For the private and public sector in any particular country it is crucial to know, which industries may exhibit comparative advantages, that for some reasons are not realized. This can efficiently help all current and potential actors to improve their economic strategy both at the micro- and macroeconomic level. In this paper we propose an approach of forecasting comparative advantages dynamics in foreign trade. The instrument is based on relative price differences and is efficient for countries in the process of economic liberalization. An empirical analysis based on the example of Central and East European countries confirms a good performance in the sense of predictive power of this instrument. On the example of Russia, experiencing a period of economic liberalization and with the prospect to join the WTO agreements, we demonstrate which sectors are most likely to contain comparative advantages in the near future.
This study aims at identifying determinants of health related quality of life in Poland, and in particular at verifying whether health domains are complements or substitutes and what the impact of heterogeneity of population on the health state valuation is. The paper uses data in panel structure coming from a survey conducted in Poland and consisting of 6700 valuations (after data cleaning) of EQ-5D health states with time trade-off method. Several econometric models are built in order to detect the impact of complementarity and heterogeneity. Random effects models as well as random parameters models estimated using Bayesian approach are used. The results show that health domains are complementary goods. Especially the lack of pain/discomfort is a complement to other health domains. Demographic factors influence how health state change impacts utility. These factors encompass sex, education, respondent’s health state and even belief in life after death.
The main goal of this paper is to analyze the matching function in the Polish labour market in 1994‒2008. Matching function is the relationship between outflows from unemployment to employment and the number of unemployed persons and vacancies as well as other variables which affect the efficiency of the matching process directly or indirectly. Such matching function in its augmented form is estimated here for Poland with the use of data from register of unemployed persons.
The results indicate that there is a statistically stronger impact of the unemployed than vacancies on new hires. Furthermore, the institutional conditions of the labour market, the structure of the unemployed and the participants of active labour market programs (ALMP) play a role in the matching process.
The aim of this paper is to examine the empirical usefulness of two new MSF – Scalar BEKK(1,1) models of n-variate volatility. These models formally belong to the MSV class, but in fact are some hybrids of the simplest MGARCH and MSV specifications. Such hybrid structures have been proposed as feasible (yet non-trivial) tools for analyzing highly dimensional financial data (large n). This research shows Bayesian model comparison for two data sets with n = 2, since in bivariate cases we can obtain Bayes factors against many (even unparsimonious) MGARCH and MSV specifications. Also, for bivariate data, approximate posterior results (based on preliminary estimates of nuisance matrix parameters) are compared to the exact ones in both MSF-SBEKK models. Finally, approximate results are obtained for a large set of returns on equities (n = 34).
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