Efficiency Wage Hypothesis—The Case of Pakistan

The object of this paper is to present an exposition of Efficiency Wage theory, and to test its basic assertions in the context of Pakistan. The Great Depression of 1929 showed that labour disequilibrium persists for long periods of time. One of the causes of this was rigidity of nominal wages, which was assumed without explanation by Keynes in his General Theory. Stagflation in the 1970s led to re-examination of Keynesian theories and a search for a satisfactory theoretical explanation of wage rigidity. Efficiency Wage theories provide an explanation by suggesting that worker productivity increases with wage. This means that firms may not have incentive to cut wages even when they are above equilibrium. Substantial empirical evidence for efficiency wages has been found in the context of advanced economies, but there is very little literature for developingcountries. Saygili (1998) has given evidence for efficiency wages in the Turkish economy. Nasir (2000) provides empirical evidence for a wage differential between private and public sectors in Pakistan, which conforms to efficiency wage considerations. In this paper, we show that the textile sector in Pakistan appears to offer efficiency wages, while other sectors conform to neoclassical competitive labour market theorie

Efficiency Wage Hypothesis—The Case of Pakistan

The goal of this section is to point out the observed difficulties with the classical/neoclassical theory of labour markets. According to classical and neoclassical economics, the labour market is a market like any other market. The equilibrium wage is determined by the intersection of the supply and demand for labour

Multicultural Teacher Preparation in Practice: A Hermeneutical Disposition

It is a fact that learning to teach is basically a social and practical activity that is supported and informed by theoretical reflections. Field experience and realities should be the core component of any teacher preparation program. That is why, most of the teacher education programs based on theory into practice model. The main aim of this research is not to reject this model, but to sketch out an alternative way of teacher preparation that is based upon teacher’s own context and socio cultural settings or in other words teacher preparation must be organized Hermeneutically. The hermeneutical approach of Hans-Georg Gadamer, is not only of philosophical importance but contains practical implications also. The concepts of understanding, interpretation and application are the core concepts of teacher preparation. In contrast to adopting an entire theory as the guiding principle to the whole content and practice of teacher preparation courses, this research argue for the focus to be on inculcating a hermeneutic disposition in all teachers preparation programs and courses. Hermeneutics is basic to human interaction, especially in dealing with student-teachers belongs to diverse socio-cultural settings or multicultural environment. The main argument or focus of this research is that it is necessary that the teacher preparation programs must be consider the problem of multiculturalism (inter and intra cultural). Multicultural Teacher Preparation (MTP) or hermeneutical mode of teacher preparation plays an important role in the preparation of teachers. It will be helpful for teachers to develop a deep level understanding of students needs belongs to various backgrounds and perspectives, not through applying a predetermined model of classroom activities, but through helping future teachers to recognize their own prejudices and how these help to determine their understandings of diversity in their future classrooms. Developing a hermeneutic disposition in teachers training facilitates and enrich experience of future teachers. A mixed method design was used to conduct the study

RELATIONSHIP BETWEEN TYPES OF REWARDS AND JOB SATISFACTION OF EMPLOYEES: EVIDENCE FROM KHYBER PAKHTUNKHWAH

The main objectives of this research study were to gauge theprevailing level of job satisfaction amongst employees. Furthermore to find an association among the levels of rewards (task significance, task involvement, task autonomy, organizational rewards, social rewards) and job satisfaction of employee’s doing jobs in private sector organizations in Khyber Pakhtunkhwah. 240 employees of five private sector universities and eight private sector banks participated in this study. A Cronbach’s Alpha, Multiple Regression and Pearson Correlation are used to test the proposed hypothesis.The findings reveal that there exists significant and positiveassociation between job satisfaction and rewards (task involvement, task autonomy and task significance). The results show that job satisfaction is insignificantly associated with organizational rewards and social rewards. The findings of this research and their implication for future research are also discussed

Appendiceal Diverticulum Masquerading as Acute Appendicitis

Appendiceal diverticula present as rare clinical findings and are most often confused with acute appendicitis due to similar presentation. The incidence in such cases is reported at a rate no greater than 1%. We present a rare case of a 65-year-old female treated for acute appendicitis who was instead found to have acute sequelae of appendiceal diverticulosis

A meta-heuristic approach for developing PROAFTN with decision tree

© 2016 IEEE. Machine learning algorithms known for their performance in using historical data and examples to predict and classify unknown instances. Decision tree is an efficient machine learning approach that can use data only without the involvement of decision maker to improve the decision making process. Multi-Criteria Decision Analysis (MCDA)is another paradigm used for data classification. In this paper, we propose a new fuzzy classification method based on MCDA called PROAFTN. To use PROAFTN, a set of parameters need to be established from data. The proposed approach uses data pre-processing and canonical genetic algorithm (GA) for obtaining these parameters from data. The generated models have been applied on popular data selected from several application domain, health, economy, etc. According to our experimental study, the new model performs significantly better than decision trees according in terms of accuracy and the interpretation of the decision rules