Łukasz Lach

Oil usage, gas consumption and economic growth: Evidence from Poland

This article investigates causal links between economic growth, oil consumption and natural gas usage in Poland on the basis of quarterly data for the period Q1 2000–Q4 2009. The application of the Toda–Yamamoto procedure, a nonlinear Granger causality test, bootstrap techniques and an analysis of vector error-correction model led to the conclusion that both oil and natural gas usage caused gross domestic product growth in the short term. However, in the long term causality ran in the opposite direction. Both these findings are believed to be the consequence of the recent transformation of the Polish economy from energy intensive activities towards services, which in general are not energy–consuming.

The relationship between budgetary expenditure and economic growth in Poland

This paper investigates the association between different kinds of budgetary expenditure and economic growth of Poland. The empirical analysis makes use of linear and nonlinear Granger causality tests to evaluate the applicability of Wagner’s Law and that of the contrasting Keynesian theory. We employ aggregate and disaggregate data with the sub-categories of most important budgetary expenditure, including health care and social security, education and science, national defence and public security expenditure and government administration expenditure for the period Q1 2000 to Q3 2008. This causality analysis indicates that total relation between budgetary expenditure and economic growth is consistent with Keynesian theory. The results of our computations have important policy implications. In case of Poland the health care expenditure was found to be as important for economic growth as expenditures on education and science. Furthermore, in order to stimulate economic growth, Polish government should consider reallocating some of national defence, public security and government administration expenditure to health care, social security, education and science expenditure.

Simulating evolution of interindustry linkages in endogenous dynamic IO model with layers of techniques

In this article, we propose a new version of dynamic input–output model in which both technological progress and deployment are endogenous, and where sector‐specific outlays on R&D speed up the development of new technologies and the installation of capital stock. In this two‐technology model, the new and old technical processes within a sector exchange their relative weights in production. We use the model to obtain projections of the interindustry linkages of sectors in the Polish economy over the next 50 years. The results of this simulation suggest an ongoing change of the composition of the set of key sectors of the Polish economy. In general, one may expect to see an ongoing drop in the importance of agriculture‐ and heavy‐industry‐related sectors on the one hand, and a rise in the importance of services‐related ones on the other.

Some remarks on a social network approach to identifying key sectors

ABSTRACT Ostensibly, certain adaptations of social network theory extend and improve the traditional key-sector approaches. Our analysis of the underlying algebraic properties shows that a social-network-based approach proposed by García Muñiz et al. [(2008) Key Sectors: A New Proposal from Network Theory. Regional Studies, 42, 1013–1030] does not relate final demand and output in ways comparable to key-sector measures that are based on the static Leontief input–output model. Using the most recent IO table for Poland we show that the modified approach can lead to spurious empirical results and, as a consequence, to false policy implications.

On approximating the accelerator part in dynamic input–output models

We release the limitations of previous studies and instead of setting the crucial parameters of the dynamic endogenous input–output model with layers of techniques on an arbitrary basis we propose a new optimization-based approach to approximating of the elements of capital matrices on the basis of recent historical data. Using recent IO data we first formally prove that in comparison to arbitrarily adjusted dynamic IO models the new theoretical approach allows one to obtain a significantly better fit to the historical data in the short-run. This result has also some implications for the long-run analyses as it suggests that using the new approach for typical empirical applications of dynamic IO models with respect to modelling future behavior of economies seems relatively much more reasonable. Having this remark in mind, in the empirical part of the paper we use the new methodological approach in a particular case study. In an illustrative empirical application we try to forecast the possible evolution of sectoral classification in the Polish economy over the next 40xa0years.

Tracing VARDI coefficients: a proposal

ABSTRACT We propose a new approach for tracing the so-called ‘value-added-(re)distribution-important coefficients’ (in short the VARDI coefficients) in a world input–output model. From the perspective of a selected group of economies, VARDI coefficients may be defined as those elements in world input–output matrix in the case of which a small change in their levels leads to the maximization of a share of this group of economies in value added in global value chains. Due to the rapid development of the World Input Output Database, this approach may be easily applied in empirical research to different groups of countries and sectors in world IO models. In an illustrative empirical case study, we use the new approach in order to answer a question regarding what the main directions of the future macroeconomic policy of the U.S. could be in order to ensure the maximization of the country’s share in global value added.