In this paper, the simultaneous effects of the inequality and redistribution on economic growth are tested for the whole sample and for a subset of democratic countries, following SYS-GMM estimation on a panel dataset over a period from 1960 to 2010. Overall, net inequality has a negative significant effect on subsequent 5 years for both samples, while redistribution impact is only significant in democracies. The findings are consistent with the fact that governments tend to significantly redistribute more in democracies.
{"title":"The Effects of Income Inequality and Redistribution in Democracies: A Dynamic Panel Data Approach","authors":"Goksu Aslan","doi":"10.12775/DEM.2017.002","DOIUrl":"https://doi.org/10.12775/DEM.2017.002","url":null,"abstract":"In this paper, the simultaneous effects of the inequality and redistribution on economic growth are tested for the whole sample and for a subset of democratic countries, following SYS-GMM estimation on a panel dataset over a period from 1960 to 2010. Overall, net inequality has a negative significant effect on subsequent 5 years for both samples, while redistribution impact is only significant in democracies. The findings are consistent with the fact that governments tend to significantly redistribute more in democracies.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"17 1","pages":"19-39"},"PeriodicalIF":0.0,"publicationDate":"2017-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42982442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Osińska, Tadeusz Kufel, Marcin Błażejowski, Paweł Kufel
We propose to apply a time-series-based nonlinear mechanism in the threshold autoregression (TAR) form in order to examine business cycles in Central and Eastern European economies and compare them to the entire EU business cycle. The threshold variables, such as consumer price index, short and long interest rates, unemployment rate and an exchange rate vs. the U.S. Dollar, have been considered. The purpose of the paper is to model and to predict business cycles in Central and East European (CEE) economies (the EU Member States) and compare them to business cycles of the entire EU28 area and Eurozone EU19. We found that the exogenous mechanism played an important role in diagnosing the phases of business cycles in CEE economies, which is in line with the entire EU economic area. The results of business cycle forecasting using bootstrap technique are quite promising, while bootstrap confidence intervals are used for diagnosis.
{"title":"Modelling and Forecasting Business Cycle in CEE Countries using a Threshold Approach","authors":"M. Osińska, Tadeusz Kufel, Marcin Błażejowski, Paweł Kufel","doi":"10.12775/DEM.2016.008","DOIUrl":"https://doi.org/10.12775/DEM.2016.008","url":null,"abstract":"We propose to apply a time-series-based nonlinear mechanism in the threshold autoregression (TAR) form in order to examine business cycles in Central and Eastern European economies and compare them to the entire EU business cycle. The threshold variables, such as consumer price index, short and long interest rates, unemployment rate and an exchange rate vs. the U.S. Dollar, have been considered. The purpose of the paper is to model and to predict business cycles in Central and East European (CEE) economies (the EU Member States) and compare them to business cycles of the entire EU28 area and Eurozone EU19. We found that the exogenous mechanism played an important role in diagnosing the phases of business cycles in CEE economies, which is in line with the entire EU economic area. The results of business cycle forecasting using bootstrap technique are quite promising, while bootstrap confidence intervals are used for diagnosis.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"145-164"},"PeriodicalIF":0.0,"publicationDate":"2016-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66550300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we investigate if the strength of firm-market volatility relationship has changed after subprime crisis on the Polish Capital Market. The empirical study concern the selected companies listed on the Warsaw Stock Exchange (WSE) from the construction and IT sectors in the 2004–2011 period. The volatility measures were computed on the basis of daily low and high prices for companies shares and WIG index. For each company ARFIMAX-FIGARCH model with additional exogenous variables, which represented market volatility, was estimated in the stable and the turbulent period. Conducted empirical studies have not shown that the negative shocks flowing from the American stock market through investors' behavior channel contributed to the increase in the fraction of firms of the construction and IT sectors listed on the WSE whose volatility is shaped by market volatility.
{"title":"Analysis of the Relationship between Market Volatility and Firms Volatility on the Polish Capital Market","authors":"A. Włodarczyk, I. Otola","doi":"10.12775/DEM.2016.006","DOIUrl":"https://doi.org/10.12775/DEM.2016.006","url":null,"abstract":"In this paper we investigate if the strength of firm-market volatility relationship has changed after subprime crisis on the Polish Capital Market. The empirical study concern the selected companies listed on the Warsaw Stock Exchange (WSE) from the construction and IT sectors in the 2004–2011 period. The volatility measures were computed on the basis of daily low and high prices for companies shares and WIG index. For each company ARFIMAX-FIGARCH model with additional exogenous variables, which represented market volatility, was estimated in the stable and the turbulent period. Conducted empirical studies have not shown that the negative shocks flowing from the American stock market through investors' behavior channel contributed to the increase in the fraction of firms of the construction and IT sectors listed on the WSE whose volatility is shaped by market volatility.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"87-116"},"PeriodicalIF":0.0,"publicationDate":"2016-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66550172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The conditions of the pension funds (OFE) functioning were essentially changed in the years 2011–2014. The aim of the paper is to find out if these modifications influence the efficiency of the pension funds and to compare the performance of these funds to stable growth open investment funds (FIO). The analysis is provided for selected funds in the years 2009–2015. We conclude that in the examined period, OFE performed better than FIO, and the modifications of the rules for the pension funds caused the increase of risk and decrease of investment efficiency of these funds’ portfolios.
{"title":"Performance of Pension Funds and Stable Growth Open Investment Funds During the Changes in the Polish Retirement System","authors":"K. Kompa, D. Witkowska","doi":"10.12775/DEM.2016.007","DOIUrl":"https://doi.org/10.12775/DEM.2016.007","url":null,"abstract":"The conditions of the pension funds (OFE) functioning were essentially changed in the years 2011–2014. The aim of the paper is to find out if these modifications influence the efficiency of the pension funds and to compare the performance of these funds to stable growth open investment funds (FIO). The analysis is provided for selected funds in the years 2009–2015. We conclude that in the examined period, OFE performed better than FIO, and the modifications of the rules for the pension funds caused the increase of risk and decrease of investment efficiency of these funds’ portfolios.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"117-131"},"PeriodicalIF":0.0,"publicationDate":"2016-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66550232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper the threshold (T-ECM) and linear (ECM) error correction models are estimated to examine the short-run and long-run Granger causality in terms of asymmetric and symmetric relationship for seven European Union economies (Germany, France, Denmark, the Netherlands, Poland, Czech Republic and the whole EU). The relationship between production, inflation and oil prices are analyzed in the presence of structural break when both, the change in intercept and the change in the slope of the trend function exist. Threshold ECMs show the asymmetric response of production and inflation to the changes in oil prices in the case of Germany, France, Poland and the EU. For other economies (Netherlands, Denmark and Czech Republic) the reaction was rather symmetric.
{"title":"Asymmetries in the Relationship between Economic Activity and Oil Prices in the Selected EU Countries","authors":"Andrzej Geise, M. Piłatowska","doi":"10.12775/DEM.2016.004","DOIUrl":"https://doi.org/10.12775/DEM.2016.004","url":null,"abstract":"In this paper the threshold (T-ECM) and linear (ECM) error correction models are estimated to examine the short-run and long-run Granger causality in terms of asymmetric and symmetric relationship for seven European Union economies (Germany, France, Denmark, the Netherlands, Poland, Czech Republic and the whole EU). The relationship between production, inflation and oil prices are analyzed in the presence of structural break when both, the change in intercept and the change in the slope of the trend function exist. Threshold ECMs show the asymmetric response of production and inflation to the changes in oil prices in the case of Germany, France, Poland and the EU. For other economies (Netherlands, Denmark and Czech Republic) the reaction was rather symmetric.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"65-86"},"PeriodicalIF":0.0,"publicationDate":"2016-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66549580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this research we have tried to identify the relationship between the exchange rate for bitcoin to the leading currencies such as Dollar, Euro, British Pound and Chinese Yuan and Polish zloty as well. We have applied ARMA and GARCH models to model and to analyze the conditional mean and variance. The appliance of GARCH models have identified some dependency in explanation conditional variance between bitcoin and US Dollar, Euro and Yuan, while ARMA analysis have shown no relations between bitcoin and other dependent variables.
{"title":"Dependency Analysis between Bitcoin and Selected Global Currencies","authors":"Beata Szetela, Grzegorz Mentel, S. Gędek","doi":"10.12775/DEM.2016.009","DOIUrl":"https://doi.org/10.12775/DEM.2016.009","url":null,"abstract":"In this research we have tried to identify the relationship between the exchange rate for bitcoin to the leading currencies such as Dollar, Euro, British Pound and Chinese Yuan and Polish zloty as well. We have applied ARMA and GARCH models to model and to analyze the conditional mean and variance. The appliance of GARCH models have identified some dependency in explanation conditional variance between bitcoin and US Dollar, Euro and Yuan, while ARMA analysis have shown no relations between bitcoin and other dependent variables.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"133-144"},"PeriodicalIF":0.0,"publicationDate":"2016-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66550306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Described in Bauman and Jacobsen (2002) stock market anomaly still remains unexplained. In long time series regressions and wide geographical spread research “Halloween effect” is significant on 19 amongst 73 markets, but also in 11 amongst 23 with long time series data. Data shows that abnormal returns could be realized also in strategies staring in October, November and December. We conclude that even with control of weather (sun hours), behavioral (sentiment index, number of IPOs) and macroeconomic (industrial production) factors, the effect persists.
{"title":"“Sell not only in May”. Seasonal Effect on Emerging and Developed Stock Markets","authors":"Tomasz Schabek, Henrique Gonçalves de Castro","doi":"10.12775/DEM.2017.001","DOIUrl":"https://doi.org/10.12775/DEM.2017.001","url":null,"abstract":"Described in Bauman and Jacobsen (2002) stock market anomaly still remains unexplained. In long time series regressions and wide geographical spread research “Halloween effect” is significant on 19 amongst 73 markets, but also in 11 amongst 23 with long time series data. Data shows that abnormal returns could be realized also in strategies staring in October, November and December. We conclude that even with control of weather (sun hours), behavioral (sentiment index, number of IPOs) and macroeconomic (industrial production) factors, the effect persists.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"17 1","pages":"5-18"},"PeriodicalIF":0.0,"publicationDate":"2016-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66550381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We analyzed FDI determinants for 26 developed economies and 25 emerging markets. The analysis was conducted using a panel regression model for the period 1996–2014 as well as macroeconomic and institutional variables. Growth dynamics, increasing welfare, and the size of the market positively influence FDI. Among institutional variables, government stability index and the rule of law index exert positive impact upon FDI. Misgivings with respect to the quality of democracy and corruption do not undermine FDI inflow.
{"title":"Determinants of Foreign Direct Investment in Developed and Emerging Markets","authors":"J. Różański, P. Sekuła","doi":"10.12775/DEM.2016.005","DOIUrl":"https://doi.org/10.12775/DEM.2016.005","url":null,"abstract":"We analyzed FDI determinants for 26 developed economies and 25 emerging markets. The analysis was conducted using a panel regression model for the period 1996–2014 as well as macroeconomic and institutional variables. Growth dynamics, increasing welfare, and the size of the market positively influence FDI. Among institutional variables, government stability index and the rule of law index exert positive impact upon FDI. Misgivings with respect to the quality of democracy and corruption do not undermine FDI inflow.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"49-64"},"PeriodicalIF":0.0,"publicationDate":"2016-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66549646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the paper we present our initial results of an empirical verification of different methodologies of quantile forecasting used in operational management to calculate the re-order point or order-up-to level as well as the optimal order quantity according to the newsvendor model. The comparison encompasses 26 procedures including quantile regression, the basic bootstrap method and popular textbook formulas. Our results, obtained on the base of 30 time series concerning such diversified phenomena as supermarket sales, passenger transport and water and gas demand, point to the usefulness of regression medians, regression quantiles, bootstrap methods and the procedures available in the SAP ERP system.
{"title":"Quantile Forecasting in Operational Planning and Inventory Management – an Initial Empirical Verification","authors":"J. Bruzda","doi":"10.12775/DEM.2016.001","DOIUrl":"https://doi.org/10.12775/DEM.2016.001","url":null,"abstract":"In the paper we present our initial results of an empirical verification of different methodologies of quantile forecasting used in operational management to calculate the re-order point or order-up-to level as well as the optimal order quantity according to the newsvendor model. The comparison encompasses 26 procedures including quantile regression, the basic bootstrap method and popular textbook formulas. Our results, obtained on the base of 30 time series concerning such diversified phenomena as supermarket sales, passenger transport and water and gas demand, point to the usefulness of regression medians, regression quantiles, bootstrap methods and the procedures available in the SAP ERP system.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"5-20"},"PeriodicalIF":0.0,"publicationDate":"2016-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66549735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this article is to present the possibilities of using such a tool as Markov Chain to analyse the dynamics of returns observed at the Warsaw Stock Exchange. Process analysis is the basis for decision-making with regard to the accepted horizon. Expected times for achieving specified states, understood as intervals of rates of return, in particular those describing negative rates of return, are extremely important. In this context, there is a possibility of determining easily the value at risk with the accepted probability.
{"title":"Using the First Passage Times in Markov Chain Model to Support Financial Decisions on the Stock Exchange","authors":"J. Stawicki","doi":"10.12775/DEM.2016.003","DOIUrl":"https://doi.org/10.12775/DEM.2016.003","url":null,"abstract":"The purpose of this article is to present the possibilities of using such a tool as Markov Chain to analyse the dynamics of returns observed at the Warsaw Stock Exchange. Process analysis is the basis for decision-making with regard to the accepted horizon. Expected times for achieving specified states, understood as intervals of rates of return, in particular those describing negative rates of return, are extremely important. In this context, there is a possibility of determining easily the value at risk with the accepted probability.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"16 1","pages":"37-47"},"PeriodicalIF":0.0,"publicationDate":"2016-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66549944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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