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Structural Decomposition of the Economic Growth in the Croatian Economy

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  • Mikulić Davor

    (Institute of Economics, Zagreb, Croatia.)

Abstract

Croatia has been falling behind more successful new member states and belongs to the group of the least developed EU economies. After joining the EU, the availability of European structural funds, the removal of all trade barriers, and the strong growth of the tourism sector resulted in accelerating growth rates. This paper aims to decompose the total economic growth in the Croatian economy in the 2010-2018 period into the effect of increasing demand and technology improvements. The study is based on the structural decomposition analysis, which is the extension of the input-output model and has been widely used in previous studies in many economies to identify the driving forces of economic growth over a certain period. Based on empirical results, it can be concluded that the total final demand effects related to the increase in the total expenditures on the total economy level have been three times more intensive than the effects of technological change. It is estimated that the increase in final demand positively affected economic activity in each sector, while the distribution of technological change effects significantly varies. The highest positive impacts of technological change are found in the manufacturing, agri-food, and hospitality sectors. On the other hand, adverse effects of technological change are found in energy products, trade and transport, and various personal and business services. Significant variations are found in the growth dynamics of manufacturing sectors. The highest cumulative growth in 2010-2018 has been recorded in the production of computers and electronics, furniture, machinery and equipment, and wood products. In the case of computers, machinery, and furniture, the main effects are related to the product mix effects. At the same time, the economic growth of the wood industry is primarily the result of technological effects and increased participation in the supply chain of other industries.

Suggested Citation

  • Mikulić Davor, 2024. "Structural Decomposition of the Economic Growth in the Croatian Economy," Zagreb International Review of Economics and Business, Sciendo, vol. 27(2), pages 311-325.
    • Handle: RePEc:vrs:zirebs:v:27:y:2024:i:2:p:311-325:n:1015
    DOI: 10.2478/zireb-2024-0029
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    References listed on IDEAS

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    1. Berg, Andrew & Ostry, Jonathan D. & Zettelmeyer, Jeromin, 2012. "What makes growth sustained?," Journal of Development Economics, Elsevier, vol. 98(2), pages 149-166.
    2. Llop, Maria, 2017. "Changes in energy output in a regional economy: A structural decomposition analysis," Energy, Elsevier, vol. 128(C), pages 145-151.
    3. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    4. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
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    More about this item

    Keywords

    economic growth; technology change; final demand; product mix; structural decomposition analysis;
    All these keywords.

    JEL classification:

    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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