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Zróżnicowanie efektów działalności gospodarczej w Polsce a wybrane cechy regionów

100%
Jankiewicz J.
Prace i Materiały Instytutu Rozwoju Gospodarczego SGH
|
2013
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vol. 91: Badania koniunktury - zwierciadło gospodarki. Część II
13-26
PL
Celem artykułu jest nakreślenie zróżnicowania regionalnego w Polsce wg wybranych cech i wskaźników statystycznych oraz próba wyjaśnienia przestrzennego zróżnicowania PKB per capita. Do opisu warunków gospodarowania w poszczególnych regionach wykorzystano m.in. dane o działalności inwestycyjnej i badawczo-rozwojowej oraz o kapitale społecznym. Opis zróżnicowania województw pod względem wybranych cech został uzupełniony grupowaniem jednostek terytorialnych metodą minimalnych wariancji Warda. Ostatecznie wyselekcjonowane zmienne wykorzystano do estymacji modelu regresji. Objaśnił on 98% zmienności produkcji łącznej per capita w województwach.
EN
The paper aims to discuss regional diversification in Poland on the basis of selected characteristics and statistical indicators and attempts to explain the diversity in GDP per capita between regions. In order to do this some data on investments and R & D activity and on social capital, among others, is analysed. The description of regional diversification is supplemented by grouping of territorial units with the Ward's minimum variance method. Ultimately selected variables were used to estimate a regression model. It explained 98% of the variation of the GDP per capita in the regions.
2
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Application of Neural Networks in Economic Forecasting

63%
Łuczyński W., Jankiewicz J.
Prace i Materiały Instytutu Rozwoju Gospodarczego SGH
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2004
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vol. 74
377-393
EN
The complexity of economic processes is reflected in the time series which register their state. Not all the aspects of the economic process can be registered. In order to obtain the useful information from statistical data, it is necessary to apply many labor-consuming and sophisticated procedures. Economic conditions are represented by objective processes, such as industrial production, product prices, export and import, employment and unemployment, job vacancies, etc. on the one hand, and behavioural modes of businessmen and consumers, their assessments and expectations as regards prices, sales, employment, and other economic indexes on the other hand. So we are dealing with objective facts (quantitative data) and subjective facts (qualitative data). Moreover, the analysed processes are all interdependent. Such a situation requires extreme methodological flexibility - a sort of methodological eclecticism. In view of the multidimensional object, the use of merely one method may yield a distorted image. That is why several different methods have been used in this study: the naive no-change method, simple linear regression, auto-regressive (integrated) moving-average model (ARMA and ARIMA), and artificial neuronal networks.
3
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Consumer Confidence Indexes in New EU Member States

63%
Kokocińska M., Jankiewicz J.
Prace i Materiały Instytutu Rozwoju Gospodarczego SGH
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2011
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vol. 86:Business Surveys, Business Cycles. Polish Contribution to the 30th CIRET Conference
161-183
EN
One of the most important economic indicators developed on the basis of agents’ opinions is consumer confidence index. Such a situation stems from the fact that consumption is usually the most important element of total demand. In well developed economies in which consumer confidence indexes have been used for many years a lot of attention is paid to analysis of their behavior. They are the element of composite leading indicators developed among others by the European Commission and the US Trade Department. In the emerging economies, in which analyses of consumer behavior were introduced relatively recently, qualitative data on consumer confidence is treated with less attention. This suggests conducting research in such a field for new EU member states. Countries which joined EU in 2004 r. are: the Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovenia, Slovakia. This group of countries was subject to analysis presented in the paper. The main aim of the research is to find and analyze relationships between consumer confidence indexes and chosen macroeconomic variables. Research questions refer to common direction in such an analysis conducted worldwide: to identify factors influencing consumers’ opinion and check whether changes of consumer confidence lead to changes of chosen economic variables. Consumption in the state of equilibrium depends on propensity to consumption (measured by confidence index) and on possibilities which are represented by disposable income. Quantitative monthly data used in the research refers to purchasing power of households and consumption expenditure. On the other hand the scope of the research was aimed at main economic time series which can influence agents expectations. Composite consumer confidence index cannot be commonly applied to describe volatility of various types of consumption, so in the research simple (component) indicators were used as well. The analysis of linear relationships is based on the cross correlations. In order to find lags and leads there were estimated Pearson correlation coefficients for shifts ±12 months. The analysis of linear relationships was extended by Granger’s causality test in order to verify whether quantitative variables influence consumer’s answers. Reverse relationships were also verified. In order to track nonlinear relationships neural networks module of Statistica was used. In the case algorithm of optimal data set for model time series was applied. Achieved results allow to identify relationships between analyzed economic time series, but also can be treated as first step for introducing consumer confidence indicators to economic forecasting in chosen developing EU economies..
4

Unemployment and Time Spent in Household Production

63%
Jankiewicz J., Garsztka P.
Ekonomista
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2019
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issue 4
432-451
PL
W ostatnich dekadach wśród naukowców wzrosło zainteresowanie lepszym zrozumieniem i pomiarem dobrobytu człowieka. Powszechnie uznaje się, że wyłączne zainteresowanie produkcją i konsumpcją, mierzonymi w rachunkach narodowych, m. in. w formie PKB, jest strategią niewystarczającą i nie powinno być jedynym źródłem wiedzy dla decydentów politycznych. Niniejszy artykuł dotyczy nierynkowej aktywności produkcyjnej, która jest źródłem ekonomicznego dobrobytu postrzeganego jako składowa obiektywnego dobrobytu gospodarstw domowych. W analizie wykorzystano mikro-dane z dwóch edycji (2003-04 i 2013) polskich badań budżetu czasu. Celem artykułu było zbadanie, w jaki sposób różnice w wykorzystaniu czasu między pracownikami zatrudnionymi a bezrobotnymi wynikają z różnych podstawowych cech demograficznych. Wyniki wskazują, ile minut dodatkowej produkcji gospodarstwa domowego odpowiada każdej godzinie czasu rynkowego nieprzepracowanej przez osoby bezrobotne w różnych typach gospodarstw domowych. Dzięki przyjętej strategii badawczej wyróżniamy grupy społeczne, które są najbardziej dotknięte podczas recesji gospodarczej i wysokiego poziomu bezrobocia, oraz te, dla których koszt niekorzystnych warunków rynkowych jest stosunkowo niski. Wyniki wskazują, że niezależnie od cech społeczno-ekonomicznych gospodarstw domowych, najwyższe stopnie kompensacji obserwuje się wśród bezrobotnych kobiet. Porównanie wyników z TUS 2004 i TUS 2013 ujawnia zmiany w alokacji czasu dla mężczyzn i kobiet. Skala substytucji w 2004 r. była największa w przypadku kobiet mających dzieci i dla najwyższego poziomu wykształcenia. W 2013 r. najwyższy stopień kompensacji charakteryzował młode matki i młodych ojców.
EN
In recent decades, great interest has arisen in the scientific community about better understanding and measuring of people's well-being. It is widely recognized that an exclusive concern with production and consumption, as measured in national accounts such as GDP, is an insufficient strategy and should not be the only source for guiding policy makers. This paper deals with nonmarket productive activities as sources of economic welfare, which are recognised as part of the objective well-being of households. In the analysis the micro data from two waves (2003-04 and 2013) of Polish time use surveys were used. The aim of the paper is to investigate how the differences in time use between employed and unemployed people arise from various underlying demographic characteristics. The results indicate how many minutes of additional household production correspond to each hour of market time not worked by unemployed individuals in various types of households. By this research strategy we distinguish the groups in society which suffer the most during recessions and high levels of unemployment, and those for which the cost of unfavourable market circumstances is comparatively low. The results indicate that, independently from the socioeconomic characteristics of households, the highest degrees of compensation are seen among unemployed women. A comparison of the results from TUS 2004 and TUS 2013 reveals changes in the allocation of time for men and women. The scale of substitution in 2004 was greatest in the case of women who have children and the highest level of education. In 2013 the highest degree of compensation characterised young mothers and young fathers.
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