scholarly journals Determinants of Corporate Dividend Policy in Polish Companies Listed on WSE

e-Finanse ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 47-55
Author(s):  
Magdalena Gostkowska-Drzewicka ◽  
Ewa Majerowska
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Stock Exchange ◽  
Structural Parameters ◽  
Random Effects Model ◽  
Profit Distribution ◽  
Dividend Payments ◽  
Warsaw Stock Exchange ◽  
History Of ◽  
Selection Of

AbstractThe purpose of this paper is to identify the factors influencing the level of dividend payments in the companies listed on the Warsaw Stock Exchange in 1998-2017 as well as to provide empirical evidence for their significance, using a panel data approach. The object of research comprised the companies listed on WSE, as of February 01, 2019. The subject of the analysis are the dividends paid by the companies and the factors potentially influencing the decisions regarding profit distribution. The models estimated for the panel data, based on the theory, allowed selection of the best model, which is the random-effects model. Moreover, these models allowed identification of the factors determining the changes in the level of dividend per share. The best model was the random-effects model. This model allowed identification of the factors impacting the changes in the level of dividend per share, that is, the value of the company’s total assets and the history of the company’s operation on the stock exchange market. All structural parameters (except the intercept) were positive. It means that growth of each of these variables causes an increase in the dividend per share.

scholarly journals Why Do Household Businesses Stay Informal?

2020 ◽  
pp. 134-157
Author(s):  
Thi Bich Tran ◽  
Hai Anh La
Keyword(s):  
Developing Countries ◽  
Panel Data ◽  
Random Effects ◽  
Random Effects Model ◽  
Qualitative And Quantitative ◽  
Quantitative Studies ◽  
Medium Enterprise ◽  
Enterprise Surveys ◽  
Net Benefits ◽  
Unbalanced Panel Data

Using unbalanced panel data from the small and medium enterprise surveys in 2005, 2007, 2009, 2011, 2013, and 2015, this chapter investigates factors associated with informality in Vietnam. We assume that household businesses, especially the top tier firms, become formal either because they perceive benefits of formalization such as an increase in the household performance, or because they want to escape bribes and harassment. Using the random effects model with controlling for the pre-formalization trends, our results show that productive household businesses stay informal because net costs from tax payment may surpass net benefits from formalization. Moreover, government controls do not promote formalization, especially among the ‘upper’ tiers of informal households. Our findings raise suspicions of collusion corruption between informal households in top tiers and officials. Future steps could be qualitative and quantitative studies to investigate collusion corruption as a determinant of informality in developing countries.

scholarly journals Strategies of Dividend policy of the companies listed on the Warsaw Stock Exchange

2015 ◽  
Vol 15 (1) ◽  
pp. 69-82
Author(s):  
Bartłomiej Jabłoński ◽  
Jacek Kuczowic
Keyword(s):  
Dividend Policy ◽  
Stock Exchange ◽  
Investor Relations ◽  
Research Results ◽  
Dividend Policies ◽  
Dividend Payments ◽  
Warsaw Stock Exchange ◽  
Development Processes ◽  
Basic Determinant ◽  
The Way

Abstract Research into the determinants of companies’ decisions about paying out dividends, which has been described in the Polish specialist literature, concentrates mainly on the dividends actually paid out. The research presented in the article refers to declarations of the companies included in their dividend policies. The aim of the article is to present an attitude to dividend policy exhibited by the companies listed on the Warsaw stock exchange. A particular attempt was made at identifying various formulas of constructing dividend policies by the companies and the declared conditions for dividend payments and their amounts. 118 dividend companies took part in the research and they were selected from among the companies listed on the Warsaw stock exchange in the years 2006-2012. The authors have analysed the dividend policy of the companies in terms of its components and the way it was formulated, as well as the determinants of decisions about dividend payments declared by the companies. The results of the analysis were referred to the types of strategies of the dividend policy presented in the specialist literature. The research results indicate that the boards of many companies do not consider formulating and publicising the principles of making dividend payments to be a relevant area of investor relations. The dividend policy of the companies is usually formulated too generally, with the use of general statements. Satisfying capital needs for the planned development processes appears to be a basic determinant of the distribution of profit, which is why residual dividend policy is prevalent in the analysed companies.

A selection of remarks on the measurement of correlations between variables of a panel data structure

2021 ◽  
Vol 66 (5) ◽  
pp. 7-25
Author(s):  
Mieczysław Kowerski ◽  
Jarosław Bielak
Keyword(s):  
Panel Data ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Correlation Coefficients ◽  
Data Dependencies ◽  
Construction Companies ◽  
Advantages And Disadvantages ◽  
Warsaw Stock Exchange

Many articles featuring panel data modelling tend to begin their considerations with an introduction of the Pearson linear correlation coefficients matrix between the analysed variables. The aim of the article is to prove such an approach unsuitable in the analysis of panel data dependencies. Instead, an attempt has been made to propose a more appropriate measure – a correlation coefficient between the empirical and fitted values of the dependent variable of the estimated panel model (with fixed or random effects) in relation to the variable whose dependency towards the dependent variable is being studied. Pearson’s linear correlation coefficient does not reflect the basic advantage of panel data, which is the ability to provide information about the dependencies of the studied phenomena simultaneously in time and space. The fact that one observation relates to object i during period t and another to object j during period t + 1 is irrelevant for the calculation of the coefficient. Pearson’s coefficient, however, can be used when conducting sub-calculations in panel data analysis. The presented considerations have been illustrated by the calculations of the relationships between the structure of capital and the profitability and size of 17 construction companies listed on the Warsaw Stock Exchange in the years 2009–2018 (170 observations) which created a balanced panel. A specification of the advantages and disadvantages of the proposed solution was formulated on the basis of the calculations.

scholarly journals FORECASTING MONEY DEMAND WITH THE INCLUSION OF FINANCIAL INNOVATION FOR THE ASSOCIATION OF SOUTHEAST ASIAN NATIONS: EVIDENCE FROM PANEL DATA ANALYSIS

2019 ◽  
Vol 1 (1) ◽  
pp. 59-74
Author(s):  
Payam Mohammad Aliha ◽  
Tamat Sarmidi ◽  
Fathin Faizah Said
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Random Effects ◽  
Money Demand ◽  
Fixed Effects ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Demand For Money ◽  
Financial Innovations ◽  
The Impact

This paper investigates the impact of financial innovations on the demand for money using a dynamic panel data for 10 ASEAN member states from 2004 to 2012 and attempt to forecast the demand for money during 2013 – 2016 to compare between forecasting performance of the fixed effects model with that of random effects model and also to compare the forecasting accuracy of dynamic forecasting and static forecasting obtained from these two models. An autoregressive model by definition is when a value from a time series is regressed on previous values from that same time series. There are two types of forecasting namely dynamic forecast and static forecast. “Dynamic forecast will take previously forecasted values while static forecast will take actual values to make next step forecast. Panel effects models assist in controlling for unobserved heterogeneity when this heterogeneity is constant over time and correlated (fixed effects) or uncorrelated (random effects) with independent variables. Hausman test indicates that the random-effects model is appropriate. We use the conventional money demand that is enriched with the number of automated teller machines (ATM) to proxy for the effect of financial innovations on money demand. By comparing the magnitude of “Root Mean Squared Error” (RMSE) as a benchmark for the two forecasts (0.1164 for dynamic forecast versus 0.0635 for static forecast) we simply find out that static forecast is superior to dynamic forecast meaning that static forecast provides more accurate forecast compared to a dynamic forecast for the fixed-effects model. Therefore, we conclude the static forecast on the basis of the random-effects model provides the most accurate forecasting. The estimation result of the chosen random-effects regression also indicates the estimated coefficient of ATM is not significant meaning that ATM does not impact money demand in ASEAN countries.

MODELLING AND ESTIMATING INDIVIDUAL AND FIRM EFFECTS WITH COUNT PANEL DATA

2018 ◽  
Vol 48 (3) ◽  
pp. 1049-1078 ◽  
Author(s):  
Jean-François Angers ◽  
Denise Desjardins ◽  
Georges Dionne ◽  
François Guertin
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Parametric Model ◽  
Random Effects Model ◽  
Road Accidents ◽  
Fixed Effects Model ◽  
Insurance Pricing ◽  
Count Panel Data ◽  
Unobservable Factors

AbstractWe propose a new parametric model for the modelling and estimation of event distributions for individuals in different firms. The analysis uses panel data and takes into account individual and firm effects in a non-linear model. Non-observable factors are treated as random effects. In our application, the distribution of accidents is affected by observable and non-observable factors from vehicles, drivers and fleets of vehicles. Observable and unobservable factors are significant to explain road accidents, which mean that insurance pricing should take into account all these factors. A fixed effects model is also estimated to test the consistency of the random effects model.

scholarly journals Global Versus Non-Global Banks: A Capital Ratios-Based Analysis

2021 ◽  
Vol 10 (2) ◽  
pp. 5-22
Author(s):  
Konstantinos Drakos ◽  
Ioannis Malandrakis
Keyword(s):  
Panel Data ◽  
Financial Crisis ◽  
Random Effects ◽  
Financial Institutions ◽  
Random Effects Model ◽  
Data Set ◽  
Leverage Ratio ◽  
Total Capital ◽  
Capital Ratios ◽  
Global Banks

Abstract This paper examines the Leverage Ratio and Total Capital Ratio of global versus non-global banks in both the pre- and post-crisis periods. A panel data set of 165 global and non-global financial institutions from 38 countries is used for the period 1999-2015 and a random effects model is employed to examine whether global banks perform better or not compared to their non-global counterparts. This study comes up with two important findings. First, global banks do not exhibit heterogeneous behaviour with respect to both ratios neither in the pre- and especially nor in the post-crisis period. Second, the Leverage Ratio is crisis-insensitive, but the Total Capital Ratio is not. Our findings encourage further research on the topic of the contribution of global banks to the financial crisis propagation (at least as far as leverage is concerned).

scholarly journals Capital Structure of Companies Listed at the Warsaw Stock Exchange and the COVID-19 Pandemic Effect on Their Risk

2021 ◽  
Vol 4 (32) ◽  
pp. 153-166
Author(s):  
Jerzy Gajdka ◽  
Marek Szymański
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Financial Management ◽  
Stock Exchange ◽  
Idiosyncratic Risk ◽  
Total Risk ◽  
Panel Data Regression ◽  
Data Regression ◽  
Warsaw Stock Exchange ◽  
The Relationship

Subject: The financial management of companies is examined in the context of the COVID-19 pandemic. Specifically, the relationship between their capital structure and risk changes during the pandemic is scrutinised. The purpose of the article: To determine how companies’ total, systematic and idiosyncratic risks changed during the COVID-19 pandemic depending on their capital structure based on a sample of organisations listed at the Warsaw Stock Exchange. Methodology: The study involves the use of a panel data regression model. Results of the research: The COVID-19 pandemic had an impact on the risk of overleveraged companies and underleveraged ones alike. Its influence on their total risk was weaker among the underleveraged organisations. Regarding systematic risk, its levels did not generally change significantly in the wake of the pandemic, but idiosyncratic risk, only in the case of the overleveraged companies increased statistically significantly.

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