Eastern Europe. The database contains detailed …rm-level accounting data for a number<strong>of</strong> …nancial ratios, activities, and ownership. While initially received <strong>from</strong> over 50 di¤erentvendors across Europe, <strong>the</strong> data is <strong>the</strong>n transformed into a single format enabling comparisonacross countries. The focus <strong>of</strong> <strong>the</strong> Amadeus database is on …nancial information, like…rm pro…t, revenue, assets, debt, and value added. In addition to that, Amadeus provides…rm-level information on year <strong>of</strong> incorporation and employment. We use <strong>the</strong> former to calculate<strong>the</strong> age <strong>of</strong> <strong>the</strong> …rm, hence <strong>the</strong> share <strong>of</strong> "<strong>new</strong>" …rms in each industry-country-year. Thevariable we create is referred to as Entry ij , and it denotes <strong>the</strong> share <strong>of</strong> …rms less than 2-yearsold in country i in industry j, calculated separately for 1998-1999 in <strong>the</strong> main regressions,and for 2006-2007 in <strong>the</strong> robustness tests. We only count <strong>the</strong> …rms that are at least 1 fullyear <strong>of</strong> age to reduce measurement error.Finally, Amadeus uses <strong>the</strong> 3-digit NACE industry classi…cation standard, which we aggregateat <strong>the</strong> 2-digit level in order to have a su¢ cient number <strong>of</strong> …rms in each industry foreach country. Columns 2 and 4 <strong>of</strong> Table 2 summarize our main Amadeus data, aggregatedat <strong>the</strong> country level, for <strong>the</strong> two time periods <strong>of</strong> interest.<strong>On</strong>e main concern is that <strong>the</strong> years 1998-1999 chosen for <strong>the</strong> main empirical exercisesmay not be "steady state" in terms <strong>of</strong> <strong>new</strong> business incorporation as <strong>the</strong>y were too closeto <strong>the</strong> peak <strong>of</strong> <strong>the</strong> dot-com bubble. Similar concerns apply to <strong>the</strong> period 2006-2007 whichcoincided with <strong>the</strong> peak <strong>of</strong> ano<strong>the</strong>r business cycle. For that reason, we calculated averageentry rates over <strong>the</strong> 1995-2007 period, using data on entry rates <strong>from</strong> Eurostat, and <strong>the</strong>ncompared <strong>the</strong> long-term averages to data for 1998-1999 and 2006-2007, again <strong>from</strong> Eurostat.Columns 3 and 5 <strong>of</strong> Table 2 presents <strong>the</strong> deviation <strong>of</strong> <strong>the</strong> latter <strong>from</strong> <strong>the</strong> long-term averagesin percentage terms, for 1998-1999 and 2006-2007, respectively. The average deviation for<strong>the</strong> 1998-1999 sample is 5.9%, and only in three <strong>of</strong> <strong>the</strong> countries in <strong>the</strong> sample is it higherthan 7%. This gives us con…dence that <strong>the</strong> years 1998-1999 are pretty much "steady state"in terms <strong>of</strong> <strong>new</strong> business creation. The same applies to <strong>the</strong> second period chosen. 22 The little overall variation in entry rates is signi…ed by <strong>the</strong> fact that even <strong>the</strong> years 2000 and 2001, whichcoincided with <strong>the</strong> peak <strong>of</strong> <strong>the</strong> internet bubble, show an average deviation <strong>of</strong> only 8.4% <strong>from</strong> <strong>the</strong> samplelong-term average.ECBWorking Paper Series No 1078August 200913
2.3 US industry-level entry dataAs a benchmark for <strong>new</strong> business incorporation into an industry, we use data on …rm entryin <strong>the</strong> respective NACE rev. 1.1 2-digit industry in <strong>the</strong> US, <strong>from</strong> <strong>the</strong> Dun and Bradstreetdatabase <strong>of</strong> over 7 million corporations over <strong>the</strong> period 1998-1999.The methodology <strong>of</strong>using US industry characteristics as a benchmark in cross-country cross-industry studieswas …rst introduced by Rajan and Zingales (1998), who argued that <strong>the</strong> composition <strong>of</strong>US industries in terms <strong>of</strong> external …nance usage can be viewed as <strong>the</strong> industries’"natural"or "technological" composition, because US …nancial markets are relatively friction-free,compared with o<strong>the</strong>r …nancial markets around <strong>the</strong> world, including most industrial countries.The methodology has been used, among o<strong>the</strong>rs, by Beck et al.(2008) to calculate <strong>the</strong>"natural" share <strong>of</strong> small …rms in an industry, by Claessens and Laeven (2003) to calculate<strong>the</strong> industry’s "natural" usage <strong>of</strong> intangibles, and most recently by Klapper et al. (2006) tocalculate <strong>the</strong> "natural" rate <strong>of</strong> business incorporation, which we use in this paper.It needs to be pointed out that proxying <strong>the</strong> "natural" rate <strong>of</strong> industry entry by entryin <strong>the</strong> respective industry in <strong>the</strong> US is somewhat arbitrary. It relies on <strong>the</strong> assumption thatbureaucratic barriers to entry are lower <strong>the</strong>re than in any country in Europe, and that <strong>the</strong>cost <strong>of</strong> …nancial intermediation and start-up …nancing is su¢ ciently lower in <strong>the</strong> US than inEurope as a whole. This technique does not argue that industries in <strong>the</strong> US have achieved<strong>the</strong> …rst best in terms <strong>of</strong> entry, but that <strong>the</strong> …nancial and regulatory environment is relativelymore conducive to entry than <strong>the</strong> countries in our sample. For example, while entry costs in<strong>the</strong> US are around 0.5% <strong>of</strong> per capita GNP, in our sample <strong>of</strong> European countries <strong>the</strong>y areon average around 20%; and while venture capital <strong>investment</strong> in <strong>the</strong> US in 1998-1999 wasabout 0.2% <strong>of</strong> GDP, it stood at 0.1% <strong>of</strong> GDP in <strong>the</strong> UK, 0.05% <strong>of</strong> GDP in France and 0.02%<strong>of</strong> GDP in Germany, with <strong>the</strong>se three countries receiving <strong>the</strong> lion share <strong>of</strong> <strong>the</strong> <strong>private</strong> <strong>equity</strong><strong>investment</strong> in Europe. Certainly, <strong>the</strong> entry costs in <strong>the</strong> US are non-zero, and it is impossibleto know if <strong>the</strong> optimal amount <strong>of</strong> venture capital <strong>investment</strong> is not much larger than 0.2%<strong>of</strong> GDP, but what matters is that <strong>the</strong>se characteristics <strong>of</strong> <strong>the</strong> US business environment aresuperior than in <strong>the</strong> countries in our sample.For robustness purposes, however, similar14 ECBWorking Paper Series No 1078August 2009
- Page 1 and 2: Working Paper SeriesNo 1078 / augus
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- Page 5 and 6: AbstractUsing a comprehensive datab
- Page 7 and 8: environment leaves the main results
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- Page 21 and 22: …rms only (less than 10 employees
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- Page 29 and 30: 4.6 RobustnessWe conduct an extensi
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- Page 35 and 36: [12] Cetorelli, N., and P.E. Straha
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- Page 39 and 40: Table 2Summary statistics on entry,
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- Page 43 and 44: Table 6Private equity timing and fi
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- Page 47 and 48: Appendix 1. Variables: definitions
- Page 49 and 50: Share shadow economyShare of the in
- Page 51: 1068 “Asset price misalignments a