scholarly journals Understanding Tax Policy: How Do People Reason?

2021 ◽  
Author(s):  
Stefanie Stantcheva
Keyword(s):  
Tax Policy ◽  
Large Scale ◽  
Social Preferences ◽  
Minor Role ◽  
Factual Knowledge ◽  
Instructional Videos ◽  
Estate Taxes ◽  
The Government ◽  
Underlying Mechanisms ◽  
Normative Criteria

Abstract I study how people understand, reason, and learn about two major tax policies: income taxation and estate taxation. Using large-scale Social Economics surveys issued to representative U.S. samples and associated experiments, I seek to elicit respondents’ factual knowledge about tax policy and the income or wealth distributions. Most importantly, I study their understanding of the mechanisms of tax policy and the reasoning that underlies their policy views. In decomposing policy views, I find that support for income and estate taxes is most strongly correlated with social preferences, i.e., the perceived benefits of redistribution and concerns around the fairness of inequality and taxation, as well as with broader views of the government. Efficiency concerns play a more minor role. These correlational patterns are confirmed by the experimental approach, which shows people instructional videos that explain the workings and consequences of one of the aspects of tax policy (the “Redistribution” and the “Efficiency” treatments) or that bring the two together and focus on the trade-off (the “Economist” treatment). The Redistribution and Economist treatments significantly increase support for more progressive income or estate taxes, while the Efficiency treatment has no effect. There are large partisan gaps in both the final policy views and at every step of the reasoning about the underlying mechanisms of taxes. Democrats’ and Republicans’ divergences in tax policy views can ultimately be traced back to different normative criteria (social preferences) and views of the government, rather than to different perceptions of the efficiency implications of taxation.

Land Use Change and Commodity Frontiers

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel M. Cáceres ◽  
Esteban Tapella ◽  
Diego A. Cabrol ◽  
Lucrecia Estigarribia
Keyword(s):  
Large Scale ◽  
Field Work ◽  
Dry Forest ◽  
Social Actors ◽  
Goods And Services ◽  
Fast Pace ◽  
Forest Use ◽  
The Government ◽  
Social Environmental ◽  
Management Recommendations

Argentina is experiencing an expansion of soya and maize cultivation that is pushing the agricultural frontier over areas formerly occupied by native Chaco forest. Subsistance farmers use this dry forest to raise goats and cattle and to obtain a broad range of goods and services. Thus, two very different and non-compatible land uses are in dispute. On the one hand subsistance farmers fostering an extensive and diversified forest use, on the other hand, large-scale producers who need to clear out the forest to sow annual crops in order to appropriate soil fertility. First, the paper looks at how these social actors perceive Chaco forest, what their interests are, and what kind of values they attach to it. Second, we analyze the social-environmental conflicts that arise among actors in order to appropriate forest’s benefits. Special attention is paid to the role played by the government in relation to: (a) how does it respond to the demands of the different sectors; and (b) how it deals with the management recommendations produced by scientists carrying out social and ecological research. To put these ideas at test we focus on a case study located in Western Córdoba (Argentina), where industrial agriculture is expanding at a fast pace, and where social actors’ interests are generating a series of disputes and conflicts. Drawing upon field work, the paper shows how power alliances between economic and political powers, use the institutional framework of the State in their own benefit, disregarding wider environmental and social costs. 

Evolution of Metastable Structures in Bimetallic Catalysts from Microscopy and Machine-Learning Molecular Dynamics

2020 ◽  
Author(s):  
Jin Soo Lim ◽  
Jonathan Vandermause ◽  
Matthijs A. van Spronsen ◽  
Albert Musaelian ◽  
Christopher R. O’Connor ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Large Scale ◽  
Materials Science ◽  
Complete Characterization ◽  
Layer By Layer ◽  
Surface Restructuring ◽  
Metastable Structures ◽  
Mechanistic Investigation ◽  
Underlying Mechanisms

Restructuring of interface plays a crucial role in materials science and heterogeneous catalysis. Bimetallic systems, in particular, often adopt very different composition and morphology at surfaces compared to the bulk. For the first time, we reveal a detailed atomistic picture of the long-timescale restructuring of Pd deposited on Ag, using microscopy, spectroscopy, and novel simulation methods. Encapsulation of Pd by Ag always precedes layer-by-layer dissolution of Pd, resulting in significant Ag migration out of the surface and extensive vacancy pits. These metastable structures are of vital catalytic importance, as Ag-encapsulated Pd remains much more accessible to reactants than bulk-dissolved Pd. The underlying mechanisms are uncovered by performing fast and large-scale machine-learning molecular dynamics, followed by our newly developed method for complete characterization of atomic surface restructuring events. Our approach is broadly applicable to other multimetallic systems of interest and enables the previously impractical mechanistic investigation of restructuring dynamics.

Financial and Economic Support of Innovation Processes in the Russian Fuel and Energy Complex

2019 ◽  
Vol 12 (3) ◽  
pp. 77-85
Author(s):  
L. D. Kapranova ◽  
T. V. Pogodina
Keyword(s):  
Oil Recovery ◽  
Large Scale ◽  
Oil And Gas ◽  
New Technologies ◽  
Innovative Development ◽  
Oil Reserves ◽  
Energy Complex ◽  
Innovation Activities ◽  
Substantial Investment ◽  
The Government

The subject of the research is the current state of the fuel and energy complex (FEC) that ensures generation of a significant part of the budget and the innovative development of the economy.The purpose of the research was to establish priority directions for the development of the FEC sectors based on a comprehensive analysis of their innovative and investment activities. The dynamics of investment in the fuel and energy sector are considered. It is noted that large-scale modernization of the fuel and energy complex requires substantial investment and support from the government. The results of the government programs of corporate innovative development are analyzed. The results of the research identified innovative development priorities in the power, oil, gas and coal sectors of the fuel and energy complex. The most promising areas of innovative development in the oil and gas sector are the technologies of enhanced oil recovery; the development of hard-to-recover oil reserves; the production of liquefied natural gas and its transportation. In the power sector, the prospective areas are activities aimed at improving the performance reliability of the national energy systems and the introduction of digital technologies. Based on the research findings, it is concluded that the innovation activities in the fuel and energy complex primarily include the development of new technologies, modernization of the FEC technical base; adoption of state-of-the-art methods of coal mining and oil recovery; creating favorable economic conditions for industrial extraction of hard-to-recover reserves; transition to carbon-free fuel sources and energy carriers that can reduce energy consumption and cost as well as reducing the negative FEC impact on the environment.

TO THE PROBLEMS OF COMBATING CORRUPTION IN MODERN RUSSIA AND INTERNATIONAL COOPERATION IN THE FIELD OF ANTI-CORRUPTION

2020 ◽  
Author(s):  
Angela Dranishnikova
Keyword(s):  
Large Scale ◽  
The State ◽  
Point Of View ◽  
Modern Life ◽  
Existing Problems ◽  
Moral Point ◽  
Material Goods ◽  
The Russian Federation ◽  
The Difference ◽  
The Government

In the article, the author reflects the existing problems of the fight against corruption in the Russian Federation. He focuses on the opacity of the work of state bodies, leading to an increase in bribery and corruption. The topic we have chosen is socially exciting in our days, since its significance is growing on a large scale at all levels of the investigated aspect of our modern life. Democratic institutions are being jeopardized, the difference in the position of social strata of society in society’s access to material goods is growing, and the state of society is suffering from the moral point of view, citizens are losing confidence in the government, and in the top officials of the state.

CORRELATION BETWEEN TAX POLICY AND CORRUPTION IN THE LEGAL PERSPECTIVE FOR COUNTRY'S ECONOMIC GROWTH

2017 ◽  
Vol 1 (2) ◽  
pp. 205
Author(s):  
Gideon J. ◽  
Edgar H. ◽  
Ivan I. ◽  
Nabil N. ◽  
Aptina A. ◽  
...  
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Tax Evasion ◽  
Tax Policy ◽  
Public Awareness ◽  
Transparency International ◽  
Tax Amnesty ◽  
Legal Perspective ◽  
State Income ◽  
The Government

<p>People Tax is the main source of state income. The better the tax policy of a country, the better the development of a country. One of the factors that influence the level of public awareness in paying taxes is corruption. Study shows that tax collection is one of them influenced by corruption. In the data of Corruption Perceptions Index 2016 reported by Transparency International, Indonesia is ranked 90 out of 176 countries. Tax evasion is a serious problem for many countries. Every year, the government loses revenue potential as many residents evade taxes in various ways. For this reason, the government implements tax amnesty. Tax amnesty is designed to permanently reduce the amount of underground economy activity, thereby increasing tax revenues in the future and developing countries can grow well.</p>

Inflammatory Biomarkers in Atrial Fibrillation

2019 ◽  
Vol 26 (5) ◽  
pp. 837-854 ◽  
Author(s):  
Effimia Zacharia ◽  
Nikolaos Papageorgiou ◽  
Adam Ioannou ◽  
Gerasimos Siasos ◽  
Spyridon Papaioannou ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Plasma Levels ◽  
Large Scale ◽  
Inflammatory Biomarkers ◽  
Inflammatory Pathways ◽  
Inflammatory State ◽  
Anti Inflammatory ◽  
Underlying Mechanisms

During the last few years, a significant number of studies have attempted to clarify the underlying mechanisms that lead to the presentation of atrial fibrillation (AF). Inflammation is a key component of the pathophysiological processes that lead to the development of AF; the amplification of inflammatory pathways triggers AF, and, in tandem, AF increases the inflammatory state. Indeed, the plasma levels of several inflammatory biomarkers are elevated in patients with AF. In addition, the levels of specific inflammatory biomarkers may provide information regarding to the AF duration. Several small studies have assessed the role of anti-inflammatory treatment in atrial fibrillation but the results have been contradictory. Large-scale studies are needed to evaluate the role of inflammation in AF and whether anti-inflammatory medications should be routinely administered to patients with AF.

Meta-Governance

2018 ◽  
Author(s):  
Morten Egeberg ◽  
Jarle Trondal
Keyword(s):  
Large Scale ◽  
Central Government ◽  
Focal Point ◽  
Reform Process ◽  
Government Agencies ◽  
Reform Processes ◽  
The Government ◽  
Central Government Agencies ◽  
Instrumental Control

Chapter 8 draws attention to meta-governance and how the governing of reforms is affected by how reform processes are organized. The chapter asks how reformers can ensure support for large-scale reforms that are likely to attract profound resistance. The focal point of the chapter is a study of geographical decentralization of central government agencies. The chapter argues that successful meta-governance can be provided for by careful organization of the reform process. The empirical case studied is a large-scale relocation of government agencies in Norway during the early 2000s. In carrying out this reform, the government succeeded against the odds. Most importantly, research has revealed huge constraints on the instrumental control of large-scale reforms in general and of geographical relocation of organizations in particular. Yet, this chapter shows that large-scale reforms can be successfully achieved through careful crafting of the reform organization.

scholarly journals Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

2021 ◽  
Vol 12 (2) ◽  
pp. 1-22
Author(s):  
Jianguo Chen ◽  
Kenli Li ◽  
Keqin Li ◽  
Philip S. Yu ◽  
Zeng Zeng
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Location Prediction ◽  
City Management ◽  
Dynamic Planning ◽  
Graph Sequence ◽  
Graph Modeling ◽  
The Government ◽  
Location Clustering ◽  
Station Location

Benefiting from convenient cycling and flexible parking locations, the Dockless Public Bicycle-sharing (DL-PBS) network becomes increasingly popular in many countries. However, redundant and low-utility stations waste public urban space and maintenance costs of DL-PBS vendors. In this article, we propose a Bicycle Station Dynamic Planning (BSDP) system to dynamically provide the optimal bicycle station layout for the DL-PBS network. The BSDP system contains four modules: bicycle drop-off location clustering, bicycle-station graph modeling, bicycle-station location prediction, and bicycle-station layout recommendation. In the bicycle drop-off location clustering module, candidate bicycle stations are clustered from each spatio-temporal subset of the large-scale cycling trajectory records. In the bicycle-station graph modeling module, a weighted digraph model is built based on the clustering results and inferior stations with low station revenue and utility are filtered. Then, graph models across time periods are combined to create a graph sequence model. In the bicycle-station location prediction module, the GGNN model is used to train the graph sequence data and dynamically predict bicycle stations in the next period. In the bicycle-station layout recommendation module, the predicted bicycle stations are fine-tuned according to the government urban management plan, which ensures that the recommended station layout is conducive to city management, vendor revenue, and user convenience. Experiments on actual DL-PBS networks verify the effectiveness, accuracy, and feasibility of the proposed BSDP system.

scholarly journals On the structural connectivity of large-scale models of brain networks at cellular level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giuseppe Giacopelli ◽  
Domenico Tegolo ◽  
Emiliano Spera ◽  
Michele Migliore
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Network Models ◽  
Brain Regions ◽  
Cellular Level ◽  
Scale Model ◽  
Mathematical Framework ◽  
Underlying Mechanisms ◽  
Experimental Findings

AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.

scholarly journals Effectiveness of a Power Factor Correction Policy in Improving the Energy Efficiency of Large-Scale Electricity Users in Ghana

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2582 ◽  
Author(s):  
Samuel Lotsu ◽  
Yuichiro Yoshida ◽  
Katsufumi Fukuda ◽  
Bing He
Keyword(s):  
Energy Efficiency ◽  
Power Factor ◽  
Large Scale ◽  
Regression Discontinuity ◽  
Power Factor Correction ◽  
Energy Crisis ◽  
Regression Discontinuity Design ◽  
The Government ◽  
Power Factor Improvement ◽  
The Impact

Confronting an energy crisis, the government of Ghana enacted a power factor correction policy in 1995. The policy imposes a penalty on large-scale electricity users, namely, special load tariff (SLT) customers of the Electricity Company of Ghana (ECG), whose power factor is below 90%. This paper investigates the impact of this policy on these firms’ power factor improvement by using panel data from 183 SLT customers from 1994 to 1997 and from 2012. To avoid potential endogeneity, this paper adopts a regression discontinuity design (RDD) with the power factor of the firms in the previous year as a running variable, with its cutoff set at the penalty threshold. The result shows that these large-scale electricity users who face the penalty because their power factor falls just short of the threshold are more likely to improve their power factor in the subsequent year, implying that the power factor correction policy implemented by Ghana’s government is effective.

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