EUROPEAN UNION VS ECONOMIC FREEDOM UNDER THE GLOBAL CRISIS IMPACT

EUROPEAN UNION VS ECONOMIC FREEDOM UNDER THE GLOBAL CRISIS IMPACT Ph.D.Professor Romeo-Victor Ionescu1 Danubius University, Romania Abstract The paper deals with the idea of analysing the impact of the economic freedom on national economic development. In order to realise this, the analysis is focused on three steps. For the beginning, we determined the place of the EU28 in the global economic freedom approach using the Index of economic freedom and the comparative analysis. The second step of the analysis consists of a TwoStep cluster analysis, supported by SPSS19 software, which is realised in order to support the idea that the economic freedom, connected to the economic development, created three clusters from the Member States. The clustering criterion is BIC (Schwarz’s Bayesian Criterion). Finally, the analysis is focused on a forecast of the index of economic freedom till the end of 2020, in order to observe if the disparities across the world economy. The dependent variables in this forecast are the economic freedom rates and the independent variable is time. The forecast method is ARIMA. Whole analysis process and all conclusions of the paper are supported by the latest official statistic data, pertinent tables and diagrams. The main conclusion of the paper is that the economic freedom supports the economic development. Its global trend was positive in 2013-2014. There is not global economic actor in world top 10 according index of the economic freedom. Only two Member States are ranked on the global top 10. Moreover, there are great disparities across the EU28 related to the economic freedom. As a result, the Member States can be grouped into three different clusters. Romania will have a positive trend of the economic freedom score until 2020, better than the global trend of this index. The disparities between EU Member States will not be fixed on short and medium term and the solutions seem to be found at national level. - Keywords, for indexing purposes: economic freedom, rule of low, government size, regulatory efficiency, open markets, economic forecasts. 1. Introduction A very sensitive issue for the economists is the economic freedom. There are a lot of approaches related to the indicators able to quantify this freedom and the way of using them. An interesting point of view has Niclas Berggren, who considers economic freedom as an intrinsic value, on one side, and as a dependent variable, on the other hand [1]. Other specialists tried to find connections between economic freedom, investment and economic growth. As a result, the economic freedom supports the FDI inflows in the host countries and the result is the economic growth. This approach is available if the host countries are characterised by appropriately skilled labour, liberalised markets and economic stability [2]. The economic freedom is opposite to socialist policies. This is why Hayek criticized socialist policies as the slippery slope that can lead to totalitarianism [3]. Other researches were focused on the idea that there is a relatively large correlation between economic freedom and both per capita income and per capita growth [4]. 1 Aurel Vlaicu Street no. 10, Galati, 800508, e-mail: [email protected] Goodin, Rice, Parpo, and Eriksson created the measure of discretionary time, as an estimate of how much time people have at their disposal during which they are free to choose the activities in which they participate, after taking into account the time they need to spend acquiring the necessities of life [5]. A recent paper deals with the connection between the economic freedom and globalisation. The analysis takes into account the government size, using the total tax revenue and total expenditures as share of GDP, and the economic growth [6]. On the other hand, some papers analysed the connection between more competitive markets’ reforms, lower human rights violation and increase government’s respect for human rights [7]. Nowadays, the importance of the economic freedom concept increased. As a result, The Heritage Foundation in Partnership with The Wall Street Journal realised and calculated the Index of Economic Freedom [8]. This index covers 186 countries in 2014. It was estimated since 1995 and is focused on the size of the economic freedom in the world. The global average economic freedom score has reached 60.3, the highest ever recorded in the 20-year history of the Index. World economic freedom has improved by 0.7 point from last year and 2.7 points from 1995. 2. Research methodology The analysis in the paper follows at least three steps. First is that of determining the place of the EU28 in the global economic freedom approach using the Index of economic freedom and the comparative analysis. This index is built on four components (see Figure 1). According to Figure 1, there are different elements in the analysis. From the legal point of view, the property rights respecting and the decrease of the corruption are very important for the national economy. Moreover, the taxation level and the impact of the government expenditures are able to support sustainable development. Other important element is the effect of the economic policies’ implementation, which is quantified by business, labor and monetary freedom. Last, but not the least, the openness degree of the national economy has positive impact on international trade, investment and finances. The second step of the analysis is the cluster analysis, which is realised in order to support the idea that the economic freedom, connected to the economic development, created three clusters from the Member States. Moreover, we can talk about a EU28 with three economic development speeds. The analysis is supported by SPSS19 software, under TwoStep cluster analysis, where the categorial variables are the above four economic indicators and the distance measure is log-likelihood. The clustering criterion is BIC (Schwarz’s Bayesian Criterion). Rule of law -property rights -freedom from corruption Government size -fiscal freedom -government spending Economic freedom Regulatory efficiency -business freedom -labor freedom -monetary freedom Open markets -trade freedom -investment freedom -financial freedom Figure 1: Index of economic freedom approach Source: personal contribution Finally, the analysis is focused on a forecast of the index of economic freedom till the end of 2020, in order to observe if the disparities across the world economy. The dependent variables in this forecast are the economic freedom rates and the independent variable is time. The forecast method is ARIMA. 3. Results The global index of economic freedom achieved 60.3 in 2014, the highest value till now, but not all its components had positive trends. The rule of low decreased by 0.3 for each of its two components; the other three elements of the index increased. The highest increased in 2014 was achieved by investment freedom (3.3) and the lowest by fiscal freedom and financial freedom (0.1). The values of ten economic freedoms in 2014 are presented in Figure 2. 80 60 40 20 0 2014 Figure 2: Index of economic freedom in 2014 Source: personal contribution According to Figure 2, the most important element which supports the economic development in 2014 is the fiscal freedom (77.3). It is followed by trade freedom (74.8) and monetary freedom (74.2). Europe achieved above or equal scores to global average for eight components of the index of freedom. The two exceptions are fiscal freedom and government spending. There are six free national economies in 2014: Hong Kong (90.1), Singapore (89.4), Australia (82.0), Switzerland (81.6), New Zealand (81.2) and Canada (80.2). 12 EU Member States are ranked as mostly free economies, 15 as moderately free economies and one as mostly unfree economy (see Table 1). Table 1: EU country rankings Rank 9 10 11 14 Country Ireland Denmark Estonia UK Overall 76.2 76.1 75.9 74.9 Change 0.5 0.0 0.6 0.1 15 16 18 19 20 21 24 26 35 42 46 49 50 51 57 58 61 62 69 70 74 86 87 119 Netherlands Luxembourg Germany Finland Sweden Lithuania Austria Czech Republic Belgium Latvia Cyprus Spain Poland Hungary Slovakia Malta Bulgaria Romania Portugal France Slovenia Italy Croatia Greece 74.2 74.2 73.4 73.4 73.1 73.0 72.4 72.2 69.9 68.7 67.6 67.2 67.0 67.0 66.4 66.4 65.7 65.5 63.5 63.5 62.7 60.9 60.4 55.7 0.7 0.0 0.6 -0.6 0.2 0.9 0.6 1.3 0.7 2.2 -1.4 -0.8 1.0 -0.3 -2.3 -1.1 0.7 0.4 0.4 -0.6 1.0 0.3 -0.9 0.3 - mostly unfree - moderately free -mostly free There are only two Member State in world 10 top (Ireland and Denmark) in 2014. Moreover, three Member States achieve better ranks than the main EU economic competitors: USA (12 th rank), Japan (25th rank) and China (137th rank). The problem is that these three European economies (Ireland, Denmark and Estonia) are small national economies. In 2014, 18 Member States improved their ranks, 2 states maintained their ranks and 8 states faced to negative trends. The highest improvement was achieved by Latvia (2.2) and the lowest by Slovakia (-2.3). Greece succeeded in increasing its index of economic freedom by 0.3 in 2014. According to Table 1, we can divide the Member States into three clusters: states with positive trend of the index of economic freedom, states with no change in economic freedom trend and states with negative trend of the index of economic freedom. In order to support this idea, we used the cluster analysis (see Figure 3). Figure 3: Cluster analysis under Index of economic freedom in 2014 Source: personal contribution According to the trend of the index of economic freedom, the result of the above cluster analysis is good enough to support the idea of three clusters across the EU28. Romania achieved a score of 65.5 and a growth of 0.4 in 2014. Its rank is supported by fiscal freedom, government spending, labor freedom, trade freedom and investment freedom (see Figure 4). 100 80 60 40 20 0 Europe Romania Figure 4: Components of the Index of economic freedom in Europe and Romania in 2014 Source: personal contribution Worst ranks are those related to propriety rights, freedom from corruption and financial freedom. 4. Discussion There is no-doubt that economic freedom is essential for the sustainable development in the world economy. On the other hand, different global economic crisis, as that starting in 2007, can have negative impact on the index of economic freedom trend. This is why the next step of the present analysis is to realise a forecast of the global index of economic freedom until 2020. We used the official data for 1995 to 2014 time period as the base of this forecast [9]. Figure 5: Global index of economic freedom forecast Source: personal contribution using SPSS19 software According to Figure 5, the economic freedom will increase slowly to 61.5 in 2020. This means an annual average increase of 0.2. Maybe the greatest problems will be in mostly unfree and repressed national economies, which represented 49.43% from the number of analyzed countries in 2014. What about Romania? The same forecast leads to a positive conclusion (see Figure 6). Figure 6: Romania’s index of economic freedom forecast Source: personal contribution using SPSS19 software According to the above forecast, Romania will achieve an index of economic freedom of 70.4 in 2020, greater than the global one. 5. Conclusions Economic freedom supports the economic development. Its global trend was positive in 2013-2014. There is not global economic actor in world top 10 according index of the economic freedom. Only two Member States are ranked on the global top 10. Moreover, there are great disparities across the EU28 related to the economic freedom. As a result, the Member States can be grouped into three different clusters. Romania will have a positive trend of the economic freedom score until 2020, better than the global trend of this index. The disparities between EU Member States will not be fixed on short and medium term and the solutions seem to be found at national level. References [1] Niclas Berggren, The Benefits of Economic Freedom, The Independent Review, v. VIII, n. 2, pp. 193– 211 (2003). [2] Marta Bengoa, Blanca Sanchez-Robles, Foreign direct investment, economic freedom and growth: new evidence from Latin America, European Journal of Political Economy Vol. 19, 529–545 (2003). [3] Hayek Friedrich, The Road to Serfdom: Text and Documents, University of Chicago Press, pp. 53– 57 (2007). [4] Morris Altman, How Much Economic Freedom is Necessary for Economic Growth? Theory and Evidence, Economics Bulletin, Vol. 15), no. 2, pp. 1–20 (2008). [5] Goodin Robert E., Rice James Mahmud, Parpo Antti Eriksson Lina, Discretionary Time: A New Measure of Freedom, Cambridge, Cambridge University Press, pp. 1–54 (2008). [6] Bergh Andreas, Martin Karlsson, Government size and growth: Accounting for economic freedom and globalization, Public Choice 142, 1-2: 195-213 (2010). [7] de Soysa Indra, Krishna Chaitanya, Do pro-market economic reforms drive human rights violations? An empirical assessment, 1981-2006, Public Choice, 163-187 (2011). [8] The Heritage Foundation, Index of Economic Freedom, Washington DC, 2014. [9] Terry Miller, Anthony B. Kim and Kim R. Holmes, 2014 Index of Economic Freedom, chart 1, Washington D.C. (2014). Annexes 1. Index of global economic freedom forecast PREDICT THRU END. * Time Series Modeler. TSMODEL /MODELSUMMARY PRINT=[MODELFIT] /MODELSTATISTICS DISPLAY=YES MODELFIT=[ SRSQUARE] /SERIESPLOT OBSERVED FORECAST /OUTPUTFILTER DISPLAY=ALLMODELS /AUXILIARY CILEVEL=95 MAXACFLAGS=24 /MISSING USERMISSING=EXCLUDE /MODEL DEPENDENT=VAR00001 INDEPENDENT=YEAR_ PREFIX='Model' /ARIMA AR=[0] DIFF=0 MA=[0] ARSEASONAL=[0] DIFFSEASONAL=0 MASEASONAL=[0] TRANSFORM=NONE CONSTANT=YES /TRANSFERFUNCTION VARIABLES=YEAR_ NUM=[0] DENOM=[0] DIFF=0 DELAY=0 TRANSFORM=NONE /AUTOOUTLIER DETECT=OFF. Time Series Modeler [DataSet0] Model Description Model Type Model ID VAR00001 Model_1 ARIMA(0,0,0) Model Summary Model Fit Percentile Fit Statistic Mean SE Minimum Maximum 5 10 25 50 75 90 95 Stationary R-squared ,689 . ,689 ,689 ,689 ,689 ,689 ,689 ,689 ,689 ,689 R-squared ,689 . ,689 ,689 ,689 ,689 ,689 ,689 ,689 ,689 ,689 RMSE ,635 . ,635 ,635 ,635 ,635 ,635 ,635 ,635 ,635 ,635 MAPE ,932 . ,932 ,932 ,932 ,932 ,932 ,932 ,932 ,932 ,932 1,695 . 1,695 ,550 . ,550 MaxAE 1,013 . 1,013 1,013 1,013 1,013 1,013 1,013 1,013 1,013 1,013 Normalized BIC -,608 . -,608 -,608 MaxAPE MAE 1,695 1,695 1,695 1,695 1,695 1,695 1,695 1,695 ,550 ,550 -,608 ,550 -,608 ,550 -,608 ,550 -,608 ,550 -,608 ,550 -,608 ,550 -,608 Model Statistics Model Fit statistics Model VAR00001-Model_1 2. Ljung-Box Q(18) Number of Stationary R- Predictors squared 1 Number of Statistics ,689 71,354 Romania’s index of economic freedom forecast PREDICT THRU END. * Time Series Modeler. TSMODEL /MODELSUMMARY PRINT=[MODELFIT] /MODELSTATISTICS DISPLAY=YES MODELFIT=[ SRSQUARE] /SERIESPLOT OBSERVED FORECAST DF Sig. 18 ,000 Outliers 0 /OUTPUTFILTER DISPLAY=ALLMODELS /AUXILIARY CILEVEL=95 MAXACFLAGS=24 /MISSING USERMISSING=EXCLUDE /MODEL DEPENDENT=VAR00001 INDEPENDENT=YEAR_ PREFIX='Model' /ARIMA AR=[0] DIFF=0 MA=[0] ARSEASONAL=[0] DIFFSEASONAL=0 MASEASONAL=[0] TRANSFORM=NONE CONSTANT=YES /TRANSFERFUNCTION VARIABLES=YEAR_ NUM=[0] DENOM=[0] DIFF=0 DELAY=0 TRANSFORM=NONE /AUTOOUTLIER DETECT=OFF. Time Series Modeler [DataSet0] Model Description Model Type Model ID VAR00001 Model_1 ARIMA(0,0,0) Model Summary Model Fit Percentile Fit Statistic Stationary R- Mean SE Minimum Maximum 5 10 25 50 75 90 95 ,845 . ,845 ,845 ,845 ,845 ,845 ,845 ,845 ,845 ,845 ,845 . ,845 ,845 ,845 ,845 ,845 ,845 ,845 ,845 ,845 RMSE 2,963 . 2,963 2,963 2,963 2,963 2,963 2,963 2,963 2,963 2,963 MAPE 4,237 . 4,237 4,237 4,237 4,237 4,237 4,237 4,237 4,237 4,237 11,010 . 11,010 11,010 11,010 11,010 11,010 11,010 11,010 11,010 11,010 MAE 2,264 . 2,264 2,264 2,264 2,264 2,264 2,264 2,264 2,264 2,264 MaxAE 5,989 . 5,989 5,989 5,989 5,989 5,989 5,989 5,989 5,989 5,989 Normalized BIC 2,472 . 2,472 2,472 2,472 2,472 2,472 2,472 2,472 2,472 2,472 squared R-squared MaxAPE Model Statistics Model Fit statistics Model VAR00001-Model_1 Ljung-Box Q(18) Number of Stationary R- Predictors squared 1 Number of Statistics ,845 47,270 DF Sig. 18 ,000 Outliers 0