Transcript Comments on *Financial Development: Structure and

Comments on
“Financial Development: Structure and Dynamics”
by Augusto de la Torre, Erik Feyen and Alain Ize
Conference on Financial Structure and Economic Development
World Bank, Washington, DC
June 16, 2011
Martin Cihak
Lead Economist, WB/FPDCE
A very relevant paper
• Outlines a comprehensive framework
– four fundamental types of frictions
– associated market failures / paradigms
• Shows some interesting empirical results
– including a useful regional study on LAC countries
• Particularly relevant for work on WBG’s new
Global Financial Development Report
– should include a part on “benchmarking” financial
sector development in countries around the globe
The findings are plausible
• The notion that financial sector development is nonlinear,
bumpy, and that there is a both a “bright” and “dark” side
to finance seems very plausible.
• It is hard to argue against ideas of path-dependence and
leapfrogging (e.g.: checks, credit cards, mobile banking,…).
• A number of observations that sound realistic (and
consistent with recent evidence):
– much of financial development is explosive
– but it has decreasing impacts (returns) on real development
– finance resembles “luxury good” (its use explodes as income
rises, yet its benefits exhibit declining returns).
– finance may become excessive at some point
– this point is influenced by quality of policies to reduce the risks
The paper has ambitious goals
• It attempts to isolate the policy component of
financial development (“enabling environment”)
from the (exogenous component of the) outcome
financial indicator.
• This is a difficult task; there is little consensus on the
appropriate methodology
Main comments
• The link between the theoretical and the
empirical parts could be strengthened
• The empirical part, as the authors say, is at this
point more an illustration than in-depth
econometric analysis.
• Need some more clarity on the hypotheses that
are being tested, what is the test, rejected/not
rejected, at what level.
• More clarity on the caveats/weaknesses of data.
Patterns of financial development
• Financial development described as a largely
logical progression
– “Gradual grinding down/easing of frictions”
– But new frictions can emerge.
– Focus on “leapfrogging”, but there may also be
“backpaddaling” and dead ends
• Results largely driven by cross-country variation
yet interpreted as developments over time
– “government borrowing appears early in the game”,
“bank deposits emerge before credit”, etc.
– yet data don’t go before 1980s
Choice of variables, data
• Overall, the choice of variables is reasonable, given the data constraints
– Indicators of reach, efficiency and liquidity, globalization, and soundness
– Some indicators could be added, e.g., on access to finance
– The indicators are analyzed one by one. How to come up with a
comprehensive assessment?
• But need more caveats on underlying data
– Imprecise proxies (net margins vs. efficiency)
– The data are basic aggregate ratios (no differentiation within systems; do not
capture evolution in financial technology--e.g. checks/cards/mobile payments)
– Missing observations, issues of comparability (accounting standards etc)
• Data adjusted for a number of controls, including GDP/capita
– The inclusion of GDP/capita is problematic
– It one of the “real” development variables that are presumably affected by
financial development (=>causality/endogeneity issues)
Econometrics: panel vs. cross-section?
• Instead of panel regressions, the authors opt to run crosssectional regressions (on medians), and to show graphically
a set of paths around that cross section.
• This approach allows for an interesting graphical
presentation.
• But some info about the dynamics of the systems may be
lost by not using the panel data for a panel regression (# of
observations could increase from ~100 to a few thousand).
• This could potentially better explain the impact of changes
in in institutional/legal/regulatory framework, innovation in
global finance, and other types shocks.
Additional econometric comments
• Core of the empirical analysis: mapping gaps into forcing variables (Tab 6):
– How does the regression technique deal with possible measurement errors in the
dependent variable (=estimated “gap”)?
– Are the “gaps” comparable across countries? (The gap in finance for each country is
given by the distance of the indicator from the “norm”, which comes from adjusting
country medians on economic development and other country-specific characteristics. )
– To what extent does the lack of significance on some of the Enabling Environment
Indicators reflect that they are correlated with real GDP growth or that they may also
explain the incidence of credit crunches?
– Credit crunches can also be approximated as in Claessens, Kose and Terrones (2011):
CC= bottom 25% of world sample of credit declines; severe CC= those in bottom 12.5 %.
– Given the high concordance between housing prices and credit (Claessens et al. 2011),
housing price busts could also be defined and included in the regression.
– Analogously, for the regressions on stock markets, the authors could also include equity
price busts (based on real stock prices) or real currency busts (based on REERs).
•
To what extent is the distance from the norm explained by the set of forcing
variables?
– For example, in Table 9, it would be useful to show not only the explained gaps but also
the actual gap.
Things to add in the explanation of
gaps in financial development…
• Influence of explicit policy actions (e.g. financial liberalization) on
reducing gaps.
• External shocks (e.g., swings in risk appetite, changes in world interest
rates) that typically affect the inflow of foreign capital and, hence, the
depth of domestic financial market
• Features of the broader policy environment (e.g., exchange rate
regime, capital market openness—this may have an impact on financial
dollarization, FX markets, FX heding instruments, and ability to manage
FX risks)
• Features of the market structure (e.g., market concentration – may
have an impact on the speed of setting up credit info sharing systems,
degree of state ownership)
• Ownership (state, foreign, domestic private– may have an impact on
speed of introduction of new technologies)
• What about appearance of derivates and sophisticated products (CDO,
CDO-sq, CDS, etc.)
Summing up…
• A very useful paper, both the theoretical part
and the empirical part.
• The link between the two parts could be
strengthened
– Also, clearer caveats on data weaknesses.
– And more clarity on the hypotheses that are being
tested.