In a seminal article, Hanushek and Woessmann explained economic growth as a function of the quality of education. While they did not find evidence of the importance of years of schooling, they argued for the relevance of cognitive skills and a basic literacy ratio for economic growth. However, this result was based on cross-country data limited to 23 observations. In this study, we extended and modified their approach based on the results of PISA (Programme for International Student Assessment) tests to explain the GDP changes over the last 50 years. Using panel data, we considered the possible lag that characterizes this relationship, used statistical methods to address the risk of reversed causality of economic performance affecting the quality of education, and extended the model by the inclusion of other potential growth factors. The results, which also included several robustness checks, confirmed the relevance of earlier education quality as a significant growth factor. Our results suggest the significance of educational skills for GDP growth, which might be treated as a confirmation of the importance of quality primary and secondary education for economic development. We showed that our results are robust to changes in the order of lags and confirmed the validity of the conclusion with the use of specification-robust Bayesian model averaging.

This article aims to determine what drives the price of Bitcoin. To achieve this aim, a large set of data is analysed using VEC models augmented by factors representing unobservable economic forces. They have been obtained by means of principal component analysis. This method enables us to contribute to the existing literature on Bitcoin in two ways. First, we employ the dimension reduction technique to combine variables from several papers. Second, we estimate several unobservable economic concepts instead of utilizing proxy variables as is usually done. We find that the main factor driving the Bitcoin price is its popularity. Hence, our result not only confirms some previous findings but reinforces them by providing a better definition of popularity. Finally, we conclude that the Bitcoin price is not affected by supply and demand factors in the way that is natural for conventional currencies.

Although the development of the card payment system allows for lowering the costs of money circulation and thereby leads to significant economic gains, relatively small amount of research has been dedicated to the analysis of the determinants of this development. Therefore, the aim of the article is to seek cross-country determinants of retail card payments focusing on trust in the system. The article concentrates on two econometric models. One is constructed with the use of representative population survey data for Poland, the other is based on panel data from the EU countries in the years 2000–2012.

This article empirically investigates the effects of corruption and privatisation on economic growth in the post-communist countries of Central and Eastern Europe and the former USSR. We use a corruption and privatisation augmented open-economy leader–follower endogenous growth model to derive our research hypotheses. In this setting, corruption, privatisation and external openness jointly determine the per capita income in the follower economy. This model predicts that economies with higher shares of private ownership, lower corruption, and higher external openness enjoy higher rates of growth. Our empirical verification of these predictions is based on a panel of 29 post-communist countries during the period 1996–2014. Our estimation results confirm the negative effects of corruption, while the positive effects of privatisation are limited to small-scale privatisation.

In this article, we study firm-level determinants of corruption using a sample of 164,000 companies from 144 countries for the 2005–2020 period. We analyze two variables related to corruption: the perception of corruption as an obstacle to doing business using an ordinal logit model and actual bribe tax payments using a fractional logit model. Controlling for other factors, both sets of our empirical results show that the extent of corruption is related to the time spent dealing with regulations and inspections. We argue that firms which spend more time dealing with administrative procedures have a greater perception of corruption and are forced to make significantly higher bribe payments. Therefore, in a successful fight against corruption, it is essential to simplify administrative procedures by reducing their number and eliminating direct contacts between firms and officials.