natgillin/translations-raw huggingface dataset:
The Commission should examine whether greater emphasis could be placed on models that rely on the use of micro-data derived from projects. 
Kommissionen br underska om strre eftertryck kan lggas p modeller som baseras p mikroekonomiska uppgifter som hmtas frn projekten.
It is also likely that a more in-depth evaluation of certain, specific themes could better lead to the identification of best practices and provide additional insight into particular issues such as for instance the impact of clustering, the significance of growth hubs in regional development vis--vis the overall objective of convergence. 
Det r ocks troligt att en mer djupgende utvrdering av vissa specifika teman bttre skulle kunna leda till att man faststller bsta praxis och fr ytterligare insikter i srskilda frgor som effekten av klustring, betydelsen av tillvxtcentrum fr regional utveckling i frhllande till det vergripande konvergensmlet.
Thirdly, greater emphasis needs to be placed on establishing linkages between the ex post assessments and thematic studies, and to ensure that results are consistent with each other. 
Fr det tredje behver strre eftertryck lggas p att koppla samman efterhandsutvrderingar och tematiska studier, och att garantera att resultaten stmmer verens med varandra.
If results appear to be incompatible, then this aspect needs to be specifically tackled. 
Om resultaten visar sig vara ofrenliga mste denna aspekt hanteras specifikt.
Fourthly, a number of recommendations for future assessments more particularly for Objective 1 Regions may be made, namely: (a) There needs to be specific focus on the reasons why private sector contributions to the structural funds projects differ markedly between the Members States. 
Fr det fjrde kan ett antal rekommendationer ges fr framtida bedmningar av i synnerhet ml 1-regioner, nmligen fljande: a) Srskild vikt br lggas vid att bedma anledningarna till att den privata sektorns bidrag till strukturfondsprojekt skiljer sig markant t mellan de olika medlemsstaterna.
This may cast important light on the different drivers to economic development in the various Objective 1 regions. (b) Another worthwhile topic to explore is whether there should be a shift in the future from grant expenditure to financial engineering measures, such as seed and venture capital funds, loans and interest rate subsidies, which may prove to be more sustainable and efficient in the long term. (c) Greater attention needs to be given to the establishment of unit costs and benchmarks for various types of projects. (d) Additional attention also needs to be given to the project application and approval process as the evaluators pointed out. (e) There should be a greater focus on internal evaluations by the relevant ministries or regional authorities in future ex post assessments. 
Detta kan belysa de olika drivkrafterna till ekonomisk utveckling i de olika ml 1-regionerna. b) En annan viktig frga att utforska r om det skall ske ett skifte i framtiden frn std i form av bidrag till finansiell ingenjrskonst, till exempel start-eller riskkapitalfonder, ln och rn-tesubventioner, vilka kan visa sig vara mer hllbara och effektiva i det lnga loppet. c) Strre uppmrksamhet br riktas p faststllande av enhetskostnader och riktmrken fr olika typer av projekt. d) Ytterligare vikt behver ocks lggas vid ansknings-och godknnandeprocessen fr projekten i enlighet med vad utvrderarna ppekade. e) Strre vikt br lggas vid interna utvrderingar av de berrda ministerierna eller regionala myndigheterna i framtida bedmningar.
Finally, it is important to strengthen the capacity of the Commission to oversee the evaluation process, including the application of complex macroeconometric models. 
Slutligen r det viktigt att strka kommissionens kapacitet att vervaka utvrderingsprocessen, inklusive tillmpning av komplexa makro-ekonometriska modeller.
One possibility to consider, in this context, would be for the relevant DGs to seek a closer collaboration with research institutes and universities specialised in this area of assessment. 
En mjlighet som borde beaktas i det hr sammanhanget r att de olika generaldirektoraten frsker f till stnd ett nrmare samarbete med forskningsinstitut och universitet som r specialiserade p detta bedmningsomrde.
Appropriate and timely supervision of contracted consultants is crucial in ensuring that objectives are met and that value for money is derived from such ex post assessments. 
Lmplig vervakning vid rtt tidpunkt av kontrakterade konsulter r grundlggande fr att garantera att mlen uppfylls och att pengarna anvnds effektivt i sdana efterhandsutvrderingar.
In conclusion, the ex post evaluation exercise must go beyond the compilation of distinct assessments, carried out at given intervals of time, but should be envisaged and managed as an integral part of an overall process. 
Som slutsats mste man vid efterhandsutvrderingarna gra mer n att sammanstlla skilda bedmningar som genomfrts vid olika tidsintervaller. Utvrderingsarbetet br betraktas och frvaltas som en del i en vergripande process.
This is another aspect where a closer, and long term collaboration with research institutes or universities could be of significant benefit in providing a more effective framework within which to integrate the specific reports and recommendations generated at each stage of the evaluation process. 
Detta r en annan aspekt dr ett nrmare och lngvarigt samarbete med forskningsinstitut eller universitet kunde vara av stor nytta fr att ge en mer ndamlsenlig ram inom vilken man kan integrera de enskilda rapporter och rekommendationer som har genererats p varje stadium i utvrderingsprocessen.
This report was adopted by the Court of Auditors in Luxembourg at its meeting of 20 July 2006. 
Denna rapport har antagits av revisionsrtten vid dess sammantrde i Luxemburg den 20 juli 2006.
12.12.2006 EN Official Journal of the European Union C 302/25 O1 748,50 O2 349,40 O3/O4 476,50 O5a Fisheries 25,10 O5b 78,90 O6 13 985,30 1 604,80 1 990,00 14 333,90 26 965,80 2 474,80 1 888,60 2 245,40 3 866,40 3 282,20 5 762,30 15 236,20 1 498,20 1 757,40 Netherlands 153,80 666,20 1 105,70 47,70 153,70 14 333,90 Kingdom 2 419,70 171,50 4 693,40 104,40 3 460,50 408,30 96 15 15 356,30 750,70 592,90 905,70 054,10 736,60 Total 1 678,40 629,90 18 913,70 14 333,90 32 131,80 11 881,70 5 762,30 19 552,70 46,20 2 127,10 14 333,90 11 501,60 1 111,20 136 396,30 Source: Special Report No 16/98 (OJ C 347, 16.11.1998). 123,00 308,40 143,20 76,30 1 257,30 122,20 680,40 2 194,40 293,30 137,60 923,30 15,40 23,60 1,10 6,10 90,80 2,10 837,20 424,90 165,40 189,30 354,10 537,60 23,80 41,40 201,00 142,70 475,90 260,70 1 220,20 1 171,70 55,30 7 (1) Names of programmes related to Structural Funds; further references can be found in the Commission budget, subsection B2. 
12.12.2006 SV Europeiska unionens officiella tidning C 302/25 Ml 1 Ml 2 Ml 3/4 Ml 5a fiske Ml 5b 748,50 349,40 476,50 13 985,30 1 604,80 1 990,00 14 333,90 26 965,80 2 474,80 1 888,60 2 245,40 3 866,40 3 282,20 5 762,30 15 236,20 1 498,20 1 757,40 lnderna 153,80 666,20 14 333,90 kungariket 2 419,70 171,50 4 693,40 104,40 3 460,50 408,30 96 15 15 356,30 750,70 592,90 905,70 054,10 736,60 Ml 6 Totalt 1 678,40 629,90 18 913,70 14 333,90 32 131,80 11 881,70 5 762,30 19 552,70 46,20 2 127,10 14 333,90 11 501,60 1 111,20 136 396,30 25,10 78,90 123,00 308,40 143,20 76,30 1 257,30 122,20 680,40 194,40 2 293,30 137,60 923,30 15,40 23,60 1,10 6,10 1 105,70 47,70 153,70 90,80 2,10 837,20 424,90 165,40 189,30 354,10 537,60 23,80 41,40 201,00 142,70 475,90 260,70 1 220,20 1 171,70 Klla: Srskild rapport nr 16/98 (EGT C 347, 16.11.1998).
Source: Special Report No 16/98 (OJ C 347, 16.11.1998). 
Klla: Srskild rapport nr 16/98 (EGT C 347, 16.11.1998).
C 302/26 EN Official Journal of the European Union 12.12.2006 ANNEX II GDP and the employment rate 1. 
C 302/26 SV Europeiska unionens officiella tidning 12.12.2006 BILAGA II BNP och sysselsttningsgrad 1.
A multiple regression analysis was conducted to test the statement in the Synthesis Report that Ôincreased levels of GDP per capita have generally not been the result of increased employment rates resulting from job creationŐ (1). 
En multipel regressionsanalys utfrdes fr att testa pstendet i den sammanfattande rapporten om att kade niver av BNP per capita i allmnhet inte har varit resultatet av kad sysselsttningsgrad till fljd av skapande av arbetstillfllen (1).
For strict comparability, the same data published in the Synthesis Report has been used in this analysis. 
Fr en strikt jmfrbarhet anvndes fr denna analys samma uppgifter som lades fram i den sammanfattande rapporten.
In the case of the dependent variable the percentage change in GDP per capita for each Objective 1 region between 1993 and 2000 was used, while as main explanatory variables, the percentage change in the employment rate as well as that of the unemployment rate was used for the same regions, and over the two years 1993 and 1999 as published in the report. 
Nr det gller den beroende variabeln anvndes procentandelen frndring i BNP per capita fr varje ml 1-region mellan 1993 och 2000, och som frmsta frklarande variabler anvndes procentandelen frndring i sysselsttningsgrad och fr arbetslshetsgrad fr samma regioner och fr de tv ren 1993 och 1999, liksom i rapporten.
The results are given in Table 1. 
Resultaten visas i tabell 1.
Table 1 (1) Regression of the change in GDP per capita on change in employment (CEMPL) and change in unemployment (CUNEMP) Regressor Coefficient Standard error C1 1,7615 1,2361 CEMPL 0,24563 0,14237 CUNEMP 0,051927 0,027418 BE Đ 16,8803 6,2156 IR 38,2350 6,5314 DX 26,9660 2,9504 R-squared 0,74449 R-bar-squared T-ratio 1,4251 [Prob] [0,161] [0,092] [0,065] [0,009] [000] [000] 0,71546 [000] 11,5126 Đ 158,5015 Đ 170,2376 Đ 1,7252 1,8939 2,7158 5,8540 9,1398 S.E. of Regression Mean of dependent variable Residual sum of squares Akaike information criterion 6,1411 F-stat. 
Tabell 1 (1) Regression av frndringen i BNP per capita vid frndring i sysselsttning (CEMPL) och frndring i arbetslshet (CUNEMP) Regressor Koefficient Medelfel C1 1,7615 1,2361 CEMPL 0,24563 0,14237 CUNEMP 0,051927 0,027418 BE Đ 16,8803 6,2156 IR 38,2350 6,5314 DX 26,9660 2,9504 T-vrde 1,4251 [Sannolikhet] [0,161] [0,092] [0,065] [0,009] [000] [000] 0,71546 [000] 11,5126 Đ 158,5015 Đ 170,2376 Đ 1,7252 1,8939 2,7158 5,8540 9,1398 Determinationskoefficient (r2) Regressionens medelfel Genomsnittlig beroende variabel Residualkvadratsumma Akaikes informationskriterium 0,74449 Justerad determinations-koefficient (rbar2) 6,1411 F-stat.
F (5,44) 6,3647 S.D. of dependent variable 1 659,4 Equation log-likelihood Đ 164,5015 Schwarz Bayesian criterion 25,6414 DW-statistic (1) 50 observations used for estimation. 
F (5,44) 6,3647 Standardavvikelse fr den beroende variabeln 1 659,4 Logaritmisk ekvation fr sannolikheten Đ 164,5015 Schwarz Bayes kriterium 25,6414 DW-statistik (1) 50 iakttagelser anvndes fr bedmningen.
BE, IR and DX are dummy variables for Belgium, Ireland and Germany. 
BE, IR och DX r dummyvariabler fr Belgien, Irland och Tyskland.
C1 is the intercept. 
C1 r interceptet.
From a preliminary assessment of the data, it emerged that three particular regions exhibited significantly different patterns of change in GDP per capita over the period as compared to the other regions, and which required specific treatment in the regression, as otherwise it would be difficult to draw general conclusions about underlying links. 
Vid en preliminr bedmning av uppgifterna framkom att tre srskilda regioner uppvisade vsentligt olika mnster av frndringar i BNP per capita ver perioden jmfrt med andra regioner, och detta krvde srskild behandling i regressionen eftersom det annars skulle bli svrt att dra allmnna slutsatser om underliggande samband.
These were; Ireland, which saw its GDP per capita rise from 81 % to 115 % of the EU average over the period; the Hainaut region in Belgium, which saw its GDP per capita decline from 82 % to 71 %; and German Objective 1 regions which saw the GDP per capita rise from a range around 50 % to close to 70 % of the EU average by the end of the period (for example, Thuringen saw its GDP per capita rise from 52 % in 1993 to 70 % in 2000). 
Detta gllde Irland, vars BNP per capita kade frn 81 % till 115 % av medelvrdet fr EU ver denna period, den andra regionen var Hainaut-regionen i Belgien vars BNP per capita minskade frn 82 % till 71 %, och den tredje kategorin gller ml 1-regionerna i Tyskland vilkas BNP per capita kade frn omkring 50 % till nra 70 % av medelvrdet fr EU i slutet av perioden (till exempel kade BNP per capita i Thringen frn 52 % r 1993 till 70 % r 2000).
To take account of such large relative changes in GDP per capita, specific statistical (or dummy) variables where included for this purpose which allowed the function to shift for these three broad regions. 
Fr att ta hnsyn till sdana stora relativa frndringar i BNP per capita infrdes srskilda statistiska variabler (dummyvariabler) fr detta syfte vilket gjorde att funktionen fr dessa tre omfattande regioner kunde variera.
The regression results shown in Table 1 provide a number of relevant points worth noting. 
De resultat av regressionen som visas i tabell 1 innehller ett antal relevanta punkter som r vrda att noteras.
Overall, 74 % of the variation in the change in GDP per capita is accounted for by the ÔexplanatoryŐ variables. 
Generellt frklaras 74 % av variationen i frndringen av BNP per capita av de ÓfrklarandeÓ variablerna.
Both main explanatory variables, that is the change in employment rates (CEMPL) and change in unemployment rates (CUNMP) are statistically significant. 
Bda de viktigaste frklarande variablerna, det vill sga frndring i sysselsttningsgrad (CEMPL) och frndring i arbetslshetsgrad (CUNEMP), r statistiskt signifikanta.
In the case of CEMPL, the coefficient estimated is 0,24, suggesting that each one percentage point increase in the employment or participation rate is associated with an improvement in GDP per capita of Objective 1 regions by a quarter of a percentage point Ń thereby, if nothing else changes, closing the GDP gap by this amount. 
Nr det gller CEMPL r den uppskattade koefficienten 0,24, vilket antyder att varje procentenhet kning i sysselsttningsgrad eller frvrvsfrekvens r knuten till en frbttring av BNP per capita i ml 1-regioner med en fjrdedels procentenhet Đ och drmed, om ingenting i vrigt frndras, minskar skillnaderna i BNP med detta belopp.
2,3210 (1) Synthesis Report, p. 
2,3210 (1) Sammanfattande rapport, s.
12.12.2006 EN Official Journal of the European Union C 302/27 5. 
12.12.2006 SV Europeiska unionens officiella tidning C 302/27 5.
This result directly contradicts the conclusion reached in the synthesis report, and provides a useful indicator of the potential there is, from an analysis of the results of Objective 1 regions over this period, to close the GDP gap by improving participation rates Ń a most relevant result from the policy perspective. 
Detta resultat str i direkt motsttning till slutsatsen i den sammanfattande rapporten, och ger en anvndbar indikator p den mjlighet som, enligt en analys av resultaten i ml 1-regioner under denna period, finns att minska skillnaderna i BNP genom att frbttra arbetskraftstalet Đ ett ur politiskt perspektiv mycket relevant resultat.
A second feature of note in the results in Table 1 relates to the impact of the changes in unemployment rates on changes in the GDP per capita. 
Ytterligare ett drag som r vrt att beakta i resultaten i tabell 1 gller effekten av frndringar i arbetslshetsgraden p frndringar i BNP per capita.
This impact (also discussed in the next section) is also statistically significant, but is rather small quantitatively, almost of an irrelevant value. 
Denna effekt (som ven tas upp i nsta avsnitt) r ocks statistiskt signifikant men r ganska liten kvantitativt sett, nstan av irrelevant vrde.
Unemployment declined marginally overall in Objective 1 regions, and this may be the reason for this result. 
Arbetslsheten gick ner marginellt totalt i ml 1-regionerna och detta kan vara orsaken till detta resultat.
To explore further the robustness of the main result in Table 1 relating to the impact of changes in the employment rate and changes in GDP per capita, Table 2 provides the regression results for all regions in the EU-15 and for which data was consistently available from Eurostat, and not just for Objective 1 regions. 
Fr att ytterligare utforska robustheten i det frmsta resultatet i tabell 1 nr det gller effekten av frndringar i sysselsttningsgrad och frndringar i BNP per capita finns i tabell 2 regressionsresultaten fr alla regioner i EU-15 och fr vilka Eurostat genomgende hade tillgngliga uppgifter, och inte bara fr ml 1-regioner.
The results from 145 regions where derived from slightly different data than in Table 1. 
Resultaten frn 145 regioner berknades utifrn ngot annorlunda uppgifter n de som anvnts i tabell 1.
Rather than taking just the rate of change between the beginning and end of the relevant period, the average rate of change was computed for the whole period. 
Istllet fr att endast faststlla graden av frndring frn brjan till slutet av den relevanta perioden berknades den genomsnittliga rliga frndringen fr hela perioden.
This was judged to give a more representative summary of developments over a number of years, in this case over the five year period between 1996 and 2000. 
Detta bedmdes ge en mer representativ sammanfattning av utvecklingen ver ett antal r, i detta fall ver femrsperioden mellan 1996 och 2000.
(Due to data limitations in the available statistics, an earlier starting point was not feasible for a number of regions.) 
(P grund av begrnsade uppgifter i den tillgngliga statistiken gick det inte att utg ifrn en tidigare startpunkt fr ett antal regioner.)
Table 2 (1) Regression of average change in GDP per capita on average change in employment (ACEMPL) and average change in unemployment (ACUNEMP) Regressor Coefficient Standard error C 5,2110 0,12999 ACEMPL 0,24119 0,63540 ACUNEMP Đ 0,0019479 0,012260 ID 4,7009 0,85873 LD 5,4309 0,84670 BED Đ 0,64276 0,25885 DED Đ 1,3747 0,17517 R-squared 0,62600 R-bar-squared T-ratio 40,086 [Prob] [000] [000] [0,874] [000] [000] [0,014] [000] 0,60974 38,4979 [000] 1,3477 Đ 177,2101 Đ 194,6286 Đ Đ Đ 3,7959 0,1588 5,4743 6,4142 2,4831 7,8479 S.E. of regression Mean of dependent variable Residual sum of squares Akaike information criterion DW-statistic 0,84193 F-stat. 
Tabell 2 (1) Regression av den genomsnittliga frndringen i BNP per capita vid frndring i sysselsttning (ACEMPL) och genomsnittlig frndring i arbetslsheten (ACUNEMP) Regressor Koefficient Medelfel C 5,2110 0,12999 ACEMPL 0,24119 0,63540 ACUNEMP Đ 0,0019479 0,012260 ID 4,7009 0,85873 LD 5,4309 0,84670 T-vrde 40,086 [Sannolikhet] [000] [000] [0,874] [000] [000] [0,014] [000] BED DED Determinationskoefficient (r2) Regressionens medelfel Genomsnittlig beroende variabel Đ 0,64276 0,25885 Đ 1,3747 0,17517 Đ Đ Đ 3,7959 0,1588 5,4743 6,4142 2,4831 7,8479 Residualkvadratsumma 97,8204 Akaikes informationskriterium DW-statistik Đ 184,2101 0,62600 0,84193 5,2359 Justerad 0,60974 determinations-koefficient (rbar2) F-stat.
F (6,138) 5,2359 S.D. of dependent variable 97,8204 Equation log-likelihood Đ 184,2101 Schwarz Bayesian criterion 1,6353 (1) 145 observations used for estimation. ID, LD, BED, DED are dummy variables for Ireland, Luxembourg, Belgium and Germany. 
F(6,138) Standardavvikelse fr den beroende variabeln Logaritmisk ekvation fr sannolikheten Schwarz Bayes kriterium 1,6353 38,4979 [000] 1,3477 Đ 177,2101 Đ 194,6286 (1) 145iakttagelseranvndesfrbedmningen.ID,LD,BEDochDEDrdummyvariablerfrIrland,Luxemburg,BelgienochTyskland.Cr interceptet.
The results indicate that the coefficient for the average change in employment is practically the same as in the previous case, that is 0,24, indicating that for all regions, a 1 % increase in the employment rate tends to be associated with a 0,24 % increase in GDP per capita. 
Resultatet pekar p att koefficienten fr den genomsnittliga frndringen i sysselsttningen r praktiskt taget densamma som i det frra fallet, det vill sga 0,24, vilket tyder p att en kning p 1 % i sysselsttningsgrad fr samtliga regioner verkar hnga samman med en kning p 0,24 % i BNP per capita.
This result is also statistically significant, as is the whole regression equation. 
Detta resultat r ocks statistiskt signifikant, liksom hela regressionsekvationen.
(An additional dummy variable for Luxembourg has been added, again because the increase in GDP per capita from 161 % in 1996 to 199 % in 2000, is markedly different from the average performance of the other regions). 
(En extra dummyvariabel fr Luxemburg har lagts till, terigen p grund av att kningen i BNP per capita frn 161 % r 1996 till 199 % r 2000 tydligt skiljer sig t frn det genomsnittliga resultatet i de andra regio-nerna.)
C 302/28 EN Official Journal of the European Union 12.12.2006 9. 
C 302/28 SV Europeiska unionens officiella tidning 12.12.2006 9.
The impact of the change in the unemployment rate variable is again minimal and in this case is statistically insignificant and negative. 
Effekten av frndringen i arbetslshetsvariabeln r terigen minimal och i detta fall statistiskt insignifikant och negativ.
The implications from these results are that the impact of changes in the unemployment rate on changes in GDP per capita does not appear strong Ń possibly because the unemployed are already accounted for in the labour force and in the measure of GDP that is used, and any change from unemployed to employed has a less easy impact to capture in statistical analysis of this type. 
Innebrden av dessa resultat r att effekten av frndringar i arbetslshetsgraden p frndringar i BNP per capita inte verkar vara stark Đ mjligen p grund av att de arbetslsa redan rknas med i arbetskraften och i mttet p BNP som anvnds, och varje frndring frn arbetsls till anstlld har en effekt som r svrare att fnga in i en statistisk analys av det hr slaget.
Certainly, more research in this area seems warranted. 
Det r tydligt att mer forskning p detta omrde verkar behvas.
12.12.2006 EN Official Journal of the European Union C 302/29 ANNEX III GDP growth and the structural funds 1. 
12.12.2006 SV Europeiska unionens officiella tidning C 302/29 BILAGA III BNP-tillvxten och strukturfonderna 1.
A multiple regression analysis was conducted to explore the link between the average annual change in GDP per capita for the Objective 1 area (the dependent variable) vis--vis the actual EU funds per capita expenditure in the Objective 1 regions of each member state. 
En multipel regressionsanalys utfrdes fr att utforska sambandet mellan den genomsnittliga rliga frndringen i BNP per capita fr ml 1-omrdet (den beroende variabeln) med de faktiska utgifterna per capita frn EU-fonderna i ml 1-regionerna i varje medlemsstat.
The same data and time period (1993 to 1999) is used as that found in the Synthesis Report. 
Samma uppgifter och tidsperiod (1993Đ1999) anvnds som i den sammanfattande rapporten.
It should be noted that modelling rates of change is a statistically demanding exercise, and often gives low levels of explained variation in the dependent variable. 
Det skall ppekas att modellering av frndringsgrad r ett statistiskt krvande arbete som ofta ger lg niv av frklarad variation i den beroende variablen.
Nonetheless, the results in Table 1 show that 53 % of the variation in the dependent variable is accounted for by the different allocations in EU Funds on a per capita basis. 
Inte desto mindre visar resultaten i tabell 1 att 53 % av variationen i den beroende variabeln beror p skillnader i tilldelning av EU-medel per capita.