1. Discussion by Aart Kraay The World Bank October 14, 2004
SMEs, Growth, and Poverty Thorsten Beck, Asli Demirgüç-Kunt, Ross Levine
Discussion by Aart Kraay
The World Bank
October 14, 2004

2. What the Paper Does:
Measures of importance of SMEs, and quality of overall business environment (BE)
Which matters more for growth: SME or BE?
Which matters more for changes in inequality: SME or BE?

3. What I Liked About the Paper:
Paper asks a great question!
Very useful questioning of conventional wisdom
$10 bn is a lot of money to spend without benefit of evidence!
Heroic efforts at cross-country data collection!

4. What We Need More of:
High-quality evidence from micro data on role of firm size
…but this is hard to do…and hard to generalize
Example 1: Firm Size and Productivity
TFP is Production / Inputs = Q/L
We measure Revenue / Costs = (PxQ)/(WxL)
OK if all firms face same P, W
But they don’t! Market power => Upward bias for large firms
Example 2: Firm Size and Job Creation
SME birth creates lots of jobs … but SME death destroys lots of jobs too
To capture this you need a census that credibly tracks entry and exit (including possibly into the informal sector)
This kind of data hard to find in developing countries

5. What I Didn’t Like: Identification Strategy
Paper rightly is concerned with direction of causation
do SMEs cause growth or does growth create opportunities for SMEs?
does BE spur growth or do perceptions of BE reflect growth?
Lots of possible omitted variables
BE, SME have substantial measurement error
All of these problems justify recourse to IV

6. Identification Strategy, Cont’d
Proposed instruments (ethnic diversity, dummies for LAC, Transition, Africa) are correlated with BE, SME
But it is very hard to believe exclusion restriction required to validate the instruments!
Ethnic diversity matters for growth only through worse BE?
Only reason transition economies grew slowly in 1990s is because they had fewer SMEs?
Africa’s difficult geography and bad institutions don’t matter for growth?
What about all the other endogenous RHS variables (including initial income by construction)?
selective instrumentation does not deliver consistent estimates of any of the coefficients of interest

7. Taking IV Seriously Table 4: Business Environment and Growth:
OLS:  = 0.73
IV:  = 2.72
Four possible explanations for IV >> OLS
“Perverse” reverse causation
“Peculiar” omitted variables
“Enormous” measurement error in BE
Invalid exclusion restrictions

8. Taking IV Seriously, Cont’d
“Perverse” Reverse Causation
Conventional wisdom (growth raises BE) implies IV < OLS
To justify IV >> OLS need high growth to cause much worse BE – why might this be?
“Peculiar” Omitted Variables
Many likely candidates (e.g. good institutions) raise growth and improve BE, this implies IV < OLS
To justify IV >> OLS need omitted variables that raise growth and lower BE, or vice versa – what could they be?

9. Taking IV Seriously, Cont’d
“Enormous” Measurement Error in BE
Attenuation bias:
(OLS) =  VAR(True BE)/VAR(Measured BE)
(IV) = 3 x (OLS) implies variance of measurement error in BE is twice variance of true BE
This means BE measures are virtually uninformative! e.g. suppose observed BE is 1 SD above the mean, best forecast of true BE is that it is only 0.33 SD above mean

10. Taking IV Seriously, Cont’d
Invalid Exclusion Restriction
True model is:
Growth =  BE + e
BE =  ELF + v
Instrumental variables regression delivers:
(IV) =  + (COV(e, ELF)/VAR(ELF))/ 
Bias is slope of regression of structural error (e) on the instrument (ELF), scaled by 
Does ELF matter for growth holding constant BE? Quite plausibly (higher inequality, higher social conflict, many other channels)

11. Summary Great question very relevant for policy!
Firm-level data will help to get closer to definitive answers on role of SMEs in growth and poverty – but doing this right will be hard
Identification in cross-country (or cross-anything) regressions is hard. Useful to:
take it as seriously as possible
recognize that there is only so much orthogonal and independent variation across countries in the things we care about (so many good things go together across countries!)