Determinants of public-private-partnership performance: the case of Pakistan

Pakistan is the sixth most populous country in the world with a population of 207.77 million and growth rate of 2.40 percent per annum (Pakistan Bureau of Statistics, 2018). Continual increases in population growth and urbanisation are applying pressure on infrastructure services demand. Currently, the country is unable to finance infrastructure projects through traditional methods. Public finance – due to budget deficit. The provisions of Fiscal Responsibility and Debt Limitation (FRDL) Act 2005 limit federal fiscal deficit to 4 percent of gross domestic product (GDP) and the current budget deficit is 4 percent of GDP. Borrowing – is unavailable because, under lending restrictions in the FRDL Act 2005 public debt is restricted to 60 percent maximum of estimated GDP. Present public debt is 59.2 percent of GDP (Ministry of Finance, 2016). Issuance of international bonds – is not available due to their high susceptibility to event-risk factors. Access to capital markets is limited to only three stock exchanges and stock issuers are unable to use savings from remote areas. There is no availability of long-term lending facilities for infrastructure projects financing. Finally, the government cannot impose new taxes or increase tax rates due to weak economic conditions and political reasons. Improvements in public infrastructure facilities have not kept pace with population growth and urbanisation. Consequently, the gap between infrastructure services demand and supply is widening. Financial constraint is the major barrier in infrastructure development alongside other problems such as a weak institutional framework, political instability and governance issues. Consequently, Pakistan ranks 115 out of 137 countries in the basic infrastructure category in Global Competitiveness Index 2017-18. Therefore, it is suspected that a large part of the population will not have access to infrastructure facilities in future, if appropriate measures are not taken now. The present infrastructure demand-supply gap needs to be addressed on priority basis. New avenues to increase infrastructure investment may be found elsewhere, beyond the scope of public resources. Accordingly, Pakistani government needs to adopt innovative approaches to deal with financial constraints for infrastructure development by avoiding future debt traps. Empirical studies suggest that public-private partnerships (PPP) may be a valuable solution to the infrastructure challenge. Therefore, it is ascertained that PPP for infrastructure development is urgently needed in Pakistan and an exploration of the factors helping or impeding their implementation is justified. However, there are a few impediments in PPP implementation in Pakistan. These includes lack of "ownership" of such projects at senior level management and a weak judicial system: there is a lack of fast track dispute-resolution mechanises. There is no PPP legislation and sector specific guidelines and standard model contracts. The financial system is weak such that long-term loans for infrastructure development are unavailable. There is limited access to the capital market. Institutional structure is ineffective, especially regarding political instability and inconsistency in policy implementation. Finally, microeconomic polices are weak. In the current literature, the majority of research focus, primarily within developed countries, has been put on PPP procurement, management and performance of PPP projects and service delivery. However, institutional capacity and the capacity of public and private sectors for implementing PPP projects has been largely ignored, with only a small number of researchers having identified the importance of institutional and public sector capacity for successful implementation of PPP projects. A comprehensive set of criteria and methodology for evaluating their capacity is missing. An extensive review of the available literature suggests that private sector capacity to implement PPP programs has not been assessed so far. Therefore, no previous analytical methodology and research technique was available to evaluate this aspect of PPP. As no studies have been carried out to determine the capacity of institutions, public and the private sector to implement PPP program in the context of Pakistan, this thesis therefore focuses on the determinants of PPP implementation. In this thesis, time series and cross-sectional primary and secondary data covering 24 years from 1991 to 2014 was used. Primary data was collected through a survey questionnaire. Secondary data was collected through official websites and financial reports of the government of Pakistan and from the World Bank database. The suitability of questionnaire was verified by using factor analysis. Cronbach's alpha was used to test reliability and consistency among questionnaire variables. Time series property of the data and unit root non-stationarity of variables within panel framework was conducted by panel unit root tests. Panel cointegration tests were performed among the variables to avoid spurious regression by utilising Persyn and Wasteland tests. The estimated model was built up within panel vector autoregression (PVAR) framework. The PVAR model was further extended to include qualitative policy variables to articulate the effects of quantitative and qualitative variables in infrastructure development of Pakistan. This model is generally known as panel vector auto regression with exogenous variables (PVAR – X). The panel regression model was estimated by ordinary least square (OLS) and generalised least square (GLS) methods. PVAR model was estimated by generalised method of moment (GMM). The post-estimation analysis was performed for checking: i) economic theory consistency and sign consistency; ii) statistical significance; iii) model adequacy; iv) goodness-of-fit tests; and v) classical testing framework was also applied (t-test, F-test, Lagrange multiplier (LM) and Wald testing approaches) for comparing growth parameter among panel and their interaction. The estimation results showed that: i) Institutions in Pakistan do not have the capacity for managing PPP program. The private sector not only lacks the capacity for participating and managing PPP projects but also are a barrier to infrastructure development; ii) The public sector has an influence on PPP undertakings for infrastructure development but the sector cannot attract private sector investment due to lack of managerial, financial and monitoring capacity. Further, the public sector does not have the capacity for mitigating project-related risks. iii) Other factors (barriers) for implementing PPP in Pakistan were also identified, which are: a) lack of good governance – administrative formalities and ambiguous rules and regulations; b) delays/deficiencies in project execution; c) public and private sectors do not have PPP related experience and qualification; and d) feasibility studies and projections for PPP projects are unrealistic. This thesis contributes to both theoretical and practical aspects of PPP implementation in Pakistan. The findings provide valuable insights on how and why PPP model may or may not work effectively in different institutional settings. These contributions extend the theoretical literature related to PPP implementation, especially in developing economies, and provides policy guidance for the government to remove barriers for implementing and encouraging PPP undertakings in Pakistan. The findings provide guidelines for PPP implementation in Pakistan and the methodology used can be extended to other developing countries and/or multi-country studies for generating useful comparisons and revealing more useful information

Production of Acidic protease using Submerged Fermentation by Rhizopus arrhizus

The study is concerned with utilize whey of milk factory as a carbon source for the production of protease. The project was planned to produce maximum protease from whey by Rhizopus arrhizus at pH 4 and 37 °C temperature. Growth media employed to culture Rhizopus arrhizus for the production of enzyme were developed and fermentation conditions was optimized through various trials. Substrate water ratio, different nitrogen sources and concentration of nitrogen source were optimized. The fermented materials were harvested after 72 hours. These were filtered and centrifuged at 10,000 rpm at -10 °C. The filtrates were subjected to enzyme assay. Absorbance of the enzyme sample was determined at 700 nm on spectrophotometer. It was observed that 90% Whey and 2.5% cotton seed meal enhanced the production of protease by Rhizopus arrhizus. Maximum enzyme activity was observed (149.26 IU/ml/min) in flask level at pH 4 and 37 °C temperature. These optimized conditions of growth media was again used in Air-Lift fermenter and determined the activity (169.78 IU/ml/min) that is greater than flask level. This is due to proper aeration and proper temperature in Air-lift fermenter.   Keywords: Acidic protease, Air-lift fermentor, submerged fermentation and Rhizopus arrhizus

Evaluation of the diagnostic value of brain natriuretic peptide for detection of left ventricular systolic dysfunction and pulmonary hypertension in patients with acute exacerbation of chronic obstructive pulmonary disease

Background: One of the most critical health concerns of our day is acute deterioration of chronic obstructive lung disease (COPD). Detecting concurrent heart illness in these individuals might be challenging.Objective: Aims of this study were determining the diagnostic value of B-type natriuretic peptide (BNP) levels in the identification of acute COPD exacerbations (AECOPD) that were linked with left ventricular (LV) dysfunction and pulmonary hypertension. Methods: a prospective study of 100 patients with acute COPD exacerbations was done. All research participants were subjected to history taking, clinical examination, laboratory testing, blood gas analysis, echocardiography, and NT-pro BNP plasma level estimation.Results: Receiver operating characteristic (ROC) curve for BNP as a diagnostic for LV systolic dysfunction showed that area under the curve (AUC) was 0.923 at cut off point of 72.1 ng/ml with sensitivity of 93.3% and specificity of 84.6% (P<0.001).Conclusion: Heart failure is confirmed when the average natriuretic (NT)-BNP level in the left ventricle during AECOPD is higher than normal, which should prompt quick treatment for both conditions

Forecasting project schedule performance using probabilistic and deterministic models

AbstractEarned value management (EVM) was originally developed for cost management and has not widely been used for forecasting project duration. In addition, EVM based formulas for cost or schedule forecasting are still deterministic and do not provide any information about the range of possible outcomes and the probability of meeting the project objectives. The objective of this paper is to develop three models to forecast the estimated duration at completion. Two of these models are deterministic; earned value (EV) and earned schedule (ES) models. The third model is a probabilistic model and developed based on Kalman filter algorithm and earned schedule management. Hence, the accuracies of the EV, ES and Kalman Filter Forecasting Model (KFFM) through the different project periods will be assessed and compared with the other forecasting methods such as the Critical Path Method (CPM), which makes the time forecast at activity level by revising the actual reporting data for each activity at a certain data date. A case study project is used to validate the results of the three models. Hence, the best model is selected based on the lowest average percentage of error. The results showed that the KFFM developed in this study provides probabilistic prediction bounds of project duration at completion and can be applied through the different project periods with smaller errors than those observed in EV and ES forecasting models

Conjugate heat and mass transfer in square porous cavity

The present article deals with the issue of heat and mass transfer in a square porous cavity having a small solid wall or block inserted at various places at bottom surface. The main objective is to investigate the effect of size of solid wall and its location inside the porous cavity on double diffusive convention. The heat and mass transfer behavior are governed by momentum, energy and concentration equations which are converted into a set of finite element equation with the help of Galerkin method. The left surface of cavity is maintained at higher temperature and concentration, Th and Ch as compared to that of right surface at Tc and Cc. The results are presented in terms of thermal, concentration and fluid flow profiles across the porous cavity

A Fuzzy Approach for Feature Evaluation and Dimensionality Reduction to Improve the Quality of Web Usage Mining Results

The explosive growth in the information available on the Web has necessitated the need for developing Web personalization systems that understand user preferences to dynamically serve customized content to individual users. Web server access logs contain substantial data about the accesses of users to a Web site. Hence, if properly exploited, the log data can reveal useful information about the navigational behaviour of users in a site. In order to reveal the information about user preferences from, Web Usage Mining is being performed. Web Usage Mining is the application of data mining techniques to web usage log repositories in order to discover the usage patterns that can be used to analyze the user’s navigational behavior. WUM contains three main steps: preprocessing, knowledge extraction and results analysis. During the preprocessing stage, raw web log data is transformed into a set of user profiles. Each user profile captures a set of URLs representing a user session. Clustering can be applied to this sessionized data in order to capture similar interests and trends among users’ navigational patterns. Since the sessionized data may contain thousands of user sessions and each user session may consist of hundreds of URL accesses, dimensionality reduction is achieved by eliminating the low support URLs. Very small sessions are also removed in order to filter out the noise from the data. But direct elimination of low support URLs and small sized sessions may results in loss of a significant amount of information especially when the count of low support URLs and small sessions is large. We propose a fuzzy solution to deal with this problem by assigning weights to URLs and user sessions based on a fuzzy membership function. After assigning the weights we apply a "Fuzzy c-Mean Clustering" algorithm to discover the clusters of user profiles. In this paper, we describe our fuzzy set theoretic approach to perform feature selection (or dimensionality reduction) and session weight assignment. Finally we compare our soft computing based approach of dimensionality reduction with the traditional approach of direct elimination of small sessions and low support count URLs. Our results show that fuzzy feature evaluation and dimensionality  reduction results in better performance and validity indices for the discovered clusters