The paper investigates the causal relationship between the trust in institutions and compliance with measures introduced to slow down the spread of the novel coronavirus COVID-19 in Slovakia. In addition, the impact of socioeconomic characteristics on compliance with introduced measures was analysed. Data were obtained from a survey carried out by the Slovak Academy of Sciences on a representative sample of the Slovak population of 1,000 respondents. To derive the causal relationship between institutional trust and compliance behaviour, a probit regression model was used. Findings suggest that trust in public institutions helps to increase compliance with social distancing. In addition, some socio-economic characteristics such as employment status, age or whether individuals felt endangered by COVID-19 had a positive and statistically significant effect on compliance with measures used to slow the spread of the COVID-19 virus. Institutional trust did not have a statistically significant effect on compliance with face-covering measures.
This article uses a recent wave of the World Bank Enterprise Survey to analyse four aspects of innovation: (i) the introduction of a new product or service, (ii) product/service upgrading, (iii) R&D and (iv) the licensing of technology. Good governance affects innovation on several dimensions. Bureaucracy, in the form of permits posing a problem for firms, can deter firms from innovating themselves, moving them towards the licensing of foreign technology, and corruption deters R&D. However, there is evidence of a negative impact of good and effective courts on innovation and R&D. Although perhaps slightly surprising, this is not inconsistent with much of the literature. In addition regional infrastructure, which is to varying degrees also determined by government policy, is significant in determining innovation. This includes transport, IT and financial infrastructure.
The process of calculating market clearing prices for cap and trade environmental pollution policies dealing with both air and water pollution remains problematic. The permit trading processes are designed to mimic the cost minimisation outcome. In the paper we design the market process for allocating permits to achieve the same type of behaviour we observe for each decision maker in the overall cost minimisation model. We aim to develop a modelling system that would be easy and efficient to operate. We use the method which is known as a computer-assisted 'smart market' and has been used in a number of electric energy pricing situations. This approach has also been proposed and applied to some types of environmental quality and resource management policies. In the paper the theoretical structure of the 'smart market' model is provided. After the review of different models that have been used to represent permit trading situations, the smart market model structure based on the shadow prices is developed.
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