Maqasid-al-Shariah-based socio-economic development index (SCECDI): The case of some selected Islamic economies / Sana Ullah and Adiqa Kausar Kiani

The main objective of this study is to develop a socio-economic development index (SCECDI), which is composed of social development index (SCDI) and economic development index (ECDI). For the analysis, we have included 14 Islamic countries which are Afghanistan, Bahrain, Bangladesh, Egypt, Indonesia, Iran, Kuwait, Malaysia, Morocco, Pakistan, Qatar, Saudi Arabia, Turkey and U.A.E for the years 2010 and 2015.Pakistan’s spending on education and health is quite low during last five years on average, while value added agriculture is the highest among all Muslim countries. Meanwhile, spending on health and education in Saudi Arabia is quite high, besides having quite high export value added and capital formation. These are required for better economic development. Highest educational profile is observed in Malaysia, while the employment rate is highest in Kuwait among all. We have diversified the summary profile for all countries of the variables included for the analysis in the study. Expected outcome is that those Islamic economies which have better economic conditions, will have more than 0.50 values for SCECDI, while others may have the value in between 0-0.50. We also demonstrate the importance of SCECDI focusing the dynamic characteristics of all Islamic countries included in the study

Relationship between Trade Openness and Inflation: Empirical Evidences from Pakistan (1976-2010).

This study empirically verifies the existence of significant relationship between inflation and trade openness for Pakistan using annual time-series data for the period of 1976 to 2010. The basic objective of this study is to examine the Romer‘s hypothesis for Pakistan with real agriculture value added, real exchange rate, real gross domestic product, financial market openness, money and quasi money and used trade openness, import openness and export openness ratios separately as explanatory variables with inflation rate as dependent variables. For this purpose, we have used multivariate Johansen (1998) and Johansen and Juselius (1990) Maximum Likelihood Cointegration Approach and a Vector Error Correction Model (VECM) and the expected empirical findings shows that there is a significant positive long-run relationship between inflation and trade openness, which rejects the existence of Romer‘s hypothesis for Pakistan. JEL classification: B26, E31, P24, P44 Keywords: Trade Openness, Inflation, Unit Root Testing, Multivariate Cointegration Approach, Vector Error Correction Model, Pakista

STOCK RETURNS PREDICTION BY USING ARTIFICIAL NEURAL NETWORK MODEL FOR PAKISTAN STOCK EXCHANGE

Artificial neural networks are extensively used to predict the financial time series. This study implements the neural network model for predicting the daily returns of the Pakistan Stock Exchange (PSE). Such an application for PSE is very rare. A multi-layer perception network is used for the model used in this study, while the network is trained using the Error Back Propagation algorithm. The results showed that the predictive power of the network was performed by the return of the previous day rather than the input of the first three days. Therefore, this study showed satisfactory results for PSE. In short, artificial intelligence can be used to give a better picture of stock market operators and can be used as an alternative or additional to predict financial variables

Mothers’ Empowerment, Children’s Inoculations and Schooling in Pakistan: Urban vs Rural Areas, Daughters vs Sons and 1998-99 vs 2007-08

Mothers’ empowerment is thought to have considerable impact on children’s health and schooling. But the evidence for developing countries of the magnitudes of such effects, how they differ between urban and rural areas, whether they differ for daughters versus sons and whether they are changing over time is limited, particularly for countries that are characterized as having relatively great gender inequality. We construct a mothers’ empowerment index from Pakistani household survey data for 1998-99 and 2007-08 and investigate the associations between mothers’ empowerment and children’s inoculations and schooling. Because mothers’ empowerment may be endogenous, we explore instrumental variable estimates using women’s ages at the time of marriage as the identifying instrument. We find that the greater mothers’ empowerment: the more likely that preschool-age children have complete inoculations and the younger is the age of starting school and the greater is the schooling progression rate. These effects are larger in absolute magnitude for urban than for rural areas (though significantly so at the 5% level only for inoculations), suggesting that the urban context facilitates the effectiveness of mothers’ empowerment on investments in children’s human capital. They also are larger in absolute magnitude for daughters than for sons (though significantly so only for the schooling progression rate), suggesting some intergenerational own-gender reinforcement. Finally, these effects are significantly larger in absolute magnitudes for 2007-08 than for 1998-99, suggesting increased impact of a given degree of mothers’ empowerment in the first decade of the 21st century

Demand for Public Health Care in Pakistan

A health care demand model is estimated for each province in Pakistan to explain the outpatient visits to government hospitals over the period 1989–2006. The explanatory variables include the number of government hospitals per capita, doctors’ fee per visit at a private clinic, income per capita, the average price of medicine and the number of outpatient visits per capita in the previous period. All variables are significant determinants of the demand for health care in at least one province but their signs, magnitudes and the levels of significance vary. These variations may be attributed to cultural, social and religious factors that vary across provinces. Variations in health care quality offered at public hospitals may also be a factor. These factors and improved accessibility of health care facilities should be the focus of public policy aimed at increasing the usage of public sector health care facilities in Pakistan.Health Care, Hospitals, Human Resources, Policy, Public Health

An Instrument for Measuring National Readiness and Capacity to Participate in Global Knowledge Base Economy

An important question often asked is what are the determinants of science, technology and innovation (STI)? Is STI a measurable quantity? How can it be measured in quantitative terms? To answers                                                          these questions, a Science, Technology and Innovation Index (STII) has been developed for top 100 economies of the world on the basis of GDP, to evaluate, determine and measure the overall scientific, technological and innovative capacity and readiness of a country. The STII relies on four dimensions, each built around two or three pillars, each of which is composed of individual indicators, for a total of 44 STI indicators. The STI index is the average of aggregate of four dimensions. The economies are ranked on the basis of STII values and classified into six groups: i.e. leaders, potential leaders, dynamic adopters, slow adopters, marginalized and laggards. For more meaningful assessment of the STI capacities of nations, it captures the achievement gap of individual countries with the highest achiever. A comprehensive analysis into the strengths and weaknesses in different dimensions of STI capability of eight East - South Asian countries is also provided. The results show that there are significant dispari¬ties between developed and developing nations in STI capacity and its various aspects. STI capacity and achievement gap analysis of individual countries provides useful information for STI policy makers to furnish their STI policies for increasing national capacity, and readiness to participate in the knowledge based economy

Demand for Public Health Care in Pakistan

A health care demand model is estimated for each province in Pakistan to explain the outpatient visits to government hospitals over the period 1989-2006. The explanatory variables include the number of government hospitals per capita, doctors’ fee per visit at a private clinic, income per capita, the average price of medicine and the number of outpatient visits per capita in the previous period. All variables are significant determinants of the demand for health care in at least one province but their signs, magnitudes and the levels of significance vary. These variations may be attributed to cultural, social and religious factors that vary across provinces. Variations in health care quality offered at public hospitals may also be a factor. These factors and improved accessibility of health care facilities should be the focus of public policy aimed at increasing the usage of public sector health care facilities in Pakistan. JEL classification: I110, I180, O150 Keywords: Health Care, Hospitals, Human Resources, Policy, Public Healt

Climate Change Impact on Wheat Yield in Pakistan (An Application of ARDL Approach)

Wheat is an important food crop of Pakistan and used in variety of ways to produce other by-products. Pakistan falls under top ten major countries of the world producing wheat. The objectives of the study are to investigate whether hasty changes in climate exerting impacts on wheat yield in Pakistan or not. The data spanning over a time period of 1991 to 2015 were used. The variables namely area under cultivation of wheat, water availability, amount of precipitation, mean temperature, and mean relative humidity are used for the purpose of estimation. The Auto Regressive Distributed Lag Model is applied for inference of results. The results of the study indicate that both in short and long run humidity rate, water usages, and area play a significant role in increasing the wheat yield whereas, precipitation shows the negative effect on wheat yield. Also, temperature does not show any significant impact in short run, while it plays a vital role in enhancing wheat yield in the long run

STOCK RETURNS PREDICTION BY USING ARTIFICIAL NEURAL NETWORK MODEL FOR PAKISTAN STOCK EXCHANGE

Artificial neural networks are extensively used to predict the financial time series. This study implements the neural network model for predicting the daily returns of the Pakistan Stock Exchange (PSE). Such an application for PSE is very rare. A multi-layer perception network is used for the model used in this study, while the network is trained using the Error Back Propagation algorithm. The results showed that the predictive power of the network was performed by the return of the previous day rather than the input of the first three days. Therefore, this study showed satisfactory results for PSE. In short, artificial intelligence can be used to give a better picture of stock market operators and can be used as an alternative or additional to predict financial variables