High-employment-growth firms – persistence over time and policy implications Björn Falkenhall Swedish Agency for Growth Policy Analysis

Background Research shows that most firms do not grow at all, and that most new jobs originate from a small number of high-growth firms These firms might carry important policy implications, and they have therefore received an increasing amount of attention among policymakers in recent years Most studies of HGFs do not examine what happens to them over time, which is a limitation If HGFs are persistent over time, then we might learn something from investigating them. This is, however, not possible if high growth rates are not persistent over time

Purpose of the study The purpose of the study (The dynamics of high-growth firms: Is high-growth persistent?) is to analyze if growth of Swedish firms during the period are characterized by persistence The analysis is based on data from Statistics Sweden and includes all private firms with more than one emloyee in all sectors in Sweden. Number of employees is used as growth indicator The study is conducted by Sven-Olov Daunfeldt (HUI Research) and Daniel Halvarsson (Ratio institute) on behalf of Growth Analysis

The dynamics of High Growth Firms Number of HGFs – – –

Two different methods are used Growth equation: Transition probabilities (the probability to transit from one category to another in the growth distribution between different periods in time):

Results for different growth categories (1)(2)(3)(4)(5)(6) g t-3 -0,0678**-0,01***-0,004***-0,067***-0,0746***-0,157*** (0,0271)(0,003)(0,001)(0,002)(0,004)(0,027) Const.-1,87***-0,649***-0,189***0,342***1,062***2,195*** (0,014)(0,001) (0,003)(0,026) Obs R2R2 0,0050,0020,0010,0280,0590,069 F-test0,0120,000

Results for different firm size Micro firms (1-9) Small firms (10-49 Medium size firms (50-249) Big firms (>250) (1.)(2.)(3.)(4.) g t-3 -0,120***-0,019*-0,0200,024 (0,003)(0,010)(0,027)0,021 Const.-0,0000,081***0,078***0,087*** (0,001)(0,004)(0,010)0,020 Obs R20,0160,0004 0,0009 F-test0,0000,0600,4650,254

Transition probabilities to transit from one growth category to another between , och , all firms t \ t+3 12 – 1011 – 2223 – 65 a 66 – 9090 – ,0070,0980,0250,4960,1750,1200,079 2 – 100,0110,1070,0470,5160,2590,0520, – 220,0200,1170,2340,2380,3700,0190, – 650,0060,1010,0490,6300,1930,0190, – 900,0160,1290,1770,2700,3800,0260, – 990,0280,1700,1530,1820,4030,0590, (HGFs)0,0550,1460,1830,0880,4430,0750,009 a Percentiles 23 to 65 contain firms that not grow.

To conclude The results indicate that firm growth is negatively correlated over time The negative correlation is espacially strong for HGFs, but mainly due to micro firms However, the results from the transition probability analysis show that HGFs are more likely than most other firms to experience positive growth, but not as high as before Observed HGFs will most likely not be HGFs in the next (three year) period, ”one hit wonders” What are the policy implications?

Competencies and institutions fostering HGF* Actors of change, a nexus of economic actors with complementary competencies that are vital in order to generate and commercialize novel ideas The institutional framework determines the incentives for these individuals to aquire and utilize knowledge, and thus the creation of HGFs Pivotal role played by tax structures, labor market regulations and the contestability of service markets Distortions introduced by these three bundles of institutions disfavor young, small firms within the service sector (frequent among HGFs) * Henrekson & Johansson (2009)

Productivity growth in the service sector Annual US productivity growth was nearly a full percentage point higher than EU-15 during the period Three-quarters of this gap is accounted for by market services (Uppenberg, 2011) The difference in productivity growth between manufacturing and services is particular big in Germany where the service sector is protected from competition and relative inefficient (The Economist, 3/18/2012) In Sweden, the private service sector contribution to labor productivity was higher than manufacturing from 1994 to 2009, but with rather large variations between different service sectors (Growth Analysis, report 2011:04)

Regulation and economic growth Regulations that restrict competition curb labor or MFP growth significantly, the negative effects tends to be stronger in ICT- intensive industries (Arnold, Nicoletti & Scarpetta, 2011) Production dynamics are lower in countries that have a relatively heavy regulatory burden. (Growth Analysis, report 2010:14) The reallocation of resources towards the highest-productivity firm is stonger where regulations are lighter (Arnold, Nicoletti & Scarpetta, 2011) The regulatory burden does not affect necessity based entrepreneurship, but there is a negative correlation between regulations and oppurtunity based entrepreneurship (Growth Analysis, 2010:14)

Conclusions Doubtful whether studies of HGF at one point in time could generate insights about how economic policy should be formulated The regulatory burden is important for all firms, but in particular important for ICT-intensive industries and opportunity based entrepreneurship, i.e. potential HGFs The importance of the institutional framework, in particular tax structures, labor market and anticompetitive regulations A focus on improving the general framework for business can therefore also be regarded as the main policy measure for HGFs