C51 - Model Construction and EstimationReturn

This paper investigates the nonlinear risk transmission from the oil and natural gas markets to the foreign exchange markets of five energy importers and one major energy exporter. We separate conditional volatility into the transitory (short-term) and permanent (long-term) parts, and then these volatilities are embedded in an elaborate robust linear quantile regression model. We find that the risk spillover effect is relatively low in Central and Eastern European countries (CEECs) probably because they pursue a managed float exchange rate regime. On the other hand, this effect is higher for Turkey and Russia, which is especially true for the effect from oil to the rouble at the highest quantile. This happens because Russia receives the largest amount of foreign currency from oil exports. The results indicate that the short-term risk spillover effect is notably stronger than the long-term one, which means that the exchange rate volatility is mainly determined by market sentiment. The rolling regression results coincide very well with the estimated quantile parameters.

This study assesses the relationship between the ownership structure and corporate tax avoidance based on annual financial data of Chinese A-share listed firms during 2010-2020. Firstly, the empirical results demonstrate that when a listed firm has multiple large shareholders (MLS), these shareholders are likely to weaken internal monitoring and collude with each other, which will lower its corporate governance level and increase its corporate tax avoidance (CTA) level. The empirical conclusion remains valid after multiple robustness tests. Secondly, the empirical result of the baseline model is significantly influenced by the nature of ownership, the quality of external audit, the tracking of securities analysts and the firm's location. Finally, the result of our mediating effect analysis shows that the presence of MLS reduces the company investment efficiency, which provokes firms to make aggressive financial choices to obtain resources to ensure their future development.

Green development prioritizes ecology and sustainability and strengthens scientific and technological innovation to drive high-quality economic development. This paper con- structs a coupled coordination model of a system evaluation index to explore the spatial and temporal pattern of green technology innovation and high-quality economic development. it also employs a Tobit regression model to analyse the influencing factors of coordinated development further. For this purpose, panel data on 30 Chinese provincial administrative regions were selected, ranging from 2010 to 2019. The results indicate that the level of coupling and coordination of green technology innovation with high-quality economic quality shows a steady upward trend and the evolution trend of "basic, moderate, and high coordination". At the same time, differences in coordinated development between regions are obvious, showing a development trend of "high in the east and low in the west". It is affected positively by the industrial structure, urbanization level, economic development level, R&D investment, foreign investment and education investment. In contrast, energy consumption has inhibited the coordinated development of green technology innovation and a high-quality economy coupling.

The aim of this paper is to develop subjective synthetic indicators that quantify the quality of life in the different countries of the EU-28, with data from the 2016 European Quality of Life Survey (EQLS). We add other indicators to the general synthetic ones in order to quantify the different dimensions of quality life due to its multidimensional nature. The successive but unchained application of the principal component analysis and the Mazziota-Pareto analysis allows us to classify 5 dimensions of quality of life: subjective component of governance, public services, environment, general satisfaction with life, and socioeconomic issues. We verify that countries with the lowest or highest positions in the general index usually keep that position in most dimensions. The spatial perspective is fundamental to study of regional development. For this reason, the next objective is the analysis of differences by spatial location using the variance analysis. The general indicator shows significant differences between EU countries but it does not show differences in the quality of life of European citizens in urban and rural areas.

Fertilizer has brought great pressure to sustainable ecological environment. Research on the effect of price on fertilizer use as well as the substitution relationship of fertilizer and other input factors of agricultural production is of great importance for green, efficient, and intensive agricultural production in the world. This study first constructs translog cost functions and models of elasticity, then uses the factor input and price data from 2004 to 2016 to measure the price elasticity of fertilizer demand, and the elasticity of factor substitution in China's maize and cabbage production. The results suggest that: the price elasticity of fertilizer demand is in a low elasticity range; there is a compensation relationship between fertilizer and labour and a substitution relationship between fertilizer and machinery in China's maize production, while these relationships in China's cabbage production are opposite.

Over the last two decades, the current accounts in the European Union (EU) have diverged substantially. This divergence has raised concerns about the sustainability of the core countries' current account surpluses since the peripheral countries' financing of their significantly rising levels of current deficits depends on them. In this study, by applying both linear and nonlinear unit root tests and taking into account structural breaks in the data-generating process, we examine the current account sustainability of the main core countries with large external surpluses. We find that the current accounts of Austria, Denmark and Germany are not on sustainable paths, which suggests that the core economies might not continue to run surpluses to finance the peripheral countries' external deficits. The results of this study imply that the policymakers in peripheral countries might take proactive measures against possible borrowing problems and capital outflow risk in the future.

This paper analyses the dynamic nexus and bidirectional spillover effect between stocks and exchange rates in seven major emerging markets and one developed market. Three types of BEKK-GARCH models were utilized in the research process - basic BEKK-GARCH, asymmetric BEKK-GARCH and asymmetric BEKK-GARCH with structural breaks. Model with breaks gave the best fitting results in six out of eight cases. VAR based volatility spillover method serves as a complementary methodology. Results showed that dynamic connection between two major asset classes behaves in accordance with the portfolio balanced approach in emerging markets, while the nexus is in line with the flow oriented theory in the US market. In addition, according to the BEKK-GARCH results, shock and volatility spillover effect is predominantly directed from exchange rate market to stock market in all countries, while in the VAR based model it is not so obvious.

Estimation of claims reserves, which should be held by the insurer so as to be able to meet expected future claims arising from policies currently in force and policies written in the past, presents an important task for insurance companies to predict their liabilities. A common approach to the reser-ving problem is based on generalized linear models (GLM). In this article, the application of genera-lized linear mixed models (GLMM) - an extension of the GLM - for estimation of the loss reserves is shown. Since the GLMM allows incorporating a random effect instead of several fixed effects corresponding to the accident years as in case of the GLM, volatility of the prediction is reduced. This allows more flexible risk valuation, which is a crucial element of risk management and capital allocation practices of non-life insurers. A real data example together with diagnostics for the model selection are provided as an illustration of the potential benefits of the presented approach.

This paper investigates the dynamic conditional correlation (DCC) between stock returns and exchange rate in four East European emerging markets. Due to persistent long memory and the presence of the asymmetric effect in all asset markets we applied DCC-FIAPARCH model. The estimated negative DCC parameters in all scrutinized countries confirmed that portfolio-balanced theory has predominance in the short run in all selected economies. DCC parameters revealed significant time-varying behaviour, especially during the major crisis periods. By embedding dummy variables in the variance equations, we came to the conclusion that global shocks affect the volatility of DCCs. Particularly, it happened during the Global Financial Crisis and European sovereign debt crisis, but the effects were not linearly equal in all countries. Complementary rolling analysis unveils how conditional volatilities of analysed assets influence DCC. The results suggested that exchange rate conditional volatility has higher influence on DCC than stock conditional volatility.

The paper quantifies the role of factors associated with the growth (or decline) of micro and small businesses in European economies. The growth is related to the levels of employment and value added in enterprises, as well as, ten institutional variables. We test the data for consistency of behavioural patterns in various countries and gradually remove outlying observations that can lead to erroneous conclusions when using the classic estimators; this is a quite unique approach in panel data analysis. In the first part of this paper we outline a highly robust method of estimation based on fixed effects and least trimmed squares (LTS). In its second part we apply this method on the panel data of 28 countries in 2002-2008 testing for the hypothesis that micro and small businesses in Europe use different strategies for their growth. We run a series of econometric tests where we regress employment and total net production in micro and small businesses on three economic factors: gross capital returns, labour cost gaps in small relative to large enterprises and GDP per capita. In addition, we test the role of 10 institutional factors in the growth of family businesses.

This research is related to the assessment of alternative unemployment rate predictions for the Romanian economy, the forecasts being provided by three anonymous forecasters: F1, F2 and F3. F3 provided the most accurate forecasts for the horizon 2001-2014, while F2 predictions are the less accurate according to U1 Theil's statistic and according to a new method that has not been used before in literature in this context. The multi-criteria ranking was applied to make a hierarchy of the forecasters regarding the accuracy and five important accuracy measures were taken into account at the same time: mean errors, mean squared error, root mean squared error, U1 and U2 statistics of Theil. The combined forecasts of forecasters' predictions are the best strategy to improve the forecasts accuracy. The filtered and smoothed original predictions based on Hodrick-Prescott filter, respectively Holt-Winters technique, are a good strategy of improving the accuracy only for F2 expectations. The assessment and improvement of forecasts accuracy have an important contribution in growing the quality of decision-making process.

This paper analyses the pay-per-bid auctions which have appeared recently on the Internet and scored an immediate business success. In these auctions bidders pay a small, but irrevocable fee each time they want to increase the price. In this paper we test the model suggested by Platt, Price and Tappen (2010), which forecasts the distribution of closing prices depending on the item's value, bid fee and price increment. The data from the Czech leading auction site Bonus.cz were chosen for the test. Observed closing prices distribution of about 69 % of commonly auctioned items fits the model. However, we find some theoretical and practical flaws in the model. Contrary to the model predictions, we observed that auctions with smaller price increments generated significantly higher revenue than auctions with higher price increments. We suggest that bidders who favour skewness in payoff distribution cause auctions with lower price increment run longer and therefore explain this discrepancy.

This paper is devoted to the estimation of the probability of default (PD) as a crucial parameter in risk management, requests for loans, rating estimation, pricing of credit derivatives and many others key financial fields. Particularly, in this paper we will estimate the PD of US banks by means of the statistical models, generally known as credit scoring models. First, in theoretical part, we will briefly introduce the two main categories of credit scoring models, which will be afterwards used in application part - linear discriminant analysis and regression models (logit and probit), including testing the statistical significance of estimated parameters. In the main part of the paper we will work with the sample of almost three hundred US commercial banks which will be separated into two groups (non-default and default) on the basis of historical information. Subsequently, we will stepwise apply the mentioned above scoring models on this sample to derive several models for estimation of PD. Further we will apply these models to the control sample to determine the most appropriate model.

This work studies implicitly weighted robust statistical methods suitable for econometric problems. We study robust estimation mainly for the context of heteroscedasticity or high dimension, which are up-to-date topics of current econometrics. We describe a modification of linear regression resistant to heteroscedasticity and study its computational aspects. For a robust version of the instrumental variables estimator we propose an asymptotic test of heteroscedasticity. Further we describe robust statistical methods for dimension reduction and classification analysis. We propose the robust quadratic classification analysis based on a new minimum weighted covariance determinant (MWCD) estimator. In general the robust methods based on down-weighting less reliable observations are resistant to outlying values (outliers) and insensitive to the assumption of Gaussian normal distribution of the data. The methods are illustrated on econometric data examples.

In this paper, we focus on thorough yield curve modelling. We build on extended classical NelsonSiegel model, which we further develop to accommodate unobserved regional common factors. We centre our discussion on Central European currencies' yield curves: CZK, HUF, PLN and SKK. We propose a model to capture regional dynamics purely based on state space formulation. The contribution of this paper is twofold: we examine regional yield curve dynamics and we quantify regional interdependencies amongst considered currencies' yield curves. We conclude that the CZK yield curve possesses its own dynamics corresponding to country specific features, whereas other currencies' yield curves are strongly influenced by the regional level, the regional slope factor or both.

In this paper I use an open economy DSGE model and estimate it for Romanian economy using Bayesian techniques. Based on estimation I derive a smoothed estimation of the output gap. I compare the results with those from standard procedures to estimate the output gap, the Hodrick Prescott ilter, the production function and an unobserved components model. The results show that the DSGE approach can give a better picture of the output gap and it is more consistent with the dynamics of Romanian economy.

The goal of this paper is to determine one of the consequences of accession of the Czech Republic to the European Monetary Union. The gravity equation is used to estimate the impact of exchange rate volatility and currency unions on international trade. Model's variables include GDPs per capita and populations of each partners, distance between them, exchange rate volatility and several dummy variables, including those, that are signifying membership of given country in the euro area. This model is estimated by general least squares method using panel data for members of the European Union.

The demand for money represents one of the most important components of the transmission mechanism. Its analysis plays an important role in the decision-making process of central banks dealing with monetary policies. This paper follows a post-Keynesian approach to the analysis of the demand for money. The econometric analysis is based on the Arestis's model, adjusted for the conditions of the Czech Republic. The cointegration analysis on the basis of both the VAR and ADL models is applied. The premise is confirmed that the demand for money in the Czech Republic from 1994 - 2000 had developed in the long-run mostly under the influence of GDP and interest rate development. This conclusion is valid for balances in both real and nominal money.