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A knowledge-based economy: new directions of macromodelling.

Article Excerpt
Abstract The development of new economies, leading to economies mostly based on knowledge, implies the construction of new, long-term macroeconometric models. They should incorporate the impacts of new technologies being endogenized, as well as human capital. The paper discusses several issues related to extending the notion of a production function. It covers the measurement and explanation of total factor productivity (TFP), the role of domestic and foreign research and development expenditures, as well as educational expenditures. The discussion is extended to include proposals to construct new submodels explaining the sections of research, education and the Information and Communication Technology (ITC) industries.

Keywords Polish economy. Knowledge based economy. Macromodelling. Knowledge capital. R&D. Human capital

JEL O10.C32.C57.E22

Introduction

The theory of economic growth has enjoyed its renaissance for over ten years, particularly the theory of endogenous and sustained growth. Various aspects of the growth theory have been elaborated recently, in the Polish literature mainly by Tokarski (2001). The subject is still vivid and continues to attract theoretical research (Nahuis 2003).

Empirical investigations following these developments have their macroeconomic and microeconomic dimensions (for instance, the innovation process analysis). Regarding the macroeconomic dimension, we need to mention empirical economic growth models conceptualized by Welfe (2000) The implementation of the concept contributed to the construction of the long-term macroeconometric model W8D of

In some sense, research activities expanding along the outlined directions triggered responses to challenges that economic sciences have to face because of the contemporary market economy transforming into a "new economy" and prospectively into a knowledge-based economy. The knowledge-based economy concept was formulated to contrast the new system with the industrial economy prevailing in the last centuries. Even though economic systems existing in the past did take advantage of knowledge that determined technological progresses, the knowledge capital started to dominate as late as in the turn of the twentieth and twenty-first centuries. This applies to the functioning of economies (relevant examples are the automation of manufacturing processes, fast transmission of management information, recently via the Internet, etc.) and economic growth (endogenization of technological progress mainly due to the development of Information and Communication Technology (ICT).)

It is not easy to find a measure indicating, whether the level of knowledge capital absorbed by an economy is sufficient to view it as a knowledge-based system (Smith 2002) However, in the economic growth analyses, a working assumption can be taken that research and development (R&D) and educational expenditures growing faster than investment outlays on fixed capital signify that such a system of economic relationships predominates. A more demanding criterion would aim to verify, whether a threshold value representing an adequately high share (e.g. 50-60%) of the Total Factor Productivity (TFP) in GDP growth has been exceeded. At the same time, the importance of fixed capital and employment growth as factors of production would be largely reduced in the system. (1)

Despite Poland's unquestionable technological backwardness, the knowledge-based economy concept was reflected in a work initiated by Kuklinski (2001) and then in empirical research. First, empirical studies were undertaken by a team headed by Zienkowski (2003). However, extensive analyses provided in the studies did not go beyond the formulation of simple regressions between GDP growth and single growth factors in the Polish economy.

The authors did not attempt to treat them within the framework of multi-regression analysis and consider with reference to the system of linkages characterizing an entire economy, including a knowledge-based economy. This gap has to be filled.

The paper analyzes the use of macroeconometric models as a major analytical tool for the knowledge-based economies. Next, the key issues in the generation and use of knowledge are discussed, i.e. the TFP dynamics and the factors behind its growth - the R&D and educational educational expenditures, investment in human capital. The paper

Towards Macroeconometric Models for the Knowledge Based Economies

Mechanisms stimulating the growth of a knowledge-based economy can be quantified by means of adequately expanded macroeconometric models. The models should enable the generation of endogenous technological/organizational progresses and explicitly react to changes in knowledge capital, while allowing for relevant feedbacks. They should make it possible to run simulation exercises useful in composing long-term growth scenarios that take into account the dynamics of knowledge capital.

One proposal that we intend to put forward to attain the presented goal involves the macroeconometric long-term model W8D of the Polish economy (see Welfe Ed. 2004a). However, the model needs to be adequately extended, modified, and transformed into a new structure-the model of a knowledge-based economy. Let us add that the model is the only operational model of this class in Poland, and one of few analogous models in Europe. (2)

The extension of the long-term econometric model W8D of the Polish economy would mainly require:

(a) The introduction of an extensive account of the consequences of increased domestic and foreign expenditures on innovations to the model. These expenditures would enlarge knowledge capital embodied in fixed capital and boost the expansion effects of broadly understood human capital

(b) Incorporation of satellite submodels into the model, which describe the functioning of the sectors of research and education (including higher education), as well as the sector of high-tech industries (with ICT industry)

(c) Regional and sectoral disaggregation of the model, which implies application of the cross-section-time series data.

Problems in Measuring TFP Dynamics

The Total Factor Productivity Concept

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