scholarly journals Assessing the Impact of Tax Evasion on Long-Term Fiscal Imbalance: A Sensitivity Analysis Application

2018 ◽  
Vol 27 (3) ◽  
pp. 331-350
Author(s):  
Lucia Mihóková ◽  
Radovan Dráb ◽  
Andrea Kralik
Keyword(s):  
Sensitivity Analysis ◽  
Tax Evasion ◽  
Analysis Application ◽  
Fiscal Imbalance ◽  
The Impact

scholarly journals Corruption, Taxation and the Impact on the Shadow Economy

Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 18 ◽  
Author(s):  
Daniel Němec ◽  
Eva Kotlánová ◽  
Igor Kotlán ◽  
Zuzana Machová
Keyword(s):  
Tax Evasion ◽  
Capital Accumulation ◽  
Shadow Economy ◽  
Labour Force ◽  
Destructive Effect ◽  
Eu Member States ◽  
Initial Assumption ◽  
The Individual ◽  
The Impact

While assessing the economic impacts of corruption, the corruption-related transmission channels which influence taxation as such have to be duly considered. Taking the example of the Czech Republic, this article aims to evaluate the impacts corruption has on the size of the shadow economy as well as on the individual sources of long-term economic growth, making use of a transmission channel through which corruption affects the tax burden components. Using the method of an extended DSGE model, it confirms the initial assumption that an increase in perceived corruption supports the shadow economy’s growth, but at the same time, it demonstrates that corruption and especially its perception has a significantly different effect on two key areas—the capital accumulation and the labour force size. It further identifies another sector of the economy representing taxes which are prone to tax evasion while asserting that corruption has a much more destructive effect on this sector of the economy, offering generalized implications for other post-communist EU member states in a similar situation.

scholarly journals Vertical Fiscal Imbalance and Regional Economic Growth

2020 ◽  
Vol 12 (6) ◽  
pp. 39-53
Author(s):  
B.I. Alekhin ◽  
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fiscal Federalism ◽  
Fiscal Decentralization ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
Fiscal Imbalance ◽  
Vertical Fiscal Imbalance ◽  
The Impact

This study examines the impact of fiscal decentralization on regional economic growth using panel data for 82 subjects of the Russian Federation for the period 2005-2018. General theoretical framework was drawn from the second-generation theory of fiscal federalism, and panel data econometrics suggested the appropriate empirical model and estimation method. The pooled mean group method was used to estimate an autoregressive distributed lags model based on Solow-Swan theory of economic growth. The results indicate that vertical fiscal gap has a negative and significant long-term impact on regional economic growth while vertical fiscal imbalance has a positive and significant long-term effect. The study is consistent with the modern theory of fiscal federalism, W.E. Oates’ matching hypothesis and previous empirical work using Russian data. The study also found evidence of conditional convergence of regional economies.

scholarly journals Tax evasion and government size: evidence from Italian provinces

2021 ◽  
Author(s):  
Elena D’Agostino ◽  
Marco Alberto De Benedetto ◽  
Giuseppe Sobbrio
Keyword(s):  
Tax Evasion ◽  
Public Expenditure ◽  
Government Size ◽  
Public Goods Provision ◽  
Capital Spending ◽  
Italian Provinces ◽  
Per Capita ◽  
The Government ◽  
The Impact

AbstractWe analyze the impact of government size, measured by total spending per capita, on tax evasion at the provincial level in Italy over the period 2001–2015. In order to solve endogeneity issues we rely on a system GMM and find that public expenditure negatively affects tax evasion, as taxpayers perceive the government is efficiently spending resources coming from the tax levy. Results are confirmed when we (1) consider expenditures related to long-term investments, namely capital spending per capita, and (2) directly test the impact of government efficiency on tax evasion. In addition, we show that the impact of public spending is heterogeneous across geographical areas: an increase in public expenditure leads to a downward shift in tax evasion only in the northern part of Italy, characterized by a relatively larger initial level of public goods provision.

scholarly journals The Fiscal Imbalances and Methodological Approaches to Their Assessment

2021 ◽  
Vol 6 (521) ◽  
pp. 219-228
Author(s):  
Y. M. Savchenko ◽  
Keyword(s):  
Tax Evasion ◽  
Tax Competition ◽  
Tax Planning ◽  
Panel Analysis ◽  
Central Concept ◽  
Fiscal Imbalance ◽  
Methodological Approaches ◽  
The Difference ◽  
The Impact

This article generalizes and systematizes approaches to determining the essence of fiscal imbalances and their types, in particular, taking into account and without taking into account the aspect of possible problems in the sphere of fiscal policy. It is also emphasized that when determining the essence of fiscal imbalances, it is important to realize the difference between accounting and financial terms, since analytics in this terminology is also based on different methods of assessing fiscal imbalance. Such deterministic factors of fiscal imbalances as internal tax competition, tax transfer and tax imbalance in general are analyzed. The conception of marginal expenditures of public funds as a central concept in determining fiscal imbalances is characterized. In addition to the traditional types of fiscal imbalances (vertical and horizontal), there is also an imbalance of justice (according to the research of scientist Dolozina I. L.), which is manifested, in particular, in tax evasion, avoidance of taxation (including aggressive tax planning) and income inequality. The generalized classification of types of fiscal imbalances with the characterizations of causes and manifestations of their occurrence is provided. The results of researches of approaches to assessing fiscal imbalances and indicators used are systematized. It is emphasized that the researchers use most of the indicators to assess fiscal imbalances specified in this article to conduct a panel analysis in order to identify the impact of equalization instruments on different territories and groups of taxpayers.

scholarly journals Dynamics of the COVID-19 pandemic in India

2020 ◽  
Author(s):  
Subhas Khajanchi ◽  
Kankan Sarkar ◽  
Jayanta Mondal ◽  
Matjaz Perc
Keyword(s):  
Sensitivity Analysis ◽  
West Bengal ◽  
Seasonal Occurrence ◽  
Contact Tracing ◽  
Short Term ◽  
Social Distancing ◽  
Oscillatory Dynamics ◽  
The Impact ◽  
Worrying Trend

Abstract Understanding the dynamics of the COVID-19 pandemic is crucial for improved control and social distancing strategies. To that effect, we have employed the susceptible-exposed-infectious-recovered model, refined by contact tracing and hospitalization data from Indian provinces Kerala, Delhi, Maharashtra, and West Bengal, as well as from overall India. We have performed a sensitivity analysis to identify the most crucial input parameters, and we have calibrated the model to describe the data as best as possible. Short-term predictions reveal an increasing and worrying trend of COVID-19 cases for all four provinces and India as a whole, while long-term predictions also reveal the possibility of oscillatory dynamics. Our research thus leaves the option open that COVID-19 might become a seasonal occurrence. We also simulate and discuss the impact of media on the dynamics of the COVID-19 pandemic.

scholarly journals Taxation and Redistribution against Inequality: A Mathematical Model

2021 ◽  
Author(s):  
Maria Letizia Bertotti
Keyword(s):  
Tax Evasion ◽  
Fiscal Policies ◽  
Policy Makers ◽  
Market Society ◽  
Welfare Policies ◽  
Redistributive Policy ◽  
Income Distributions ◽  
Long Run ◽  
The Impact

Reducing inequality is a tremendously important sustainable development goal. Albeit providing stylised frames for modelling, also mathematics can contribute to understanding and explaining the emergence of collective patterns in complex socio-economic systems. It can then effectively help to identify actions and measures to be taken and support policy-makers towards adoption of conceivable welfare measures aimed at halting the growth of inequality. Based on these assumptions, we here discuss some variants of a mathematical “micro-to-macro” model for the dynamics of taxation and redistribution processes in a closed trading market society. The model has an exploratory character resulting from possible tuning of various parameters involved: through its analysis, one can foresee the consequences on the long-run income distributions of different fiscal policies and differently weighted welfare policies, interventions, and subsidy provision, as well as the impact of the extent of tax evasion. In short, the model shows that in the long term redistributive policy results in a lower level of economic inequality in society.

scholarly journals Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0

2020 ◽  
Vol 13 (12) ◽  
pp. 5973-6009
Author(s):  
Virginie Moreaux ◽  
Simon Martel ◽  
Alexandre Bosc ◽  
Delphine Picart ◽  
David Achat ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Soil Carbon ◽  
Biogeochemical Processes ◽  
Forest Operations ◽  
Time Step ◽  
Vegetation Control ◽  
Clear Cutting ◽  
Go Model ◽  
The Impact

Abstract. The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon submodel is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time step. It represents a forest stand covering typically 1 ha and can be straightforwardly upscaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close to nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables.The sensitivity analysis demonstrates an interaction between the sensitivity of variables, with the climate and soil hydraulic properties being dominant under dry conditions but the leaf biochemical properties being most influential with wet soil. The sensitivity profile of the model changes from short to long timescales due to the cumulative effects of the fluxes of carbon, energy and water on the stand growth and canopy structure. Apart from a few specific cases, the model simulations are close to the values of the observations of atmospheric exchanges, tree growth, and soil carbon and water stock changes monitored over Douglas fir, European beech and pine forests of different ages. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

scholarly journals Probabilistic Prediction of Corrosion Damage of Steel Structures in the Vicinity of Roads

2020 ◽  
Vol 12 (23) ◽  
pp. 9851
Author(s):  
Monika Kubzova ◽  
Vit Krivy ◽  
Katerina Kreislova
Keyword(s):  
Sensitivity Analysis ◽  
Prediction Models ◽  
Steel Structures ◽  
Corrosion Damage ◽  
Accurate Estimate ◽  
Steel Bridge ◽  
Probabilistic Prediction ◽  
Winter Maintenance ◽  
The Impact

The design, construction, and maintenance of steel structures must be carried out in a way that ensures they will be able to reliably operate for the whole duration of their planned service life. To ensure sufficient durability, it is necessary to determine and evaluate the characteristics of the appropriate environment in which the structure will be placed. This submission focuses on the specific environment surrounding roads that are treated with de-icing salts during winter maintenance. It investigates the dependency between corrosive damage to the structure and the relevant parameters of the environment. Basic corrosive factors include temperature, relative humidity, deposition of chlorides and sulfur dioxide, precipitation, the pH of precipitation as well as many other parameters. An accurate estimate of corrosive damage requires an analysis of the long-term trends in concentrations of individual corrosive factors, while respecting their randomly varying attributes. The article, hence, introduces and evaluates stochastic prediction models that are based on long-term programs focusing on the evaluation of the corrosive aggressiveness of the environment, while taking into account random variations of the nature of the input parameters. The use of stochastic prediction models allows us to perform sensitivity analysis that can determine the impact of specific corrosive factors on the corrosive damage caused to the structure. The article is supplemented by sensitivity analysis focusing on an evaluation from the effects of the deposition of chlorides on the corrosive damage to steel bridge structures. The analysis was carried out using data obtained from experimental measurements of the deposition rates of chlorides in the vicinity of roads in the Czech Republic.

Suppressed, but Not Forgotten

2011 ◽  
Vol 70 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Beat Meier ◽  
Anja König ◽  
Samuel Parak ◽  
Katharina Henke
Keyword(s):  
Memory Trace ◽  
Thought Suppression ◽  
Test Phase ◽  
Indirect Test ◽  
Final Test ◽  
Test Experiment ◽  
And Control ◽  
Cue Words ◽  
The Impact

This study investigates the impact of thought suppression over a 1-week interval. In two experiments with 80 university students each, we used the think/no-think paradigm in which participants initially learn a list of word pairs (cue-target associations). Then they were presented with some of the cue words again and should either respond with the target word or avoid thinking about it. In the final test phase, their memory for the initially learned cue-target pairs was tested. In Experiment 1, type of memory test was manipulated (i.e., direct vs. indirect). In Experiment 2, type of no-think instructions was manipulated (i.e., suppress vs. substitute). Overall, our results showed poorer memory for no-think and control items compared to think items across all experiments and conditions. Critically, however, more no-think than control items were remembered after the 1-week interval in the direct, but not in the indirect test (Experiment 1) and with thought suppression, but not thought substitution instructions (Experiment 2). We suggest that during thought suppression a brief reactivation of the learned association may lead to reconsolidation of the memory trace and hence to better retrieval of suppressed than control items in the long term.

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