The Impact of Media Campaigns on Tax Filing: Quasi-Experimental Evidence from Pakistan

This paper examines the effect of mass media campaigns on income tax filing using survey data from Pakistan. We use information collected about a pro-tax filing communication campaign shortly after the 2013-14 tax filing deadline by Pakistan’s Federal Board of Revenue. We use an inverse probability-weighted regression adjustment estimator to construct comparable treatment and control groups in terms of media exposure and control for predictors of income tax filing. We find that respondents’ likelihood of income tax filing significantly increased in response to exposure to newspaper advertisements of information provision surrounding tax eligibility but not those concerning the tax filing deadline or the benefits associated with tax filing in the form of non-application of financial penalties. TV advertisements that relied on moral suasion and solely portrayed selfemployed taxpayers did not significantly improve tax filing for the entire survey population but were effective among the self-employed. This highlights the importance of the content of the message as well as the implementation of targeted media campaigns by a tax administration to enhance income tax filing

One Size Does Not Fit All: A Field Experiment on the Drivers of Tax Compliance and Delivery Methods in Rwanda

Although field experiments in tax compliance represent a growing area of research, the literature has so far focussed exclusively on high and middle-income countries. This paper starts to fill this gap by reporting the results of a tax field experiment in Rwanda, while also highlighting some characteristics that may be common to other low-income countries. We evaluate an intervention carried out by the Rwanda Revenue Authority (RRA), which involved sending messages to taxpayers to nudge their declaration behaviour during the filing period of January-March 2016. Focussing particularly on business profits tax, our study is designed to address two interrelated questions. First, what are the key drivers of compliance in Rwanda? Second, what is the best delivery method to reach taxpayers with messages designed to improve compliance? Although other studies have explored delivery methods in the context of taxpayer communication, our study is the first one to interact these methods with different message contents. As a result, we evaluate a set of nine treatments that combine three message contents (deterrence, fiscal exchange, reminders) and three delivery methods (letters, SMS, emails) – as compared to a control group that received no message. We find that friendly approaches to taxpayers are generally more effective than deterrence. However, small taxpayers are still quite responsive to the possibility of being fined and prosecuted (deterrence). We also show that low-cost delivery methods like SMS and emails can be highly effective as compared to letters

Student Behaviour Analysis To Detect Learning Styles Using Decision Tree, Naïve Bayes, And K-Nearest Neighbor Method In Moodle Learning Management System

A learning management system (LMS) manages online learning and facilitates inter- action in the teaching and learning processes. Teachers can use LMS to determine student activities or interactions with their courses. Everyone learns uniquely. It is necessary to understand their learning style to apply it in students’ learning activi- ties. One factor contributing to learning success is the use of an appropriate learning style, which allows the information received to be appropriately conveyed and clearly understood. As a result, we require a mechanism to identify learning styles. This study develops a learning style detection system based on learning behavior at the LMS of Christian Vocational School Petra Surabaya for the subject of Network System Administration using the Decision Tree, Naïve Bayes, and K-Nearest Neigh- bor. The results of the study showed that the Decision Tree method could better detect and predict learning styles, namely using the 80:20 train split test, which obtained an accuracy of 0.96 process time of 0.000998 seconds, while the K-Fold 10 Cross-Validation test obtained an accuracy of 0.98 and a processing time of 0.04033 seconds

Harnessing Innovative Data and Technology to Measure Development Effectiveness

In this study, the authors discuss and show how new kinds of digital data and analytics methods and tools falling under the umbrella term of Big Data, including Artificial Intelligence (AI) systems, can help measure development effectiveness. Selected case studies provide examples of assessments of the effectiveness of ODA-funded policies and programmes. They use different data and techniques. For example, analysis of mobile phone data and satellite images: to estimate poverty and inequality, traffic congestion, social cohesion or machine learning approaches to social media analysis to understand social interactions and networks, and natural language processing to study changes in public awareness. A toolkit contains resources and suggestions on key steps and considerations, including legal and ethical, when designing and implementing projects aimed at measuring development effectiveness through new digital data and tools. The chapter closes by describing the core principles and requirements of a vision of a ‘Human AI’, which would reflect and leverage the key features of current narrow AI systems that are able to identify and reinforce the neurons that help them reach their goals. A Human AI would be a data and machine-enabled human system (such as a society) that would seek to continuously learn and adjust to improve—rather than prove after the facts—the effectiveness of its collective actions, including development programming and public policies

Determinants of voluntary tax compliance intention for e-filing among salaried taxpayers

Generally, worldwide tax administrators including the Inland Revenue Board of Malaysia (IRBM) are facing difficulties in addressing tax compliance complexity that is proven to be highly challenging. Numerous innovative efforts, including the e-filing system - a costly investment, initiated by the IRBM to encourage compliance. However, these efforts failed to achieve the targeted compliance outcome, the taxpayers’ behavioural intention remains unclear especially salaried taxpayers. This study investigates the voluntary tax compliance intention among salaried taxpayers in Klang Valley. It aims to identify the determinants and their dimensions of the voluntary tax compliance intention via the e-filing system. Furthermore, an examination was performed on the applicability of Decomposed Theory of Planned Behaviour in voluntary tax compliance intention setting. Based on the data collection on 20 participating headquarter offices, 303 usable responses were obtained and empirically tested for this study. The samples tested, using Smart PLS 3.2.8, found that the decomposed constructs presented a better explanatory power for behavioural intention. Most of the dimensions and constructs were proven to be significant. Where dimensions like general tax filing knowledge and perceived usefulness were found to be significant towards attitude. While peer influence and mass media referent were significant towards the subjective norm. Furthermore, facilitating conditions and ability to pay were also significant towards perceived behavioural control. In contrast, dimensions like perceived ease of use and compatibility were not significant towards attitude. While self-efficacy was not significant towards perceived behavioural control. The subjective norm construct was also found to be insignificant towards intention. Overall, the findings have theoretical and practical impact, particularly to the tax administrators, in understanding the changes in salaried taxpayers voluntary tax compliance behavioural intention. Therefore, this study has created a platform for further studies with various available options of dimensions

Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

A Study of Tax Authority Information Assistance in Malaysia: Determinants of Its Usage and Impacts on Tax Compliance

This study examines the use of tax authority information assistance among Malaysian self-lodgers. Specifically, it examines the elements associated with its usage and its significance for tax compliance. Data was collected using a mixed-methods approach. The survey data was analysed using SPSS while interviews were manually analysed. The results suggested and threat coping appraisals as significant in motivating the use of information assistance. Additionally, the use of information assistance is associated with administrative compliance