- . In terms of data, we need to compute the fraction of public goods in total consumption αi, which we construct using the WIOD World Input-Output Database, and we need information on labor income taxes. In order to compute net real wages we resort to the OECD Tax Database, which provides data on combined central and sub-central government income tax plus employee social security contribution, as a percentage of gross wage earnings, for people whose income is 100 percent of the average wage (OECD (2016)). In the OECD Tax Database the average wage is defined as the average annual gross wage earnings of adult, full-time, manual and non-manual workers. Data are available for each year for 14 countries in our sample, all except Lithuania, Latvia and Cyprus. For these three countries we compute the tax rate as the average of the tax rate for all the other NMS countries, by year.
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- 3. If the two criteria above do not fill the missing cells: (a) Use WTO values to impute Trains values if WTO is not missing (b) Missing values for 2003 are replaced with values from 2002. This could happen because some NMS lowered their tariff before the formal access to the European Union. We do not replace the missing values with zeros, but we impute the non-zero value of the previous year.
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- A EU Accession and the Freedom of Movement of Workers In this Appendix we describe in detail the process that resulted in the entry of ten new countries into the European Union in 2004, i.e. the EU membership process.
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- ——— (2002): “Technology, Geography, and Trade,†Econometrica, 70, 1741–1779.
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- After having performed the algorithm described above, we have the flows of migrants from each pair of countries as well as the stock of people in each country and year, but we do not have information on the stock of people in the RoW. We use information on population levels and on the share of population between 15 and 64 years old from the World Bank World Development Indicators database to construct the stock of people in the rest of world in 2002.50 We further use the average year-nationality-skill share from our 17 countries (EU members plus NMS countries) and apply them to the RoW population to split people in the relevant groups for our analysis. Some destination-origin-nationality-skill-year sequences of migration flows consists in sequences of zeros followed by positive values. While sequences of tiny values followed by larger flows do not represent an issue, sequences of zeros followed by positive values cannot be handled by the model.
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Ahlfeldt, G. M., S. J. Redding, D. M. Sturm, and N. Wolf (2015): “The economics of density: Evidence from the Berlin Wall,†Econometrica, 83, 2127–2189.
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- Artuç, E. and J. McLaren (2015): “Trade Policy and Wage inequality: A Structural Analysis with Occupational and Sectoral Mobility,†Journal of International Economics, 97, 278–294.
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- Average effectively applied tariff rate 2002 2003 2004 2005 2006 2007 Years NMS(exp)-NMS(imp) EU15(exp)-NMS(imp) NMS(exp)-EU15(imp) Note: These graphs show the evolution of the average effectively applied rate between NMS and EU-15, as well as within NMS. Averages have been constructed using the WTO and TRAINS tariff data, as described in Section 4 and Appendix B.3.1, using the same set of 10 EU-15 countries and 7 NMS countries as in our data set on gross migration flows.
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- Average tariff 2002 2003 2004 2005 2006 2007 Years TRAINS WTO Trains adjusted Trains vs WTO + Trains adjusted - simple average (b) Weighted average 0 1 2 3 4
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- Average tariff 2002 2003 2004 2005 2006 2007 Years TRAINS WTO Trains adjusted Trains vs WTO + Trains adjusted - weighted average B.3.1 Tariffs The bilateral tariff data are constructed using the information in the WITS database. We use effectively applied rates and we combine information from two different datasets, the TRAINS data set and the WTO data set; the two datasets are compatible because TRAINS combines information from different sources, among which WTO data. We start from the TRAINS data set, which is the most complete of the two and we proceed as follows to make the series complete: 1. Use average EU-25 tariff applied to NMS8 to replace missing tariff when the destination country of the exported good is a EU-15 country and the origin belongs to the NMS8 group. 2. Use average EU27 tariff applied to NMS2 to replace missing tariff when the destination country of the exported good is a EU-15 country and the origin country belongs to the NMS2 group.
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- B Data B.1 List of Countries The sample includes 17 European countries and a constructed rest of the world (RoW). Of our 17 countries, 10 are pre-2004 EU members and 7 countries joined the EU in 2004. The list of pre2004 EU members includes Austria, Belgium, Germany, Denmark, Spain, France, Greece, Italy, Portugal, and the United Kingdom while the new members are Cyprus, Czech Republic, Estonia, Hungary, Lithuania, Latvia and Poland. Overall, these 17 countries cover about 91 percent of the population of the 25 members of the European Union in 2004.
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- Before 2004. Panel (a) shows that, before the 2004 enlargement, workers could flow freely within the EU-15 member states but not between EU-15 and NMS as well as between NMS countries.
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- Belgium and Denmark opened their labor market to NMS countries on May 2009, while Austria and Germany opened their labor markets at the end of the transitional period, on May 2011. 41 The EU-25 member states that decide to lift restrictions can, throughout the remainder of the transitional period, be able to reintroduce them, using the safe-guard procedure set out in the 2003 Accession Treaty, should they undergo or foresee disturbances on their labor markets. Notwithstanding the restrictions, a member state must always give preference to EU-2 (Malta and Cyprus) and EU-8 workers over those who are nationals of a non-EU country with regard to access to the labor market.
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Dustmann, C., J. Ludsteck, and U. Schönberg (2009): “Revisiting the German Wage Structure, †The Quarterly Journal of Economics, 124, 843–881.
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- Emigration shares 2002 2003 2004 2005 2006 2007 Years DE ES FR IT UK Rest of EU25 (b) High skill 0 .2 .4 .6 .8 1
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- Finally, in the Slovenian survey information on the country of origin is available from 2008 on only.
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- First, we compare the final migration data set with the raw data in terms of (i) the share of each country population relative to the aggregate population, and (ii) the ratio between low and high skill workers. In terms of the share of each country population relative to the aggregate population we find that the correlation between the raw and final data is 0.998 in 2002, the first year in the sample. The correlation between the 2002-2007 changes of the same shares is 0.542. In terms of the ratio of low to high skill workers, the cross-country correlation between the raw and final data is 0.996, while the correlation between the 2002-2007 changes is 0.865. Overall, we conclude that the data comparison in terms of population shares and skill ratio is quite satisfactory.
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- in case the member state notified the European Commission of a serious disturbance in its labor market or threat thereof.41 The transitional arrangements were scheduled to end irrevocably seven years after accession—i.e. on April 30th, 2011.
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- is the lead of the (log) population in country i. We estimate (25) as an IV regression, using two-period lagged values of real wages as instruments similar to Artuç et al. (2010), and clustering standard errors at the country level.
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- Once again, with the exclusion of Switzerland our data is entirely consistent with the information 52 The 2011 Population and Housing Census marks a milestone in census exercises in Europe. For the first time, European legislation defined in detail a set of harmonized high-quality data from the population and housing censuses conducted in the EU Member States. 53 The figures mentioned in Dustmann et al. (2015)’s quote come from the Polish Labour Force Survey, a rotating quarterly panel conducted in Poland by the Polish Central Statistical Office. The survey registers the country of present residence for individuals who are part of the household but who have been residing abroad for more than 3 months. 54 The New York Times article “Pictures Tell the Story of Portuguese in France†captures the importance of the Portuguese presence in France in the 1960s.
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- Phase 1. On May 1st, 2004, the U.K. (together with Ireland and Sweden) opens its borders to NMS countries, which reciprocate by opening their borders to British citizens. All the other EU-15 countries keep applying restrictions to NMS countries, except to Cyprus and Malta. All NMS countries decide to open their border to EU-15 member states, except for Hungary, Poland, and Slovenia which apply reciprocal measures. Finally, NMS countries lift all restrictions among each others.
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- Poland lifted the reciprocal measures on January 1st, 2007, while Hungary simplified the reciprocal measures on January 1st, 2008.
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Redding, S. J. (2016): “Goods trade, factor mobility and welfare,†Journal of International Economics, 101, 148–167.
Redding, S. J. and D. M. Sturm (2008): “The costs of remoteness: Evidence from German division and reunification,†The American Economic Review, 98, 1766–1797.
Redding, S. J. and E. Rossi-Hansberg (2016): “Quantitative Spatial Economics,†Working Paper 22655, National Bureau of Economic Research.
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- Table B.1: Nationality mapping - before 2004 Before 2004 Code Label EU-15 survey NMS8 survey 0 Nationals EU-15 NMS8 111 EU-15 EU-15 EU-15 911 Non EU-15 NMS8 or other ** NMS8 or other ** 800 Non-National/Non-Native * EU-15, NMS8 or other ** EU-15, NMS8 or other ** After 2004 0 Nationals EU-15 NMS8 1 EU-15 EU-15 EU-15 2 NMS10 NMS8 NMS8 Multiple codes Other categories Other Other Notes: * Non-National/Non-Native in case the distinction EU/Non-EU is not possible ** NMS8 using levels of â€Âother†flows based on 2004-8 data, residual belongs to â€Âother†the series.47 Since the analysis carried on in the paper refers to the 2002-2007 period and some of the destination-origin-year-months with incomplete observations refer to countries that we drop from the analysis, the potential impact of the interpolations and projections on the results is even smaller.
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- Table B.2: Imports and exports shares, EU-15 and NMS, 2002 and 2007 Imports shares NMS importing from: EU-15 importing from: Other NMS EU-15 RoW NMS Other EU-15 RoW 2002 5.7 52.6 41.7 3.9 46.9 49.2 2007 9.1 48.0 43.0 5.2 42.3 52.5 Change +3.4-4.6 +1.3 +1.3-4.6 +3.3 Exports shares NMS exporting to: EU-15 exporting to: Other NMS EU-15 RoW NMS Other EU-15 RoW 2002 6.2 54.6 39.2 3.8 43.8 52.4 2007 9.3 50.1 40.6 4.9 40.8 54.3 Change +3.1-4.5 +1.4 +1.1-3.0 +1.9 Notes: This table shows the weighted average imports and exports shares for NMS and EU-15 countries. Averages have been constructed using the WTO and TRAINS tariff data, as described in Section 4 and Appendix B.3.1, using the same set of ten EU-15 countries and seven NMS countries as in our data set on gross migration flows. The remaining countries are aggregated into the Rest of the World (RoW). coming from the census.
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- The Case of Poland The variable nationality for Poland is available only since 2004 and it only includes three codes: 0 “National / Native of own Countryâ€Â, 5 “EU28â€Â, and 8 “Europe outside EU28â€Â. In order to separate EU-15 from NMS10 nationals, we construct an alternative nationality variable for Poland applying the origin-year-specific shares of EU-15, NMS10, and Other nationals computed for Hungary to the survey for Poland. We choose Hungary as a reference because, just like Poland and unlike other NMS countries, it applies reciprocal measures to EU-15 nationals.
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- The estimate of the elasticity of substitution turns out to be pretty robust to alternative different specifications, methodologies, and levels of data aggregation. Table E.1 reports an alternative set of estimates using OLS with linear or spline (with break in 1993) trends, at the industry-region and country-level. It also reports a set of estimates based on an alternative way to construct the data series for hours and wages based on Autor et al. (2008). In this case we construct a fix-weighted ratio of high-skill to low-skill wages for a composition-constant set of sex-education-experience groups.
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- The third case we consider features another country which has experienced throughout history large outflows of population: Italy. According to the 2011 Italian Census, the top four countries in terms of stock of Italian-born population are France, Germany, Switzerland, and the United Kingdom.
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- Third, the survey does not report the exact date of migration but only the country in which the interviewed individual was living 12 months before. In other words, an individual that is interviewed in April of 2006 in the United Kingdom and declares that 12 months before she was living in Poland could have migrated out of Poland any time in the previous 12 months. Therefore, we spread the sampling weight associated to this individual to the previous 12 months.
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- Timmer, M. P., E. Dietzenbacher, B. Los, R. Stehrer, and G. J. de Vries (2015a): “An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production,†Review of International Economics, 23, 575–605.
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- Timmer, M. P., E. Dietzenbacher, B. Los, R. Stehrer, and G. J. Vries (2015b): “An Illustrated User Guide to the World Input–Output database: The Case of Global Automotive Production,†Review of International Economics, 23, 575–605.
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Tombe, T. and X. Zhu (2015): “Trade, Migration and Productivity: A Quantitative Analysis of China,†Manuscript, University of Toronto.
- We assign Ireland, The Netherlands, Malta, Sweden and Slovenia to the RoW aggregate because their EU-LFS country surveys do not contain sufficient information regarding the country of residence 12 months before the worker was interviewed. Specifically, Ireland does not provide information on the country of origin for any year in the survey, making it impossible to construct migration flows from any country in the sample to Ireland. The country surveys for the Netherlands and Malta are available from 2006 and 2009 onward respectively, hence after the enlargement of the European Union. The case of Sweden presents two different problems: first, data before 2005 contain information on the country of residence 12 months before only if this is Sweden itself.
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- We build wages, for each country i and year t ∈ [2002 − 2009], as the ratio of the economy-wide “Labour compensation†(in millions of national currency) and “Number of persons engaged†(in thousands) from the WIOD Socio-Economic Accounts (SEA) data set (Timmer et al. (2015b)).
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- We define 3 nationalities, “EU-15â€Â, “NMS10†and “Other†based on table B.1. 48 After 2004, the surveys for Latvia report the category NMS13 instead of distinguishing between NMS10 and NMS3. When creating nationalities described below, we use NMS13 in place of NMS10 for Latvia. 49 For destination-origin pairs that appear before 2004 but not after, we assign, for each destination, the average share across all origins. Note that in more than 99 percent of the cases this happens when country of origin is missing.
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- We perform the following procedure to, essentially, replace zeros with small positive values. We start from the stock of individuals in 2002, which includes three zeros: high skill EU nationals in 50 Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values used are midyear estimates.
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