In this paper, we examine the impact of the UEFA EURO 2012™ on the Polish economy. The simulations are based on a dynamic computable general equilibrium (CGE) model and cover the years 2008-2020. We find that the main source of economic benefits is the acceleration of investments in transport infrastructure, which fosters growth of total factor productivity and the inflow of foreign direct investment. This contrasts with the results for more developed countries hosting major sporting events, where infrastructure effects are reported to be of less importance. Overall cumulative real GDP gains amount to 2.1% of the 2009 GDP level under the basic scenario.
Głównym celem artykułu jest opisowa oraz statystyczna analiza podstawowych czynników kształtujących zróżnicowanie stóp bezrobocia na poziomie województw Polski w latach 2002-2010. W pracy znajdują się zarówno opisowe analizy przeciętnych stóp bezrobocia w latach 2002-2010, jak i grupy kwartylowe owej zmiennej makroekonomicznej w kolejnych latach rozważanego przedziału czasu. Ponadto w artykule przedstawiony jest prosty model teoretyczny, w którym przyrosty stóp bezrobocia rejestrowanego w kolejnych latach i województwach uzależnione są od przeszłych wartości owych stóp, jak i stóp wzrostu realnego PKB w województwach. Przyjęcie założenia, iż przyrosty stóp bezrobocia są zależne od stopy wzrostu gospodarczego wynika przede wszystkim z następujących faktów. Po pierwsze, popyt na pracę jest popytem pochodnym względem zapotrzebowania zgłaszanego przez konsumentów na rynku towarowym. Po drugie, wynika z typowo keynesowskiego podejścia do sytuacji na rynku pracy, gdzie Keynes przyczyny podstawowej niesprawności rynku pracy jaką jest występowanie bezrobocia przymusowego upatrywał w niedostatecznym popycie na dobra i usługi czyli na rynku towarowym. Uzależnienia zaś zmian bieżących stóp bezrobocia od poziomu tych stóp z poprzedniego okresu wynika z inercyjnego charakteru zjawiska bezrobocia w Polsce. Parametry tak skonstruowanego modelu teoretycznego zostały dla porównania oszacowane zarówno metodą najmniejszych kwadratów (MNK), jak i uogólnioną metodą momentów (UMM) z wykorzystaniem procedury fixed effect oraz w przypadku przeszłych stóp bezrobocia zerojedynkowych zmiennych przełącznikowych. Wprowadzenie do estymowanych równań procedury fixed effect pozwala uwzględnić przestrzenną heterogeniczność rozważanych w artykule zmiennych makroekonomicznych. Natomiast wprowadzenie zmiennych przełącznikowych wynika stąd, iż pełnią one rolę zmiennej korygującej oddziaływanie stóp bezrobocia z poprzedniego okresu na zmianę bieżącej stopy bezrobocia i zależy od tego czy przyrost tej stopy jest dodatni czy ujemny. Słowa kluczowe: regionalne różnice w poziomie bezrobocia, GDP i poziom bezrobocia, analiza panelowa miejscowego bezrobocia, procedura fixed effect.
In the article the authors attempted to develop the neoclassical model of economic growth, repealing two assumptions regarding the Solow growth model. First of all, the authors assume that the growth path of the number of employees is increasing asymptotically to a fixed value, not to infinity as in the Solow model. The growth paths of the number of employees were determined based on demographic forecasts and the economic activity coefficient, which in the paper is understood as the ratio of the number of employees to the number of people. Secondly, the authors repeal the assumption of a fixed investment rate by taking into account the trend of changes in investment rates (a growing or declining trend). The theoretical model obtained was subjected to calibration and then numerical simulations were carried out. It was assumed that investment rates in the Polish economy decrease (from 25 to 15%) or grow (from 15 to 25%). Numerical simulations were based on demographic forecasts for the Polish economy up to 2050. Moreover, two scenarios for shaping the economic activity coefficient were considered: realistic one when in the period 2000-2050 it increased from 0.38 to 0.5. In the second scenario, it was optimistic that the increase would be 50% higher than in the first option and in 2050 it would reach 0.56. Important conclusions from the study can be presented as follows: (i) the population decline can be offset by the growing economic activity rate and therefore does not have a negative impact on economic growth, (ii) the negative impact of demographic changes on economic growth can also be offset by growing investment rates.
List of figures xi List of tables xiii Author biographies xv). (a) Scenario I, (b) scenario V, and (c) scenario IX * , k P * , y R * and y P * in the several variants relative to Variant I (Variant I = 100) 6.10 Ratios of average estimated k R * , k P * , y R * and y P * in the several variants relative to Variant I, assuming that either economy invests 10% of its savings in the other economy (Variant I = 100) 6.11 Selected numerical simulation results in Variant A (ω = 20%) 6.12 Selected numerical simulation results in Variant B (ω = 40%) 6.13 Selected numerical simulation results in Variant C (ω = 50%) 6.14 Selected simulation results in Variant D (ω = 60%) 6.15 Selected simulation results in Variant E (ω = 80%) 6.16. Selected results of numerical simulations in Variant F (s R = 25% and s P = 15%) 6.17 Selected results of numerical simulations in Variant F (s R = 15% and s P = 25%) 6.18 Ratios of average estimated k R * , k P * , y R * and y P * in the several variants relative to Variant I (Variant I = 100) 8.1 Simulations of labour productivity at standard (S), logistic (L) and post-Malthusian (PM) trajectories of the number of workers and at δ = 0.07, n = 0.01, α ≈ 0.68261 and m = e 9.1 Simulation of labour productivity at ω = 3 Tables xiv Tables 9.2 Simulation of labour productivity at ω = 5 9.3 Simulation of labour productivity at ω = 10 9.4 Simulation of labour productivity at ω = 25 9.5 Simulation of labour productivity at ω = 50 10.1 Scenarios of epidemic development 10.2 Epidemiological indicators in consecutive scenarios 10.3 Economic indicators in consecutive scenarios at K1/K * = 0.4 (a poorly developed economy) 10.4 Economic indicators in consecutive scenarios at K1/K * = 0.9 (a strongly developed economy)Author Biographies Paweł Dykas is an Associate Professor at the Department of Mathematical Economics of the Jagiellonian University in Krakow (Poland) and is also the author and co-author of over 50 academic publications such as The Neoclassical Model of Economic Growth and Its Ability to Account for Demographic Forecasts (2018), Demographic Forecasts and Volatility of Investment Rates vs. Labour Productivity Trajectories (2019) and An Impact of the Variable Technological Progress Rate on the Trajectory of Labour Productivity (2020). Recently, he has co-edited and contributed to The Socioeconomic Impact of COVID-19 on Eastern European Countries (Routledge, 2022). His main interests include the mathematical theory of economic growth, an analysis of the spatial diversity of economic development and an analysis of regional differences in the labour market. Tomasz Tokarski is Full Professor of Economics at the Department of Mathematical Economics of the Jagiellonian University in Krakow (Poland) and is also the author and co-author of over 200 academic publications such as Wybrane Modele Podażowych Czynników Wzrostu Gospodarczego (Selected Supply Models of Economic Growth) (2005), Ekonomia Matematyczna Modele Mikroekonomiczne (Microeconomic models of Mathematical Economics) (2011), Ekonomia Matematycz...
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