scholarly journals Institutional Factors Influencing Political Trust in Modern Russia

2020 ◽  
Vol 12 (4) ◽  
pp. 077-093
Author(s):  
Marina Yu. Malkina ◽  
◽  
Vyacheslav N. Ovchinnikov ◽  
Konstantin A. Kholodilin ◽  
◽  
...  

The aim of this study is to analyze and assess the impact of institutional factors on political trust in various levels of government (federal, regional and local) in modern Russia. Data and methods. The study is based on microdata from the European Bank for Reconstruction and Development (EBRD) “Life in Transition Survey” (LiTS). We examined such institutional factors of political trust as perceived government performance and level of corruption, as well as the level of interpersonal trust. The subjective decile of household wealth was an additional explanatory variable in our analysis. We estimated the model parameters using linear regressions with instrumental variables. Results and their application. First, we found that in 2016 the perceived effectiveness of the federal government was the main determinant of Russian trust in the president. At the same time, the perceived level of local corruption was a major factor of Russian citizens’ (mis)trust in local authorities. Second, we found that poor households turned out to be the most loyal groups of the population towards the Russian president, and we explained this phenomenon by the active redistributive policy of the federal authorities. Third, we revealed a significant positive relationship between political and interpersonal trust at the micro level. In conclusion, we made recommendations on the effective management of political trust in modern Russia.

2020 ◽  
pp. 62-79
Author(s):  
P. N. Pavlov

The paper analyzes the impact of the federal regulatory burden on poverty dynamics in Russia. The paper provides regional level indices of the federal regulatory burden on the economy in 2008—2018 which take into account sectoral structure of regions’ output and the level of regulatory rigidity of federal regulations governing certain types of economic activity. Estimates of empirical specifications of poverty theoretical model with the inclusion of macroeconomic and institutional factors shows that limiting the scope of the rulemaking activity of government bodies and weakening of new regulations rigidity contributes to a statistically significant reduction in the level of poverty in Russian regions. Cancellation of 10% of accumulated federal level requirements through the “regulatory guillotine” administrative reform may take out of poverty about 1.1—1.4 million people.


Asian Survey ◽  
2020 ◽  
Vol 60 (5) ◽  
pp. 978-1003
Author(s):  
Jacqueline Chen Chen ◽  
Jun Xiang

Existing studies of the impact of economic development on political trust in China have two major gaps: they fail to explain how economic development contributes to the hierarchical trust pattern, and they do not pay enough attention to the underlying mechanisms. In light of cultural theory and political control theory, we propose adapting performance theory into a theory of “asymmetrical attribution of performance” to better illuminate the case of China. This adapted theory leads to dual pathway theses: expectation fulfillment and local blaming. Using a multilevel mediation model, we show that expectation fulfillment mainly upholds trust in the central government, whereas local blaming undermines trust in local governments. We also uncover a rural–urban distinction in the dual pathway, revealing that both theses are more salient among rural Chinese.


2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.


Author(s):  
Julie Vinck ◽  
Wim Van Lancker

Belgium has been plagued by comparatively high levels of child poverty, and by a creeping, yet significant, increase that started in the good years before the crisis. This is related to the relatively high share of jobless households, the extremely high and increasing poverty risk of children growing up in these households, and benefits that are inadequate to shield jobless families with children from poverty. Although the impact of the Great Recession was limited in Belgium, the crisis seems to have had an impact on child poverty, by increasing the number of children living in work-poor households. Although the Belgian welfare state had an important cushioning impact, its poverty-reducing capacity was less strong than it used to be. The most important lesson from the crisis is that in order to make further headway in reducing child poverty, not only activation but also social protection should be improved.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego

AbstractEpidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ($$R_t$$ R t ). The relationship between public health interventions and $$R_t$$ R t was explored, firstly using a hierarchical clustering algorithm on initial $$R_t$$ R t patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, $$R_t$$ R t , and daily incidence counts in subsequent months. The impact of updating $$R_t$$ R t every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future $$R_t$$ R t (75 days lag), while a lower $$R_t$$ R t was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated $$R_t$$ R t produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when $$R_t$$ R t was kept constant. Monitoring the evolution of $$R_t$$ R t during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated $$R_t$$ R t values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of $$R_t$$ R t over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.


Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 102
Author(s):  
Frauke Kachholz ◽  
Jens Tränckner

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.


Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 463
Author(s):  
Gopinathan R. Abhijith ◽  
Leonid Kadinski ◽  
Avi Ostfeld

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.


Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 387
Author(s):  
Yiting Liang ◽  
Yuanhua Zhang ◽  
Yonggang Li

A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.


2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shuai Yang ◽  
Haijun Jiang ◽  
Cheng Hu ◽  
Juan Yu ◽  
Jiarong Li

Abstract In this paper, a novel rumor-spreading model is proposed under bilingual environment and heterogenous networks, which considers that exposures may be converted to spreaders or stiflers at a set rate. Firstly, the nonnegativity and boundedness of the solution for rumor-spreading model are proved by reductio ad absurdum. Secondly, both the basic reproduction number and the stability of the rumor-free equilibrium are systematically discussed. Whereafter, the global stability of rumor-prevailing equilibrium is explored by utilizing Lyapunov method and LaSalle’s invariance principle. Finally, the sensitivity analysis and the numerical simulation are respectively presented to analyze the impact of model parameters and illustrate the validity of theoretical results.


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