Real Tax Research Articles

Vehicular crowd-sensing: a parametric routing algorithm to increase spatio-temporal road network coverage

ABSTRACT Current vehicles are equipped with a number of environmental sensors to improve safety and quality of life for passengers. Many researchers have shown that these sensors can also be exploited for opportunistic crowd-sensing. Useful new services can be developed on top of these data, like urban surveillance of Smart Cities. The spatio-temporal sensing coverage achievable with Vehicular Crowd-Sensing (VCS), however, is an open issue, since vehicles are not uniformly distributed over the road network, undermining the quality of potential services based on VCS data. In this paper, we present an evolution of the standard A routing algorithm, meant to increase VCS coverage by selecting a route in a random way among all those satisfying a parametric constraint on the total cost of the path. The proposed solution is based on an edge-computing paradigm, not requiring a central coordination but rather leveraging the computational resources available on-board, significantly reducing the back-end infrastructure costs. The proposed solution has been empirically evaluated on two public datasets of 450,000 real taxi trajectories from two cities, San Francisco and Porto, characterized by a very different road network topology. Results show sensible improvements in terms of achievable spatio-temporal sensing coverage of probe vehicles.

부동산 보유세제 재설계를 위한 연구

가칭 ‘종부세 위헌소송 모임’은 종합부동산세법에 대한 위헌소송을 제기한다고 하고 있고, 2020년에 부과된 종합부동산세는 세금폭탄이라는 주장과 적정한 부담이라는 주장이 대립하고 있다. 이러한 논란의 핵심은 종합부동산세와 재산세로 대표되는 우리나라의 보유세 체계가 적절하게 납세자의 조세부담능력을 평가하여 세금을 부과하고 있는가이다. 공정·공평한 조세부담은 누구나 주장하고 지지하는 원칙이나 모두에게 공정·공평한 세금은 존재할 수 없다. 공정·공평한 세금이 쉽지 않은 목표라면 예측 가능하고 비교적 단순한 조세체계를 갖추어 효율적인 세무행정이 될 수 있도록 하는 것도 하나의 대안이 될 수 있다.<BR> 정부의 다양한 부동산 대책에도 불구하고 최근 몇 년동안 부동산 가격은 급등하였다. 부동산에 대한 투기수요를 억제하고 국민의 주거를 안정시키는 것이 우리 정부의 부동산 정책이라면 다주택자에 대한 보유세 강화는 타당한 제도로 평가할 수 있다. 다주택자라는 기준이 투기수요를 억제하고 부동산가격을 안정시킬 수 있는 지에 대해서는 고민해 볼 필요가 있다. 복수의 주택을 보유하는 것이 범죄는 아니며 필요에 따라 복수의 주택을 소유할 수 있다. 2주택자라 하더라도 2주택을 모두 주거용으로 보유자가 사용하고 있다면 이를 중과하여야 할 이유가 없어 보인다. 따라서 다주택자라는 기준보다는 실거주용 주택과 임대용 주택으로 구분하여 달리 과세하는 방법을 대안으로 제시한다.<BR> 구체적으로는 부동산 보유세 중 재산세는 지방자치단체가 제공하는 다양한 서비스에 대한 대가의 성격이 많음을 고려하여 누진세율보다는 부동산의 사용 목적이나 기능에 따라 서로 다른 비례세율을 적용하여야 한다. 종합부동산세는 주거 목적이 아닌 부동산 보유에 대하여 부과하는 조세로 개정되어야 한다. 고가 아파트라는 이유로 주거 목적으로 보유하는 부동산에 대하여 지나치게 높은 누진세율을 적용하는 것은 합리적인 근거가 부족하다. 부동산 보유세는 시장가격을 반영하여 부과하는 것이 원칙이나 매년 이를 평가하는 현재의 공시지가제도보다는 매입시에 신고된 실거래가를 기준으로 매년 일정 비율을 한도로 과세표준을 증감하는 방안이 타당하다고 판단된다. 이러한 변화로 부동산을 매매하는 국민은 미래의 조세부담을 예측할 수 있으며 실주거 목적의 주택 소유자가 보호받는 제도가 될 수 있다.

Joint Rebalancing and Vehicle-to-Grid Coordination for Autonomous Vehicle Public Transportation System

An Autonomous Vehicle (AV) is believed to be the next generation transport that can enhance safety and efficiency for smart mobility. In an AV-based public transportation system, the full autonomy of AVs enables high-efficiency transport services and the potential ride-sharing feature of AV system enhances the utilization. The system manages a fleet of AVs, determines their assignments to transport requests, sends instructions concerning the optimized plans, and recommends the parking locations for the unoccupied AVs. The parking location of an empty AV is crucial in the sense that rebalancing AVs to areas with high potential service demand can curtail the unnecessary waiting time for passengers. As AVs are generally electric, proper parking locations can also facilitate vehicle-to-grid (V2G) support. In this paper, we propose a joint rebalancing and V2G coordination strategy for AV-based public transportation system. We formulate the problem as an integer linear program and propose a heuristic based on Genetic Algorithm and Model Predictive Control to solve the problem in low time complexity. Extensive experiments are performed with the real taxi service data from New York City. The formulated integer linear program is solved dynamically where each problem instance contains 3 to 5 AVs and 3 to 8 requests in 30s time interval. Compared with the transport system without rebalancing, the results show that the coordination strategy is efficient and effective in reducing unnecessary waiting time for passengers while satisfying V2G support. Compared to computational time with the standard solver, the proposed heuristic dramatically reduces the computational time.

How Does Profit Shifting Affect the Balance of Payments?

Profit shifting by multinational enterprises—through manipulation of transfer prices of related-party trade, intragroup lending, or the location of intangibles—affects international flows, raising the question of its impact on the current account and external balances. This paper approaches this question theoretically and empirically. In theory, profit shifting distorts the components of the current account and bilateral current account balances but leaves a country’s aggregate net balance unaffected. There is, however, a real effect on current account balances, because taxes are paid to different jurisdictions. Moreover—in practice—the measured current account could change, because not all transactions are equally easy to track. Our panel empirical results broadly confirm that the current account balance tends to be, on average, unaffected by profit shifting, but taking heterogeneity into account we find that both the real tax effect and mismeasurement strengthen income balances—and thus the current account—in investment hubs.

Державне регулювання розвитку підприємництва в аграрному секторі

The purpose of the article is to reveal the essence and main directions of state regulation of the development of entrepreneurship in the agricultural sector in modern conditions. Research methods. The methodological basis of the study was a set of methods of scientific knowledge of the system and mechanism of state regulation of the development of entrepreneurship in the agricultural sector. The achievement of the goal was facilitated by general scientific methods: methods of empirical research (measurement, comparison, observation); methods of theoretical research (analysis and synthesis); as well as local (specific) methods: methods of situation analysis (computational-constructive method). Research results. It has been established that state regulation of the development of entrepreneurship in the agricultural sector is the integrity of the implemented protectionist measures that guarantee the financial, budgetary, legal, economic, investment security of the competitive functioning of business entities in a market environment in order to optimize the conditions and consequences of entrepreneurial activity, the formation of a decent level of food security of the state, adaptation of producers to modern conditions of instability and coronacrisis. It is substantiated that the financial costs for state support of agricultural producers should be at least 1% of the volume of agricultural production, but in reality they amount to 0.4%. It was revealed that agricultural producers do not have real tax support. It has been established that the implementation of the priority of state regulation of small business entities, individual entrepreneurs and households will only contribute to an increase in the integral efficiency of the use of budgetary funds. Scientific novelty. The essence and main directions of state regulation of the development of entrepreneurship in the agricultural sector in modern conditions are disclosed and a methodological approach to substantiating the main directions of modification of state regulation that contributes to solving the problems of the functioning of entrepreneurship in the agricultural sector of the economy is proposed. Attention is focused on the main components of expenditures for programs of state support for the development of entrepreneurship in the agricultural sector for 2021-2023. Practical significance. It is advisable to use the methodological approach as a base in the system of analysis of indicators of state regulation of entrepreneurship development in the agricultural sector according to the statistical reporting of business entities and macro-indicators of the socio-economic state of the country. Tabl.: 1. Figs.: 1. Refs.: 25.

DMP: Content Delivery With Dynamic Movement Pattern in Vehicular Networks

Vehicular ad-hoc networks (VANETs) have been widely studied in intelligent transportation. Content delivery is an important topic that attracts many researchers. Due to vehicles that may have intermittent connections and uncertain routes, it is difficult to select an appropriate node. In this paper, we analyze the movement pattern of vehicles from real taxis’ trajectories and propose a framework for delivery prediction, which aims to select appropriate nodes. First, we propose the framework which consists of a contact clique model, a social clique model, and a prediction model based on Markov chains, to characterize the movement pattern of vehicles. Second, we capture dynamic movement patterns by dividing the time requirement into equal length slots and construct clique sequences. Based on the fact that the sociality of nodes has strong temporal correlations, we utilize the prediction model to derive future cliques and evaluate two kinds of delivery performance in the future. Finally, we design a content delivery algorithm with dynamic movement pattern (DMP) to select the appropriate node. In our experiment, DMP performs better than that of other methods in terms of overhead, average hops. Also, as the number of nodes increases, our algorithm keeps small fluctuations in node sociality.

Analysis of road tax in the international context

Research background: Reducing the costs of transport companies is a permanent and important task for the sustainability of the company's development. The operation of transport companies brings externalities, which ultimately burden the company, which creates pressure to eliminate them by those who cause them. This pressure increases costs for transport companies, so they often try to avoid responsibility for environmental pollution. The European Union supports the creation of legislative instruments that would favor transport companies that give preference to greener and more fuel-efficient vehicles when operating. However, the modernization of the vehicle fleet also brings with it increased costs for investments in fixed assets. Purpose of the article: The aim of this article is to analyze the real tax burdens in the individual Member States and to point out that rates within the European Union are not uniform and represent a space for speculative behavior by transport operators. At the same time, it should be pointed out that the motivation of carriers to reduce transport externalities is insufficient if Member States are left a large margin of manipulation. Methods: We obtained data on road tax rates from the laws in individual countries. We used Scania truck data to analyze the impact of rates. Findings &amp; Value added: When creating the price, it is necessary to consider all costs related to the implementation of transport. One of these costs is the motor vehicle tax. This tax represents a fixed cost for the carrier, which burdens the vehicle regardless of whether the vehicle is in operation or in technical readiness. We found that the adjustment of road tax resp. motor vehicle taxes has significant shortcomings in the EU. Not only do some countries do not favor the use of clean vehicles, but tax rates also vary greatly from one Member State to another.

Удосконалення механізму стратегічного управління структурними трансформаціями економіки міст обласного значення Львівської області

The article analyzes the content of development strategies of cities of region significance in Lviv region and identifies the lack of goals, objectives and measures to improve the sectoral structure of the economy, as well as the limited ability of local authorities to influence the structure of the cities’ economy with the help of instruments that provide tax preferences for enterprises of priority industries, investors, small and medium-sized businesses. In order to eliminate shortcomings in the strategic management of structural transformations of cities, directions of improvement of the existing institutional mechanism in terms of taxation of the investment, innovation and entrepreneurial activity of enterprises of priority sectors of the economy, investors who finance the development of high-tech industries and high-tech types of economic activity, as well as enterprises operating within special modes of economic activity, are proposed. It is substantiated that the introduction of real tax preferences for enterprises will ensure the implementation of effective structural policy at the local level, since the authorities will receive real levers to increase investment, innovative, entrepreneurial activity in priority sectors of the economy. In order to strengthen control and responsibility for the implementation of strategic tasks, it is proposed to use the problem-target method in strategic planning of city development, which, unlike the program-target approach, provides for a clear allocation of resources between the goals aimed at solving structural problems in the economy. As result of the study, the list of indicators of structural changes in the economy and the basic principles of establishing quantitative criteria for achieving strategic goals to improve the structure of the economy of cities of region significance are determined.

Educational research on solving real tax problems in cross-border e-commerce

The paper considers current taxation problems in cross-border electronic commerce in goods, the share of which in total trade continues to grow. Considering the field of economics as a part of university education, which can play a prominent role in solving the current problems, we suggests possible ways of regulating the cross-border e-commerce taxation by involving digital platforms in the taxation process and making them fully or partially liable for tax obligations. In addition, the establishment of university educational courses in the field of economics has been proposed as a way to improve the economic situation

Missed Opportunities of Simplification Regarding Personal Income Tax Systems in Hungary

The paper investigates – considering also the simplified basic elements of the current system – the possibilities of simplifying the Hungarian personal income tax system’s composition in the previous years, while tax burden curves of the system change as little as possible. Tax burden curves of the theoretical, simplified tax model established for this investigation are fitted to the curves of the real tax system, while the parameters of the theoretical model are determined by a computer program. Since the modern Hungarian income taxation had been introduced, the system has long been subject to a wide variety of changes concerning the basic elements examined in the study. Selecting some of these years of changes, the study analyses the possibilities for simplification in order to ask the question again: whether it is necessary to maintain complex tax systems at all costs, possibly in favour of achieving the most equitable income tax system. The results of the investigation indicate that our simpler theoretical system could have replaced with a good approximation the elements of Hungarian tax systems of previous years with multi-bracket and sometimes complicated tax credit, which even applied more tax benefit elements compared to the theoretical system. On this basis, it may be an important aspect also for the more distant future that in the course of developing personal income tax systems, the sophisticated equity of the systems should be observed through the mathematical spectacles of simplification options.

Towards a true tax reform: Proposal to reactivate the economy. Towards real tax reform: Proposal to revive the economy

Every one that proposes and publishes a tax reform renews the hope of good news or at least that the situation does not worsen, this year 2020 did not happen, which is not new. The current government promised not to raise taxes, which is also new. While it is true that the Federation Revenue Law for FY 2020 does not provide for the increase in tax rates, it does show the eventual creation of new contributions, a situation that has gone unnoticed by the majority of the population, moreover, of the fervent followers of the person now holding the Presidency of the Republic. Thus, this reform tightens the audit but does not encourage job creation or the preservation of existing ones; 2019 ended without economic growth and that does not seem to matter to this regime, indolent of an economic crisis in the wake of today's pandemic. That is why the proposals for improvement must come from individuals, from the civil society which, though belittled by authority, must take the baton, now distracted and empty; the gravity of the situation deserves it, it claims.

Reference-Based Framework for Spatio-Temporal Trajectory Compression and Query Processing

The pervasiveness of GPS-enabled devices and wireless communication technologies results in massive trajectory data, incurring expensive cost for storage, transmission, and query processing. To relieve this problem, in this paper we propose a novel framework for compressing trajectory data, REST ( Re ference-based S patio- t emporal trajectory compression), by which a raw trajectory is represented by concatenation of a series of historical (sub-)trajectories (called reference trajectories) that form the compressed trajectory within a given spatio-temporal deviation threshold. In order to construct a reference trajectory set that can most benefit the subsequent compression, we propose three kinds of techniques to select reference trajectories wisely from a large dataset such that the resulting reference set is more compact yet covering most footprints of trajectories in the area of interest. To address the computational issue caused by the large number of combinations of reference trajectories that may exist for resembling a given trajectory, we propose efficient greedy algorithms that run in the blink of an eye and dynamic programming algorithms that can achieve the optimal compression ratio. Compared to existing work on trajectory compression, our framework has few assumptions about data such as moving within a road network or moving with constant direction and speed, and better compression performance with fairly small spatio-temporal loss. In addition, by indexing the reference trajectories directly with an in-memory R-tree and building connections to the raw trajectories with inverted index, we develop an extremely efficient algorithm that can answer spatio-temporal range queries over trajectories in their compressed form. Extensive experiments on a real taxi trajectory dataset demonstrate the superiority of our framework over existing representative approaches in terms of both compression ratio and efficiency.

Optimal Assignments in Mobility-on-Demand Systems Using Event-Driven Receding Horizon Control

We develop an event-driven Receding Horizon Control (RHC) scheme for a Mobility-on-Demand System (MoDS) in a transportation network where vehicles may be shared to pick up and drop off passengers so as to minimize a weighted sum of passenger waiting and traveling times. Viewed as a discrete event system, the event-driven nature of the controller significantly reduces the complexity of the vehicle assignment problem, thus enabling its real-time implementation. Simulation results using actual city maps and real taxi traffic data illustrate the effectiveness of the RH controller in terms of real-time implementation and performance relative to known greedy heuristics.

Vehicle-Assisted Data Delivery in Smart City: A Deep Learning Approach

Collecting the massive internet of things data produced in a large smart city is quite challenging, and recent advances in vehicle-to-everything communication makes urban vehicles to be a good candidate to conduct this task. Hence, this paper proposes a novel deep learning algorithm called DeepVDD to facilitate vehicle-assisted data delivery. First, a theoretical analysis is presented to quantitatively reveal the correlation between vehicle mobility and the success ratio of vehicle-assisted data delivery. Based on the findings in analysis, DeepVDD adopts a novel multi-headed neural network to determine the strategies for vehicles to deliver data. Comprehensive evaluations have been executed based on the real taxi mobility data in Tokyo, Japan. The results have validated that, compared with other state-of-art algorithms, DeepVDD not only improves the success ratio of data delivery, but also significantly reduces the communication overhead of vehicular networks.

THE ROLE OF MANAGERIAL ABILITY IN INDONESIA: INVESTMENT OPPORTUNITY SETS, ENVIRONMENTAL UNCERTAINTY, TAX AVOIDANCE

Purpose of the study: This study aims to obtain empirical evidence of the effect of investment factors that consist of investment opportunity sets and environmental uncertainty on tax avoidance and the role of managerial ability in moderating these effects.&#x0D; Methodology: The analysis was conducted on 49 manufacturing companies listed on the Indonesia Stock Exchange from 2012 to 2018. It was chosen through a purposive sampling method, so 343 observations were obtained. This study engages two-panel data regression models, a model with and without moderation managerial ability. Also, this study employs factor analysis to produce investment opportunity sets that can represent this variable.&#x0D; Main Findings: This study reveals that investment opportunity sets and environmental uncertainty positively affect tax avoidance. Meanwhile, managerial ability failed to moderate the effect of investment opportunity sets and environmental uncertainty on tax avoidance.&#x0D; Implications: The results of the profiling can be used as an early warning, especially for account representatives and tax auditors at the Indonesia Tax Authority, so that potential tax exploration and examination can be more in-depth for firms that fulfill these characteristics. Also, this study provides advice to the Government of Indonesia to provide tax holidays for firms with high IOS who invest in the real sector and tax incentives for firms that are facing an environment with high uncertainty.&#x0D; Novelty: This study deploys managerial ability as a moderating variable between the relationship of investment opportunity sets and environmental uncertainty to tax avoidance. The managerial ability has an important role in firms' IOS and environmental uncertainty faced by the firms because the level of managers will produce differences in the economic outcomes and the effectiveness of the discretion.

Urban sensing as a random search process

We study a new random search process: the taxi drive. The motivation for this process comes from urban sensing in which sensors are mounted on moving vehicles such as taxis, allowing urban environments to be opportunistically monitored. Inspired by the movements of real taxis, the taxi drive is composed of both random and regular parts: passengers are brought to randomly chosen locations via deterministic (i.e. shortest paths) routes. We show through a numerical study that this hybrid motion endows the taxi drive with advantageous spreading properties. In particular, on certain graph topologies it offers reduced cover times compared to random walks and persistent random walks.

Fiscal equalization as a driver of tax increases: empirical evidence from Germany

This paper exploits the devolution of taxing powers in the German federation to study the effects of fiscal equalization on subnational governments’ tax policy. Based on an analysis of the system of fiscal equalization transfers, we argue that the redistribution of revenues provides incentives for states to raise rather than to lower their tax rates. The empirical analysis exploits differences in fiscal redistribution among the states and over time. Using a comprehensive simulation model, the paper computes the tax-policy incentives faced by each state over the years and explores their empirical effects on tax policy. The results support a robust and strong incentive effect that works through the tax-base. When facing full equalization, a state is predicted to set the rate of the real estate transfer tax at about 1.3 percentage points higher than without. Our analysis also shows that the incentive to raise tax rates has proliferated because individual states’ decisions to raise their tax rates have intensified fiscal redistribution over time.

부동산에 대한 취득세 세율체계 정비방안 연구

부동산에 대한 취득세 세율체계 정비방안 연구

The Effect of Tax Revenues on Inflation in Selected OECD Countries

If the seniorage leads revenue through state which can cause inflation at the same time, the expected income growth does not occur because of being delays in tax collection. In countries where the price elasticity of the tax system is less than 1, the Olivera-Tanzi effect, which states that the flaw in tax collection creates inflation and reduces real tax revenues, advocated a negative relationship between tax revenues and inflation. However, the main point here is the real value of taxes. In countries that adopt more liberal policies, the share of tax revenues in GDP is low. In this context, the aim of this study is to examine the effects of tax revenues on inflation in 28 OECD countries for the period 1995-2018 through panel data analysis. In the study, the horizontal cross-section dependency was neglected and first generation panel unit root tests were applied. Since the variables are stationary at the level, the cointegration test that gives the long-term relationship has not been passed. As a result of the Hausman test, it has been determined that the model will be estimated based on random effects. As a result of the study, it was determined that the increasing in tax revenues will increase inflation.

GPS-based citywide traffic congestion forecasting using CNN-RNN and C3D hybrid model

Traffic congestion prediction in citywide road networks is a challenging research field in metropolitan transportation operation and management. Recent advances in GPS technology offer great opportunities to improve upon the limitations on the availability and quality of traffic data. Motivated by the success of deep neural networks and considering the spatial dependencies and temporal evolutions of network traffic, we propose an innovative deep learning-based mapping to cube architecture for network-wide urban traffic forecasting. Experiments using real Taxi GPS vehicle trajectory data confirm the accuracy and effectiveness of the proposed approach combining 3-Dimensional Convolutional Networks (C3D) with Convolutional Neuron Networks (CNNs) and Recurrent Neuron Networks (RNNs), called CRC3D as a hybrid method integrating CNN-RNNs and C3Ds. We also compared a variety of recurrent neural network architectures. Results show that CRC3D succeeds in inheriting the advantages of C3D and CNN-RNN, and show its consistent and satisfactory results in urban complex system.