Cointegration analysis of the monthly time-series relationship between retail sales and average wages in Croatia

A dynamic econometric model of Croatian monthly retail sales and wages is estimated through testing sequential model reduction validity. Such an approach aims at developing well-performing and interpretable dynamic relationships as data-description models. In addition to the model in levels a more economically interpretable error correction model was estimated enabling direct evaluation of the short-run impact of wage change to retail change as well as the periodic adjustment to the long-run equilibrium. It was established that, both in the short-run and in the long run, retail sales respond to wages thus forming a stable dynamic relationship

Information and communication technology (ICT) policy in the Central and South-Eastern Europe

Primary social aspects relevant for ICT include economic (commercial) and political issues as well as the traditionally ICT-intensive fields of high-tech and sciences. Aside of being the highest-growth sector in most western economies, ICT is inevitably a major factor in successful transition of the post-Communist and developing societies in the Central and South Eastern Europe (CSEE). The Stability Pact incorporated ICT policy issues as part of the “Third Wave” infrastructure reconstruction of the CSEE region strongly emphasising issues such as electronic networks and reforms to modernise business and governmental procedures. Among most crucial aspects are legislation and the role of government specially regarding the de-regulation and ICT market liberalisation issues. These are precisely the aspects that individual CSEE countries should solve themselves though the Stability Pact process should provide help and guidance (same holds for EU processes and pre-accession criteria)

Multivariate analysis of the European economic and defence

In this paper we model the defence and economic structure of 39 European countries using cluster and factor analytic methods. Initial results from standard cluster analysis performed on the original variables are compared with the results obtained from a confirmatory factor model estimated with maximum likelihood method within the general LISREL framework. Namely, a K-means cluster analysis is performed on latent scores calculated from the LISREL model. The results indicate that general clustering patters do not cut across East-West or transitional/non-transition division lines, rather it is found that a more subtitle grouping of countries exists where the more developed transitional countries clearly cluster closer to some West European countries than to the other transitional countries. It is subsequently found that noted differences exist also among the EU countries, which generally do not belong to a single cluster, regardless of the methods used

Regional development assessment using parametric and non-parametric ranking methods: A comparative analysis of Slovenia and Croatia

In this paper we describe several regional development-assessment methods and subsequently apply them in a comparative development level analysis of the Slovenian and Croatian municipalities. The aim is to compare performance and suitability of several parametric and non-parametric ranking methods and to develop a suitable multivariate methodological framework for distinguishing development level of particular territorial units. However, the usefulness and appropriateness of various multivariate techniques for regional development assessment is generally questionable and there is no clear consensus about how to carry out such analysis. Two main methodological approaches are based on parametric and non-parametric methods, where in the former an explicit econometric model containing theory-implied causal and possibly simultaneous relationships is estimated using likelihood-based methods and formally assessed in terms of the goodness of fit and other test statistics, subsequently allowing for estimation of the development level on a metric scale, while in the later, territorial units or regions are essentially classified into clusters or groups differing in the development level, but no formal inferential methods are applied to confirm the validity of the model, or to establish the difference in the development level on a metric scale. The possible advantages of the first approach are in the existence of formal testing and evaluation procedures, as well as in producing interval ranks of the analysed units, while its disadvantages are in the lack of robustness; often unrealistic distributional assumptions; and possible invalidity of the theoretically implied causal relationships. In this paper we consider a parametric, inferential approach based on maximum likelihood estimation of the linear structural equation model with latent variables for metric-scale development ranking, and a non-parametric approach based on cluster analysis for development grouping. Our analysis is based on ten regional development variables such as income per capita, population density, age index, etc. which are similarly collected and generally compatible for both analysed countries. Within the parametric approach, a simultaneous equation econometric model is estimated and latent scores are computed for each underlying latent development variable, where three latent constructs are postulated corresponding to economic, structural and demographic development dimensions. In the non-parametric approach, a combination of Ward?s hierarchical method and K-means clustering procedure is applied to classify the territorial units. We apply both methodological frameworks to Slovenian and Croatian municipality data and assess their regional development level. We further compare the performance of both methods and show to which degree their results are compatible. Finally, we propose a unified framework based on both parametric and non-parametric methods, where clustering techniques are performed both on the original development indicators and on the computed latent scores from the structural equation model, and compare these results with the results from each of the two methods applied separately. We show that a combined parametric/non-parametric approach is superior to each approach applied individually and propose a methodological framework capable of estimating the development level of territorial units or regions on a metric scale, while in the same time preserving the robustness of the non-parametric techniques.

Fiscal policy and regional development: an empirical analysis of the war-affected regions in Croatia

The paper analyses the effectiveness of the current Croatian regional fiscal policy in terms of its potential effects on stimulating economic growth in the war-affected regions. It is investigated whether sector (production vs. services), firm size, and the after-tax profit affect the investment behaviour in terms of the profit share re-investment. We estimate single and multigroup structural equation models treating firm size and re-investment behaviour as latent variables. The result suggest significant differences between production and service sector firms, and also some differences between firms of different sizes in respect to their re-investment tendencies. Namely, we find the relationship between the latent size normalised to net profit and re-investment share most pronounced among small and medium production firms, while such effect was not found for service sector and large firms. The results suggest that the enterprise size and sector do affect profit-share re-investment and that a more efficient fiscal policy could be designed by differently treating firms of different sectors and sizes

PCV81 AN ECONOMIC EVALUATION OF THE ADDITION OF FIXED-DOSE NIACIN EXTENDED-RELEASE AND SIMVASTATIN THERAPY TO THE MANAGED CARE FORMULARY IN TERMS OF OPTIMAL LIPID VALUE ATTAINMENT

Digitalitzat per Artypla

Covariance structure analysis of regional development data: an application to municipality development assessment

This paper presents the results of the second phase of the project whose main objective is to provide an analytical basis for evaluating the level of development of the Croatian territorial units, i.e. municipalities in this particular case. In the second phase, a structural equation model with latent variables is estimated with the purpose to test the validity of the first (simple) model and its results. The structural model takes into account complex casual relations between simple and joint indicators (factors) used in the model, but its output is a single development level scale which allows interval ranking of the territorial units. On the other hand, the first model makes distinctions between municipalities according to each collective indicator (economic, structural and demogeographic), but it assumes that collective indicators are independent. As the intention from the beginning of the project was to try to categorise territorial units according to the methodology used by Structural Funds and based on NUTS classification, the first model was used for the final evaluation and categorisation of the territorial units, but it was somewhat changed according to the results of the structural equation model