## _wp04112

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### Introduction and motivation
- Rationale for financial liberalization centers on two potential benefits:
  - Quantity effect: higher levels of savings and investment.
  - Quality effect: a more efficient allocation of capital.
- This paper reports evidence of a quality effect and proposes a new measure of allocative efficiency based on variation in expected returns across firms.

### Measure of allocative efficiency and data
- Allocative efficiency measure:
  - Dispersion in Tobin’s Q in a given country and year, controlling for industry and age effects.
- Sample:
  - 413 firms in five emerging market economies—India, Jordan, Korea, Malaysia, and Thailand—from 1980 to 1994.
- Distinction between:
  - Financial liberalization: reduction in the role of government and increase in the role of markets in allocating credit; measured using a new financial-liberalization index incorporating credit controls, interest rate controls, entry barriers for banks, regulations, privatization, and restrictions on international financial transactions.
  - Financial deepening: increase in the volume of credit intermediated; typically measured by indicators such as M2, credit to the private sector, or stock market capitalization relative to GDP.

### Theoretical intuition and model (Section III)
- Mechanism and predictions:
  - If liberalization enhances efficiency, variation in expected returns should be lower in more liberalized financial sectors and higher in less liberalized sectors.
  - Removal of government controls reallocates credit from firms with low expected returns to firms with high expected returns, reducing dispersion in marginal returns.
- Model setup (selected equations and assumptions):
  - Firm profit: π_t = f_t(K_t,L_t) - w_t L_t - φ(I_t) - R_t K_t.
  - Capital law of motion: K_t = (1-δ)K_{t-1} + I_t.
  - CRS production: f1>0, f2>0, f11<0, f22<0, f12>0; φ' > 0, φ'' > 0.
  - Steady state conditions:
    - f1(K*,L*) - R φ'(I*) = 0
    - f2(K*,L*) = w
    - K* = I*/δ
- Role of controls:
  - Price controls (differential interest rates) and quantity controls (I = ÃI) generate cross-firm variation in marginal returns; liberalization eliminates these controls and reduces dispersion.
- Timing assumption:
  - Adjustments are assumed to be quick (completed within a year), justifying use of annual data to approximate steady-state responses.

### Empirical measure: dispersion in Tobin’s Q (Section IV)
- Rationale:
  - Use dispersion in Tobin’s Q as proxy for dispersion in expected marginal returns to capital (Q ≈ discounted sum of expected future profits per asset).
  - Q should equal unity in perfectly functioning markets absent measurement error.
- Practical approximations:
  - Denominator uses only tangible assets.
  - Market value of debt replaced by book value of debt.
  - Replacement cost of tangible assets approximated by adjusting book values for cumulative inflation (formula assumes δ = 0.05).
  - Use average Q as proxy for marginal Q.
- Adjustments and controls:
  - Correct for industry and age effects by regressing log Q on age and industry fixed effects for each country-year:
    - q_i = α + β Age_i + Σ_j γ_j (Industry_j) + ε_i
  - Construct adjusted Q: q̂_i = mean(q) + e_i, where e_i is the residual from the age-industry regression.
- Inequality/dispersion indices used:
  - (1) Gini coefficient
  - (2) Mean log deviation (entropy class α=0)
  - (3) Theil index (entropy class α=1)
  - (4) Half the squared coefficient of variation (entropy class α=2)
- Sensitivity notes:
  - Gini: most sensitive near the mean.
  - Mean log deviation: most sensitive to bottom of distribution.
  - Coefficient of variation: most sensitive to top of distribution.
  - Theil: constant sensitivity across distribution.

### Data construction (Section V)
- Financial liberalization index:
  - New index covering 36 countries over 1973 to 1996.
  - Six policy dimensions scored 0–3 (0 = fully repressed, 1 = partially repressed, 2 = largely liberalized, 3 = fully liberalized):
    - Credit controls
    - Interest rate controls
    - Entry barriers
    - Regulations
    - State ownership in financial sector
    - Restrictions on international financial transactions
  - Policy changes recorded as shifts in scores; reversals recorded as shifts from higher to lower scores.
- Corporate finance data:
  - Firm-level data from IFC Corporate Finance Database: annual information on up to the 100 largest publicly traded, non-financial firms in thirteen developing countries.
  - Study uses five countries due to sample selection and data limitations: India, Jordan, Korea, Malaysia, Thailand.
  - Table 1 in the source summarizes firm-count coverage by country-year.
- Sample biases:
  - Focusing on large, publicly listed firms biases against detecting a positive effect of liberalization (large firms more likely well-connected under repression).
  - Unbalanced sample biases against finding a decrease in dispersion if entry patterns change after liberalization.

### Descriptive evidence (Section VI)
- Pre/post liberalization dates used (Demirgüc-Kunt and Detragiache (1998)):
  - India 1991, Jordan 1988, Korea 1991, Malaysia 1987, Thailand 1989.
- Key pre/post changes in Gini coefficient (dispersion in Q):
  - Jordan: Gini dropped by 41 percent, from 0.30 to 0.17.
  - India: Gini dropped by 19 percent, from 0.25 to 0.20.
  - Malaysia: Gini decreased by 11 percent.
  - Thailand: Gini decreased by 7 percent.
  - Korea: Gini decreased by 2 percent.
- Comparative notes:
  - Theil index often shows a somewhat larger percentage decline than the Gini, indicating larger changes in distribution tails.
  - Mean log deviation and coefficient of variation also show declines larger than the Gini, indicating effects at both lower and upper tails.
- Time patterns:
  - Several countries exhibit a gradual increase in dispersion up to a few years before liberalization, then a decline after liberalization (example: Jordan rise from 1980 to 1987, then fall).
  - Interpreted as prolonged channeling of credit to favored firms lowering their marginal product while constrained firms retain high marginal returns.

### Panel regressions and robustness (Section VII)
- Baseline regression:
  - Dependent variable: dispersion in adjusted log Q.
  - Controls: cumulative inflation (five-year cumulative), trade openness, private credit growth, stock market capitalization, stock market turnover.
  - Fixed effects preferred over random effects (Hausman test where indicated).
- Fixed effects coefficients on financial liberalization (selected; absolute t-stats in brackets; significance markers preserved):
  - Gini: -0.215 [4.82]***
  - Theil: -0.459 [4.91]***
  - Mean log deviation: -0.776 [3.34]***
  - Squared coefficient of variation: -0.448 [5.02]***
- Financial deepening controls (Table 3 summary):
  - Deepening measures: private credit/GDP, stock market capitalization/GDP, stock market turnover/capitalization.
  - When included with liberalization:
    - Financial liberalization remains significant at the 1-percent level.
    - Stock market turnover significant at the 5-percent level.
    - Private credit and stock market capitalization often insignificant.
  - Bank credit sometimes obtains a positive coefficient when liberalization is controlled for (suggesting possible misallocations during lending booms).
- Dynamic panel (Arellano-Bond GMM) results (selected; robust z statistics in brackets; significance preserved):
  - Gini specifications:
    - -0.112 [1.64]
    - -0.130 [1.84]*
    - -0.066 [1.09]
    - -0.176 [3.42]***
  - Theil specifications:
    - -0.247 [1.89]*
    - -0.286 [1.99]**
    - -0.157 [1.31]
    - -0.387 [4.17]***
  - Lagged dependent variables indicate persistence (example: 0.562 [4.81]*** in a reported specification).
  - Mean log deviation and Squared CV: liberalization coefficients generally correctly signed and often significant; stock market turnover often significant when included.
- Additional robustness checks:
  - Dropping one country at a time: main results hold.
  - Crisis dummy (currency/banking crisis): coefficient positive (crises widen variation) but almost always insignificant and does not change main results.
  - Individual subcomponents of liberalization: no single subcomponent as robust as the aggregate index.
  - Interactions between liberalization and deepening: no new robust patterns.
  - Allowing liberalization coefficient to vary by country: India coefficient negative but insignificant; Jordan significantly more negative than India; Korea and Malaysia insignificantly more negative than India; Thailand significantly more positive than India (fragile due to limited observations per country).

### Key empirical conclusions (Section VIII)
- Main empirical conclusion:
  - Financial liberalization improves allocative efficiency: strongly negatively associated with dispersion in Tobin’s Q, consistent with model prediction that liberalization equalizes access to credit and reduces variation in expected marginal returns across firms.
- Robustness and interpretation:
  - Effect robust to controls for inflation, trade openness, private credit growth, stock market capitalization, stock market turnover, persistence, endogeneity, crises, and specification checks.
  - Result is notable given biases against detecting an effect (large-firm focus and unbalanced sample).
- Additional findings:
  - Financial liberalization, rather than financial deepening, appears more important for improving allocative efficiency. Standard measures of deepening were often insignificant or wrongly signed when liberalization controlled.
  - Stock market turnover (liquidity) has an independent positive effect on efficiency — possibly through easier equity issuance or more accurate valuations.
  - Dispersion in marginal returns often increases prior to liberalization, consistent with prolonged channeling of credit to favored firms and denial to others.
- Policy implication:
  - Policies that liberalize financial sectors (removing differential price and quantity credit controls, reducing entry barriers, improving regulatory/prudential frameworks, reducing state ownership, easing international transaction restrictions) can improve capital allocation across firms, increasing allocative efficiency even if aggregate savings/investment levels do not rise.

*IMF Working Paper content unit _wp04112 (sections II–VIII, Appendix I) as provided.*

### References..............................................................................................................

### _wp04112 - References.........................................................................................................................

### Introduction and motivation
- Rationale for financial liberalization centers on two potential benefits:
  - Quantity effect: higher levels of savings and investment.
  - Quality effect: a more efficient allocation of capital.
- This paper reports evidence of a quality effect and proposes a new measure of allocative efficiency based on variation in expected returns across firms.

### Measure of allocative efficiency and data
- Allocative efficiency is measured by the dispersion in Tobin’s Q in a given country and year, controlling for industry and age effects.
- Sample: 413 firms in five emerging market economies—India, Jordan, Korea, Malaysia, and Thailand—from 1980 to 1994.
- Distinction emphasized between:
  - Financial liberalization: reduction in the role of government and increase in the role of markets in allocating credit; measured using a new financial-liberalization index incorporating credit controls, interest rate controls, entry barriers for banks, regulations, privatization, and restrictions on international financial transactions.
  - Financial deepening: increase in the volume of credit intermediated; typically measured by indicators such as M2, credit to the private sector, or stock market capitalization relative to GDP.

### Theoretical intuition
- If liberalization enhances efficiency, variation in expected returns should be lower in more liberalized financial sectors (market allocation) and higher in less liberalized sectors (government allocation).
- Mechanism: removal of government controls leads to reallocation of credit from firms with low expected returns to firms with high expected returns, altering expected returns across firms and reducing dispersion.

### Main empirical findings
- Descriptive evidence: dispersion in Tobin’s Q decreased in all five countries following financial liberalization.
- Panel regressions: the coefficient on financial liberalization is strongly negative, robust to controls for omitted variables, time trends, endogeneity, and other factors.

### Additional findings
- Financial liberalization appears more important than financial deepening for improving allocative efficiency.
  - Once financial liberalization is controlled for, increased bank credit is associated with lower allocative efficiency—potentially reflecting misallocations of credit during lending booms.
- Stock market liquidity (measured by stock market turnover relative to market capitalization) lowers dispersion of marginal returns; this effect persists after controlling for financial liberalization.
  - Possible interpretations: an independent effect of stock market liquidity on allocative efficiency or improved accuracy of stock market valuation as liquidity increases.
- In several countries, dispersion in Q increased gradually prior to liberalization, suggesting worsening credit allocation over time as credit continued to be directed toward already large firms.

### Organization of the paper
- Section II reviews literature on quantity and quality effects of financial liberalization and related literature on financial deepening.

*Source: _wp04112 - References, https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2004/_wp04112.pdf*

### Section III then presents a simple model that shows how government intervention in credit

### _wp04112 - Section III then presents a simple model that shows how government intervention in credit

### Related literature: quantity, quality, and deepening
- Quantity effects
  - Theoretical channels that could raise savings and investment after liberalization include: higher interest rates following removal of interest rate ceilings (McKinnon (1973), Shaw (1973)); better insurance against future risk inducing shifts to higher-risk-higher-return projects (Obstfeld (1994)); increased bank competition internalizing investment externalities (Ueda, 2000).
  - Ambiguous/negative channels include: income vs. substitution effects may offset higher rates; improved insurance may lower incentives to save (Devereux and Smith, 1994).
  - Empirical findings are mixed: Bandiera and others (2000) find no increase in savings in eight developing countries; Jayaratne and Strahan (1996) find deregulation of bank branches in the U.S. did not increase bank lending; Sancak (2002) finds 1980 Turkish reforms did not reduce financing constraints.
- Quality effects
  - Existing studies generally find positive quality effects but have definitional issues. Cho (1988) reports a decrease in variation in borrowing costs after liberalization in Korea; Galindo, Schiantarelli, and Weiss (2002) report positive effects on allocative efficiency using firm-level data for 12 developing countries; Chari and Henry (2003) find capital account liberalization improves allocation across countries.
  - Critique: reductions in variation in borrowing costs can be tautological; investment-weighted vs size-weighted ex post marginal returns may not properly indicate improved allocation because a perfectly efficient economy should show equal marginal products across firms.
- Financial deepening vs liberalization
  - Prominent literature (King and Levine, 1993; Levine, Loayza, and Beck, 2000) ties financial deepening (M2, private credit/GDP) to growth.
  - Other studies: Rajan and Zingales (1998) show industries dependent on external finance grow more slowly in countries with less developed financial markets; Wurgler (2000) finds capital flows to growing industries in deeper financial sectors; Beck, Levine, and Loayza (2000) link deepening to TFP increases; Love (2001) links deepening to lower sensitivity of investment to internal funds.
  - This paper: explicitly controls for both financial liberalization and financial deepening and reports that financial liberalization, rather than financial deepening, improves allocative efficiency.

### The model (Section III): government controls generate dispersion in marginal returns
- Setup
  - Firm profit function: π_t = f_t(K_t,L_t) - w_t L_t - φ(I_t) - R_t K_t  (equation (1) in source)
  - Capital law of motion: K_t = (1-δ)K_{t-1} + I_t  (equation (2) in source)
  - f: CRS production function with f1>0, f2>0, f11<0, f22<0, f12>0; φ' > 0, φ'' > 0.
  - Unique steady state (K*, I*, L*) determined by:
    - f1(K*,L*) - R φ'(I*) = 0 (equation (3))
    - f2(K*,L*) = w  (equation (4))
    - K* = I*/δ  (equation (5))
- Main mechanism
  - Fully liberalized financial sector: a common market interest rate R implies equal marginal returns to capital across otherwise identical firms.
  - Price controls (differential interest rates across firms): firms facing higher interest rates set lower K* and thus exhibit higher marginal returns; variation in interest rates across firms → variation in marginal returns.
  - Quantity controls (government-determined investment ÃI): adding constraint I = ÃI with Lagrange multiplier λ modifies the capital market condition to f1(K*,L*) - R φ'(I*) = -λ (equation (3’)). If ÃI < I* then λ>0 and marginal return > R; if ÃI > I* then λ<0 and marginal return < R.
  - Uniform binding interest-rate ceilings that induce rationing produce the same pattern as quantity controls: firms with credit access have low marginal returns, credit-constrained firms have high marginal returns.
- Prediction
  - Eliminating price or quantity controls (financial liberalization) reallocates credit from over-investing (low marginal return) firms to under-investing (high marginal return) firms, reducing dispersion in marginal returns — i.e., improving allocative efficiency.
  - Assumption: adjustments are quick (completed within a year), so steady-state values approximated with annual data.

### Dispersion in Tobin’s Q as the empirical measure (Section IV)
- Rationale
  - Use dispersion in Tobin’s Q as a proxy for dispersion in expected marginal returns to capital (Q ≈ discounted sum of expected future profits per asset); Q should equal unity in perfectly functioning markets absent measurement error.
  - Focus on ex-ante expected marginal returns; ex-post realized returns may rise in dispersion after liberalization if firms select higher-risk-higher-return projects (Obstfeld, 1994).
- Practical approximations used to compute Q
  - Denominator uses only tangible assets (no data on non-tangible assets).
  - Market value of debt replaced by book value of debt.
  - Replacement cost of tangible assets approximated by adjusting book values for cumulative inflation (formula in source assumes δ = 0.05).
  - Use average Q as proxy for marginal Q.
- Adjustments and controls
  - Correct for industry and age effects by regressing log Q on age and industry fixed effects for each country-year:
    - q_i = α + β Age_i + Σ_j γ_j (Industry_j) + ε_i  (equation (6))
  - Construct adjusted Q: q̂_i = mean(q) + e_i  (equation (7)), where e_i is the residual from the age-industry regression.
- Inequality/dispersion measures (four indices)
  - (1) Gini coefficient (definition equation (8))
  - (2) Mean log deviation (entropy class α=0) (equation (10))
  - (3) Theil index (entropy class α=1) (equation (11))
  - (4) Half the squared coefficient of variation (entropy class α=2) (equation (12))
  - Notes on sensitivities:
    - Gini: most sensitive near the mean.
    - Mean log deviation: most sensitive to bottom of distribution.
    - Coefficient of variation: most sensitive to top of distribution.
    - Theil: constant sensitivity across distribution.

### Data (Section V)
- Financial liberalization index
  - New index covering 36 countries over the 24-year period from 1973 to 1996.
  - Six policy dimensions scored 0–3 (0 = fully repressed, 1 = partially repressed, 2 = largely liberalized, 3 = fully liberalized):
    - Credit controls (directed credit, credit ceilings, high reserve requirements)
    - Interest rate controls (government-controlled rates; floors/ceilings/bands)
    - Entry barriers (licenses, foreign bank participation limits, specialization limits)
    - Regulations (operational restrictions considered repression; prudential regulations considered reforms)
    - State ownership in financial sector
    - Restrictions on international financial transactions (capital/current account convertibility, multiple exchange rates)
  - Policy changes recorded as shifts in scores; reversals recorded as shifts from higher to lower scores.
- Corporate finance data
  - Firm-level data from IFC Corporate Finance Database: annual information on up to the 100 largest publicly traded, non-financial firms in thirteen developing countries (source list provided).
  - Due to sample selection and data limitations, this study uses five countries: India, Jordan, Korea, Malaysia, Thailand.
  - Table 1 (in source) summarizes firm-count coverage by country-year.
- Sample considerations and biases
  - Focusing on large, publicly listed firms biases against detecting a positive effect of liberalization (large firms more likely well-connected and less constrained under repression).
  - Use of unbalanced sample biases against finding a decrease in dispersion if entry patterns change; liberalization expected to lower entry barriers and potentially increase dispersion among new entrants, again biasing against detecting efficiency gains.

### Descriptive statistics (Section VI): unconditional patterns
- Pre/post liberalization comparison (liberalization dates used from Demirgüc-Kunt and Detragiache (1998): India 1991, Jordan 1988, Korea 1991, Malaysia 1987, Thailand 1989)
- Key pre/post changes in Gini coefficient (dispersion in Q)
  - Jordan: Gini dropped by 41 percent, from 0.30 to 0.17.
  - India: Gini dropped by 19 percent, from 0.25 to 0.20.
  - Malaysia: Gini decreased by 11 percent.
  - Thailand: Gini decreased by 7 percent.
  - Korea: Gini decreased by 2 percent.
- Comparative notes
  - Theil index often shows a somewhat larger percentage decline than the Gini, suggesting larger changes in tails of the distribution.
  - Mean log deviation (sensitive to lower tail) and coefficient of variation (sensitive to upper tail) also show declines larger than the Gini, indicating both low-Q and high-Q firms were affected.
- Time patterns
  - Several countries show a gradual increase in dispersion (worsening allocative efficiency) up until a few years before liberalization, then a decline after liberalization (example: Jordan rise from 1980 to 1987, then fall).
  - Interpretation: prolonged channeling of credit to same firms can reduce their marginal product while constrained firms remain high-productivity.

### Panel regressions and robustness (Section VII)
- Baseline approach
  - Panel regressions of dispersion in adjusted log Q on financial liberalization index, controlling for: cumulative inflation (five-year cumulative), trade openness, private credit growth, stock market capitalization, stock market turnover.
  - Fixed effects preferred over random effects (Hausman test rejects RE in favor of FE where indicated).
- Fixed effects results (selected coefficients; absolute t-stats in brackets; significance markers preserved)
  - Financial liberalization coefficients across four dispersion measures (Fixed Effects):
    - Gini: -0.215 [4.82]***
    - Theil: -0.459 [4.91]***
    - Mean log deviation: -0.776 [3.34]***
    - Squared coefficient of variation: -0.448 [5.02]***
  - Cumulative inflation and trade openness: mixed significance; trade openness often negative and significant at 5 percent in FE.
- Financial deepening controls (Table 3 summary)
  - Financial deepening measures used: private credit/GDP, stock market capitalization/GDP, stock market turnover/capitalization.
  - When included separately with liberalization:
    - Financial liberalization remains significant at the 1-percent level.
    - Stock market turnover significant at the 5-percent level.
    - Private credit and stock market capitalization often insignificant.
  - When liberalization combined with deepening indicators, liberalization remains significant; bank credit sometimes obtains a positive coefficient (suggesting possible short-run misallocation during credit booms).
- Controlling for persistence and endogeneity (Arellano-Bond dynamic panel GMM; Table 4)
  - Approach: include lagged dependent variable, first-differencing, instrumenting with lagged levels.
  - Selected results (robust z statistics in brackets; significance preserved):
    - Gini (Arellano-Bond): Financial liberalization coefficients in various specifications include:
      - -0.112 [1.64]
      - -0.130 [1.84]*
      - -0.066 [1.09]
      - -0.176 [3.42]***
    - Theil (Arellano-Bond): Financial liberalization coefficients include:
      - -0.247 [1.89]*
      - -0.286 [1.99]**
      - -0.157 [1.31]
      - -0.387 [4.17]***
    - Mean log deviation and Squared CV: financial liberalization coefficients remain correctly signed and often significant; stock market turnover often significant when liberalization included.
  - Lagged dependent variables show persistence (e.g., 0.562 [4.81]*** for a reported specification).
- Additional robustness checks (Section D)
  - Dropping one country at a time: results hold.
  - Crisis dummy (currency/banking crisis): coefficient positive (crises widen variation) but almost always insignificant and does not change main results.
  - Running regressions on individual subcomponents of liberalization: no single subcomponent as robust as the aggregate index.
  - Interactions between liberalization and deepening: no new interesting patterns.
  - Allowing the liberalization coefficient to vary by country: India coefficient negative but insignificant; Jordan significantly more negative than India; Korea and Malaysia insignificantly more negative than India; Thailand significantly more positive than India (note fragility due to only 11–12 observations per country).

### Key empirical conclusions (Section VIII)
- Main finding
  - Financial liberalization improves allocative efficiency: it is strongly negatively associated with dispersion in Tobin’s Q, consistent with the model prediction that liberalization equalizes access to credit and reduces variation in expected marginal returns across firms.
- Robustness and interpretation
  - Effect robust to controls for inflation, trade openness, private credit growth, stock market capitalization, stock market turnover, persistence, endogeneity, crises, and various specification checks.
  - Result is notable given biases against detecting an effect: focus on large publicly listed firms and use of an unbalanced sample both bias against finding decreases in dispersion.
- Additional findings
  - Financial liberalization, rather than financial deepening, appears more important for improving allocative efficiency. Standard measures of deepening (bank credit, stock market capitalization) were often insignificant or wrongly signed when liberalization controlled.
  - Stock market turnover (liquidity) has an independent positive effect on efficiency — possibly reflecting easier equity issuance or more accurate valuations.
  - Dispersion in marginal returns often increases prior to liberalization, consistent with prolonged channeling of credit to favored firms and denial to others.
- Policy implication (implicit in findings)
  - Policies that liberalize financial sectors (removing differential price and quantity credit controls, reducing entry barriers, improving regulatory/prudential frameworks, reducing state ownership, easing international transaction restrictions) can improve capital allocation across firms, increasing allocative efficiency even if aggregate savings/investment levels do not rise.

*Italic source attribution line: IMF Working Paper content unit _wp04112 (sections II–VIII, Appendix I) as provided.*

### REFERENCES

### REFERENCES

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### Risk, diversification, crises, and financial fragility
- Acemoglu, Daron, and Zilibotti, 1997, “Does Prometheus Unbound by Chance? Risk, Diversification, and Growth,” Journal of Political Economy, Vol. 105, No. 4, pp. 709–51.  
- Devereux, Michael B., and Gregor W. Smith, “International Risk Sharing and Economic Growth,” International Economic Review, Vol. 53, No. 2, pp. 363–84.  
- Obstfeld, Maurice, 1994, “Risk-Taking, Global Diversification, and Growth,” American Economic Review, Vol. 84, No. 5, pp. 1310–29.  
- Bordo, Michael D., Barry Eichengreen, Daniela Klingebiel, and Maria Soledad Martinez Peria, 2000, “Financial Crises: Lessons from the Last 120 Years,” Economic Policy: A European Forum, No. 32 (April), pp. 51–82.  
- Demirgüc-Kunt, Aslí, and Enrica Detragiache, 2001, “Financial Liberalization and Financial Fragility,” in Financial Liberalization: How Far, How Fast? ed. by Gerard Caprio, Patrick Honohan and Joseph E. Stiglitz (New York: Cambridge University Press).  
- Chari, Anusha, and Peter Blair Henry, 2003, “The Invisible Hand in Emerging Markets: Discerning or Indiscriminate?,” Working Paper, University of Michigan Business School. Available via the Internet at: http://webuser.bus.umich.edu/achari/achari.htm.  
- Phelan, Christopher, “Repeated Moral Hazard and One-Sided Commitment,” Journal of Economic Theory, Vol. 66, No. 2, pp. 488–506.  
- Hellmann, Thomas, Kevin Murdock, and Joseph Stiglitz, 1996, “Financial Restraint,” Chapter 6, The Role of Government in East Asian Economic Development, edited by Masahiko Aoki, Hyung-Ki Kim, and Masahiro Okuno-Fujiwara (New York: Oxford University Press).  

### Measurement, capital controls, and inequality
- Edison, Hali, and Francis Warnock, 2003, “A Simple Measure of the Intensity of Capital Controls,” Journal of Empirical Finance, Vol. 10, No. 1-2 (February), pp. 81–03.  
- Bandiera, Oriana, Gerard Caprio, Patrick Hanohan, and Fabio Schiantarelli, 2000, “Does Financial Reform Raise or Reduce Saving?,” Review of Economics and Statistics, Vol. 82, No. 2 (May), pp. 239–63.  
- Beck, Thorsten, Ross Levine, and Norman Loayza, 2000, “Finance and the Sources of Growth,” Journal of Financial Economics,58 (October), pp. 261–300.  
- Cowell, Frank, 1995, Measuring Inequality (Englewoods Cliffs, New Jersey: Prentice-Hall, 2nd ed.).  
- Deaton, Angus, 1997, The Analysis of Household Surveys: A Microeconometric Approach to Development Policy (Baltimore: Johns Hopkins University Press).  

### Other contributions and technical papers
- Booth, Laurence, Varouj Aivazian, Aslí Demirgüc-Kunt, and Vojislav Maksimovic, 2001, “Capital Structures in Developing Countries,” Journal of Finance, Vol. 56, pp. 87–130.  
- Ito, Motoshige, Masahiro Okuno, Kazuharu Kiyono, and Kotaro Suzumura, 1998, Sangyo Seisaku no Keizai Bunseki, Tokyo Daigaku Shuppankai (Tokyo: University of Tokyo Press).  
- Singh, Ajit, and Javid Hamid, in collaboration with Bahram Salimi and Yoichi Nakano, 1992, Corporate Financial Structures in Developing Countries, IFC Technical Paper 1 (Washington, DC: International Finance Corporation). Available via the Internet at http://www.ifc.org/economics/pubs/techpap1/tp1.pdf  
- Devereux, Michael B., and Gregor W. Smith, “International Risk Sharing and Economic Growth,” International Economic Review, Vol. 53, No. 2, pp. 363–84.  
- McKinnon, Ronald, 1973, Money and Capital in Economic Development (Washington: Brookings Institution).  

*Source: _wp04112 - REFERENCES*

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