Governments worldwide cannot collect the required tax revenue for their planned activities. This study aims to assess how inefficient VAT audit function and related factors affect tax revenue performance in Amhara Region, Ethiopia. The study used primary data sources from 377 VAT registered taxpayers in Amhara Region. It also used the Ability to Pay theory of taxation, structural equation model, path diagram, and multiple regression with SPSS/AMOS software for data analysis to identify the relationship between VAT audit and tax revenue performance. Even though the Amhara Region has revenue potential to cover its expenditures, because of inefficient VAT audit functions, poor system of tax education, lack of tax resources, and long time served tax rate, the tax revenue performance is inefficient. The study assured that VAT audit and tax education significantly affect tax revenue performance. The scarcity of resources for the VAT audit function is a critical problem. Even if the existed technology networked up to woreda levels, tax auditors did not use this system appropriately. Long-time-served tax rates also greatly influence tax revenue performance. The study recommended that there should be a chain mentor relationship between experienced auditors to new and ineffective auditors. The government should supply appropriate technology that is simple to use and quickly detect tax evasion. The existed tax rate and the system of tax education should be revised. The above findings are essential for taxpayers, policymakers, and tax authorities to understand, analyze, and use the main causes of VAT audit problems on tax revenue performance.

Tax evasion is the illegal withholding or underpayment of taxes, typically accomplished by intentionally providing false or no evidence to tax authorities. Tax evasion has had a severe detrimental influence on the economy of the Amhara National Regional State, Ethiopia. The Amhara Regional State lost tax revenue in recent years due to tax evasion. The objective of this study was to see how tax evasion, taxpayers’ psychological egoism, and other relevant factors affect tax revenue collection performance in the Amhara Region, Ethiopia. Data were collected from 395 VAT-registered taxpayers through a structured questionnaire. The structural equation model and multiple regression analysis method were utilized for empirical test based on the softwares of SPSS and AMOS. This research revealed that tax evasion and psychological egoism negatively affect tax revenue collection performance. Tax education and technology significantly and positively affected tax revenue collection performance. Meanwhile, the relationships between the above factors (tax evasion, tax education, and technology) and the tax revenue collection performance are reliably mediated by taxpayers’ psychological egoism. Those findings can give clues to researchers, tax experts, and policymakers for improving the tax revenue collection performance in Amhara Region. The government can enhance public education to reduce tax evasion and such misbehavior caused by taxpayers’ psychological egoism. Meanwhile, the most up-to-date tax invoicing technologies, like artificial intelligence and machine learning technology should be adopted.

The achievement of China’s low-carbon development and carbon neutrality depends heavily on the decrease of manufacturing carbon emissions. From coagglomeration’s dynamic evolution perspective, by using panel-threshold-STIRPAT and mediation-STIRPAT models, this study examines the relationships among industrial coagglomeration, green innovation, and manufacturing carbon emissions and explores the direct and indirect function mechanisms. Panel data of China’s 30 provinces from 2010 to 2019 are employed. The results imply that, first, the impact of industrial coagglomeration on manufacturing carbon emissions is nonlinear and has significant threshold effects. Industrial coagglomeration negatively affects manufacturing carbon emissions, and as the coagglomeration level deepens, the negative effect has a diminishing trend in marginal utility. Once the coagglomeration degree exceeds a certain threshold, the negative impact becomes insignificant. At present, for 90% of China’s regions, an increase in industrial coagglomeration level can help reduce manufacturing carbon emissions. Second, green innovation is a vital intermediary between industrial coagglomeration and manufacturing carbon emissions. It is a partial intermediary when industrial coagglomeration is at a relatively lower-level stage and a complete intermediary when industrial coagglomeration is at a relatively higher-level stage. These findings reveal the significance of optimizing industrial coagglomeration and the level and efficiency of green innovation to decrease carbon emissions.