Energy Demand in Pakistan: A Disaggregate Analysis

This study examines the demand for energy at disaggregate level (gas, electricity and coal) for Pakistan over the period 1972-2007. Over main results suggest that electricity and coal consumption responds positively to changes in real income per capita and negatively to changes in domestic price level. The gas consumption responds negatively to real income and price changes in the short-run, however, in the long-run real income exerts positive effect on gas consumption, while domestic price remains insignificant. Furthermore, in the short-run the average elasticities of price and real income for gas consumption (in absolute terms) are greater than that of electricity and coal consumption. The differences in elasticities of each component of energy have significant policy implications for income and revenue generation.Energy Demand, Disaggregate Analysis, Cointegration

Energy Demand in Pakistan: A Disaggregate Analysis

This study examines the demand for energy at disaggregate level (gas, electricity and coal) for Pakistan over the period 1972-2007. Over main results suggest that electricity and coal consumption responds positively to changes in real income per capita and negatively to changes in domestic price level. The gas consumption responds negatively to real income and price changes in the shortrun, however, in the long-run real income exerts positive effect on gas consumption, while domestic price remains insignificant. Furthermore, in the short-run the average elasticities of price and real income for gas consumption (in absolute terms) are greater than that of electricity and coal consumption. The differences in elasticities of each component of energy have significant policy implications for income and revenue generation.Pakistan, Energy Demand

Energy Demand in Pakistan: A Disaggregate Analysis

This study examines the demand for energy at disaggregate level (gas, electricity and coal) for Pakistan over the period 1972-2007. Over main results suggest that electricity and coal consumption responds positively to changes in real income per capita and negatively to changes in domestic price level. The gas consumption responds negatively to real income and price changes in the shortrun, however, in the long-run real income exerts positive effect on gas consumption, while domestic price remains insignificant. Furthermore, in the short-run the average elasticities of price and real income for gas consumption (in absolute terms) are greater than that of electricity and coal consumption. The differences in elasticities of each component of energy have significant policy implications for income and revenue generation.Energy Demand, Cointegration, Pakistan

Population pharmacokinetic modeling to understand antineoplastic treatment

Introduction: The pronounced variability in pharmacokinetics of antineoplastic drugs caused by known and unknown sources translates into variability in therapeutic outcome. This is a major concern for these drugs with a narrow therapeutic index because even small changes in concentrations may lead to untoward results. Tools to handle this problem and to predict optimal doses for patients remain to be established. Objectives: The main objective was to develop nonlinear mixed effects (NLME) models to understand the pharmacokinetics / pharmacodynamics of antineoplastic drugs, to quantify the associated variability and its sources and subsequently to make use of these models to predict drug exposure / toxicity under different therapeutic regimens. Methods: A standard diagnostic tool for NLME models called visual predictive checks (VPCs) was adapted to account for multimodality from unknown sources in distributions of pharmacokinetic parameters. Allocation of patients to a subpopulation was compared based on individual probability or on overall likelihood. This approach (mixture VPCs) was tested using both simulated data and real data. Empirical pharmacokinetic NLME models were developed for mitotane and methotrexate, whereas a semi-physiological pharmacokinetic-pharmacodynamic model was developed for 5-fluorouracil. Further evaluation was performed to identify covariates (e.g., demographic characteristics, organ function) influencing the pharmacokinetics and pharmacodynamics of studied drugs. Simulations were designed to understand and visualize drug exposure and toxicity under different dosing schedules in virtual subjects. Results: Mixture VPCs based on individual probability were found to be most useful to capture model misspecifications, which were not evident from the former classical approach. Mixture VPCs were further useful to diagnose bias associated with the allocation of individuals to subpopulations. An enzyme autoinduction model for mitotane supported concentration dependent metabolic enzyme induction, leading to change in drug clearance. Body mass index was related to mitotane volume of distribution. Simulations showed that a high dose regimen is most suitable to achieve appropriate exposure early, with a first therapeutic drug monitoring on day 16 of treatment. Myelosuppression under 5-fluorouracil was characterized by a linear relationship with the plasma concentrations. Body surface area influenced the pharmacokinetics of the parent drug and its metabolite, whereas cisplatin co-administration increased myelosuppression. Any covariate effects regarding methotrexate pharmacokinetics were clinically irrelevant due to marginal explanation of between-patient variability. Specifically, body surface area based methotrexate dosing was not found to be superior to flat dosing. Conclusions: The methods developed and the findings of the research work presented in this thesis are useful to assist the adjustment of doses and dosing schedules in antineoplastic drug treatment

Impact of RISK on BEHAVIOURAL Biases across the Stock Market Investors: Evidence from Pakistan

The study aimed at exploring the major behavioural factors that affect the investment decision of individual investors of Lahore Stock exchange. The objective was also to gain the insight of both type of behavioural finance and standard finance and see where standard finance theories fail to address market anomalies. This research was conducted in Lahore stock exchange with the help of structured and closed ended questionnaires survey. Data was analysed using quantitative technique. The empirical investigation was carried out by using two statistical techniques. First exploratory factor analysis was used to find out the most influential factors that affect the investment decision. Then discriminant analysis is used to identify the relationship between the independent variables and dependent variables.Conclusion of this study helps the investors and broker sitting in stock exchange and new investors coming in the market. It is also helpful to others to investigate the other factors that affect the investment decision of investors. Keywords: Disposition Effect, Overconfidence, Herding, Gambler Fallac

Impact of Export on Economic growth of Pakistan

This research paper employed Augmented Dickey- Fuller to determine “impact of export on economic growth” while granger causality test which is statistically hypothesis test was used to determined the direction of causality between the selected variables under consideration whether selected time series is useful in forecasting. Correlation analysis was also deployed to determine the degree of relationship between the selected variables and the result shows that all the variables are highly correlated. The study uses time series data from 1992-2015, data obtained from the World Bank. The study reviles that export has an optimistic and significant impact on economic growth in Pakistan peroxide by GDP. Export was also found to be confidently and significantly impacting to economic growth in Pakistan proxied by GDP. Foreign reserve also has a optimistic and positive impact on economic growth of the country. Research result shows that the overall regression was statistically significant at both 99% and 95% level of confidence. The result of R2 (0.99) shows that the line of best fit was highly fitted. The result of the granger causality test shows that GDP granger causes Import & FDI. The research finds that, growth-export hypothesis is valid in Pakistan context. We therefore recommend among other things, that the government of Pakistan should take some necessary steps to restructure the Import sector so as to improve their contribution to the growth of Pakistani economy. The government should introduce more policies that will adequately boost the export sector of the Pakistan economy so that it will impact more meaningfully on economic growth of the Pakistan; other programs that encourages increase in foreign reserve should also be adopted in other to increase the growth of the economy in the country

Energy Demand in Pakistan: A Disaggregate Analysis

Energy is considered to be the life line of an economy, the most vital instrument of socioeconomic development and has been recognised as one of the most important strategic commodities [Sahir and Qureshi (2007)]. Energy is not only essential for the economy but its supply is uncertain [Zaleski (2001)]. Energy is a strategic source that influenced the outcomes of wars, fueled and strangled economic development and polluted as well as clean up the environment. In the era of globalisation, a rapidly increasing demand for energy and dependency of countries on energy indicate that energy will be one of the biggest problems in the world in the next century. This requires for alternative and renewable sources of energy. Traditional growth theories focus much on the labour and capital as major factor of production and ignore the importance of energy in the growth process [Stern and Cleveland (2004)]. The neo-classical production theories stresses that economic growth increases with the increases in labour, capital and technology. Today energy is indispensable factor and plays an important role in the consumption as well as production process.1 Research suggests that energy plays an important role as compared to other variables included in the production and consumption function for countries which are at intermediate stages of economic development [IEA (2005)]. When we examine disaggregating components of energy demand, it is seen that electricity is the highest quality energy component and its share in energy consumption increases rapidly. Natural gas, petroleum and coal follow electricity respectively

Improving the prediction of firm performance using nonfinancial disclosures: A machine learning approach

Purpose: The purpose of this study is to test whether the prediction of firm performance can be enhanced by incorporating nonfinancial disclosures, such as narrative disclosure tone and corporate governance indicators, into financial predictive models. Design/Methodology/Approach: Three predictive models are developed, each with a different set of predictors. This study utilises two machine learning techniques, random forest and stochastic gradient boosting, for prediction via the three models. The data are collected from a sample of 1250 annual reports of 125 nonfinancial firms in Pakistan for the period 2011-2020. Findings: Our results indicate that both narrative disclosure tone and corporate governance indicators significantly add to the accuracy of financial predictive models of firm performance.Practical implications: Our results offer implications for the restoration of investor confidence in the highly uncertain Pakistani market by establishing nonfinancial disclosures as reliable predictors of future firm performance. Accordingly, they encourage investors to pay more attention to these disclosures while making investment decisions. In addition, they urge regulators to promote and strengthen the reporting of such nonfinancial information. Originality: This study addresses the neglect of nonfinancial disclosures in the prediction of firm performance and the scarcity of corporate governance literature relevant to the use of machine learning techniques. <br/

Heat Transfer Applications of TiO2 Nanofluids

To achieve acme heat transfer is our main disquiet in many heat transfer applications such as radiators, heat sinks and heat exchangers. Due to furtherance in technology, requirement for efficient systems have increased. Usually cooling medium used in these applications is liquid which carries away heat from system. Liquids have poor thermal conductivity as compared to solids. In order to improve the efficiency of system, cooling medium with high thermal conductivity should be used. Quest to improve thermal conductivity leads to usage of different methods, and one of them is addition of nanoparticles to base liquid. Application of nanofluids (a mixture of nanoparticles and base fluid) showed enhancement in heat transfer rate, which is not possible to achieve by using simple liquids. Different researchers used TiO2 nanoparticles in different heat transfer applications to observe the effects. Addition of titanium oxide nanoparticles into base fluid showed improvement in the thermal conductivity of fluid. This chapter will give an overview of usage of titanium oxide nanoparticles in numerous heat transfer applications