Volume 12, Issue 1

Due to its unique role in the separation of powers framework, judiciary is typically among the first targets of illiberal take-overs. The popular perception of the judicial system – translating into its legitimacy – might prove to be its ultimate safeguard or primary source of vulnerability. This paper employs cross-country survey data to uncover to what extent the idea of separation of powers between the judiciary and the executive is embedded in public perception. It analyses the data on trust in the judiciary (or the legal system) the Police and the national government. Assuming that separation of powers is well embedded in the public opinion, one could expect that courts and the police would be assessed separately (i.e., not highly correlated confidence levels). Moreover, it is reasonable to expect that confidence in the police and in the government – Montesquieu executive branch – would be higher than between the police and the judiciary. On the contrary, if respondents assessed institutional performance within functional clusters, courts and the police would be assessed jointly (i.e., highly correlated confidence levels). Evidence form WVS and European Social Survey suggests, that the latter is the case. Interestingly, the finding holds in both democratic and non-democratic systems, indicating serious vulnerability for liberal (constitutional democracy) design.

This study examines whether the introduction of compulsory bicycle liability insurance is socially desirable when evaluation bias—the difference between the objective and subjective evaluations of liability amounts—exists. The main results of this study are summarized as follows. First, when there is no evaluation bias, the introduction of compulsory bicycle liability insurance is socially desirable when the interest rate is high without any condition, and the loading rate is low, the maximum amount of liability is small, and the effort cost is high if the loading rate is higher than the interest rate. Second, if there is an evaluation bias and the accident probability is uniformly distributed, more severe additional conditions are needed for deriving the same results. The study concludes that the evaluation bias prevents the realization of the situation in which the introduction of compulsory bicycle liability insurance is socially desirable.

An optimally designed tax amnesty scheme can serve as a strategic component in a larger tax reform process. Such a reform can particularly assist in the tax collection efforts of developing economies like Pakistan. Pakistan’s tax amnesty schemes in 2018 and 2019 helped grow the tax base substantially. India’s and Indonesia’s schemes in 2016 also showed promise. My study compares the recent tax amnesties adopted by these three countries (Pakistan, India and Indonesia). Based on these experiences, I propose improvements in the composition of Pakistan’s tax amnesty design. An optimal tax policy cannot rely only on wide-spread enforcement, particularly in countries with large underground economies--like Pakistan, India and Indonesia. Instead, it should focus more on the optimal amnesty design alongside targeted enforcement efforts, aimed especially at documenting and taxing large underground economic activities.

This research ferreted out to inspect the interconnection between emotional intelligence (EI), Blockchain technology application (BLO) and the effectiveness of Accounting information system (AIS). Survey-based data obtained from 412 respondents were applied to validate the model hypotheses. Building on the statistical analysis with the support of SPSS 25.0 and SMART- PLS (partial least squares) 3.2.8 software package, the model results inferred the impact of EI on BLO. Besides, the outputs of the study accentuated on the importance of BLO on the effectiveness of AIS. These significant additions will optimistically inspire other scholars to carry on exploring the relationship between EI and BLO in enhancing the effectiveness of AIS in research settings as well as in explaining the results. On the other hand, taking these results into consideration could promote much better solutions for issues relevant to EI and new technology application among public sector organization (PSO) in term of increasing the performance of AIS.

Poverty is a global issue and a lot of attention and efforts of the international community have been made to deal with this problem. Especially in the context of the COVID-19 pandemic, when a part of the population could fall into poverty due to rising unemployment and income deduction, identifying the factors affecting poverty becomes particularly important. Financial inclusion has been recognized as one important factor affecting poverty reduction. This research is conducted to investigate the impact of financial inclusion and other control variables on poverty reduction. The study employs Principal Component Analysis (PCA) to build a financial inclusion index. Using 2SLS and the GMM regressions for a panel data of 29 European countries during the period from 2011 to 2017, the results show that financial inclusion has a negative impact on poverty at all three poverty lines of USD1.9, 3.2, and 5.5 per day. The proportion of the population aged 15–64 and the ratio of service employment to the total number of employment also have a negative effect on all three levels of POV1.9 , POV3.2, and POV5.5. In contrast, GDP per capita, trade openness and the proportion of the population aged from 25 with at least secondary school education have a positive impact on poverty at three levels of poverty . The results confirm that financial inclusion plays an important role in reducing poverty. The study provides a number of recommendations to governments to promote financial inclusion and reduce poverty in the countries.