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- Convergence of Inflation and Unemployment Rates: a Signal of Economic Slowdown?Stanislava Hronová, Luboš Marek, Richard HindlsIn economic theory the Phillips curve presents the relationship between the unemployment rate and inflation rate. The inflation and unemployment rate bring important information about the stages of the economic cycle. This article attempts to find an answer to the question of whether the development of the difference between the unemployment and inflation rate, the so-called signal gap, may be an indicator of changes in the economic cycle. Quarterly data on the Czech Republic, France, Great Britain and the Republic of Korea were used to verify this hypothesis.
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Dynamic linear model, unemployment rate, inflation rate, signal gap, GDP - Inflation Forecasting and Targeting: Experience from Central EuropeJiří Šindelář, Petr BudinskýThis paper deals with inflation forecasting and targeting performance of selected Central and Eastern-European central banks. Using battery of absolute and scaled forecasting errors along with significance tests, we have evaluated inflation predictions on the optimal monetary policy transmission horizon (14–16 months), as well as adherence to long-term inflation targets. Out of the evaluated Czech, Hungarian and Polish central banks, complemented by the European Central Bank for comparison, it was found, that even though the bank´s performance improved during the last decade, notably with the forecasting component, some issues are still present. These are mostly connected to the inflation targeting mechanism, which was found to contain systemic bias in the case of the Czech national bank, as well as failing in comparison with the naïve benchmark in the case of the European Central Bank. Both outcomes pave the way for further investigation in a wider economical context.
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Central bank, inflation forecasting, inflation targeting, forecasting error - Sensitivity Analysis of Price Indices in Models of Demand SystemsRenata Benda-Prokeinová, Martina Hanová, Natalia TurčekováThe primary motivation of the paper is to point out the sensitivity of price indices calculated by the model of demand systems in different price and quantitative levels. We simulated different prices and quantities, so increasing the values of the variables reduced their variance. We would like to point out the significant role of variability and thus the deviation of input data, which is the basis for identifying consumer behavior.
From the methodology, we used the Linearized Almost Ideal Demand System and focused on the partial output of specific expenditure elasticities calculated by price indices – Stone, Laspeyres and Törnqvist index. Following we are wondering which index can consider as the most trustworthy?
In the analysis, we realized that the price variance would affect the indices' values more significantly, than the more considerable variance of the quantity consumed. It means that elasticities characterize consumer behavior in terms of prices, not in terms of quantity consumed.Keywords
Variance, expenditure elasticity, consumer demand model, meat items - The article deals with the analysis of Russian consumer price statistics as a system of absolute and relative indicators. The sampling method and design used by the national statistical office Rosstat are considered as Russian experience and adaptation of the CPI international standard. The survey of the system of consumer price statistics is realized on the basis of the indicator representativeness, the assessment of time and spatial differentiation and similarity in consumer prices. The main indicators of this system are the price indices. These include the consumer price index, fundamental consumer price index and cost of living index which are intended for dynamics analysis with additive seasonal decomposition of time series and to spatial differentiation of price level in Russian regions and cities.
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Consumer price index, cost-of-living index, Russian consumer price statistics - Recursive Estimation of Volatility for High Frequency Financial DataPetr Vejmělka, Tomáš CipraThe paper deals with recursive estimation of financial time series with conditional volatility. It surveys the recursive methodology suggested in Hendrych and Cipra (2018) and adjusts it for various alternatives of GARCH models which are usual in financial practice. Such a recursive approach seems to be suitable for the dynamic estimation with high-frequency data. The paper verifies the applicability of recursive algorithms of particular models to high-frequency data from the Czech environment, particularly in the context of risk prediction.
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GARCH, high-frequency financial time series, recursive estimation, risk prediction, volatility - This study intends to determine the drivers of high food prices in Turkey by employing the Structural Vector Auto Regression (SVAR) model for the January 2011 and March 2021 periods. The study has used external and domestic factors such as oil prices, world food prices, interest rate, exchange rate, money supply growth rate, producer price in agricultural goods. The findings indicate that all determinants show a significant positive contribution to the explanation of food prices except oil prices. The most substantial explanatory factor of food price is the price inertia shock in food prices. Domestic factors such as producer prices, interest rate, money supply, and exchange rate have also contributed to high food prices, while oil prices and world food prices have not played any substantial role. The results are robust compared to a different SVAR model identified by Cholesky decomposition. It is inferred that both exchange rate and monetary expansion have been quite effective in variations of food price in recent years. Overall, the findings indicate that controlling the food price movements is critical to ensuring overall price stability in the Turkish economy.
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Food prices, monetary policy, Turkey, SVAR - An Overview of Methodologal Issues in Data Envelopment Analysis: a Primer for Applied ResearchersViera Mendelová, Pavol Kráľ
Data envelopment analysis (DEA) as a method of measuring the efficiency of decision-making units (DMUs) has become an attractive tool used in managerial decision-making in many real-world applications. However, like other sophisticated methods, the application of DEA to a selected decision problem is not straightforward and requires to be carried out in a sequence of successive phases. Moreover, the practical application of DEA presents a range of procedural issues to be examined and resolved. The paper provides a concise guidance through individual steps of DEA analysis process focusing on applied researchers. It includes comprehensive overview of possible issues together with recommendations and hints of possible solutions supported by references to relevant literature pres nting more details and alternative viewpoints.
KeywordsDEA, methodology