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An Analysis of the Relationships among NASDAQ Baltic Stock Exchanges: VAR Approach

100%

Zięba Ł.

nr Vol. 34, No 3

51-65

The author examines the relationships among three stock exchanges of selected Baltic countries: Latvia, Estonia, and Lithuania. The respective stock exchange indexes are used as variables, OMXR for Latvia, OMXT for Estonia, and OMXV for Lithuania. The regression equations are estimated with the use of Vector Autoregressive (VAR) model. The author employs 80 observations for the sample period from2002 Q1 to 2021 Q4. After determining the optimal lag order, the impulse response function is calculated. The variance decomposition is carried out subsequently. A causality among the stock exchanges in question is determined. (original abstract)

Analiza powiązań pomiędzy cenami wieprzowiny na rynku polskim i wybranych rynkach krajów Unii Europejskiej

84%

Gędek S.

nr z. 3

92-96

Analiza powiązań cenowych pomiędzy polskim rynkiem wieprzowiny a rynkami wybranych krajów UE przeprowadzona została przy pomocy modelu VAR. Funkcje odpowiedzi na impuls (IRF) wyznaczone w oparciu o wyniki estymacji modelu VAR pozwoliły na opis dynamiki dostosowań cenowych. Uzyskane wyniki wskazują na przyspieszenie reakcji cenowych polskiego rynku wieprzowiny po akcesji Polski do UE. (abstrakt oryginalny)

The VAR model was used in the analysis of pork price linkages between Polish market and the markets of selected EU countries. Impulse response function (IRF), the result of VAR model estimation, was used to describe the price adjustment dynamics. The analysis was based on the monthly pork price notations between 01.1999 and 03.2009. It was found strong evidence that polish pork market has reacted faster to the EU market price impulse in the post-accession period. (original abstract)

How do firms respond to demand and supply shocks?

67%

Gradzewicz M.

nr nr 75

The study aims to identify the granular demand and productivity shocks, their properties, and the responses of the important firm-level variables to these shocks. We use comprehensive data from the Polish enterprise sector that cover the 2002-2019 period. As the data do not include prices, the identification of the demand shocks relies on the information on inventory changes. We utilize the control function approach to estimate the parameters of the production function and to identify productivity shocks. We use projection methods with granular data to identify the dynamic impulse-response function. We show that the distributions of the two shocks differ: i.e., supply (productivity) shocks are symmetrically distributed, and the distribution of demand shocks is negatively skewed. Moreover, both distributions have fat tails. Productivity shocks have much more persistent effect on firms' outcomes than demand shocks. Following demand shocks, there are short-lived increases in output, market share, productivity, real wages and markups; whereas investment and employment demand remain elevated for a longer period. We also find a very limited transmission of productivity into wages and we showed that proxies for prices increase after demand shocks, and they decrease after the supply shock, in a theory-consistent way. (original abstract)

What Simple Econometric Analysis Will Tell Us about the Relationship between Macroeconomic Variables, Stock Market Indices, and the Activity of the Banking Sector?

51%

Gomola A.

nr nr 1

1-46

The main goal of macroprudential policy is to reduce the systematic risk and the macroeconomic costs of financial instabilities. After the financial crisis of 2008, the macroprudential framework has been developed. In the paper we test the role of the banking sector's activity in the strength of the causal relationships between the real sector and the financial system. One of the main goals of macroprudential framework is to reduce the credit supply and strengthen the financial system. We examine the strength of the relationship between several macroeconomic variables, such as industrial production, the interest rate, stock market values, the unemployment rate, and particularly the volume of credit to the non-financial sector. The empirical analyses are performed with reference to three economies: Poland, Germany, and the United Kingdom. Substantial diversity of sources of economic growth as well as the size of the financial system in the case of the countries in question allows for a better understanding of the connections between the financial sector and the real sector. Moreover, each of them experienced the 2008 crisis in a different way. (original abstract)