ASSESSMENT OF EU12 COUNTRIES’ EFFICIENCY USING MALMQUIST PRODUCTIVITY INDEX Michaela Staníčková Department of European Integration, Faculty of Economics, VŠB-Technical University of Ostrava

CONTENT I.INTRODUCTION II.THEORETICAL BACKGROUND OF EFFICIENCY ANALYSIS A. Background of Efficiency Analysis B. Problematic of Efficiency Evaluation III.DEA APPROACH FOR EFFICIENCY ANALYSIS A. DEA Background for Measuring National Efficiency B. Fundamental Characteristics of Empirical Analysis IV.APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU12 COUNTRIES V.CONCLUSION

ACKNOWLEDGEMENT „Macroeconomic Efficiency as a Factor of Competitiveness in EU Member States in a Globalized Economy“. Project registration number: SP 2013/45 Period of research: – Recipient: VŠB–TU Ostrava, Faculty of Economics, Department of European Integration Supervisor: Team Leader: Team Members: Ing. Boris Navrátil, CSc. Ing. Michaela Staníčková doc. Ing. Jana Hančlová, CSc. Ing. Lukáš Melecký Ing. Bohdan Váhalík Bc. Nikol Pešlová Bc. Karolína Popelářová Bc. Tomáš Vyvial

Aim of the paper: –The aim of the paper is to measure efficiency changes over the references periods and to analyse a level of productivity in individual EU12 countries based on the Malmquist Index, and then to classify EU12 countries according to efficiency results. Research premises (assumptions): − The efficiency is perceive like a „mirror“ of competitiveness. − DEA method evaluates the efficiency of countries with regard to their ability to transform inputs into outputs → countries achieving best (better) results in efficiency coefficients are countries best (better) at converting inputs into outputs. − Countries achieving greater level of efficiency = better using of competitive advantages = better competitive potential and perspectives. Research hypothesis: –More advanced Central European countries achieving best results in efficiency (especially Visegrad countries and Slovenia) are countries best at converting inputs into outputs and therefore having greater performance and productive potential than less advanced EU12 countries (Balkan and Baltic countries). I. INTRODUCTION

In recent years, the topics about measuring and evaluating of competitiveness and efficiency have enjoyed economic interest. No uniform definition and understanding of these terms, these multidimensional concepts remain ones of the basic standards of performance evaluation and there are also seen as a reflection of success of area in a wider comparison. Performance, efficiency and competitiveness are complementary objectives, which determine the long-term development of area/organization. Performance management is one of the major sources of sustainable national efficiency and effectiveness. II. THEORETICAL BACKGROUND OF EFFICIENCY ANALYSIS (i)

Efficiency and effectiveness analysis is based on the relationship between the inputs (entries), the outputs (results) and the outcomes (effects). Efficiency is given by the ratio of inputs to outputs, but there is difference between the technical efficiency and the allocative efficiency. Effectiveness implies a relationship between outputs and outcomes. II. THEORETICAL BACKGROUND OF EFFICIENCY ANALYSIS (ii) Fig. 1 The relationship between the efficiency and the effectiveness Source: [9], p. 3

Techniques to measure efficiency are improved and investigations of efficiency become more frequent. Nevertheless, the measurement of efficiency and effectiveness of countries resp. their factors, remains a conceptual challenge, because there are difficulties in measuring efficiency and effectiveness. M.J. Farrell [1957], proposed an activity analysis approach for single input/output situations. Twenty years after Farrell’s model, and building on those ideas, A. Charnes, W. W. Cooper and E. Rhodes [1978] introduced a powerful methodology which has been titled Data Envelopment Analysis (DEA) in the form of CCR model assuming constant returns to scale (CRS). DEA was proposed to assess the relative efficiencies of multi-input/multi-output production units. The performance of countries can be evaluated in either a cross-sectional or a time-series manner, and the DEA is a useful method for both types of efficiency evaluation. II. EVALUATION OF EFFICIENCY (iii)

Measuring the efficiency level of evaluated countries is based on following procedure: III. DEA APPROACH FOR EFFICIENCY ANALYSIS (i) Source: Own elaboration, 2013 Data Envelopment Analysis (DEA) method – developed/advanced approach: Malmquist index based on input oriented Charnes-Cooper-Rhodes (IO CCR CRS) model. Number of performance measures? - Empirically, when the number of performance measures is high in comparison with the number of DMUs, then most of DMUs are evaluated efficient – in basic models, not in multi-period MI.

III. DEA APPROACH FOR EFFICIENCY ANALYSIS (ii) Territorial definition: 12 countries – „new“ EU Member States (without Croatia); national level Reference period: reference years 2000 (beginning of growth period) and 2011 (last year of complete data- base for all evaluated countries; post-crisis year) reference periods for MI: , , , Indicators: 66 selected indicators (38 inputs, 28 outputs) – 62 used indicators (37 inputs, 25 outputs) Database indicators: based on Country Competitiveness Index (CCI) - pillars of CCI are grouped according to the different dimensions (input versus output aspects) of national competitiveness they describe. ‘Inputs’ and ‘outputs’ are meant to classify pillars into those which describe driving forces of competitiveness, also in terms of long-term potentiality, and those which are direct or indirect outcomes of a competitive society and economy Eurostat, World Bank, Euro barometer, Organisation for Economic Co-operation and Development (OECD), European Cluster Observatory. Territorial definition: 12 countries – „new“ EU Member States (without Croatia); national level Reference period: reference years 2000 (beginning of growth period) and 2011 (last year of complete data- base for all evaluated countries; post-crisis year) reference periods for MI: , , , Indicators: 66 selected indicators (38 inputs, 28 outputs) – 62 used indicators (37 inputs, 25 outputs) Database indicators: based on Country Competitiveness Index (CCI) - pillars of CCI are grouped according to the different dimensions (input versus output aspects) of national competitiveness they describe. ‘Inputs’ and ‘outputs’ are meant to classify pillars into those which describe driving forces of competitiveness, also in terms of long-term potentiality, and those which are direct or indirect outcomes of a competitive society and economy Eurostat, World Bank, Euro barometer, Organisation for Economic Co-operation and Development (OECD), European Cluster Observatory.

III. DEA APPROACH FOR EFFICIENCY ANALYSIS (iii)

The Malmquist index (MI) measures the efficiency change of production of unit M 0 between successive periods t and t+1 M 0 (x t+1, y t+1, x t, y t ) We can decompose MI (M 0 ) into two components: M 0 = TEC 0. TSF 0 TEC 0 = the change of technical efficiency = is change in the relative efficiency of unit DMU 0 in relation to other units (i.e. due to the production possibility frontier) between time periods t and t+1, TSF 0 = the change of technology efficiency = describes the change in the production possibility frontier as a result of the technology development between time periods t and t+1. III. DEA APPROACH FOR EFFICIENCY ANALYSIS (iv)

TEC 0 = the change of technical efficiency = TSF 0 = the change of technology efficiency = III. DEA APPROACH FOR EFFICIENCY ANALYSIS (v) = function that assigns for production unit 0 degree of effectiveness in time t with input x and output y TEC or TSF Efficiency meaning < 1Improving = 1Unchanging > 1Declining

III. DEA APPROACH FOR EFFICIENCY ANALYSIS (vi)

III. DEA APPROACH FOR EFFICIENCY ANALYSIS (vii) Model AModel B min subject to min subject to

III. DEA APPROACH FOR EFFICIENCY ANALYSIS (viii) Model CModel D min subject to min subject to

The initial hypothesis of efficiency being a mirror of competitive potential was partly confirmed through analysis by Malmquist index. Some of countries have reached the best results and recorded predominantly total efficiency increase through the time period and other countries have reached predominantly total efficiency decrease during reference years. Most of evaluated countries have recorded both increasing and decreasing trend in efficiency development during reference years of period and , but in years , most of countries have recognized considerable deterioration in efficiency (due to economic crisis). It is recognized gradually improving in economic development in years , but it is very slow. Apparently the best results are traditionally achieved by economically powerful countries which were ‘efficient’ or ‘highly efficient’ during the reference periods. IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (i)

IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (ii) ‘Efficient’ countries’: Slovenia ‘Highly efficient countries’: Czech Republic, Slovakia, Poland, Malta, Latvia ‘Slightly inefficient countries’: Estonia, Cyprus, Lithuania ‘Inefficient countries’: Bulgaria, Romania, Hungary ‘Efficient’ countries’: Slovenia ‘Highly efficient countries’: Czech Republic, Slovakia, Poland, Malta, Latvia ‘Slightly inefficient countries’: Estonia, Cyprus, Lithuania ‘Inefficient countries’: Bulgaria, Romania, Hungary Source: Own calculation and elaboration, 2013

IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (iii) Source: Own calculation and elaboration, 2013

IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (iv) Source: Own calculation and elaboration, 2013

MI = IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (v) Source: Own calculation and elaboration, 2013 MI = total productivity efficiency change TEC = the change of technical efficiency TSF = the change of technology efficiency

MI = IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (vi) Source: Own calculation and elaboration, 2013 MI = total productivity efficiency change TEC = the change of technical efficiency TSF = the change of technology efficiency

MI = IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (vii) Source: Own calculation and elaboration, 2013 MI = total productivity efficiency change TEC = the change of technical efficiency TSF = the change of technology efficiency

MI = IV. APPLICATION OF DEA METHOD TO EFFICIENCY ANALYSIS OF EU MEMBER STATES (viii) Source: Own calculation and elaboration, 2013 MI = total productivity efficiency change TEC = the change of technical efficiency TSF = the change of technology efficiency

Applying DEA method presents a convenient (possible) way of comparing efficiency across DMUs at national (country) level. Based on the DEA method has been found out: there is a distinct gap between economic and social standards in terms of evaluated countries, so differences still remain; according to MI results, in EU12 countries was mostly achieved noticeable productivity decreases and performance deteriorating during reference years; more or less balanced performance and efficiency trend were recognized during the reference periods; most countries experienced decline in their performance as a result of economic crisis. The economic crisis has threatened the achievement of sustainable development in the field of competitiveness. The crisis has underscored importance of competitiveness-supporting economic environment to enable economies better absorb shocks and ensure solid economic performance going in future. Subsequent research orientation: analysis of distance from efficient frontier through macroeconomic modelling to finding the common and individual trends of macroeconomic efficiency; analysis of slacks for optimal settings of inputs and outputs for each country in a given period of time. V. CONCLUSION

ACKNOWLEDGEMENT Michaela Staníčková Department of European Integration Faculty of Economics, VŠB-Technical University of Ostrava €UR Katedra evropské integrace Q/A Comments Suggestions Thank You for Your Attention