Fabio Canova and Alain Schlaepfer, "Has the Euro-Mediterranean Partnership affected Mediterranean Business Cycles?", Journal of Applied Econometrics, Vol. 30, No. 2, 2015, pp. 241-262. The folders cs-data.zip (90kb) and cs-code.zip (54kb) contain the data in ASCII format and the matlab codes, respectively, that were used in the paper. Unix/Linux users should use "unzip -a". The folder cs-data.zip contains three data files: countrydata.txt, tradedata.txt and financedata.txt. countrydata.txt contains quarterly series on real GDP, unemployment rate, industrial production, real income and real sales for 19 Mediterranean countries, where available. All series end in 2010q1. Starting dates depend on data availability and can be backed out from the end data and series length. The order of countries (and country identifiers) are: 1. Algeria, 2. Croatia, 3. Cyprus, 4. Egypt, 5. France, 6. Greece, 7. Israel, 8. Italy, 9. Jordan, 10. Lebanon, 11. Macedonia, 12. Malta, 13. Morocco, 14. Portugal, 15. Serbia, 16. Slovenia, 17. Spain, 18. Tunisia, 19. Turkey The data file is organized in the following columns 1. Country identifier (as listed above) 2. Real GDP 3. Unemployment rate 4. Industrial production 5. Real income 6. Real sales Data sources vary by country and by data series and are described in detail in the paper appendix. Data are in ASCII format. A matlab code that extracts the data in country specific mat files as used as inputs in the matlab programs is included in the cs-code.zip folder ('ascii2matCountry.m'). tradedata.txt contains annual series on bilateral trade values in million US dollar from 1980-2010 (where available) for 18 Mediterranean countries. The order of countries (and country identifiers) are: 1. Algeria, 2. Croatia, 3. Egypt, 4. France, 5. Greece, 6. Israel, 7. Italy, 8. Jordan, 9. Lebanon, 10. Macedonia, 11. Malta, 12. Morocco, 13. Portugal, 14. Serbia, 15. Slovenia, 16. Spain, 17. Tunisia, 18. Turkey The data file is organized in the following columns: 1. Country identifier (as listed above) 2. Direction of trade identifier (1=export, 2=import) 3-33. Year 1980-2010 Within each country block, trading partners are organized in rows in the following order: 1. World (IFS Total), 2. World (DOTS Total), 3. Algeria, 4. Croatia, 5. Cyprus, 6. Egypt, 7. France, 8. Greece, 9. Israel, 10. Italy, 11. Jordan, 12. Lebanon, 13. Macedonia, 14. Malta, 15. Morocco, 16. Portugal, 17. Slovenia, 18. Spain, 19. Tunisia, 20. Turkey Source: IMF Direction of Trade Statistics. Data are in ASCII format. A matlab code that extracts the data in country specific mat files as used as inputs in the matlab programs is included in the cs-code.zip folder ('ascii2matTradeFinance.m') financedata.txt contains information on aggregate and bilateral financial linkage of mediterranean countries. The first block of aggregate data is organized as follows: The order of countries (rows) is 1. Cyprus, 2. France, 3. Greece, 4. Italy, 5. Jordan, 6. Portugal, 7. Spain, 8. Tunisia, 9. Turkey The series (columns) are: 1. Total foreign assets (1998) 2. Total foreign liabilities (1998) 3. GDP (1998) 4. Total foreign assets (2000) 5. Total foreign liabilities (2000) 6. GDP (2000) 7. Total foreign assets (2009) 8. Total foreign liabilities (2009) 9. GDP (2009) The second block of bilateral data is a matrix of bilateral foreign investment from 2007. The order of countries is: 1. Algeria, 2. Croatia, 3. Cyprus, 4. Egypt, 5. France, 6. Greece, 7. Israel, 8. Italy, 9. Jordan, 10. Lebanon, 11. Malta, 12. Morocco, 13. Portugal, 14. Slovenia, 15. Spain, 16. Tunisia, 17. Turkey. Rows represent recipient and columns represent sender countries. The last column contains the total. Source: BIS Locational Banking Statistics (aggregate data) and IMF Country Portfolio Investment Survey (bilateral data). Data are in ASCII format. A matlab code that extracts the data to mat files as used as inputs in the matlab programs is included in the cs-code.zip folder ('ascii2matTradeFinance.m'). ***** The folder cs-code.zip contains the matlab codes described above, as well as the algorithms for dating of business cycle turning points and computation of business cycle statistics as described in the paper. The directory Matlab-functions contains a toolbox to compute turning points of individual cycles and aggregate reference cycles (as described in Harding and Pagan (2006)), plus a set of business cycle statistics. The directory Matlab-programs contains programs to prepare data from ASCII files into mat files as used as inputs by other programs. 1) ascii2matCountry.m Prepares country data from countrydata.txt into mat files as used by BBQ2008.m 2) ascii2matTradeFinance.m Perpares trade and financial data from tradedata.txt and financialdata.txt as used by trade_pattern.m and fin_bilateralizer.m It also contains programs used to date business cycle turning points and to compute business cycle statistics: 1) BBQ2008.m Computes turning points of a set of series, plus turning points of a reference cycle 2) regions.m Computes reference cycle for a region (collection of countries). Needs countries' individual cycles (from BBQ2008.m) as inputs 3) averagedurationcountries.m Computes average duration of booms and recessions for countries. Needs countries' individual reference cycles (from BBQ2008.m) as inputs. Output is a 6*n matrix 'avdur', where n is the number of countries. Each column consists of: [average duration of booms; average duration of recessions; avg dur of booms (1st part of sample); average duration of recessions(1st part of sample); average duration of booms (2nd part of sample); average duration of recessions(2nd part of sample)] 4) averagedurationregions.m Computes average duration of booms and recessions for regions. Needs regional reference cycles (from regions.m) as inputs. 5) averageamplitudes.m Computes average amplitudes of booms and recessions for countries or regions, measured in change of GDP or IP. Needs reference cycles (from BBQ2008.m or region.m) plus country data on GDP or IP as inputs. 6) averagecummovcountries.m Computes average actual cumulative movement, triangular approximation and excess cumulative movement of booms and recessions for countries. Needs countries' individual reference cycles (from BBQ2008.m) plus country data on GDP or IP as inputs. 7) averagecummovregions.m Computes average actual cumulative movement, triangular approximation and excess cumulative movement of booms and recessions for regions. Needs regional reference cycles (from region.m) plus country data on GDP or IP as inputs. 8) regconcordence.m Computes bilateral concordence index for countries or regions. Needs reference cycles (from BBQ2008.m or region.m) as inputs. 9) trade_pattern.m Computes bilateral trade index from data file. 10) trade_conc_correlation.m Computes simple and rank correlations (plus regression statistics) of bilateral trade index and bilateral concordence index. Needs bilateral trade index and bilateral concordence index as inputs. 11) fin_bilateralizer.m Computes bilateral investment index from data file. Alain Schlaepfer alain.schlaepfer [at] upf.edu