International Financial Integration and Entrepreneurship

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International Financial Integration and Entrepreneurship Laura Alfaro and Andrew Charlton Discussion by Jean Imbs IMF 7 th Jacques Polak Conference 9-10 November 2006 The views expressed in this paper are those of the author(s) only, and the presence of them, or of links to them, on the IMF website does not imply that the IMF, its Executive Board, or its management endorses or shares the views expressed in the paper.

The Questions Finance crowds local entrepreneurs out (or relaxes borrowing constraints?) Finance increases the likelihood of crises (or fosters risk sharing?) Old Question, New Data

The Data 98 countries, 24 million firms (listed and unlisted), classified into SIC industries Entrepreneurship : Firm Entry (% firms younger than 2 years) Firm Size (# employees) Skewness in Firm Size distribution Finance: - AREAER IMF indices - K inflow / GDP, K inflow+outflow / GDP, FDI inflow / GDP Foreign Liabilities (Stock) / GDP

The Method 1. Cross-Section: E = α K + β X + δ + ε ic c c i ic Isolates country component of firm data. Other determinants of firm size, age, distribution? E.g. regulations (labor, product market?) Omitted Variables is usual cheap shot, but unfortunately crucial 2. Rajan Zingales: E = d + d + γ Lib. EUS + ε ic i j c i ic Control set now as general as it gets. But firm age/size/entry in US plausible benchmark? WalMart in India?

The Method 3. Diff in Diff: DE = γ Lib + βdx + d + ν ic c i ic Controls crucial again to isolate treatment effect of liberalization. Financial liberalizations do not occur in a vacuum: is DX c controlling for all there is?

The Usual Suspects Omitted Variables Treatment Endogeneity: Countries with many young, small firms tend to attract foreign capital. Problem in cross-sectional sectional and diff in diff estimates. Stress Rajan-Zingales approach: differential effects probably not caused by aggregate firm characteristics. Sampling: US 7m observations, France 4m, Japan, Germany, Italy, Netherlands, Czech Rep all 1m. Doesn t t appear to correlate with financial development, but focus on sub-sample sample where proportion of firm universe is known (and constant)?

The Usual Suspects Measurement: Entrepreneurship or Firm Size / Age? Entry is about proportion of young firms Skewness is about size distribution Industry with many large and old firms will be skewed Industry with high exit rate may be skewed Sufficient statistics for entrepreneurship? More likely, paper about effect of finance on firm characteristics. cs.

The Point Key point: In spite of nitpicking discussant s s checklist, results are eminently convincing and robust. But is that surprising? Results here are quite similar to things we already know about the effects of finance on (small, young) firms. Given literature, difficult to see how could have found otherwise.

The Literature Beck, Demirguc-Kunt Kunt, Laeven, Maksimovic (2004, 2005): Financial Development (Private Credit) boosts growth of small firms. (using a Rajan-Zingales methodology) Beck, Levine (2002): Financial Development boosts creation of new firms (though Banks vs. Markets does not) Henry (2000, 2003): Liberalizations of Stock Market / Capital Account boost Investment. nt. Bertrand, Schoar, Thesmar (2004): French Banking Deregulation boosted firm creation (and exit) in bank dependent industries. And altered market structure. Black, Strahan (2005): US branching deregulation boosted incorporations.

The Contribution What is new here? Exceptional data and international coverage (with sampling issues). Differences with Beck s s recent data? => Effects of Finance Universal? Finance is measured by Foreign Capital or Capital Account Liberalization Indices rather than Private Credit. => Origin of Capital Matters? Foreign vs. Domestic? => Are measures here capturing something Private Credit did not?

The Contribution What Capital? Paper begins analyzing an FDI channel. E = α ShareForeign + βx + δ + ε ic ic c i ic Foreign-owned owned firms increase the share of young firms. But silent as to whether displace local ones. Why not simply use data to decompose E ic into local vs. foreign firms? => Would answer first question paper set out to examine. But endogeneity issue. Sectors with lots of young, dynamic firms tend to attract FDI.

The End Rich data should enable an answer to question whether foreign capital has crowding out effects. Not clear whether can answer the crisis-growth question. Can and should do more than just replicating existing results.