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FORECASTING THE DIRECTION OF CHANGES IN CROATIA´S INDUSTRIAL PRODUCTION WITH ICI AND CROLEI

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Author(s): Mirjana Cizmesija Vlasta Bahovec

Journal: Revista Investigación Operacional
ISSN 0257-4306

Volume: 30;
Issue: 2;
Start page: 140;
Date: 2009;
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Keywords: Business Survey | Industrial Confidence Indicator (ICI) | Croatian Leading Economic Indicator (CROLEI)

ABSTRACT
The Industrial Confidence Indicator (ICI) and the Croatian Leading Economic Indicator (CROLEI) can be used to forecast thedirection of changes (Sosic,I. Cizmesija, M., 2003) in developments of the national economy, especially for the manufacturingindustry.ICI and CROLEI are two leading indicators calculated on different methodological grounds. In spite of the methodologicaldifferences, they are mutually correlated, and they are also correlated with the industrial production. This means that theseindicators are two very important tools in the manufacturing activity prognostics. The Croatian experience has shown that ICIcorrectly predicts the direction of changes in the industrial production with a lead of one or two quarters (quarterly data) andCROLEI with a lead of about six months (monthly data). Some results of correlation analysis in Croatia confirm theseconclusions3. A more refined and more reliable statistical analysis of forecasting results is restricted, since series of values ofsurvey variables are short. Empirical modifications are conducted to make a comparison of the two indicators. Monthly values ofCROLEI are expressed as quarterly data, in order to align it with ICI, which is based on quarterly surveys. Industrial production isexpressed as percentage rate of the industrial production volume change (a rate of change in the current quarter over the samequarter in the previous year).One could recently notice that the prognostic features of the mentioned indicators are no longer satisfying as in the first part of the observed period (1996 – 1999). It is necessary to conduct revisions of the mentioned indicators with the goal to improve the newprediction characteristics.
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