Imputation System Research Articles

A Curious Concession? Australia’s Withholding Tax Exemption for Franked Dividends

This article considers the tax treatment of dividends paid by Australian companies to non-resident shareholders, which benefit from a withholding tax exemption to the extent that the dividend is “franked” under Australia’s imputation system. The article considers the appropriateness of maintaining the withholding tax exemption now that more than 35 years have passed since the imputation system was introduced in Australia in 1987. It examines the original rationale for introducing the exemption and questions whether that rationale remains valid in 2023, given changes to corporate and individual tax rates in the intervening periods. The article also notes that to a potentially significant extent, the ongoing availability of this concession benefits foreign revenue authorities where non-resident shareholders live in countries which maintain a “classical” approach to taxation of dividends and allow credits for foreign withholding tax to be offset against tax liabilities in the country of residence. The article concludes that a comprehensive policy-based review of the concession is long overdue, that removal or modification of the exemption should be considered, and that the potential additional Australian tax revenue resulting from changes to the concession could be significant.

Enhancing statistics and machine learning results from an interventional longitudinal dietary study applying a data imputation system

Enhancing statistics and machine learning results from an interventional longitudinal dietary study applying a data imputation system

Kamel: A Scalable BERT-Based System for Trajectory Imputation

Numerous important applications rely on detailed trajectory data. Yet, unfortunately, trajectory datasets are typically sparse with large spatial and temporal gaps between each two points, which is a major hurdle for their accuracy. This paper presents Kamel; a scalable trajectory imputation system that inserts additional realistic trajectory points, boosting the accuracy of trajectory applications. Kamel maps the trajectory imputation problem to finding the missing word problem; a classical problem in the natural language processing (NLP) community. This allows employing the widely used BERT model for trajectory imputation. However, BERT, as is, does not lend itself to the special characteristics of trajectories. Hence, Kamel starts from BERT, but then adds spatial-awareness to its operations, adjusts trajectory data to be closer to the nature of language data, and adds multipoint imputation ability to it; all encapsulated in one system. Experimental results based on real datasets show that Kamel significantly outperforms its competitors and is applicable to city-scale trajectories, large gaps, and tight accuracy thresholds.

Dividend policy and firm liquidity under the tax imputation system in Australia

PurposeThe primary goal of this paper is to investigate the relationship between stock market liquidity and firm dividend policy within a market implementing the tax imputation system. The main aim is to understand how the tax imputation system influences the relationship between firm dividend policy and stock market liquidity within a cross-sectional framework.Design/methodology/approachThis paper investigates the relationship between stock market liquidity and the dividend payout policy under the full tax imputation system in the Australian market. This study uses the Generalized Least Squares regressions with firm- and year-fixed effects.FindingsIn contrast to the negative relationship between the liquidity of common shares and the firms' dividends documented in countries with the double tax system, the study reveals that in Australia, the dividend payout ratios are positively associated with liquidity after controlling for various explanatory variables with both the contemporaneous and lagged time periods. Such a finding is robust to the use of alternative liquidity proxies and to the sub-period tests and remains during the COVID-19 pandemic period.Research limitations/implicationsThe insights derived from this study have significant implications for various stakeholders within the economy. The findings provide regulators with valuable insights to conduct a more holistic assessment of how the tax system impacts the economy, especially concerning the dividend choices of firms. Within the context of a full tax imputation system, investors can make investment decisions without factoring in the taxation impact. Simultaneously, firms can be relieved of concerns about losing investors who prioritize liquidity, particularly when a high dividend payout might not align optimally with their financial strategy.Originality/valueThis study contributes to the literature by extending the literature on the tax clientele effects on dividend policy, providing evidence that the tax imputation system can moderate the impact of liquidity on dividend policy. This study examines the impact of the dividend tax imputation system on the substitution effect between dividends and liquidity.

Semantic understanding and prompt engineering for large-scale traffic data imputation

Intelligent Transportation Systems (ITS) face the formidable challenge of large-scale missing data, particularly in the imputation of traffic data. Existing studies have mainly relied on modeling network-level spatiotemporal correlations to address this issue. However, these methods often overlook the rich semantic information (e.g., road infrastructure, sensor location, etc.) inherent in road networks when capturing network-wide spatiotemporal correlations. We address this limitation by presenting the Graph Transformer-based Traffic Data Imputation (GT-TDI) model, which imputes missing values in extensive traffic data by leveraging spatiotemporal semantic understanding of road networks. The proposed model leverages semantic descriptions that capture the spatial and temporal dynamics of traffic across road networks, enhancing its capacity to infer comprehensive spatiotemporal relationships. Moreover, to augment the model’s capabilities, we employ a Large Language Model (LLM) and prompt engineering to enable natural and intuitive interactions with the traffic data imputation system, allowing users to query and request in plain language, without requiring expert knowledge or complex mathematical models. The proposed model, GT-TDI, utilizes Graph Neural Networks (GNN) and Transformer architectures to perform large-scale traffic data imputation using deficient observations, sensor social connectivity, and semantic descriptions as inputs. We evaluate the GT-TDI model on the PeMS freeway dataset and benchmark it against cutting-edge models. The experimental evidence demonstrates that GT-TDI surpasses the cutting-edge approaches in scenarios with intricate patterns and varying rates of missing data.

Multi-ethnic Imputation System (MI-System): A genotype imputation server for high-dimensional data

ObjectiveGenotype imputation is a commonly used technique that infers un-typed variants into a study’s genotype data, allowing better identification of causal variants in disease studies. However, due to overrepresentation of Caucasian studies, there’s a lack of understanding of genetic basis of health-outcomes in other ethnic populations. Therefore, facilitating imputation of missing key-predictor-variants that can potentially improve a risk health-outcome prediction model, specifically for Asian ancestry, is of utmost relevance. MethodsWe aimed to construct an imputation and analysis web-platform, that primarily facilitates, but is not limited to genotype imputation on East-Asians. The goal is to provide a collaborative imputation platform for researchers in the public domain towards rapidly and efficiently conducting accurate genotype imputation. ResultsWe present an online genotype imputation platform, Multi-ethnic Imputation System (MI-System) (https://misystem.cgm.ntu.edu.tw/), that offers users 3 established pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1 for conducting imputation analyses. In addition to 1000 Genomes and Hapmap3, a new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. MI-System further offers functions to create customized reference panels to be used for imputation, conduct quality control, split whole genome data into chromosomes, and convert genome builds. ConclusionUsers can upload their genotype data and perform imputation with minimum effort and resources. The utility functions further can be utilized to preprocess user uploaded data with easy clicks. MI-System potentially contributes to Asian-population genetics research, while eliminating the requirement for high performing computational resources and bioinformatics expertise. It will enable an increased pace of research and provide a knowledge-base for genetic carriers of complex diseases, therefore greatly enhancing patient-driven research. Statement of significanceMulti-ethnic Imputation System (MI-System), primarily facilitates, but is not limited to, imputation on East-Asians, through 3 established prephasing-imputation pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1, where users can upload their genotype data and perform imputation and other utility functions with minimum effort and resources. A new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. Utility functions include (a) create customized reference panels, (b) conduct quality control, (c) split whole genome data into chromosomes, and (d) convert genome builds. Users can also combine 2 reference panels using the system and use combined panels as reference to conduct imputation using MI-System.

Corporate payouts in Australia

Kahle and Stulz (2021) find that inflation-adjusted corporate payouts (dividends and repurchases) in the US are three times larger over the period 2000–2019 (post-2000) compared to the 1971–1999 period (pre-2000), and that the growth in the payouts comes from repurchases instead of dividends. We investigate the corporate payouts in Australian equity markets with a dividend imputation system and find that the payouts increase by almost 80% from the pre-2000s to the 2000s. Unlike in the US, the payout increase is largely driven by dividends instead of share repurchases in Australia. Similar to the US, Australian top payers have also become bigger, older, more profitable, and have more free cash flow in the 2000s than before. Moreover, top Australian payers pay out more of their free cash flow, since they spend less on capital expenditures.

Article: The Distorting Effects of Imputation Systems on Tax Competition in the EU

The design of corporate income tax systems and thus the taxation of (cross-border) dividends are encompassed within the sovereignty of the Member States of the European Union (EU). However, these rules are restricted by the EU regulatory framework and the case law of the European Court of Justice (ECJ) which prohibit discrimination of foreign- against domestic-sourced dividends. Therefore, five EU Member States abolished their discriminatory imputation systems in favour of shareholder relief systems between 1999 and 2019 which had not only legal but also economic implications. In this simulation study, the authors assess how and to what extent the abolishment of discriminatory imputation systems in the EU Member States affected a country’s tax location attractiveness for capital investments and tax competition. The analysis is based on the cost of capital (CoC) and effective average tax rates (EATR) using the Devereux/Griffith methodology. Overall, under the discriminatory imputation systems, the authors find lower CoC and EATR for investments located in the shareholder’s residence country compared to foreign investment alternatives. The advantageousness is, on average, reversed after the switch to the shareholder relief systems and places additional tax competition pressure on the affected Member States. Corporate tax systems, Dividend taxation, Devereux/Griffith methodology, European Court of Justice, Internal market, Effective tax rates, Cost of capital JEL classification: H21, H24, H25, K34

Prediksi Tingkat Penjualan Pupuk Urea dengan Metode Monte Carlo

The development of science and information technology over time is very rapid in today's era, one of which is the agricultural sector. In the agricultural sector, there are many things that utilize technology, such as shallot cultivation. The need for shallots is very high, so many farmers plant shallots. To produce shallots of good quality and have a high selling price, farmers provide nutrition for the shallots they plant. The nutrient that onions really need is urea fertilizer. The fluctuating need for fertilizer for each farmer results in the availability of fertilizer in Kiosks often experiencing shortages. This has an impact on the scarcity of the availability of urea fertilizer. So this research was carried out to predict the level of sales of urea fertilizer in maintaining the need for fertilizer for shallot plants at Kiosk Pak De. Fertilizer availability aims to prepare stocks to avoid scarcity at a later time. The method used in this study is the Monte Carlo Method. This method is a method that can predict based on repeated random sampling. This method can also be used in various aspects of imputation systems and prediction of missing data. The data used in this study are sales data for urea fertilizer from 2020 to 2021. Sales data for 2020 are used to predict sales for 2021 and sales data for 2021 are used to predict sales for 2022. The results obtained from this study are the prediction rate for in 2020 with an accuracy rate of 92% and an accuracy in 2021 of 92.25%. From these results it can be concluded that this method can help Kios Pak De in maintaining scarcity in the sale of urea fertilizer

Dementia-related user-based collaborative filtering for imputing missing data and generating a reliability scale on clinical test scores.

Medical doctors may struggle to diagnose dementia, particularly when clinical test scores are missing or incorrect. In case of any doubts, both morphometrics and demographics are crucial when examining dementia in medicine. This study aims to impute and verify clinical test scores with brain MRI analysis and additional demographics, thereby proposing a decision support system that improves diagnosis and prognosis in an easy-to-understand manner. Therefore, we impute the missing clinical test score values by unsupervised dementia-related user-based collaborative filtering to minimize errors. By analyzing succession rates, we propose a reliability scale that can be utilized for the consistency of existing clinical test scores. The complete base of 816 ADNI1-screening samples was processed, and a hybrid set of 603 features was handled. Moreover, the detailed parameters in use, such as the best neighborhood and input features were evaluated for further comparative analysis. Overall, certain collaborative filtering configurations outperformed alternative state-of-the-art imputation techniques. The imputation system and reliability scale based on the proposed methodology are promising for supporting the clinical tests.

Analysis of HLA Variants and Graves' Disease and Its Comorbidities Using a High Resolution Imputation System to Examine Electronic Medical Health Records.

Hyperthyroidism is a prevalent endocrine disorder, and genetics play a major role in the development of thyroid-associated diseases. In particular, the inheritance of HLA has been demonstrated to induce the highest susceptibility to Graves’ disease (GD). However, thus far, no studies have reported the contribution of HLA to the development of GD and the complications that follow. Thus, in the present study, to the best of our knowledge, for the first time, a powerful imputation method, HIBAG, was used to predict the HLA subtypes among populations with available genome-wide SNP array data from the China Medical University Hospital (CMUH). The disease status was extracted from the CMUH electronic medical records; a total of 2,998 subjects with GD were identified as the cases to be tested and 29,083 subjects without any diagnosis of thyroid disorders were randomly selected as the controls. A total of 12 HLA class I genotypes (HLA-A*02:07-*11:01, HLA-B*40:01-*46:01 and *46:01-*46:01, and HLA-C*01:02-*01:02, *01:02-*03:04, and *01:02-*07:02) and 17 HLA class II genotypes (HLA-DPA1*02:02-*02:02, HLA-DPB1*02:01-*05:01, *02:02-*05:01, and *04:01-*05:01, HLA-DQA1*03:02, HLA-DRB1*09:01-*15:01, and *09:01-*09:01) were found to be associated with GD in the Taiwanese population. Moreover, the HLA subtypes HLA-A*11:01, HLA-B*46:01, HLA-DPA1*01:03, and HLA-DPB1*05:01 were found to be associated with heart disease, stroke, diabetes, and hypertension among subjects with GD. Our data suggest that several HLA alleles are markedly associated with GD and its comorbidities, including heart disease, hypertension, and diabetes.

Efficient and effective data imputation with influence functions

Data imputation has been extensively explored to solve the missing data problem. The dramatically rising volume of missing data makes the training of imputation models computationally infeasible in real-life scenarios. In this paper, we propose an efficient and effective data imputation system with influence functions , named EDIT, which quickly trains a parametric imputation model with representative samples under imputation accuracy guarantees. EDIT mainly consists of two modules, i.e., an imputation influence evaluation (IIE) module and a representative sample selection (RSS) module. IIE leverages the influence functions to estimate the effect of (in)complete samples on the prediction result of parametric imputation models. RSS builds a minimum set of the high-effect samples to satisfy a user-specified imputation accuracy. Moreover, we introduce a weighted loss function that drives the parametric imputation model to pay more attention on the high-effect samples. Extensive experiments upon ten state-of-the-art imputation methods demonstrate that, EDIT adopts only about 5% samples to speed up the model training by 4x in average with more than 11% accuracy gain.

Handling missing data in near real-time environmental monitoring: A system and a review of selected methods

High-frequency water quality monitoring systems provide valuable measurements for predicting the trend of water quality, warning of abnormal activities or operating hydrological models. However, missing values are prevalent due to network miscommunication, device replacement or failure. Applying datasets with missing values can lead to biased results in statistical analysis or hydrological modelling work. We develop a cloud-based data processing system combining advanced algorithms to impute monitoring data in near real-time. The system provides high compatibility for supporting different water quality variables, imputation algorithms and extensive scalability to support numerous data streams. Based on the proposed approach, we review various imputation methods which can be applied to water quality data. Overall, this work provides a systematic design of a water quality data imputation system, explores the advantages and limitations of selected data imputation methods and analyses the imputation performance of two real-time water quality monitoring systems located in both the USA and Australia. The results provide practical guidelines for data imputation applications in water quality data.

1985 reform of the Australian tax system

After the tumult of the Whitlam government, the Fraser government (1975-1983) saw consolidation with less reform. The 1975 Asprey report remained largely unactioned, despite the fundamental problems that burdened the Australian tax system. The 1983 election of the Hawke government, however, set in train a series of economic reforms, and tax would play a big part in these. This paper tracks those developments, starting with the tax avoidance and evasion issues that plagued the era and the 1981 Campbell Committee financial system review. The main focus, though, is on the 1985 draft white paper and tax summit that delivered the first instalment of the Asprey blueprint. While the broad-based consumption tax didn’t get up, the package reformed Australia’s income tax system, with a capital gains tax, a fringe benefits tax, a foreign tax credit system and a dividend imputation system.

Research on Legal Liability of Unmanned Driving

The arrival of the era of driverless driving has impacted the relationship between people and vehicles with drivers as the core in the traditional sense, which makes the driver's obligations gradually shift to the new product of driverless cars, and makes it difficult for driverless cars to be applied to the traditional motor vehicle imputation system regulated by the "motor vehicle side", which makes the traffic charges fail under the current criminal system. The existing legal system is aimed at the gaps in the application of some laws inevitably brought about by the development of traditional motor vehicles,It is necessary to standardize and allocate relevant specific responsibilities from the perspectives of civil, administrative and criminal law, and analyze the development direction of relevant supporting systems of driverless technology from the perspective of responsibility allocation and commitment from different legal angles.

Corporate payout policy: does product market competition matter? Evidence from Australia

PurposeThe purpose of this paper is to examine the impact of product market competition on dividend payout and share repurchases in Australia in which a full dividend imputation system has been in place since 1987.Design/methodology/approachPanel data estimation with industry and year-fixed effects is employed to examine the role of industry competition on dividend payout and share repurchases. The paper uses a sample of ASX200 non-financial firms, including 4,272 observations over the period 1992–2015. To address the endogeneity problem, the authors utilize the event of Australia–United States Free Trade Agreement (AUSFTA), which became effective on 01 January 2005, and perform a difference-in-difference analysis.FindingsThe authors find that firms operating in competitive markets are likely to pay more dividends and repurchase more shares to reduce agency costs. The positive relation between industry competition and dividends is stronger among firms where the CEO and the Chairman of the Board are the same person and among firms with higher market-to-book ratio and higher standard deviation of stock returns. The study results are robust when the authors account for the impact of franking credit on dividend payment. In the difference-in-difference analysis, the authors find strong evidence of a casual relation that product competition drives changes in dividend policy.Practical implicationsThe findings are consistent with the notion that intense product market competition can mitigate agency conflicts between managers and shareholders and with the information signalling explanation of market competition. As such, regulators may want to introduce policies that encourage more market competition (e.g. market deregulation) to enhance market efficiency.Originality/valueThis study incorporates product market competition in explaining the firm payout policy.

A high-resolution HLA imputation system for the Taiwanese population: a study of the Taiwan Biobank.

An imputation algorithm for human leukocyte antigen (HLA) is helpful for exploring novel disease associations. However, population-specific HLA imputation references are essential for achieving high imputation accuracy. In this study, a subset of 1012 individuals from the Taiwan Biobank (TWB) who underwent both whole-genome SNP array and NGS-based HLA typing were used to establish Taiwanese HLA imputation references. The HIBAG package was used to generate the imputation references for eight HLA loci at a two- and three-field resolution. Internal validation was carried out to evaluate the call threshold and accuracy for each HLA gene. HLA class II genes found to be associated with rheumatoid arthritis (RA) were validated in this study by the imputed HLA alleles. Our Taiwanese population-specific references achieved average HLA imputation accuracies of 98.11% for two-field and 98.08% for three-field resolution. The frequency distribution of imputed HLA alleles among 23,972 TWB subjects were comparable with PCR-based HLA alleles in general Taiwanese reported in the allele frequency net database. We replicated four common HLA alleles (HLA-DRB1*03:01, DRB1*04:05, DQA1*03:03, and DQB1*04:01) significantly associated with RA. The population-specific references provide an informative tool to investigate the associations of HLA variants and human diseases in large-scale population-based studies.

Rule-Based Effective Collaborative Recommendation Using Unfavorable Preference

The biggest challenge in collaborative filtering recommendation system research is data sparsity ; it mainly occurs as user rates very few items from widely available options. Data Imputation techniques address the data sparsity problem by filling the missing values and then predicting the likeliness of the user. Most of the existing imputation systems assign high ratings to the items or incorporate additional information to enhance the performance of collaborative filtering recommendations. This paper proposes an association rule-based imputation method (RUBLE) to improve the top- $N$ prediction performance of the collaborative filtering recommendation. The proposed method identifies the unfavorable items of each user using the association rule mining technique and imputes them with low values. The proposed method not only addresses the sparsity problem but also provides a better quality of recommendation by eliminating the unfavorable items in top- $N$ predictions. Existing collaborative methods can quickly adapt to the proposed method as it is method agnostic. The experimental results show that the proposed method enhances the accuracy of the traditional recommender methods by two times on average and significantly outperforms existing imputation based approaches.

In a Cage of Law: Liability Imputation System in the Tort Law on Kept Animals – A Chinese–German Comparative Study

The imputation of liability for damages caused by kept animals found in China’s Tort Law is a unique, synthetic, and multidimensional dual system. On the one hand, hazard-based liability is the dominant factor, and on the other is fault-based liability the auxiliary factor. The Tort Law on kept animals is oriented towards the types of liability for damages caused by kept animals, rather than towards categories of animal types, and it categorizes liability degrees under both normal and special circumstances. While underlining the merits achieved by this liability imputation system in terms of its structure (on the macro-level), this Article also probes into the problems and difficulties arising out of some key junctures (on the micro-level), especially as the system is put into practice and its operational complexity is revealed. Because of the strong affinity of the Chinese civil law, and especially tort law, with its German counterpart, this Article references the German tort law on animal keeper’s liability for an historical and comparative legal analysis, bringing more light to the Chinese system of liability. The imputation of liability for damages caused by kept animals found in China’s Tort Law is a unique, synthetic, and multidimensional dual system. On the one hand, hazard-based liability is the dominant factor, and on the other is fault-based liability the auxiliary factor. The Tort Law on kept animals is oriented towards the types of liability for damages caused by kept animals, rather than towards categories of animal types, and it categorizes liability degrees under both normal and special circumstances. While underlining the merits achieved by this liability imputation system in terms of its structure (on the macro-level), this Article also probes into the problems and difficulties arising out of some key junctures (on the micro-level), especially as the system is put into practice and its operational complexity is revealed. Because of the strong affinity of the Chinese civil law, and especially tort law, with its German counterpart, this Article references the German tort law on animal keeper’s liability for an historical and comparative legal analysis, bringing more light to the Chinese system of liability.

Tax Avoidance at Public Corporations Driven by Shareholder Taxes: Evidence from Changes in Dividend Tax Policy

ABSTRACTWe exploit changes in a country's integration of corporate and shareholder taxes to identify the effect of investor-level taxes on costly corporate tax avoidance. Specifically, we rely on European countries eliminating imputation systems in different years in response to supranational judicial rulings. These eliminations, which are exogenous to the firm, remove managers' disincentive to engage in tax avoidance if they consider investor-level taxes. Using a difference-in-differences model with fixed effects, we find that the average firm affected by an elimination reduces its cash effective tax rate by 5.5 percent. Placebo tests support that this effect exists only for countries and years for which eliminations occur. Consistent with our cross-sectional predictions, we find that results are stronger for firms with lower growth opportunities, higher dividend payout, lower foreign income, and higher closely held ownership. Further analysis provides evidence consistent with shifting income to foreign countries as one method of tax avoidance.JEL Classifications: G38; G32; G15; H26.