ESSAYS ON EVASION AND ENFORCEMENT IN VALUE ADDED TAX (VAT)

Value added tax (VAT) based on credit invoice system is the most common consumption tax in the world. Despite its self-regulating nature, VAT faces challenges in developing countries who have limited state capacity to check evasion and enforce tax on informal sectors of the economy. The tax authorities introduce policy interventions that can target the evasive behavior of firms interacting with informal sectors. My dissertation seeks to provide insight into three such policy reforms in Pakistan’s VAT regime. Therefore, this dissertation is composed of three essays. In first essay of my dissertation, titled “Using Computerization to enforce VAT: Evidence from Pakistan”, I study a policy intervention which empowered a computerized system to check invoices and reject input tax claims based on risk-based criteria. I use administrative tax data for the universe of VAT returns filed in Pakistan from tax year 2009 to 2016 to estimate the impact of this reform on the firms operating domestically. Using the exporters not subject to the reform as a control group, I find that the input tax claims fell by 2.36 million Pak Rs. per treated firm, representing a decline in input tax claims to the tune of Pak Rs. 86 billion. Firm heterogeneity analysis by business activity and firm structure shows a decline ranging from 30% to 90%. Surprisingly, the corporations and partnerships also show significant reduction in input tax claims from 50-70%. Contrary to the expectations, the huge volume of evasion shows that VAT implementation in limited tax capacity regimes may not yield the expected revenue efficiency gains. Second essay of my dissertation titled, “Is Minimum the Maximum? Tax Burden on Informal Sector in VAT: Evidence from Pakistan”, analyzes another policy reform. In developing countries, a substantial amount of revenue at import stage is now collected from VAT instead of traditional import tariffs. This modern approach assumes negligible VAT evasion at post-importation stage. I test this assumption through universe of monthly VAT returns filed in Pakistan for tax years 2009 to 2016 to estimate evasion by firms exclusively engaged in imports. I utilize kinks produced by minimum value addition thresholds to estimate evasion of VAT post-importation. I estimate an average evasion rate of nearly 78%. Using changes in thresholds over years, I provide evidence that this minimum tax collection is the best-case scenario for revenue efficiency. The firms show strong bunching at or below threshold with about 40-60% of the firms showing bunching behavior. My results support the view that, absent deviations from standard, replacing high import tariffs with VAT would decrease welfare. Third essay of my dissertation titled, “The Deterrence Value of Tax Audits: Estimates from a Randomized Audit Program”, analyzes a randomized audit program. It is a joint project with Michael Best and Mazhar Waseem. In modern tax systems audit is the sole instrument through which the tax authority can detect noncompliance and create deterrence. We exploit a national program of randomized audits covering the entire population of VAT filers from Pakistan to study how much evasion audit uncovers and how much evasion it prevents by changing behavior. While audit uncovers a substantial amount of evasion (the evasion rate among firms in the bottom three size quartiles is more than 100%), it does not deter future cheating. Examining more than ten intensive and extensive margin outcomes, we detect no effect of audit on proximate or distant firm behavior. Our results suggest audits are sub optimally utilized in checking mechanical violations of law instead of creating deterrence against evasion

The Impacts of Entrepreneurial Orientation on Organizational Performance: Study of Pakistani SMEs

Entrepreneurial orientation has been the area of interest by many researchers in the field of entrepreneurship and management. However, empirical evidences reveal that most of these studies have been conducted in developed countries and have reported mixed results. Analyses on the subject in developing countries are lacking. This study investigates the role of entrepreneurial orientation on firm performance. This study used survey data from a random sample of 213 small and medium sized enterprises (SMEs) located in Sialkot region, Province of Punjab Pakistan. The findings support the hypothesis that entrepreneurial orientation associates with firm performance. This study contributes to the body of knowledge by taking EO as five dimensional construct (innovativeness, risk taking, proactiveness, competitive aggressiveness, autonomy) rather three dimensional construct. and organizational performance comprising of non financial indicators such as customer satisfaction, employees satisfaction, service quality, innovation and growth. The study offers suggestions to policy makers and future directions

The Effect of Training and Development Practices on Employees’ Organizational Commitment among the Employees in Private Health Care Sector in Khyber Pakhtunkhwa, Pakistan

This study examined the relationship between training and development practices, and organizational commitment for a sample of employees working in private healthcare sector in Khyber Pakhtunkhwa, Pakistan. The results showed that training and development practices were positively related to organizational commitment. To examine this relationship, a survey was conducted on 134 employees working in private healthcare sector in Khyber Pakhtunkhwa, Pakistan, selected randomly. Correlation and regression analysis techniques were used to analyze the relationship of training and development practices and organizational commitment. The results of the study showed that organizational commitment of private healthcare sector employees were dependent on the training and development practices

Does Organizational Learning Orientation Matter? Investigating the Impact of Learning Orientation on SMES Performance

The purpose of this study was to conduct an investigation into the link between organizational learning orientation and business performance in small and medium sized enterprises (SMEs).  Data were analysed using sample of 213 SMEs belonging to the manufacturing sector in Sialkot, Pakistan. The findings indicated that learning orientation is positively and significantly associated with the organizational performance of SMEs. The implications and limitations of the study are discussed and possible future research directions are provided

Association of hypoadiponectemia with smokeless/dipping tobacco use in young men

Background: Low levels of adiponectin, an adipocytokine with anti-diabetic, antiatherogenic and cardioprotective properties, is associated with increased risk of coronary disease in young men. Previous studies have demonstrated that smokeless tobacco is linked with a reduction of plasma adiponectin levels. However, the influence of smokeless tobacco (dipping tobacco) on plasma adiponectin levels still remains unknown. This study was conducted to assess the plasma adiponectin levels in young men who were using dipping tobacco. Methods: This was a community based study, which consisted of 186 young lean healthy males aged 20 to 35 years. Among these, 96 men were dipping tobacco users (BMI = 23.07 ± 2.68) and 90 were non-dipping tobacco users (BMI = 23.67 ± 1.46). Serum adiponectin levels were assessed by Enzyme Linked ImmunoSorbent Assay (ELISA). Results: A statistically significant difference in the mean adiponectin level between tobacco dipper and non-dipper groups was observed (p = 0.0001). A significant difference between the two groups was also observed in baseline parameters including triglyceride and random blood sugar levels (p < 0.05). However, no significant difference was observed between the two groups in other clinical parameters. Conclusions: Findings of this study suggest that dipping tobacco use was significantly associated with low level of adiponetin in community dwelling young males. This emphasizes the importance of developing community intervention to reduce the use of dipping tobacco, which will reduce the tobacco associated disease burden in the community and will improve public health

Job behaviors and their impact on Performance Appraisal Effectiveness: Conceptual Propositions

The current study is a prepositional study which looks employee behaviours and their impact on human resource intervention effectiveness. It is a literature based study. Extant literature has been explored and relationships have been presented in a new way. The study is the first one in conceptually presenting new insights. The study is believed to open a fresh research discussion. It has theoretical implications. The study recommends empirical testing of the proposition presented in this study. The study has all the limitations of a social science research

LEARNING ORIENTATION AND PERFORMANCE: THE INTERACTION EFFECT OF ENTREPRENEURIAL ORIENTATION

The current study examines the impact of learningorientation (LO) on organizational performance and also themoderating role of entrepreneurial orientation (EO) on therelationship between LO and organizational performance amongthe small and medium enterprises (SMEs) in Pakistan. Thisquestionnaire survey was conducted among 213 managers/ ownersof manufacturing SMEs. Previous studies on LO in combinationwith EO have been conducted in large organizations in developedeconomies. Studying the relationship between LO and performanceand moderated by EO in manufacturing SMEs in a developingeconomy like Pakistan, this research attempts to fill this gap. Thefindings reveal that there exist a positive relationship between LOand organizational performance. The findings also demonstratethat the effects of LO on organizational performance are positivelymoderated by EO. The paper also includes research implicationsand possible future directions

Improving M-Learners\u27 Performance through Deep Learning Techniques by Leveraging Features Weights

© 2013 IEEE. Mobile learning (M-learning) has gained tremendous attention in the educational environment in the past decade. For effective M-learning, it is important to create an efficient M-learning model that can identify the exact requirements of mobile learners (M-learners). M-learning model is composed of features that are generated during M-learners\u27 interaction with mobile devices. For an adaptive M-learning model, not only learning features are required, but it is also important to determine how they differ for various M-learners, their weights, and interrelationship. This study proposes a robust and adaptive M-learning model that is based on machine learning and deep learning (ML/DL) techniques. The proposed M-learning model dynamically explores learning features, their corresponding weights, and association for M-learners. Based on learning features, the M-learning model categorizes M-learners into different performance groups. The M-learning model then provides adaptive content, suggestions, and recommendations to M-learners in order to make learning adaptive and stimulating. For comparative analysis, the prediction accuracy of five baseline ML models was compared with the deep Artificial Neural Network (deep ANN). The results demonstrated that deep ANN and Random Forest (RF) models exhibited better prediction accuracy. Subsequently, both models were selected for developing the M-learning model which included the performance categorization of M-learners under a five-level classification scheme and assigning weights to various features for providing adaptive help and support to M-learners. Our explanatory analysis has shown that behavioral features besides contextual features also influence the learning performance of M-learners. As a direct outcome of this research, more efficient, interactive, and useful mobile learning applications can be developed that accurately predict learning objectives and requirements of diverse M-learners thus helping M-learners in enhancing their study behavior

Semantic Orientation of Crosslingual Sentiments: Employment of Lexicon and Dictionaries

Sentiment Analysis is a modern discipline at the crossroads of data mining and natural language processing. It is concerned with the computational treatment of public moods shared in the form of text over social networking websites. Social media users express their feelings in conversations through cross-lingual terms, intensifiers, enhancers, reducers, symbols, and Net Lingo. However, the generic Sentiment Analysis (SA) research lacks comprehensive coverage about such abstruseness. In particular, they are inapt in the semantic orientation of Crosslingual based code switching, capitalization and accentuation of opinionative text due to the lack of annotated corpora, computational resources, linguistic processing and inefficient machine translation. This study proposes a Heuristic Framework for Crosslingual Sentiment Analysis (HF-CSA) and takes into consideration the NetLingua, code switching, opinion intensifiers, enhancers and reducers in order to cope with intrinsic linguistic peculiarities. The performance of proposed HF-CSA is examined on Twitter dataset and robustness of system is assessed on SemEval-2020 task9. The results show that HF-CSA outperformed the existing systems and reached to 71.6% and 76.18% of average accuracy on Clift and SemEval-2020 datasets respectively