## _wp09183 - References

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---

### I. Introduction
- Objective: present stylized facts on how countries recover from recessions; focus on rebound speed and persistence.
- Key literature points:
  - Negative shocks, particularly financial crises, can generate a sizeable permanent loss in the level of output compared with the pre-crisis trend (Cerra and Saxena, 2008).
  - Cerra and Saxena (2005b) show permanent shocks account for most variation in emerging market output fluctuations.
  - Recessions are often abrupt and violent but short-lived; expansions are smoother and longer-lived (Mitchell, 1927; Hamilton, 1989).
  - Paper investigates asymmetries in policy effectiveness and country characteristics during recoveries versus later expansion years.

### II. Methodology and data
- Empirical model:
  - Panel with country fixed effects; general form includes GROWTHTROUGH* and interactions with X (see Equation (1) in source).
  - Recovery defined as year(s) of positive growth immediately following a trough (the final year in a sequence of years with negative annual growth).
  - Regressions restricted to years with positive GDP growth.
  - γ measures asymmetric impact of policy/structural variable X on recovery speed; δ measures impact in "normal" expansion years; δ+γ measures total effect in recovery years.
- Identification and endogeneity:
  - Country fixed effects to control for time-invariant factors.
  - Address reverse causation/endogeneity for macro policy by using lagged policy variables and focusing on asymmetric impact (recovery year relative to other expansion years).
- Data coverage and samples:
  - Annual observations spanning 1960 to 2005.
  - Up to 197 countries; unbalanced panel of up to 5482 observations.
  - Favorite subsample excludes countries with population less than one million.
  - Favorite subsample counts: total of 550 recovery episodes; 63 in advanced economies and 487 in developing countries (229 episodes in Sub-Saharan Africa and 258 episodes in developing countries outside SSA).
- Variable construction notes:
  - LSIZE = log of total GDP (constant USD) averaged over 1960-2004 (or 1970-2000 in some tables).
  - Policy variables often lagged by one year; exchange rate regime contemporary in some regressions.
  - Trend-based fiscal measure: GDP_DEF_LT (deficit relative to trend GDP).

### III. Results — speed of recovery: stylized facts and key estimates
- Baseline finding:
  - Recovery year growth typically slower than other expansion years.
  - Table 1 LTROUGH coefficients:
    - ALL: LTROUGH = -0.441** (0.19)
    - IND: LTROUGH = -1.042*** (0.27)
    - DEV: LTROUGH = -0.362* (0.21)
    - DEV NO SSA: LTROUGH = -0.747*** (0.26)
    - SSA: LTROUGH = 0.286 (0.36) — positive but not statistically significant.
- Robustness excluding very small countries (population < 1 million) — Table 2:
  - ALL: LTROUGH = -0.341 (0.21)
  - IND: LTROUGH = -0.857*** (0.26)
  - DEV NO SSA: LTROUGH = -0.710** (0.31)
- Country size:
  - No consistent evidence that larger economic size (LSIZE) speeds recovery; LTROUGH*LSIZE not significant overall (Table 3).
- Macroeconomic policy asymmetric impacts in recovery years:
  - Monetary policy (Table 4):
    - MONEYGR positively correlated with GDP growth in expansions for developing countries: a ten percentage point increase in MONEYGR ≈ a 0.5 percentage point increase in GDP growth (text point estimate interpretation).
    - INDUSTRIAL: LTROUGH*MONEYGR = 0.128** (0.061) (Table 4, column 2).
    - MONEYGR coefficients: MONEYGR = 0.0550*** (ALL) (0.016); MONEYGR = 0.0595*** (DEV) (0.019).
  - Fiscal policy (Tables 5 and 6):
    - LTROUGH*GDP_DEF positive and significant in IND and DEV NO SSA:
      - LTROUGH*GDP_DEF = 0.117** (IND, Table 5 column 2; (0.055)) — interpreted as: an increase in the deficit by 1 percentage point of GDP raises the post-recession rebound by 0.12 percentage points.
    - Robust to GDP_DEF_LT: LTROUGH*GDP_DEF_LT = 0.118* (IND, Table 6 column 2; (0.058)).
  - Foreign aid (Table 7):
    - Aid growth (AID_GR) insignificant in typical expansion years but asymmetric positive effect in SSA:
      - LTROUGH*AID_GR = 0.04896** (SSA, Table 7 column 5; standard error (2.11) as reported).
  - Exchange rate regime (Tables 8–11):
    - Floating regime facilitates rebound in some samples:
      - LTROUGH*FLOATING = 1.204* (IND, Table 8 column 2; (0.60)).
    - Three-way regime classification (Table 9):
      - LTROUGH*INTERM = -1.602*** (ALL, Table 9 column 1; (0.55))
      - LTROUGH*FIX = -0.785* (ALL, Table 9 column 1; (0.42))
    - Intermediate and fixed regimes hinder recovery relative to floating; robust controlling for currency crises.
  - Real exchange rate changes (Tables 12 and 13):
    - In normal expansion years: DRER = 1.624*** (ALL, Table 12 column 1; (0.53)).
    - Asymmetric (recovery) effect: LTROUGH*DRER = -2.930** (ALL, Table 12 column 1; (1.38)), with larger negative impacts for developing countries and SSA.
- Structural policies and characteristics:
  - Labor market rigidities (Tables 14–15):
    - ROE interactions generally insignificant (Table 14).
    - EROE shows some evidence of damping recovery:
      - LTROUGH*EROE = -0.00845* (ALL, Table 15 column 1; (0.0043)).
  - Trade openness (Tables 16–20):
    - OPEN reduces recovery speed:
      - LTROUGH*OPEN = -0.0155*** (ALL, Table 16 column 1; (0.0041)) — interpreted: each additional 10 percent of trade to GDP reduces rebound growth by 0.17 percentage points (text interpretation).
    - Results hold controlling for economic size (Table 17) and depth of recession (Table 19).
    - Interaction LTROUGH*OPEN*LSIZE = 0.00329 (ALL, Table 17 column 1; (0.0021)); point estimates imply positive effect of openness beyond LSIZE = 25.4 (text notes only 9 countries exceed this LSIZE).
    - Fiscal policy less effective in more open economies:
      - LTROUGH*GDP_DEF_LT*OPEN = -0.000724** (ALL, Table 20 column 1; (0.00035)).
  - Capital account openness (Tables 21–22):
    - KAOPEN shows limited impact; marginal evidence that industrial countries with more open capital accounts experience slightly slower growth.
    - Interaction of KAOPEN with OPEN yields limited and marginally significant effects.
- Real external shocks (Table 18):
  - RSHOCK (trading partners' growth) has a large and significant direct impact on country growth for ALL, IND, DEV.
  - Controlling for RSHOCK, strong partner growth has an equally large significant impact on the recovery rebound for developing but not industrial countries.
- Depth of recession and robustness (Table 23):
  - LDEPTH negatively related to growth in non-recovery years:
    - IND: coefficient -0.07283*** (Table 23 column 2; (0.00840))
    - DEV: coefficient -0.03166*** (Table 23 column 3; (0.00903))
  - Asymmetric effects: in industrial countries a deeper recession associated with lower recovery growth; in SSA a deeper recession associated with slightly stronger recovery (LTROUGH*LDEPTH results).
  - Policy asymmetries largely robust when using first two post-trough years; some asymmetric effects lose significance when including second year.

### IV. The aftermath of banking crises
- General patterns (Table 24):
  - Banking crises reduce growth, particularly in industrial countries:
    - BANK_CRISIS = -1.808*** for IND (Table 24 column 2; (0.58))
  - Recoveries following banking crises are particularly sluggish:
    - LTROUGH*BANK_CRISIS = -1.261*** for DEV NO SSA (Table 24 column 4; (0.40)) — implies growth is 1¼ percentage points lower in post-trough recovery from a banking crisis relative to other recessions.
    - Regional variation: effects differ by region and country size; some effects significant only for large SSA countries.
- Policies that matter for banking-crisis recoveries:
  - Fiscal policy (Table 25):
    - Fiscal stimulus especially effective for industrial countries recovering from banking crises:
      - LTROUGH*BANK_CRISIS*GDP_DEF = 0.302*** (IND, Table 25 column 2; (0.063)) — each percentage point of additional fiscal deficit to GDP boosts post-trough growth by 0.3 percentage points above its effect in other recoveries.
  - Foreign aid (Table 26):
    - Aid helps recovery from banking crises for developing countries, particularly SSA:
      - LTROUGH*BANK_CRISIS*AID_GR = 3.651* (DEV, Table 26 column 1; (2.18))
      - LTROUGH*BANK_CRISIS*AID_GR = 10.73** (SSA, Table 26 column 3; (4.76))
  - Trade and capital openness, and exchange rate regime (Tables 27–28):
    - For industrial countries, trade and capital account openness individually and jointly help recover from banking crises (Table 27; some interactions significant).
    - Floating regimes are less helpful for industrial countries recovering from banking crises relative to their benefit in other recoveries, but floats are particularly useful for developing countries recovering from banking crises:
      - LTROUGH*BANK_CRISIS*FLOATING = 1.804** (ALL, Table 28 column 1; (0.76)).

### V. Conclusions and policy implications
- Stylized facts summary:
  - Recovery growth rates vary significantly across countries and reflect macroeconomic and structural policy differences.
  - Fiscal and monetary stimulus and foreign aid can be more effective in boosting a rebound from recession than their effects on growth in other expansion stages.
  - Real appreciation, fixed and intermediate exchange rate regimes, and trade openness are associated with slower recoveries.
- Notable policy findings:
  - Fiscal policy is less effective in lifting recovery growth in more open economies; suggests need for coordination of fiscal stimulus across countries to offset import leakages and spillovers.
  - Monetary and fiscal policies tend to have stronger effects in the immediate recovery year than in later expansion years (asymmetric effectiveness).
- Banking-crisis-specific conclusions:
  - Banking-crisis-related recoveries are more sluggish than other recoveries.
  - Fiscal policy, foreign aid, trade and capital openness, and exchange rate regime choices have disparate impacts on recovery from banking crises compared to other recessions.
- Suggested avenues for further research:
  - Relationship between openness to trade and capital flows and recovery dynamics.
  - Asymmetric effectiveness of macroeconomic policies and the exchange rate regime across business cycle stages.

### Appendix: Data sources and variable definitions (selected)
- Data period: annual observations 1960–2005.
- Sample size: up to 197 countries; up to 5482 observations.
- Key variable definitions:
  - LTROUGH: Dummy variable taking value 1 in the first year of a recovery. Source: authors’ calculations based on World Bank's World Development Indicators (WDI).
  - GROWTH: Growth rate of real GDP per capita. Source: WDI.
  - LSIZE: Log of average total GDP in constant USD. Source: WDI.
  - MONEYGR: Percent change in broad money. Source: EIU.
  - GDP_DEF: Government Budget Deficit to GDP. Source: WDI and national sources.
  - GDP_DEF_LT: Government budget deficit to trend GDP. Source: author calculations based on WDI and national sources.
  - ROE: Rigidity of employment index (0=less rigid to 100=more rigid). Source: WDI.
  - RULE of LAW: Index of rule of law. Source: Kaufman et al. (2008).
  - EROE: ROE * RULE OF LAW.
  - OPEN: Trade openness measured as (X+M)/GDP averaged over 1970-2000. Source: WDI.
  - RSHOCK: GDP growth of trading partners weighted by export shares (Jaimovich and Panizza (2007) measure divided by total exports over GDP).
  - KAOPEN: Index of capital account openness. Source: Chinn and Ito (2008).
  - AID_GR: Growth rate of net aid flows. Source: authors' calculation based on OECD DAC data.
  - FLOATING, FIX, INTERM: Exchange rate regime dummies based on Levy Yeyati and Sturzenegger (2005).
  - CURRENCY CRISIS: Dummy = 1 if country-year experienced a currency crisis.
  - BANKING CRISIS: Dummy = 1 if country-year experienced a banking crisis. Source: Caprio and Klingebiel (2003) and Laeven and Valencia (2008).
  - DRER: Percentage change in the real exchange rate (positive = appreciation). Source: authors’ calculation based on PWT data.
  - LDEPTH: Lagged recession depth = lag of percentage deviation of actual output from log-linear trend output.

*Source: _wp09183 - References (PDF content supplied).*

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

### _wp09183 - References..............................................................................................................

### I. Introduction
- Objective: present stylized facts on how countries recover from recessions; focus on rebound speed and persistence.
- Key literature points:
  - Negative shocks, particularly financial crises, can generate a sizeable permanent loss in the level of output compared with the pre-crisis trend (Cerra and Saxena, 2008).
  - Cerra and Saxena (2005b) show permanent shocks account for most variation in emerging market output fluctuations.
  - Recessions are often abrupt and violent but short-lived; expansions are smoother and longer-lived (Mitchell, 1927; Hamilton, 1989).
  - This paper investigates asymmetries in policy effectiveness and country characteristics during recoveries versus later expansion years.

### II. Methodology and data
- Empirical model (panel, country fixed effects):
  - General form: GROWTHTROUGH* + X terms with interactions (see Equation (1) in source).
  - Recovery defined as year(s) of positive growth immediately following a trough (the final year in a sequence of years with negative annual growth).
  - Regressions restricted to years with positive GDP growth.
  - γ measures asymmetric impact of policy/structural variable X on recovery speed; δ measures impact in "normal" expansion years; δ+γ measures total effect in recovery years.
- Identification and endogeneity strategy:
  - Use country fixed effects to control for time-invariant factors.
  - Address reverse causation/endogeneity for macro policy by:
    - Using lagged policy variables (ordering identification from VAR literature).
    - Focusing on asymmetric impact (recovery year relative to other expansion years).
- Data coverage:
  - Annual observations spanning 1960 to 2005.
  - Up to 197 countries, yielding an unbalanced panel of up to 5482 observations.
  - Favorite subsample excludes countries with population less than one million.
  - Favorite subsample counts: total of 550 recovery episodes; 63 in advanced economies and 487 in developing countries (229 episodes in Sub-Saharan Africa and 258 episodes in developing countries outside SSA).
- Variable construction notes:
  - LSIZE = log of total GDP (constant USD) averaged over 1960-2004 (or 1970-2000 in some tables).
  - Policy variables often lagged by one year; exchange rate regime contemporary in some regressions.
  - Trend-based fiscal measure: GDP_DEF_LT (deficit relative to trend GDP).

### III. Results — speed of recovery: stylized facts and key estimates
- Baseline finding on recovery speed:
  - Recovery year growth typically slower than other expansion years.
  - Table 1 estimates (LTROUGH coefficients):
    - ALL: LTROUGH = -0.441** (standard error (0.19))
    - IND (industrial): LTROUGH = -1.042*** (0.27)
    - DEV (developing): LTROUGH = -0.362* (0.21)
    - DEV NO SSA (non-SSA developing): LTROUGH = -0.747*** (0.26)
    - SSA: LTROUGH = 0.286 (0.36) — positive but not statistically significant.
- Robustness to excluding very small countries (population < 1 million) — Table 2:
  - ALL: LTROUGH = -0.341 (0.21)
  - IND: LTROUGH = -0.857*** (0.26)
  - DEV NO SSA: LTROUGH = -0.710** (0.31)
- Country size:
  - Table 3 finds no consistent evidence that larger economic size (LSIZE) speeds recovery; interaction LTROUGH*LSIZE not significant overall.
- Macroeconomic policy effects (asymmetric impacts in recovery years):
  - Monetary policy (Table 4):
    - MONEYGR (real growth rate of broad money) is positively correlated with GDP growth in expansions for developing countries: a ten percentage point increase in MONEYGR ≈ a 0.5 percentage point increase in GDP growth (point estimates described in text).
    - Industrial countries show a strong asymmetric effect: LTROUGH*MONEYGR = 0.128** (Table 4, column 2; standard error (0.061)) while MONEYGR = 0.0353 (insignificant in IND column).
    - Note: MONEYGR coefficients in tables: MONEYGR = 0.0550*** (ALL) (0.016); MONEYGR = 0.0595*** (DEV) (0.019).
  - Fiscal policy (Tables 5 and 6):
    - LTROUGH*GDP_DEF (lagged deficit/GDP) positive and significant in IND and DEV NO SSA: e.g., LTROUGH*GDP_DEF = 0.117** (IND, Table 5 column 2; (0.055)); effect interpreted as: an increase in the deficit by 1 percentage point of GDP raises the post-recession rebound by 0.12 percentage points (columns 2 and 4, text).
    - Robust to alternative fiscal measure GDP_DEF_LT (deficit relative to trend GDP): LTROUGH*GDP_DEF_LT = 0.118* (IND, Table 6 column 2; (0.058)).
  - Foreign aid (Table 7):
    - Aid growth (AID_GR) has an insignificant effect in typical expansion years but an important asymmetric positive effect in SSA: LTROUGH*AID_GR = 0.04896** (SSA, Table 7 column 5; standard error (2.11) reported in table).
  - Exchange rate regime (Tables 8–11):
    - Floating regime facilitates rebound: LTROUGH*FLOATING = 1.204* (IND, Table 8 column 2; (0.60)); floaters experience recovery growth rates more than a percentage point higher than fixed/intermediate regimes in some samples (text).
    - When comparing regimes (Table 9, 3-way classification with floating excluded):
      - LTROUGH*INTERM = -1.602*** (ALL, Table 9 column 1; (0.55))
      - LTROUGH*FIX = -0.785* (ALL, Table 9 column 1; (0.42))
    - Intermediate and fixed regimes hinder recovery relative to floating; results robust controlling for currency crises (Tables 10 and 11).
  - Real exchange rate changes (Tables 12 and 13):
    - In normal expansion years DRER (percentage change in real exchange rate) correlated with higher growth: DRER = 1.624*** (ALL, Table 12 column 1; (0.53)).
    - Asymmetric effect in recovery years: LTROUGH*DRER = -2.930** (ALL, Table 12 column 1; (1.38)), and particularly large negative impact for developing countries and SSA (Table 12 and Table 13 robustness controlling for currency crises).
- Structural policies and characteristics:
  - Labor market rigidities (Tables 14–15):
    - ROE (World Bank employment rigidity index) interactions generally insignificant (Table 14).
    - EROE (ROE * rule of law) shows some evidence that effective labor market rigidities dampen recovery: LTROUGH*EROE = -0.00845* (ALL, Table 15 column 1; (0.0043)), but results are not very strong.
  - Trade openness (Tables 16–20):
    - Trade openness (OPEN = (X+M)/GDP averaged 1970-2000) reduces recovery speed:
      - LTROUGH*OPEN = -0.0155*** (ALL, Table 16 column 1; (0.0041)) — interpreted in text as: each additional 10 percent of trade to GDP reduces rebound growth by 0.17 percentage points.
    - Results hold controlling for economic size (Table 17) and for depth of recession (Table 19).
    - Interaction with economic size: LTROUGH*OPEN*LSIZE = 0.00329 (ALL, Table 17 column 1; (0.0021)); point estimates imply positive effect of openness beyond LSIZE = 25.4 (text notes only 9 countries exceed this LSIZE).
    - Hypothesis tested: fiscal policy less effective in more open economies (Table 20):
      - LTROUGH*GDP_DEF_LT*OPEN = -0.000724** (ALL, Table 20 column 1; (0.00035)), indicating fiscal policy multipliers smaller with greater openness. Controlling for OPEN strengthens main fiscal effect but does not fully explain sluggish recovery for open economies.
  - Capital account openness (Tables 21–22):
    - KAOPEN index shows limited impact on recovery speed; marginal evidence that industrial countries with more open capital accounts experience slightly slower growth.
    - Interaction of capital account openness with trade openness yields limited and marginally significant effects.
- Real external shocks (Table 18):
  - RSHOCK (growth of trading partners weighted by export shares) has a large and significant direct impact on country growth for ALL, IND, DEV (RSHOCK coefficients significant in columns reported).
  - Controlling for RSHOCK, strong partner growth has an equally large significant impact on the recovery rebound for developing but not industrial countries.
- Depth of recession and robustness (Table 23):
  - LDEPTH (lagged percentage deviation from trend) negatively related to growth in non-recovery years:
    - For industrial countries: coefficient -0.07283*** (Table 23 column 2; (0.00840))
    - For developing countries: coefficient -0.03166*** (Table 23 column 3; (0.00903))
  - Asymmetric effects: in industrial countries a deeper recession associated with lower recovery growth; in SSA a deeper recession associated with slightly stronger recovery (Table 23, LTROUGH*LDEPTH results).
  - Results on policy asymmetries robust when using first two post-trough years, though some asymmetric effects lose significance when including the second year (text summary).

### IV. The aftermath of banking crises
- General patterns (Table 24):
  - Banking crises reduce growth, particularly in industrial countries (BANK_CRISIS = -1.808*** for IND, Table 24 column 2; (0.58)).
  - Recoveries following banking crises are particularly sluggish:
    - LTROUGH*BANK_CRISIS = -1.261*** for DEV NO SSA (Table 24 column 4; (0.40)); for non-SSA developing countries, growth is 1¼ percentage points lower in post-trough recovery from a banking crisis relative to recovery from other recessions (text).
    - Banking crisis interaction effects differ by region; not all effects significant for average SSA country but significant for large SSA countries (text).
- Policies that matter for banking-crisis recoveries:
  - Fiscal policy (Table 25):
    - Fiscal stimulus particularly effective for industrial countries recovering from banking crises:
      - LTROUGH*BANK_CRISIS*GDP_DEF = 0.302*** (IND, Table 25 column 2; (0.063)) with interpretation: each percentage point of additional fiscal deficit to GDP boosts post-trough growth by 0.3 percentage points above its effect in other recoveries (text).
  - Foreign aid (Table 26):
    - Aid helps recovery from banking crisis-related recessions for developing countries, particularly SSA:
      - LTROUGH*BANK_CRISIS*AID_GR = 3.651* (DEV, Table 26 column 1; (2.18)) and especially large for SSA: LTROUGH*BANK_CRISIS*AID_GR = 10.73** (SSA, Table 26 column 3; (4.76)).
  - Trade and capital openness, and exchange rate regime (Tables 27–28):
    - For industrial countries, trade and capital account openness individually and jointly help recover from banking crises (Table 27; some interaction coefficients significant).
    - Floating regimes are less helpful for industrial countries recovering from banking crises relative to their benefit in other recoveries, but floats are particularly useful for developing countries recovering from banking crises (Table 28):
      - LTROUGH*BANK_CRISIS*FLOATING = 1.804** (ALL, Table 28 column 1; (0.76)); region-specific variation noted in tables.

### V. Conclusions and policy implications
- Summary of stylized facts:
  - Recovery growth rates vary significantly across countries and reflect macroeconomic and structural policy differences.
  - Fiscal and monetary stimulus and foreign aid can be more effective in boosting a rebound from recession than their effects on growth in other expansion stages.
  - Real appreciation, fixed and intermediate exchange rate regimes, and trade openness are associated with slower recoveries.
- Notable policy findings:
  - Fiscal policy is less effective in lifting recovery growth in more open economies; suggests need for coordination of fiscal stimulus across countries to offset import leakages and spillovers.
  - Asymmetric policy effectiveness: monetary and fiscal policies tend to have stronger effects in the immediate recovery year than in later expansion years.
- Banking-crisis-specific conclusions:
  - Banking-crisis-related recoveries are more sluggish than other recoveries.
  - Fiscal policy, foreign aid, trade and capital openness, and exchange rate regime choices have disparate impacts on recovery from banking crises compared to other recessions.
- Suggested avenues for further research:
  - Relationship between openness to trade and capital flows and recovery dynamics.
  - Asymmetric effectiveness of macroeconomic policies and the exchange rate regime across business cycle stages.

### Appendix: Data sources and variable definitions (selected)
- Data period: annual observations 1960–2005.
- Sample size: up to 197 countries; up to 5482 observations.
- Key variable definitions (as in Appendix):
  - LTROUGH: Dummy variable taking value 1 in the first year of a recovery. Source: authors’ calculations based on World Bank's World Development Indicators (WDI).
  - GROWTH: Growth rate of real GDP per capita. Source: WDI.
  - LSIZE: Log of average total GDP in constant USD. Source: WDI.
  - MONEYGR: Percent change in broad money. Source: EIU.
  - GDP_DEF: Government Budget Deficit to GDP. Source: WDI and national sources.
  - GDP_DEF_LT: Government budget deficit to trend GDP. Source: author calculations based on WDI and national sources.
  - ROE: Rigidity of employment index (0=less rigid to 100=more rigid). Source: WDI.
  - RULE of LAW: Index of rule of law. Source: Kaufman et al. (2008).
  - EROE: ROE * RULE OF LAW.
  - OPEN: Trade openness measured as (X+M)/GDP averaged over 1970-2000. Source: WDI.
  - RSHOCK: GDP growth of trading partners weighted by export shares (Jaimovich and Panizza (2007) measure divided by total exports over GDP).
  - KAOPEN: Index of capital account openness. Source: Chinn and Ito (2008).
  - AID_GR: Growth rate of net aid flows. Source: authors' calculation based on OECD DAC data.
  - FLOATING, FIX, INTERM: Exchange rate regime dummies based on Levy Yeyati and Sturzenegger (2005).
  - CURRENCY CRISIS: Dummy = 1 if country-year experienced a currency crisis.
  - BANKING CRISIS: Dummy = 1 if country-year experienced a banking crisis. Source: Caprio and Klingebiel (2003) and Laeven and Valencia (2008).
  - DRER: Percentage change in the real exchange rate (positive = appreciation). Source: authors’ calculation based on PWT data.
  - LDEPTH: Lagged recession depth = lag of percentage deviation of actual output from log-linear trend output.

*Source: _wp09183 - References (PDF content supplied).*

### REFERENCES

### _wp09183 - REFERENCES

### Output and Growth Dynamics
- Becker, Torbjorn, and Paolo Mauro, 2006, “Output Drops and the Shocks that Matter,” IMF Working Paper 06/117 (Washington: International Monetary Fund).
- Cerra, Valerie, and Sweta Chaman Saxena, 2008, “Growth Dynamics: The Myth of Economic Recovery,” American Economic Review, Vol. 98(1), pp. 439-57.
- __________ 2005a, “Growth Dynamics: The Myth of Economic Recovery,” IMF Working Paper 05/147 (Washington, International Monetary Fund).
- __________ (2005b). “Did Output Recover from the Asian Crisis?” IMF Staff Papers, Vol. 54(1), pp. 1-23.
- Hausmann, Ricardo, Francisco Rodriguez, and Rodrigo Wagner, 2006, “Growth Collapses” Harvard CID Working Paper No. 136
- Clemens, Michael, Steven Radelet, and Rikhil Bhavnani, 2004, “Counting Chickens When They Hatch: The Short-term Effect of Aid on Growth,” Working Papers 44, Center for Global Development.

### Shocks, Cycles, and Monetary Policy
- Blanchard, Olivier, and Justin Wolfers, 2000, “The Role of Shocks and Institutions in the Rise of European Unemployment: The Aggregate Evidence,” Economic Journal, Royal Economic Society, Vol. 110(462), pp. C1–33.
- Hamilton, James D., 1989, “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle,” Econometrica, Vol. 57, pp. 357–84.
- Mitchell, Wesley C., 1927, Business Cycles: The Problem and its Setting (New York: NBER).
- Romer, Christina, and David Romer, 1989, “Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz,” NBER Macroeconomics Annual, Vol. 4, pp. 121–70.
- Christiano, Lawrence, Martin Eichenbaum, and Charles Evans, 1999, “Monetary Policy Shocks: What Have We Learned, and To What End,” in Handbook of Macroeconomics, Vol. 1A, edited by John B. Taylor and Michael Woodford. (Amsterdam: Elsevier Science).
- Kim, Chang-Jin, James Morley, and Jeremy Piger, 2005, “Nonlinearity And The Permanent Effects of Recessions,” Journal of Applied Econometrics, Vol. 20, pp. 291–309
- Lo, Ming Chien, and Jeremy Piger, 2005, “Is the Response of Output to Monetary Policy Asymmetric? Evidence from a Regime-Switching Coefficients Model,” Journal of Money, Credit, and Banking, Vol. 37 (5), pp. 865–86.
- Jaimovich, Dany, and Ugo Panizza, 2007, “Procyclilcality or Reverse Causality?” Working Papers 599, Research Department (Washington: Inter-American Development Bank).

### Financial Crises, Banking, and Recovery
- Calvo, Guillermo, Alejandro Izquierdo, and Ernesto Talvi, 2006, “Phoenix Miracles in Emerging Markets: Recovering Without Credit from Systemic Financial Crises,” BIS Working Papers No 221.
- Laeven, Luc A., and Fabian Valencia, 2008, “Systemic Banking Crises: A New Database,” IMF Working Paper 08/224 (Washington, International Monetary Fund).
- Caprio, Gerard, and Daniela Klingebiel, 2003, “Episodes of Systemic and Borderline Financial Crises.” Available via the internet: http://go.worldbank.org/5DYGICS7B0.
- Kaminsky, Graciela, and Carmen Reinhart, 1999, “The Twin Crises: The Causes of Banking and Balance-of-Payments Problems,” American Economic Review, Vol. 89(3), pp. 473–500.

### Exchange Rates and Regimes
- Fischer, Stanley, 2001, “Exchange Rate Regimes: Is the Bipolar View Correct?,” Journal of Economic Perspectives, Vol. 15, No. 2 (Spring), pp. 3-24.
- Levy, Yeyati, Eduardo, and Federico Sturzenegger, 2005, “Classifying Exchange Rate Regimes: Deeds vs. Words,” European Economic Review, Vol. 49(6), pp. 1603–35.
- __________ 2003, “To Float or to Fix: Evidence on the Impact of Exchange Rate Regimes on Growth,” American Economic Review, Vol. 93(4), pp. 1173–93.
- International Monetary Fund, 2007, “Exchange Rates and Adjustment of External Imbalances” in World Economic Outlook, April (Washington).

### Aid, Capital Flows, and External Financing
- Bulíř, Aleš, and A. Javier Hamann, 2003, “Aid Volatility: An Empirical Assessment,” IMF Staff Papers, Vol. 50, No. 1, pp. 64-89.
- Easterly, William R., Ross Levine and David Roodman, 2004, “New Data, New Doubts: A Comment on Burnside and Dollar's Aid, Policies, and Growth” American Economic Review, Vol. 94(3), pp. 774–80.
- Rajan, Raghuram G., and Arvind Subramanian, 2008, “Aid and Growth: What Does the Cross-Country Evidence Really Show?,” Review of Economics and Statistics, MIT Press, Vol. 90(4), pp. 643–65.
- UNCTAD, 2008, Trade and Development Report Commodity Prices, Capital Flows and the Financing of Investment (Geneva).

### Governance, Openness, and Data Sources
- Chinn, Menzie, and Hiro Ito, 2008, “A New Measure of Financial Openness” Journal of Comparative Policy Analysis, Vol. 10(3), pp. 309–22.
- Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi, 2008, “Governance Matters VII: Governance Indicators for 1996-2007,” World Bank Policy Research Working Paper No. 4654 (Washington: The World Bank).
- Nickell, Stephen, and Luca Nunziata, 2001, “Labour Market Institutions Database” (unpublished). Available via the internet: http://www.econ.upf.edu/~reiter/webbcui/combineddata/LMIDB.pdf

*Source: _wp09183 - REFERENCES*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09183.pdf_