks of high monitoring and minimal task complexity.…”

“…So, it can be realized that very little publication is being observed for call centers. Job stress can be conceptualized as a negative mental state caused by a dynamic interaction between an individual and a work environment, as a personal response to work environment characteristics that threaten an employee emotionally or physically (Job stress negatively affects productivity or performance (Lee et al, 2019;Rehman, Ali, Idrees, Ali, & Zulfiqar, 2022;Sarwar, Ali, Bhatti, & ur Rehman, 2021).…”

Fiscal Policy, Private Investment and Manufacturing Sector Performance: Empirical Evidence from Nigeria with ARDL Technique

“…In development literature, manufacturing and industrialisation has been accepted as the major driving force of a modern economy, serving as the channels through which the production of goods and services, income levels and employment generation can be enhanced. In finding the model that best explains the state of manufacturing in Nigeria, pieces of literature have advocated fiscal policy (Uffie & Aghanenu, 2019;Abdulkarim & Saidatulakmal, 2021;Ighoroje & Akpokerere, 2021) and private investment activities (Rehman, Ali, Idrees, Ali & Zulfiqar, 2022;Iortyer & Onuh, 2022;Duramany-Lakkoh, Jalloh & Jalloh, 2021;Chinodzama, 2021;Ebelebe & Amaefule, 2020).…”

“…So, the problem of Nigeria's manufacturing sector is not finance alone. In a bid to find the most significant determinants of the manufacturing sector together with finance, works of literature such as Rehman, Ali, Idrees, Ali and Zulfiqar (2022), Iortyer and Onuh (2022), Duramany-Lakkoh, Jalloh and Jalloh (2021), Chinodzama (2021) and Ebelebe and Amaefule (2020) show that private investment positively determines manufacturing sector performance, while Abdulkarim and Saidatulakmal (2021) has reported that taxes are deleterious to investment in Nigeria from 1980 to 2017. This was in disagreement with Ighoroje and Akpokerere (2021) who posit that fiscal policy affects the output of the industry sector in the short run as well as in the long run.…”