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This paper aims to analyse the determinants of the proportion of quantitative data in financial statement footnote disclosures. Quantitative data represents “hard” information and has been considered to be more persuasive than qualitative data. The primary focus is on income tax footnotes because revenue agents use them as a reference in tax audits, and citizen groups use them to analyse tax inequalities. This study posits that firms with lower effective tax rates (“tax aggressive” firms) disclose less quantitative data in their income tax footnotes.

The multivariate analysis uses data from the contents of income tax footnotes extracted from 10-K filings in eXtensible Business Reporting Language (XBRL). It uses the alphanumeric characters identified in the income tax footnotes to calculate the proportion of quantitative data relative to the entire footnote disclosure as the dependent variable in a multivariate regression analysis.

The findings show that firms which avoid more taxes disclose less quantitative data in income tax footnotes after controlling for the readability of the income tax footnotes and the entire annual report. Therefore, firms seem to reduce the publication of measurable data accessible to revenue agencies and citizen groups.

This analysis provides evidence that firms weigh the financial reporting requirements and tax audit risks when they disclose quantitative income tax data. Also, it supports the Financial Accounting Standards Board’s (FASB’s) proposal to require more disaggregated income tax disclosure. To the researcher’s knowledge, this is the first analysis that focuses on the determinants of disclosing quantitative data in income tax footnotes.

This study aims to explore the evidence of the probability of firms’ tax avoidance and the downward convergence trend of national statutory tax rates and firms’ effective tax rates.

This research employs exploratory data analysis using interactive data manipulation and visualization tools, namely, R with SparkR, dplyr, ggplot2 and googleVis (GeoChart and Motion Chart) packages. This analysis is based on the world-scale accounting data of all listed firms from 148 countries spanning 30 years.

The results reveal the following: three types of evidences on probability of firms’ tax avoidance, showing a non-random distribution of firms’ effective tax rates and return on assets, cross-sectional variation of firms’ effective tax rates in each country, and the trend of difference between effective tax rates and statutory tax rates, and the downward convergence trend of statutory tax rates and firms’ effective tax rates.

The results highlight the prominent issues of world-scale tax avoidance and tax rate competition and facilitate a collaborative discussion between laymen and professionals using objective evidence.

A novel methodology is adopted through the visualization of world-scale accounting data, which can facilitate a new perspective, revealing unexpected patterns and trends in otherwise hidden information. This study also highlights the importance of global consideration of firms’ tax avoidance and tax rate competition, using objective evidence.

The last 60 years have seen Australia and the United Kingdom diverge, both socially and economically. This paper considers how the widening social gap between the two countries is reflected by their respective redistributive systems. The analysis is based upon two microsimulation procedures – one static and the other dynamic – both of which are used to consider the probable distributional effects that would arise if elements of the Australian and UK tax and benefits systems were exchanged. The static microsimulation analysis presented suggests that comparisons based purely upon cross-sectional survey data are affected by population heterogeneity, which tend to overstate the redistributive effect of the Australian transfer system relative to the UK. Nevertheless, the dynamic microsimulations suggest that, on balance, the Australian transfer system is more redistributive than the UK system, and reflects a greater concern for redistribution between households. The UK system, in contrast, reflects a greater concern for redistribution through the life course.

Objective – Measurement of the incidence of health financing contributions across socio-economic groups has proven valuable in informing health care financing reforms. However, there is little evidence as to how to carry out financing incidence analysis (FIA) in lower income settings. We outline some of the challenges faced when carrying out a FIA in Ghana, Tanzania and South Africa and illustrate how innovative techniques were used to overcome data weaknesses in these settings.

Methodology – FIA was carried out for tax, insurance and out-of-pocket (OOP) payments. The primary data sources were Living Standards Measurement Surveys (LSMS) and household surveys conducted in each of the countries; tax authorities and insurance funds also provided information. Consumption expenditure and a composite index of socio-economic status (SES) were used to assess financing equity. Where possible conventional methods of FIA were applied. Numerous challenges were documented and solution strategies devised.

Results – LSMS are likely to underestimate financial contributions to health care by individuals. For tax incidence analysis, reported income tax payments from secondary sources were severely under-reported. Income tax payers and shareholders could not be reliably identified. The use of income or consumption expenditure to estimate income tax contributions was found to be a more reliable method of estimating income tax incidence. Assumptions regarding corporate tax incidence had a huge effect on the progressivity of corporate tax and on overall tax progressivity. LSMS consumption categories did not always coincide with tax categories for goods subject to excise tax (e.g. wine and spirits were combined, despite differing tax rates). Tobacco companies, alcohol distributors and advertising agencies were used to provide more detailed information on consumption patterns for goods subject to excise tax by income category. There was little guidance on how to allocate fuel levies associated with ‘public transport’ use. Hence, calculations of fuel tax on public transport were based on individual expenditure on public transport, the average cost per kilometre and average rates of fuel consumption for each form of transport. For insurance contributions, employees will not report on employer contributions unless specifically requested to and are frequently unsure of their contributions. Therefore, we collected information on total health insurance contributions from individual schemes and regulatory authorities. OOP payments are likely to be under-reported due to long recall periods; linking OOP expenditure and illness incidence questions – omitting preventive care; and focusing on the last service used when people may have used multiple services during an illness episode. To derive more robust estimates of financing incidence, we collected additional primary data on OOP expenditures together with insurance enrolment rates and associated payments. To link primary data to the LSMS, a composite index of SES was used in Ghana and Tanzania and non-durable expenditure was used in South Africa.

Policy implications – We show how data constraints can be overcome for FIA in lower income countries and provide recommendations for future studies.

Brazil’s regional inequality is an important topic due to the large and persistent differences in development between states and the high levels of inequality in the country. These variations in development can potentially render survey data inaccurate since the significance of capital income varies across the states. Besides, previous studies incorporating tax and national accounts data globally have mainly focused on measuring the income distribution at the country-level. This approach can limit the understanding of inequality, especially when considering large countries such as Brazil.

The methodology used to construct these estimates follows the guidelines of the Distributional National Accounts, whose core goal is to provide income distribution measures consistent with macroeconomic aggregates and harmonized across countries and time. The procedure has three main steps: first, it corrects the survey’s underrepresentation of top incomes using tax data. Then, it accounts for national income items not included in the survey or tax data, such as imputed rents and undistributed profits. Finally, it ensures that all components match the national income.

Compared to survey-based estimations, the results reveal a new angle on the state-level inequality. This study indicates that Amazonas, Rio de Janeiro and São Paulo have a more concentrated income distribution. The top 1\% of earners in these states receives around 28\% of total pre-tax income, while the top 10\% receive nearly 60\%. On the other end, Amapá (AP), Acre (AC), Rondônia (RO) and Santa Catarina (SC) are the states where the income distribution is less concentrated. There were no significant changes in the income distribution across the states during the period analyzed.

This study combines survey, tax and national accounts data to construct new estimates of Brazil’s state-level income distribution from 2006 to 2019. Previous results only considered income captured in surveys, which usually misses a significant part of capital incomes. This limitation may bias comparisons as capital income has different importance across the states. The new estimates represent the income of top groups more accurately, account for the entire national income and enable to compare regional inequality levels consistently with other countries.

The purpose of this paper is to examine the use of Section 1031 of the Internal Revenue Code (IRC), a piece of US tax law that allows for tax‐deferred exchanges of like‐kind property.

The paper derives a theoretical premium value for exchanges and presents the first national level analysis of Federal tax data on the use of like‐kind exchanges involving farmland between 1999 and 2005.

There is significant interest in Section 1031 from stakeholders in rural communities because there is widespread belief that the recent growth in farmland values may have, in part, been stimulated by Section 1031 exchanges of farmland. Despite these concerns, little is known about the extent of such exchanges.

This paper provides insight into the value and use of the IRC's Section 1031 provision. Based on simulations of a theoretical model using plausible assumptions about asset growth, the paper shows how proposed tax changes will affect the tax value of the deferral.

This paper discusses a pedagogical approach that incorporates multiple critical topics in the accounting curriculum using an integrated tax research case. Our approach is designed to develop students research, data management and analysis, critical thinking, decision-making, and professional communication skills. These goals are achieved through the use of an integrated assignment requiring students to conduct research, decide how to use an assortment of information sources, conduct analysis of data and business documents, and arrive at and communicate a conclusion. The key issue is reasonable compensation, a highly litigated tax issue which requires students to identify relevant authority found across many court cases. The use of a closely held business with multiple family members with different fact patterns exposes students to different outcomes with a varying degree of complexity. Students must analyze business documents and firm- and industry-level data to determine the appropriate tax treatment. Further, the case scenario exploits the fact that reasonable compensation is a tax issue in which circuit courts have ruled differently on the same issue, requiring in-depth research and interpretation of primary authority. Students are also exposed to differing outcomes based on entity type. We provide discussion of our multiple implementations and student questionnaire results to support the efficacy of our approach. We have prepared resources to help instructors implement this pedagogical approach, including a completed data analysis, supporting summary tables, and an in-depth discussion of the primary authority related to reasonable compensation.

Ideal estimates of the intergenerational elasticity (IGE) in income require a large panel of income data covering the entire working lifetimes for two generations. Previous studies have demonstrated that using short panels and covering only certain portions of the life cycle can lead to considerable bias. I address these biases by using the PSID and constructing long time averages centered at age 40 in both generations. I find that the IGE in family income in the United States is likely greater than 0.6 suggesting a relatively low rate of intergenerational mobility in the United States. I find similar sized estimates for the IGE in labor income. These estimates support the prior findings of Mazumder (2005a, b) and are also similar to comparable estimates reported by Mitnik et al. (2015). In contrast, a recent influential study by Chetty, Hendren, Kline, Saez (2014) using tax data that begins in 1996 estimates the IGE in family income for the United States to be just 0.344 implying a much higher rate of intergenerational mobility. I demonstrate that despite the seeming advantages of extremely large samples of administrative tax data, the age structure, and limited panel dimension of the data used by Chetty et al. leads to considerable downward bias in estimating the IGE. I further demonstrate that the sensitivity checks in Chetty et al. regarding the age at which children’s income is measured, and the length of the time average of parent income used to estimate the IGE suffer from biases due to these data limitations. There are also concerns that tax data, unlike survey data, may not adequately reflect all sources of family income. Estimates of the rank–rank slope, Chetty et al.’s preferred estimator, are more robust to the limitations of the tax data but are also downward biased and modestly overstate mobility. However, Chetty et al.’s main findings of sizable geographic differences within the US in rank mobility are unlikely to be affected by these biases. I conclude that researchers should continue to use both the IGE and rank-based measures depending on their preferred concept of mobility. It is also important for researchers to have adequate coverage of key portions of the life cycle and to consider the possible drawbacks of using administrative data.