This article contributes to the discussion on political socialization concept and research. The paper makes a critical insight in research history and development in the area of political socialization with the conclusions that there is no universal definition of political socialization and the field is still burdened by many theoretical and empirical controversies which could be resolved by examining causal mechanisms operating in the process of political socialization. The literature review describes the development of research in this field and shows that there is persistent need for retesting basic hypotheses. Showing the advantages and disadvantages of the panel data design the paper demonstrates why it is most suitable type of data for testing majority of the hypotheses of political socialization.
In this paper we analyse the saving mobility of Polish households, e.g. the mobility of households between classes of different saving rates. The analysis is based on the household budget panel data of 3001 Polish households surveyed in the same month during four consecutive years. The panel sample group was selected by authors from 30 000 households surveyed by Polish Central Statistical Office each year. We apply the Markov mobility matrices. The long term ergodic structure of households with regard to saving rates is estimated. It illustrates the probability of a household to fall into one of the saving rates range. Our results show that during four consecutive years (1997-2000), one third of the households which saved less than 20% of the household disposable income remained in their class. In the class of households that saved more than 20% of the household disposable income half of the households kept these high saving rates. In the long term, the probability of falling into a group of households with lowest saving is 0.2. Groups falling into -20% to -5% and -5% to 5% saving rates would be the least numerous. The highest probability (0.3) was to get into a group that saved more than 20% of the household disposable income. It shows the tendency towards polarization of the households with regard to saving rates.
We study the sovereign credit rating determinants of Visegrad Four countries in the period 1993 – 2012. The ratings come from four major credit rating agencies – Moody’s, S&P, Fitch and R&I. We use linear model with fixed effects. Besides the economic variables inflation, unemployment, broad money to GDP, import to export, openness of the economy, government gross debt, primary balance and size of the government we found out that voice & accountability score of Worldwide Governance Indicators is suitable representative of socio-political situation. Both EU and EMU membership provide additional information to other explanatory variables. The government finance is the most influential determinant in the researched dataset. Unlike in other academic papers, the growth of GDP was not significant variable to explain the sovereign ratings.
Existing empirical research fails to provide robust support concerning the impact of the financial development on the economic growth, in the presence of the substantial variations across different time periods and the country groups. It is suggested that the variations in question are to be accounted for by a threshold effect, in support of which, it seems to have been found the modest empirical evidence. Panel-data analysis for a set of 32 developing and developed countries for the period of 1990 - 2001 indicates a threshold level of financial development, with the implication that the positive effects fail to materialize at the relatively lower stages of financial development. Moreover, financial development has actually got a negative impact on GDP per capita, unless it exceeds the threshold level.
The severe material deprivation rate indicates the proportion of the population that cannot fulfil at least four of the nine needs identified as basic ones in the European conditions. Due to being an absolute measure, it is very useful for cross-country comparison. This study attempts to identify country-level factors affecting severe material deprivation rate by the use of the GEE methodology which enables to analyse correlated fractional outcome data. It is found that severe material deprivation rate is affected by such factors as: median equalised disposable income, relative median at-risk-of-poverty gap, long-term unemployment rate, GDP per capita and share of social protection expenditure in GDP. Results reveal that GEE models with clog log link function exhibit the best goodness of fit. Due to these models imposing non-constant marginal effects, therefore, changes of the severe material deprivation rates depend on levels of country-level factors.
This paper presents empirical evidence suggestive of the existence of a mutually reinforcing relationship between social capital and trust. Using cross-sectional data from the Polish General Social Survey 2002, as well as longitudinal data from the Social Diagnosis 2000-2007, it was shown that individuals re-create their patterns of social ties through their norms of trust. People who formed ties solely with their kin were convinced that they can trust only a few people in the world while those with both kin and non-kin mem- bers in their social networks were more inclined to believe in the benign naturę of humanity. These results, derived from cross-sectional data, are confirmed by the panel dataset which we use also for proving the converse hypothesis: people with higher levels of trust are more likely to form social ties with the non-kin. These findings are especially pertinent to Poland, a post-communist country seeking to build a civil society - social networks based on kin members combined with Iow levels of generał social trust can be a major obstacle in developing a civil society here.
Analysis of the empirical relationship between investment in information technology (IT) and growth rate of real GDP per capita in a panel of selected European countries for the period 1999 - 2001 seems to suggest that a 10% increase in the level of investment into IT (as % of GDP) would increase real GDP per capita by 1.2%, controlling for other variables. Switching to a decomposition approach (creating an interaction term), a 10% increase in the level of software and services (as % of GDP) would increase real GDP per capita by roughly 1%, controlling for other variables. Nevertheless, as has been shown in this study using correlation analysis and previous other studies, information technology on its own may not lead to accelerated economic growth unless accompanied by investment into human capital accumulation, research and development and other IT infrastructure. In this respect, the results of this paper seem to be consistent with previous other empirical findings.
Demand for foreign investment can create a financial gap characterising a lack of home resources. Harrod-Domar model gives a benchmark but the gap can be smaller what can be tested under an assumption of non-zero elasticity of substitution of domestic for foreign capital. New capital is characterised by capital mobility. A more open capital account implies a higher productive performance but for strong economies only. An approach based on a Feldstein-Ha-rioka hypothesis is used to quantify a measure of capital mobility by econometric models. Technique of panel data regressions is briefly mentioned as a tool which helps to solve the problem of not sufficiently long individual time -series. Analysis of twelve European transition economies is performed.
The purpose of this paper is to investigate the effects of public spending on economic growth and examine the sources of economic growth in developed countries since the 1990s. This paper analyses whether public spending effect on economic growth based on Cobb-Douglas Production Function with the two econometric models with Autoregressive Distributed Lag (ARDL) and Dynamic Fixed Effect (DFE) for 21 developed countries (high-income OECD countries), over the period 1990 – 2013. In comparison to similar empirical studies, our paper will add to the existing literature by extending the sample of developed countries and providing the latest empirical evidence for non-linear and structural breaks. Our model results are parallel to each other and the models support that public spending has an important role for economic growth. This result is accurate with theories and previous empirical studies.
The intellectual property as assets in intangible form is classified in most countries under the definitions of the TRIPS Agreement and PCT according to the manner of its protection. This article presents results of an analysis of relationship between the protection of intellectual property rights at certain globalisation level and verification of their influence on macroeconomic indicators in selected countries of a similar intellectual property protection system under the PCT. The time and cross-sectional data enabled to test the objections by applying a non-parametric statistical method – panel data regression with the effect of random cross-sectional variables. The conclusions show that there is a statistically significant probability of the relation between the quantity of registered patents and the level of GDP, GDP per capita and ANNI.
The aim of the article is to discuss a model used to determine the number of losses in automobile insurance. The model is based on panel data. Although the aim is to model the number of losses, due to hunger for bonus not all the losses are revealed. Thus the data on the number and also the value of claims are used. Common use of these two types of data enables estimation of the true number of losses that occur (not just those that are claimed). This is done with the use of true data from the Polish market. The discussion of particular factors that influence the severity of losses (moral hazard, hunger for bonus, observed and unobserved characteristics of the insured) is included.
The goal of this article is to apply panel data approach to the analysis of claim frequency in automobile insurance. The model which is constructed estimates the influence of particular characteristics of the insured on their insurance loss number, but it also enables identification of the hunger for bonus effect. Panel data approach allows for identification of drivers' individual effects that influence their driving quality, but cannot be quantified directly, such as for example tendency to drive fast. This is done thanks to repetitive observation of the same individuals. Having information on their number of losses claimed in different bonus-malus system classes, it is possible to separate their individual skills from the hunger for bonus phenomenon, as well as identify the scale of the latter, which differs in particular classes. Chapter one is an introduction. In chapter two main benefits from the use of panel data have been described. Recent publications considering the topic are mentioned as well, with emphasis on the differences between other authors' approaches and this one. Chapter three contains a brief description of the methods applied, which are Poisson regression mixed models. In chapter four the basic model is adjusted to the conditions of hunger for bonus and it is shown, how this phenomenon is identified. In chapter five empirical analysis based on the real market data of approximately 21 thousand observations is done. The model is estimated and the conclusions are discussed with a short simulation study of the insurance company financial state.
In this article the authors interconnect the framing and agenda-setting theories of mass-communication effects. They postulate that the framing process creates conditions for the agenda-setting process and argue that differently framed news have different effects in the agenda-setting process. They hypothesise that issue-specific frames, episodic frames, and value frames have a stronger agenda-setting effect than generic frames, thematic frames, and strategy frames and suggest explaining the role of frames in the agendasetting process through the theory of cognitive dissonance. The hypotheses are tested using matched panel survey data on respondents’ personal agendas and using a content analysis of the media in relation to one particular issue. The selected issue – the restitution of property to the Catholic Church – was chosen because it contains a rich combination of frames. Moreover, this is an issue on which it is possible to study the effect of a ‘focusing event’, which may have an additional and distinct effect in addition to the ‘regular’ frames. The authors show that differently framed news do indeed have distinctive effects on personal agenda-setting. Some frames have a strong positive effect, while others have no effect. They even identify one frame that appears to have a slightly negative net effect on personal agenda-setting. This is a somewhat revolutionary fi nding, since it demonstrates that, unlike the predictions made by the agenda-setting theory, people may (under certain conditions) react to the heightened media exposure of an issue by denying its importance.
The main aim of this paper is to demonstrate how psychological longitudinal research data can be analysed using panel data methods. The determinants of dynamics of PTSD symptoms are used as an example. The approach used here allows for treating data from three measures as unity and incorporating them into one model, instead of estimating three independent data sets. It enables for formal verification of the independent variables – temperamental traits and trauma characteristics – influence on the dependent variable – dimensionally expressed PTSD symptoms intensity. As a result it is possible to verify the hypothesis of different influence of trauma intensity on PTSD symptoms in different family members by comparing parametres' estimates in one model encorporating group of interactive variables. Such approach seems to be an interesting option, contrary to comparisons of parametres' estimates derived from different models.
For a number of decades, the European Union has witnessed an intense global competition to attract foreign direct investment (FDI). This competition has led to significant inflows and outflows in the member states, with positive implications for economic growth, employment and productivity for the host and sending countries. The paper uses data from 2005 – 2017 to identify the main drivers of FDI in the EU separately for sending and receiving, Euro area and Non-Euro countries. Analysis focuses on finding the levers that promote the Union in its entirety as a major competitor for FDI. An empirical analysis is conducted for selected variables (economic development, taxation, unit labour costs, trade openness, interest rate differential, macroeconomic stability, infrastructure and competitiveness) using the two-step System Generalised Method of Moments (GMM). The results are robust and consistent with the supporting literature.
Autonomy of local governments consists also in the financial autonomy. In the SR, the municipal financial autonomy is importantly influenced by dominant position of shared tax in the municipal tax revenue. When considering only own revenues (own tax and nontax), the financial autonomy of municipalities is low. In this paper the financial autonomy of municipalities in the SR is analysed in the period 2005 – 2019. Inequalities in financial autonomy are analysed at the base of the Gini index. Higher inequalities are observed in case of the exclusion of shared tax, what confirms that the shared tax serves as a channel of horizontal fiscal equalization. Employing the panel regression, determinants of financial autonomy are analysed. The negative relationship is observed in case of the population growth, use of returnable financial resources, financial crisis and also the portion of shared tax on municipal tax revenue, when considering the financial autonomy based on own resources.
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