Determining Factors of Private Investment: Empirical Study of Pakistan

There is an ample amount of work on private investment for the cases of both developed and developing economies. Blejer and Khan (1984) study the investment function for developing countries using pooled data of 24 countries for the period 1971-1979. They find credit availability and infrastructural public investments are positively related to private investment. They observe that crowding-out phenomena works in case of non-infrastructural investment. As quoted by Saker (1993), behavior of private investment is quite different in developed and developing economies. Credit availability and government investment appear to be strong boosters of private investment in case of developing economies. Utilizing the Pakistani data set from FY 1974 to FY 1992, Saker (1993) concludes that private investment is positively correlated with output growth, private sector credit availability and government infrastructural investment. Oshikoya (1994) models private investment function for various middle-income and low-income African countries for the period 1971-1988. He finds that real output growth, real exchange rate, credit availability and government infrastructural investment are positively related to domestic private investment in studied African countries. Inflation and external debt servicing add to macroeconomic uncertainty and are, therefore negatively related to private investment

Impact evaluation of structural adjustment program: a case of Pakistan

We analyzed the effect of Structural Adjustment Program (SAP) on macroeconomic variables of Pakistan using annual time series data for the years 1981-2001. The impact of four policy instruments of SAP, i.e. reduction in budget deficit, increase in indirect taxes,adjusting the exchange rate and sliding down of subsidies, on employment, income distribution, per-capita income and inflation has been analyzed. It is found that the first policy instrument, i.e. decrease in budget deficit has affected employment, income distribution and inflation adversely. The second policy instrument of imposition of indirect tax negatively affected the employment, income distribution, per capita income and positively affected the inflation. The third policy instrument of SAP was adjustment of exchange rate. It is estimated that adjusting exchange rate has resulted into increased unemployment and inflation. The fourth policy instrument of shrink in subsidies augmented the unemployment, unequal distribution of income and inflation and dwindled the percapita income. It appears that SAP has adversely affected the major socioeconomic variables of the economy. Currently the government is considering for loan from IMF, so it is proposed to avoid such type of policy directives from IMF.Structural Adjustment Program, Budget deficit, Indirect taxes, Exchange rate, Subsidies, Employment, Income distribution, Per-capita income, Inflation,Pakistan

The Impact of Social Media on Fashion Industry: Empirical Investigation from Karachiites

This study is an attempt to investigate the impact of social media on fashion industry as social media is getting very much in and within the past decade a remarkable development has been witnessed. Businesses are using social media as a promotional tool. Fashion industry is one of the businesses where frequent changes occur and social media is the most convenient and cheapest mean to communicate. Based on convenience sampling, five organizations were selected and a sample of 130 respondents was obtained which had two variables i.e. Social media and Fashion industry which further defused into four sub variables each.Reliability of the questionnaire fell within the acceptable band. As a preliminary investigation, correlation between the variables is obtained which is 45.4% and significant at 1% confidence level. Further, the results obtained through regression shows that social media is a significant predictor of fashion industry. Keywords: Social media, Fashion industry, Face book

Pituitary stalk interruption syndrome presenting in a euthyroid adult with short stature

Pituitary stalk interruption syndrome (PSIS) is a distinct and rare clinical entity responsible for congenital hypopituitarism resulting in deficiency of pituitary hormones with deficiency of the growth hormone (100%) and gonadotropins (97.2%) being its most common presentation at the time of hospital encounter (Wang et al., 2015). Isolated sparing of thyroid-stimulating hormone (TSH) with deficiency of the remaining anterior pituitary hormones may be present in PSIS, as is true in our case. Therefore, it should be kept in mind at the time of examination in suspected cases of PSIS

Efficient probabilistic inversion of geophysical data

Estimation of uncertainties is critical for subsequent decision making in all applications of geosciences such as geological hazard analysis and risk mitigation, management and exploitation of subsurface resources, and environmental waste disposal. More efficient probabilistic inversion methods in geosciences are vital to making rapid and improved predictions of geological hazards and estimation of subsurface resources from geophysical data, and estimation of associated uncertainties. While this thesis focuses on seismic data inversion for the estimation of geological properties, the methods developed may find a wide variety of applications in all fields of research that involve spatial data analysis. New concepts, models and methods are developed to perform more efficient probabilistic inversion by making use of the latest developments in machine learning and Bayesian inverse theory to solve geophysical inverse problems. The major contribution of this thesis is the development of efficient geostatistical inversion methods for approximate inference for structured inverse problems where probabilistic dependence between unknown model parameters may be expressed as a Markov random field (MRF). These methods are many orders of magnitude faster than the corresponding sampling based methods in such types of inverse problems. Further, some of the commonly used but avoidable assumptions in conventional geostatistical inversion methods are progressively relaxed and finally removed in this research. The faster inversion methods allow more complex models to be evaluated for more accurate predictions and improved estimation of uncertainty for given compute power and time. Most existing geostatistical inversion methods are based on the localized likelihoods assumption, whereby the seismic data at a location are assumed to depend on the geology only at that location. Such an assumption is unrealistic because of imperfect seismic data acquisition and processing, and fundamental limitations of seismic imaging methods. It is also assumed in most such previous research that the data are completely free of any correlated noise or errors. Although these requirements are almost never met in reality, existing methods use these assumptions to make solutions computationally tractable. Both of these assumptions are progressively removed in this thesis while still allowing computationally tractable solutions to be found for suitably structured problems. The class of problems considered here spans a broad range of spatial data analysis and geosciences, where geology at a location is assumed to depend directly only on the geology within some pre-specified neighbourhood of that location – the so called Markovian assumption – which is the core assumption across the entire literature of geostatistics and has been proven to be valid for all practical purposes. Exact Bayesian inference is intractable in most models of practical interest because it requires normalization of the posterior distribution by integrating model parameters over a very high dimensional space. Therefore, approximate inference is used in practice. Stochastic sampling (e.g., by using Markov-chain Monte Carlo – McMC) is the most commonly used approximate inference method but is computationally expensive and detection of its convergence is often based on subjective criteria and hence is unreliable. New Bayesian inversion methods are introduced that estimate the spatial distribution of geological properties from attributes of seismic data, by showing how the usual probabilistic inverse problem can be solved using an optimization framework while still providing full probabilistic results – the so called variational inference approach. The intractable posterior distribution is replaced by a tractable approximation in the variational approach. Inference can then be performed using the approximate distribution in an optimization framework, thus circumventing the need for sampling, while still providing probabilistic results. The methods developed in this thesis infer the post-inversion (posterior) probability density of the unknown model parameters from seismic data and geological prior information. These methods are shown to be robust against weak prior information and correlated noise in the data. The methods are computationally efficient, and are expected to be applicable to 3D models of realistic size on modern computers without incurring any significant computational limitations

Public investment, private investment, governance and tourism growth in five South Asian Association for Regional Cooperation countries

The present research investigates the effects of public and private investment in Travel and Tourism (T&T), and their interaction effect on tourism growth in five South Asian Association for Regional Cooperation (SAARC) countries. It also examines the interaction effect of public and private investment with governance on tourism growth in the region. The panel data for the five SAARC countries, from 1996 to 2015, is analyzed using Fully Modified Ordinary Least Squares and Pooled Mean Group methods. The study findings reveal that public investment, private investments, and their interaction positively affect tourism growth. The interaction effects of governance with public and private investments produce mixed results for the three indicators of governance. The interaction of political stability and absence of violence with private investment shows positive effect, however, its interaction with public investment illustrates negative effect on tourism growth. In addition, the interaction effect of control of corruption and public investment on tourism growth is positive, while there is an evidence of negative effect of the interaction of control of corruption and private investment. Similarly, the interaction effect of rule of law and public investment on tourism growth is positive, whereas, it is negative in case of the interaction of rule of law and private investment. Therefore, it is recommended that public investment needs to be increased in T&T, in addition to ensure conducive environment for private sector participation in order to reap its full potential. The study also suggests improving the governance, as it enhances the efficiency and productivity of public and private investments in T&T

Impact of Financial Leverage on Firms’ Profitability: An Investigation from Cement Sector of Pakistan

This research is an attempt to establish a stochastic relationship between Financial leverage and Profitability of cement sector operating in Pakistan. For this purpose 18 cement manufacturers out of 21 are incorporated in the study and six years annual data from 2005 to 2010 regarding financial leverage and profitability of the said firms were taken into consideration. The sample size for eighteen firms for six years consists of 108 observations. An Ordinary Least Square model is applied on the data to establish a causal relationship between the variables. The study finds that financial leverage has a statistically significant inverse impact on profitability at 99% confidence interval. Keywords: Financial Leverage, Firms’ profitability, OLS JEL: C12, G32, L6

Vascular Surprises in Calot’s Triangle during Laproscopic Choleystectomy

Background: To identify the vascular anomalies,variations of Calot’s triangle during laparoscopic cholecystectomy  Methods:  In this prospective observational study one thousand patients with a diagnosis of cholithiasis were included. Exclusion criteria were patients younger than 12 years and older than 80 year.  Calot’s triangle dissection was done meticulously.Cystic artery and hepatic artery anomalies and variations were observed and analyzed on SPSS 21.   Results: The age varied from 12 to 80 years. On the basis of distributional variation the cystic artery was single in 90% cases, branched in 7% cases and absent in 3% cases. On positional variations the cystic artery was superomedial to the cystic duct in 85% cases, anterior in 7% cases, and posterior in 3% cases and low lying in 5% of the cases. On the basis of length variation results showed that 80% cases had a normal cystic artery .A short cystic artery was found in 5% cases and a long cystic artery was present in 5%. Other arterial variations are of hepatic artery i.eMoynihan’s Hump (3%) and right hepatic artery present in Calots triangle in 5% Conclusions:  For the safety of laparoscopic cholecystectomy one should be well aware of the anatomical variations of the cystic and hepatic arter

Climate Change Adaptation in Agriculture: IoT-Enabled Weather Monitoring

Smart farming is a new technology concept that uses advanced electronic sensors to collect data from a variety of agricultural landscapes. This data is used to make predictions about weather patterns, soil fertility, crop quality, and water requirements. The information can be used by experts and local farmers to make better decisions about short- and long-term planning. One of the key aspects of smart farming is the automation of some farming processes, such as smart irrigation and water management. This can be done using predictive algorithms on SoC or microcontrollers to determine how much water is needed right now for a particular agricultural sector. The use of the Internet of Things (IoT) eliminates the need for manual labor to collect this crucial agricultural data. This is because IoT systems can collect data automatically and in real time, which canlead to more accurate and timely insights. This paper will present a research study on the development of a smart farming system. The study will investigate the use of different types of sensors, data collection and analysis techniques, and communication protocols. The results of the study will be used to design and implement a prototype system. The prototype system will be evaluated in a field trial to assess its effectiveness in improving agricultural productivity. The paper will conclude with a discussion of the potential benefits of smart farming systems for agriculture. The paper will also discuss the challenges that need to be addressed in order to make these systems more widely available and affordable