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This study focuses on the crucial task of forecasting tax revenue for India, specifically the Goods and Services Tax (GST), which plays a pivotal role in fiscal spending and taxation policymaking. Practically, the GST time series datasets exhibit linear and non-linear fluctuations due to the dynamic economic environment, changes in tax rates and tax base, and tax non-compliance, posing challenges for accurate forecasting. Traditional time-series forecasting methods like ARIMA, assuming linearity, often yield inaccurate results. To address this, we explore alternative forecasting models, including Trigonometric Seasonality Box-Cox Transformation ARIMA errors Trend Seasonal components (TBATS) and Neural Networks: Artificial Neural Networks (ANN), Neural Networks for Autoregression (NNAR), which capture both linear and non-linear relationships. First, we test single time series models like Exponential Smoothing (ETS), TBATS, ANN, and NNAR. Second, we also test hybrid models combining linear models, non-linear models, and neural network models. The findings reveal that the Hybrid Theta-TBATS model offers superior forecasting accuracy, challenging recent research favouring neural network models. The study highlights the effectiveness of advanced non-linear models, particularly TBATS and its hybridisations with linear models, in GST revenue forecasting. Our study also found that the single TBATS is the second-best model, which offers better forecasting accuracy. These insights have significant implications for policymakers and researchers in taxation and fiscal planning, emphasising the need to incorporate non-linear dynamics and advanced modelling techniques to enhance the accuracy of GST revenue forecasts. [ABSTRACT FROM AUTHOR]

The present study aims to assess the mediating role of IT governance between corporate governance mechanisms and business continuity, and transparency & disclosure during the pandemic of Covid-19 in Jordan. The study uses a sample of 232 questionnaires retrieved from different firms of different sectors. The sample includes a survey response from board members, senior executives, auditors, IT experts, and other practitioners. Factor analysis and structural equation modeling were conducted to estimate the results. The results indicate that IT governance exhibits a statistically significant positive effect on business continuity and transparency & disclosure. Further, the results reveal that corporate governance mechanisms are less efficient in their influence on business continuity and transparency & disclosure in the absence of the mediating effect of IT governance during the pandemic. The current study's findings provide insight and empirical evidence to the importance of IT governance and its role in business continuity and transparency & disclosure in constraining the negative effects during any crisis. The current study provides a novel contribution as it links corporate governance, transparency, and IT governance in the context of Covid-19 in an emerging country. [ABSTRACT FROM AUTHOR]

The current study aims to assess the effect of board of directors' composition on the profitability of Indian pharmaceutical companies. The analysis is based on 82 companies, analyzed over ten years, from 2008 to 2017. The least squares regression model is used for analysing the data. One accountingbased measure (return on assets, ROA) and one marketing-based measure (Tobin Q) are used as proxies for firms' profitability. Leverage, firms' size and age are used as control variables. The findings reveal that board of directors' composition as measured by the percentage of independent board members negatively and significantly affects firm's profitability measured by ROA. On the other hand, board of directors' composition positively and significantly affects profitability measured by Tobin Q. Furthermore, firms' size and age positively and significantly impact profitability. This topic is largely neglected by researchers of Indian origin at home and abroad. The present study provides an insight for pharmaceutical companies to consider a high level of professionalism of their board members. Greater board independence could bring more expertise, improving profitability. Accordingly, the current research has implications for board members of pharmaceutical companies, especially government-owned ones. [ABSTRACT FROM AUTHOR]