Deep Integration and Economic Growth: Counterfactual Analysis in Europe

This study explores the concept of counterfactual analysis in economic growth, particularly focusing on synthetic counterfactuals to understand complex relationships. It discusses the challenges of projecting GDP growth rates over extended periods, providing insights into identifying growth factors and constructing similar country models for analysis.

• Economic Growth
• Counterfactual Analysis
• Europe
• Synthetic Counterfactuals
• GDP Growth

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1. Comments on: Deep integration an Economic Growth: Counterfactual Evidence from Europe (Nauro F. Campos and Fabrizio Coricelli and Luigi Moretti) By Neven Mates Standard disclaimer applies, represents only my views Dubrovnik June 13, 2016

2. Counterfactual What if We cannot know, this is counterfactual Example: What would be with X had Y not hapend? But this paper suggests that answering this question is easy. It uses Synthetic counterfactuals .

3. Synthetic counterfactuals (1)

4. Synthetic counterfactuals (2)

5. Synthetic counterfactuals (3)

6. Projecting GDP growth rates over longer periods is not easy (1) Levine (1992): How robust are various variables in projecting GDP growth over longer time? Almost all results are fragile except for investment to GDP ratio. And to a lesser extent, the initial income level.

7. Projecting GDP growth rates over longer periods is not easy (2) Take a similar country Which hardly exist or construct a new one.

8. Take 7 growth factors (1) 1. The pre-treatment (year by year) GDP per capita (PPP Converted at 2005 constant prices, rgdpch) 2. The pre-treatment average of the investment share of per capita GDP (PPP Converted at 2005 constant prices, ki) 3. Population growth (popgr), all from Penn World Tables 7.0; 4. Share of agriculture in value added (agr) 5. Share of industry in value added (ind) 6. Secondary gross school enrolment (sec) 7. Tertiary gross school enrolment (ter), all from World Bank.

9. Take 7 growth factors that would give you a similar country (2) Try to find a combination of weights and select a set of donor , non-EU countries, by which you can via linear combination approximate characteristics (explanatory variables, and the GDP per capita) of countries, in pre-EU period.

10. 2004 1973

11. 2004 1995

12. Table A.1 Denmark Treated 14,128.42 13,715.86 18.60 0.01 6.47 32.07 20.46 93.01 United Kingdom Treated 13,913.92 13,957.56 14.06 0.01 Ireland Treated 8,184.70 Synthetic deviation (%) -2.9 4.0 2,429.2 75.0 13.6 -6.3 -15.0 Synthetic deviation (%) 0.3 32.3 236.3 Synthetic 8,188.56 22.51 deviation (%) 0.0 20.3 816.3 -42.5 30.8 41.0 -20.3 rgdpch ki popgr agr ind ter sec 19.35 0.18 11.32 36.44 19.18 79.05 18.59 0.02 18.71 0.00 16.31 33.96 11.62 74.38 0.02 9.38 44.41 16.38 59.25 41.55 14.88 75.39 36.12 18.98 75.18 -13.1 27.5 -0.3 Greece Treated 15,438.97 15,445.26 30.69 0.01 Spain Treated 14,801.19 14,780.81 22.62 0.01 8.56 33.63 19.70 76.32 Portugal Treated 9,851.04 Synthetic deviation (%) 0.0 -12.4 110.5 Synthetic deviation (%) -0.1 -12.2 88.6 7.0 12.1 29.2 -8.9 Synthetic 9,839.44 22.86 deviation (%) -0.1 -3.4 243.5 -37.5 22.6 66.0 33.8 rgdpch ki popgr agr ind ter sec 26.88 0.02 19.86 0.02 9.16 37.69 25.46 69.50 23.67 0.01 22.00 30.77 10.58 49.59 0.02 13.75 37.73 17.56 66.35 15.92 74.83 26.01 75.15 63.4 0.4 Austria Treated 25,563.83 25,551.33 22.20 0.00 3.67 33.67 28.22 98.79 Finland Treated 21,584.77 21,599.32 24.06 0.00 7.02 33.99 40.85 108.30 Sweden Treated 24,649.82 24,639.28 17.56 0.00 4.04 30.62 32.59 93.12 Synthetic deviation (%) 0.0 20.1 82.9 -12.0 4.5 4.7 -0.4 Synthetic deviation (%) 0.1 6.2 153.5 107.5 2.1 -18.5 -15.5 Synthetic deviation (%) 0.0 33.9 175.5 105.4 7.4 20.4 -1.6 rgdpch ki popgr agr ind ter sec 26.67 0.01 3.23 35.17 29.55 98.41 25.56 0.01 14.57 34.69 33.28 91.50 23.52 0.01 8.30 32.90 39.23 91.62

13. Table A.2 Czech Republic Treated 15,261.36 15,245.73 22.17 4.38 39.11 0.00 20.00 91.86 Estonia Treated 7,783.55 Hungary Treated 11,036.94 11,031.31 17.07 7.66 29.89 0.00 21.70 90.97 Synthetic deviation (%) -0.1 77.8 145.0 -5.5 -2,945.8 84.3 -8.1 Synthetic 7,774.22 20.46 10.89 32.54 deviation (%) -0.1 -5.5 99.8 5.2 -118.2 -23.1 -22.7 Synthetic deviation (%) -0.1 24.3 32.1 13.4 -694.4 74.9 -15.1 rgdpch ki agr ind popgr ter sec 39.41 10.73 36.94 0.01 36.86 84.45 21.64 5.45 30.94 -0.02 31.60 97.77 21.21 10.12 33.89 0.01 37.95 77.22 0.00 24.30 75.54 Latvia Treated 6,377.26 Lithuania Treated 7,586.69 Poland Treated 8,928.35 Synthetic 6,368.92 22.70 12.13 32.58 deviation (%) -0.1 86.1 41.5 5.3 -188.3 -29.9 -29.4 Synthetic 7,580.47 19.09 14.80 33.80 deviation (%) -0.1 78.2 24.0 0.0 -810.9 -11.4 -23.7 Synthetic 8,932.19 27.74 10.16 34.61 deviation (%) 0.0 73.9 31.8 -1.4 360.3 -21.5 -20.3 rgdpch ki agr ind popgr ter sec 12.20 8.57 30.95 -0.01 26.21 88.04 10.71 11.94 33.80 0.00 27.87 85.84 15.95 7.71 35.09 0.00 31.52 95.16 0.01 18.37 62.15 0.01 24.69 65.49 0.01 24.75 75.89 Slovak Republic Treated 10,898.34 10,193.11 21.38 5.90 37.00 0.00 18.69 89.36 Slovenia Treated 15,292.52 15,291.48 23.12 4.51 36.91 0.00 31.50 89.73 Synthetic deviation (%) -6.5 39.2 38.5 -2.6 -35.1 90.0 -1.4 Synthetic deviation (%) 0.0 39.2 52.8 0.4 879.2 58.5 2.3 rgdpch ki agr ind popgr ter sec 29.77 8.17 36.02 0.00 35.51 88.14 32.18 6.89 37.07 0.01 49.93 91.78