## _wp0435 - 1.  Exchange Rate Regimes and Capital Account Developments in Selected

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### Introduction and hypothesis
- Examines hypothesis that financial market liberalization can create a basis for more stable exchange rates via “endogenous liquidity,” where deviations of exchange rates from equilibrium levels (defined here by the Hodrick–Prescott filter) attract stabilizing flows of liquidity.
- Context: gradual switch from pegs to floats in Central European countries and implications for maintaining pegs in liquid markets versus market-determined exchange rates.
- Cited theoretical and empirical predecessors: Sarno (2003); Faruqee and Redding (1999); Evans and Lyons (2002); Bacchetta and van Wincoop (2003); Derviz (2003).

### Model and theoretical framework
- Core mechanism:
  - Large deviations from longer-term pricing levels attract marginal liquidity, speeding return toward trend.
  - Two agent types in three-period model (Faruqee–Redding / Evans–Lyons framework):
    - Noninformational (“noise”) traders who push exchange rates away from the liquidation price.
    - Informational traders (market makers) who provide liquidity for expected profit, bringing rates back toward market-clearing level.
  - Price discovery timeline: T1 and T2 reveal successive estimates 1EP3 and 2EP3 of final liquidation price P3, with posterior sample variances 2 1 σ and 2 2 σ such that 2 2 2 1 σσ≥.
- Endogenous-liquidity implications:
  - Deeper order book (more market makers) → faster reversion to P3; speed of adjustment ω increases with absolute value of transitory demand η (0>∂∂ηω).
- Empirical error-correction representation:
  - Decomposition: e = f + n, with f the Hodrick–Prescott trend and n transitory demand.
  - Empirical equation (4) structure: Δx_it = α n_{t-1} + β n_{t-1}^3 + Σ δ_i + ε_t, where α captures proportional mean reversion, β captures additional mean reversion from endogenous liquidity, and iδ tests the random walk (null iδ = 0).

### Data, stylized facts, and measures of liberalization/liquidity
- Sample and series treatment:
  - End-period daily, weekly, and monthly exchange rate data from May 1998 until December 2002 for USD and EUR against CZK, HUF, PZL, and SLK; all series logged.
  - Hodrick–Prescott filter parameter λ used: 6,250,000 for daily data (common-rule values cited: λ = 14,400 monthly, 260,100 weekly, 6,250,000 daily).
  - All level series nonstationary I(1); differenced series stationary I(0).
- Distributional properties and durations:
  - Excess kurtosis present in daily and most weekly and monthly returns; many series fail normality at 1 percent.
  - Mean duration of a departure from trend about 40 trading days; most currencies had 20–30 periods when they remained above or below trend for at least 5 trading days.
- Country-specific liquidity indicators (as reported):
  - Czech koruna:
    - Most heavily traded market.
    - Around 40 new private koruna-denominated eurobond issues per year for the past six years.
    - Outstanding eurobonds > US$3 billion.
    - 2002 average real one-month interbank rate 1.6 percent.
    - Turnover peaked at US$5 billion per day in late 1998/early 1999 and declined thereafter.
    - CNB monthly average interventions during 2000-2002 < US$100 million (≈0.2 percent of koruna-market turnover).
  - Hungary:
    - Forint-denominated eurobonds first issued in 2001; outstanding volume about US$100 million.
    - 2002 average real one-month interbank rate 3.5 percent.
    - Closely regulated until June 2001.
  - Slovak Republic:
    - No koruna-denominated eurobonds issued yet.
    - 2002 average real one-month interbank rate 4.3 percent.
  - Poland:
    - No summary eurobond data available.
    - 2002 average real one-month interbank rate peaked at almost 7 percent.

### Empirical results: speeds of adjustment, α and β estimates
- General findings:
  - Results broadly supportive of endogenous liquidity hypothesis; effects comparable to random walk components in exchange rate determination.
  - Speed of adjustment typically faster vis-à-vis the euro than the dollar.
  - Liquid, liberalized markets (notably Czech Republic) show faster adjustment; smaller or less liberalized markets (Slovak Republic, Hungary in late 1990s) show slower adjustment.
- Daily-data estimates without lagged dependent variables (Table 3):
  - α point estimates imply return-to-trend in absence of nonlinear process between 7 and 60 days (up to 12 weeks).
  - Linear adjustment (n) effect about ten times stronger than nonlinear effect (n^3) when evaluated at absolute-value mean.
  - Many α and β estimates have expected negative signs; a few instances of α>0 (four in Poland, one in Slovak Republic) but nonlinear β often overcompensates.
- Daily-data estimates with lagged dependent variables (24 lags, Table 4):
  - Inclusion of lagged terms increases magnitudes of α and β and improves joint significance and explained variance.
  - Seven out of twelve estimated β parameters for EUR exchange rates statistically significant and negative.
  - Recursive estimates indicate declining absolute-value βs with increasing absolute-value αs in maturing markets (e.g., Czech koruna), interpreted as markets requiring smaller shocks to trigger nonlinear adjustment as proportional adjustment strengthens.
- Weekly-data estimates (Tables 5–6):
  - Weekly results broadly similar to daily results; adjusted R2 higher (explaining between 5 and 10 percent of dependent-variable variance).
  - Weekly α estimates imply return-to-trend between 2 and 15 weeks absent nonlinear process.
  - Median comparisons to Faruqee–Redding (G-7):
    - Median α ≈ -0.15 (vs. G-7 median -0.18).
    - Median β ≈ -85 (vs. G-7 median -15), implying larger nonlinear triggers required in transition economies.
- Forecasting and random-walk comparisons (Annex II):
  - Random-walk model performs quite similarly to Faruqee–Redding model without lagged variables; Faruqee–Redding model with lagged variables often yields lower out-of-sample RMSE.
  - Reported RMSEs (RMSE x 100) for CZK/EUR: 1 week 0.217, 2 weeks 0.167, 1 month 0.172 across models in table.

### Central bank interventions and volatility
- Intervention behavior and quantitative scale:
  - Central banks predominantly “leaned against the wind” to slow real appreciation rather than smoothing short-term nominal volatility.
  - Quantitative interventions were small and infrequent relative to market turnover; example: CNB monthly average < US$100 million during 2000–2002 (~0.2 percent of turnover).
- Regression evidence (January 1999–December 2002):
  - Controlling for contagion and trend, big-intervention months in the Czech Republic were associated with bigger volatility.
  - Similar exercises for Hungary and Slovak Republic yielded statistically insignificant results.
- Conclusion: limited role for interventions in curbing exchange-rate volatility in sample; interventions may have fueled volatility in some instances.

### Policy implications and conclusions
- Main policy-relevant conclusions:
  - Early liberalization of foreign exchange markets and financial-account transactions may lead to greater market liquidity and faster exchange-rate adjustment, increasing viability of floating regimes and making pegs harder to sustain.
  - Early liberalization is necessary but not sufficient; market size and depth matter (e.g., Slovak Republic floated early but market remained thin).
  - Central banks need not be overly concerned with short-run nominal exchange-rate volatility due to self-correcting endogenous-liquidity tendencies; Visegrád Four central banks typically focused on leaning against real appreciation.
  - Endogenous liquidity effects empirically comparable to autoregressive/random-walk components; they speed self-correction but do not guarantee lower nominal volatility or closer alignment to fundamental levels.
- Country-specific takeaways:
  - Strongest support for endogenous liquidity in Czech koruna market and, more recently, in post-2000 Hungarian forint market.
  - Polish zloty appears as an outlier: similar dollar and euro volatility, occasional α>0 (proportional mean reversion positive), and large βs in daily regressions—implying adjustment occurs only after large departures from trend.
- Suggested extensions:
  - Consider impact of central bank interventions on speed of exchange-rate adjustment.
  - Need for longer consistent time series to determine appropriate testing frequency.

*Source: _wp0435 - 1.  Exchange Rate Regimes and Capital Account Developments in Selected (IMF working paper content, May 1998–December 2002 sample period).*

### 1.  Exchange Rate Regimes and Capital Account Developments in Selected

### _wp0435 - 1.  Exchange Rate Regimes and Capital Account Developments in Selected

### Major Sections (1991–2002 and empirical specifications)
- 1. Exchange Rate Regimes and Capital Account Developments in Selected Countries, 1991–2002
- 2. Dollar and Euro Exchange Rate Daily Returns: Sample Moments and Kurtosis tests, May 1998–December 2002
- 3. Daily Data Without Lagged Dependent Variables
- 4. Daily Data With Lagged Dependent Variables
- 5. Weekly Data Without Lagged Dependent Variables
- 6. Weekly Data With Lagged Dependent Variables

### Figures and Empirical Illustrations
- Figure 1. Time Line of Exchange Rate Determination
- Figure 2. Average Daily Foreign Exchange Turnover and Monthly Foreign Exchange Interventions, 1997-2002
- Figure 3. The Czech Republic, Hungary, Poland, and the Slovak Republic: Daily U.S. Dollar and Euro Exchange Rates and the Hodrick–Prescott Filter, May 1998–December 2002
- Figure 4. The Czech Republic, Hungary, Poland, and the Slovak Republic: Daily U.S. Dollar and Euro Exchange Rate Returns and Deviations from the Hodrick–Prescott Filter, May 1998–December 2002
- Figure 5. Recursive Estimates of α and β and Their Two Standard Errors

### Annexes and Models
- Annex I. The Farquee-Redding Model of Endogenous Liquidity
- Annex II. The Meese-Rogoff “ Race”

*Source: _wp0435 - 1.  Exchange Rate Regimes and Capital Account Developments in Selected*

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

### _wp0435 - References

### Introduction and hypothesis
- Examines the hypothesis that financial market liberalization can create a basis for more stable exchange rates via “endogenous liquidity,” where deviations of exchange rates from equilibrium levels (defined here by the Hodrick–Prescott filter) attract stabilizing flows of liquidity.
- Context: gradual switch from pegs to floats in Central European countries and implications for maintaining pegs in liquid markets versus market-determined exchange rates.
- Theoretical and empirical predecessors cited: Sarno (2003); Faruqee and Redding (1999); Evans and Lyons (2002); Bacchetta and van Wincoop (2003); Derviz (2003).

### Model and theoretical framework
- Core mechanism: large deviations from longer-term pricing levels attract marginal liquidity, speeding return toward trend.
- Two agent types in the three-period model (Faruqee–Redding / Evans–Lyons framework):
  - Noninformational (“noise”) traders who push exchange rates away from the liquidation price.
  - Informational traders (market makers) who provide liquidity for expected profit, bringing rates back toward market-clearing level.
- Price discovery and time-line: T1 and T2 trading reveal successive estimates 1EP3 and 2EP3 of final liquidation price P3, with posterior sample variances 2 1 σ and 2 2 σ such that 2 2 2 1 σσ≥.
- Endogenous liquidity implication: the deeper the order book (more market makers), the faster the reversion to P3; the speed of adjustment ω increases with the absolute value of transitory demand η (0>∂∂ηω).
- Error-correction empirical representation:
  - Decomposition: e = f + n, with f the Hodrick–Prescott trend and n transitory demand.
  - Empirical equation (4): ()
    t
    x
    itittt
    enneεδβα
    ∑
    +∆++=∆
    −−−
    1
    3
    11
    , where ttt fen−=, α captures proportional mean reversion, β captures additional mean reversion from endogenous liquidity, and iδ tests the random walk (null iδ = 0).

### Data, stylized facts, and measures of liberalization/liquidity
- Sample: end-period daily, weekly, and monthly exchange rate data from May 1998 until December 2002 for USD and EUR against CZK, HUF, PZL, and SLK; all series logged.
- Hodrick–Prescott filter parameter λ used: 6,250,000 for daily data (note: they also state common rule λ = 14,400 monthly, 260,100 weekly, 6,250,000 daily).
- All level series found nonstationary I(1); differenced series stationary I(0).
- Distributional properties:
  - Excess kurtosis present in daily and most weekly and monthly returns; many series fail normality at 1 percent.
  - Mean duration of a departure from trend about 40 trading days; most currencies had 20–30 periods when they remained above or below trend for at least 5 trading days.
  - Country-specific liquidity indicators:
    - Czech koruna: most heavily traded market; around 40 new private koruna-denominated eurobond issues per year for the past six years; outstanding eurobonds > US$3 billion; 2002 average real one-month interbank rate 1.6 percent.
    - Hungary: forint-denominated eurobonds first issued in 2001; outstanding volume about US$100 million; 2002 average real one-month interbank rate 3.5 percent; closely regulated until June 2001.
    - Slovak Republic: no koruna-denominated eurobonds issued yet; 2002 average real one-month interbank rate 4.3 percent.
    - Poland: no summary eurobond data available; 2002 average real one-month interbank rate peaked at almost 7 percent.
  - Trading turnover and intervention notes (Figure 2 and text):
    - Czech turnover peaked at US$5 billion per day in late 1998/early 1999 and declined thereafter.
    - CNB monthly average interventions during 2000-2002 < US$100 million (≈0.2 percent of koruna-market turnover).

### Empirical results: speeds of adjustment, α and β estimates
- General findings:
  - Results broadly supportive of endogenous liquidity hypothesis; effects comparable to random walk components in exchange rate determination.
  - Speed of adjustment typically faster vis-à-vis the euro than the dollar.
  - Liquid, liberalized markets (notably Czech Republic) show faster adjustment; smaller or less liberalized markets (Slovak Republic, Hungary in late 1990s) show slower adjustment.
- Daily-data estimates (without lagged dependent variables, Table 3):
  - α point estimates imply return-to-trend in absence of nonlinear process between 7 and 60 days (up to 12 weeks).
  - Linear adjustment (n) effect about ten times stronger than nonlinear effect (n^3) when evaluated at absolute-value mean.
  - Many α and β estimates have expected negative signs; a few instances of α>0 (four in Poland, one in Slovak Republic) but with nonlinear β often overcompensating for these cases.
- Daily-data estimates with lagged dependent variables (24 lags, Table 4):
  - Inclusion of lagged terms increases magnitudes of α and β and improves joint significance and explained variance.
  - Seven out of twelve estimated β parameters for EUR exchange rates statistically significant and negative.
  - Recursive estimates indicate declining absolute-value βs with increasing absolute-value αs in maturing markets (e.g., Czech koruna), interpreted as markets requiring smaller shocks to trigger nonlinear adjustment as proportional adjustment strengthens.
- Weekly-data estimates (without and with lagged dependent variables, Tables 5–6):
  - Weekly results broadly similar to daily results; adjusted R2 higher (explaining between 5 and 10 percent of dependent-variable variance).
  - Weekly α estimates imply return-to-trend between 2 and 15 weeks absent nonlinear process.
  - Median comparisons to Faruqee–Redding (G-7): our median α ≈ -0.15 (vs. G-7 median -0.18), our median β ≈ -85 (vs. G-7 median -15), implying larger nonlinear triggers required in transition economies.
- Random walk testing and forecasting (Annex II):
  - Random-walk model performs quite similarly to Faruqee–Redding model without lagged variables; Faruqee–Redding model with lagged variables often yields lower out-of-sample RMSE.
  - Reported RMSEs (RMSE x 100) for CZK/EUR: 1 week 0.217, 2 weeks 0.167, 1 month 0.172 across models in table (full table shows model comparisons for HUF/EUR, PZL/EUR, SLK/EUR as well).

### Central bank interventions and volatility
- Central banks predominantly “leaned against the wind” to slow real appreciation rather than smoothing short-term nominal volatility.
- Quantitative interventions were small and infrequent relative to market turnover; example: CNB monthly average < US$100 million during 2000–2002 (~0.2 percent of turnover).
- Regression evidence (January 1999–December 2002) controlling for contagion and trend: big-intervention months in the Czech Republic were associated with bigger volatility; similar exercises for Hungary and Slovak Republic yielded statistically insignificant results.
- Conclusion: limited role for interventions in curbing exchange-rate volatility in sample; interventions may have fueled volatility in some instances.

### Policy implications and conclusions
- Early liberalization of foreign exchange markets and financial-account transactions may lead to greater market liquidity and faster exchange-rate adjustment, increasing viability of floating regimes and making pegs harder to sustain.
- Early liberalization is necessary but not sufficient; market size and depth matter (e.g., Slovak Republic floated early but market remained thin).
- Central banks need not be overly concerned with short-run nominal exchange-rate volatility due to self-correcting endogenous-liquidity tendencies; Visegrád Four central banks typically focused on leaning against real appreciation.
- Endogenous liquidity effects empirically comparable to autoregressive/random-walk components; they speed self-correction but do not guarantee lower nominal volatility or closer alignment to fundamental levels.
- Specific country conclusions:
  - Strongest support for endogenous liquidity in Czech koruna market and, more recently, in post-2000 Hungarian forint market.
  - Polish zloty appears as an outlier: similar dollar and euro volatility, occasional α>0 (proportional mean reversion positive), and large βs in daily regressions—implying adjustment occurs only after large departures from trend.
- Suggested extensions: consider impact of central bank interventions on speed of exchange-rate adjustment; need for longer consistent time series to determine appropriate testing frequency.

*Source: _wp0435 - References (IMF working paper content, May 1998–December 2002 sample period).*

### References

### _wp0435 - References

### Exchange rate determination, volatility, and market microstructure
- Bacchetta, Phillippe, and Eric van Wincoop, 2003, “Can Information Heterogeneity Explain the Exchange Rate Determination Puzzle?” CEPR Discussion Paper No. 3808 (London: Centre for Economic Policy Research).
- Beine, Michel, Sébastien Laurent, and Christelle Lecourt, 2003, “Official Central Bank Interventions and Exchange Rate Volatility: Evidence from a Regime-Switching Analysis,” European Economic Review, Vol. 47 (October), pp. 891–911.
- Bofinger, Peter, and Wollmershaeuser, Timo, 2001, “Managed Floating: Understanding the New International Monetary Order,” CEPR Discussion Paper, No. 3064 (London: Centre for Economic Policy Research).
- Devereux, Michael B., and Philip R. Lane, 2003, “Understanding Bilateral Exchange Rate Volatility,” Journal of International Economics, Vol. 60 (May), pp. 109–132.
- Evans, Martin D. D., and Richard K. Lyons, 2002, “Order Flow and Exchange Rate Dynamics,” Journal of Political Economy, Vol. 110 (February), pp. 170–180.
- Faruqee, Hamid, and Lee Redding, 1999, “Endogenous Liquidity Providers and Exchange Rate Dynamics,” Canadian Journal of Economics, Vol. 32 (August), pp. 976–994.
- Faruqee, Hamid, and Lee Redding, 2001, “Asset Markets and Endogenous Liquidity,” Scottish Journal of Political Economy, Vol. 48 (May), pp. 196–209.
- Meese, Richard A., and Kenneth Rogoff, 1983, “Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample?” Journal of International Economics, Vol. 14 (February), pp. 3–24.
- Sarno, Lucio, 2003, “Nonlinear Exchange Rate Models: A Selective Overview,” IMF Working Paper 03/111 (Washington: International Monetary Fund). Available via the Internet: http://www.imf.org/external/pubs/cat/longres.cfm?sk=16541.0
- Wickham, Peter, 2002, “Do ‘Flexible’ Exchange Rates of Developing Countries Behave Like the Floating Exchange Rates of Industrialized Countries?” IMF Working Paper 02/82 (Washington: International Monetary Fund). Available via the Internet: http://www.imf.org/external/pubs/cat/longres.cfm?sk=15636.0

### Central bank intervention, policy regimes, and crises
- Holub, Tomáš, 2004, “Foreign Exchange Interventions Under Inflation Targeting: The Czech Experience,” Czech National Bank Internal Research and Policy Note, No.1/2004 (Prague: Czech National Bank). Available via the Internet: http://www.cnb.cz/en/pdf/IRPN_1_2004.pdf
- Kóbor, Ádám, and István P. Székely, 2004, “Foreign Exchange Market Volatility in EU Accession Countries in the Run-Up to Euro Adoption: Weathering Uncharted Waters,” IMF Working Paper 04/16 (Washington: International Monetary Fund). Available via the Internet: http://www.imf.org/external/pubs/ft/wp/2004/wp0416.pdf
- Stix, Helmut, 2001, “Does Central Bank Intervention Influence the Probability of a Speculative Attack? Evidence from the EMS,” OeNB Working Paper 80, (Wien: Oesterreichische Nationalbank). Available via the Internet: http://www2.oenb.at/workpaper/wp80.pdf
- Panthaki, Jehan, 2004, “Can Volatility in the Zloty/Euro Exchange Rate Be Explained by the U.S. Dollar/Euro Cross Rate?” unpublished note, International Monetary Fund (Washington: International Monetary Fund).
- Beine, Michel, Sébastien Laurent, and Christelle Lecourt, 2003, “Official Central Bank Interventions and Exchange Rate Volatility: Evidence from a Regime-Switching Analysis,” European Economic Review, Vol. 47 (October), pp. 891–911.

### Capital account, regimes, and historical perspectives
- Eichengreen, Barry, 2001, “Capital Account Liberalization: What Do Cross-Country Studies Tell Us?” The World Bank Economic Review, Vol. 15, No. 3, pp. 341–365.
- Ghosh, Atish R., Anne-Marie Gulde, and Holger C. Wolf, 2003, Exchange Rate Regimes: Choices and Consequences, MIT Press (Boston: Massachusetts).
- Reinhart, Carmen M., and Kenneth S. Rogoff, 2002, “The Modern History of Exchange Rate Arrangements: A Reinterpretation,” NBER Working Paper No. 8963 (Cambridge, Mass.: National Bureau of Economic Research). Available via the Internet: http://papers.nber.org/papers/w8963.pdf

### Econometric methods, cointegration, and theoretical models
- Cogley, Timothy, and James M. Nason, 1995, “Effects of the Hodrick–Prescott Filter on Trend and Difference Stationary Time Series: Implications for Business Cycle Research,” Journal of Economic Dynamics and Control, Vol. 19 (January–February), pp. 253–278.
- Granger, Clive W.J., and Pierre L. Siklos, 1997, “Regime-Sensitive Cointegration with an Application to Interest-Rate Parity,” Macroeconomic Dynamics, Vol. 1, No. 3, pp. 640–657.
- Johansen, Soren, and Katerina Juselius, 1990, “Maximum Likelihood Estimation and Inference on Cointegration, with Applications to the Demand for Money,” Oxford Bulletin of Economics and Statistics, Vol. 52 (May), pp. 169–209.
- Merton, Robert C., 1987, “A Simple Model of Capital Market Equilibrium with Incomplete Information,” Journal of Finance, Vol. 42 (July), pp. 483–511.

### Country and regional studies
- Darvas, Zsolt, and György Szapáry, 2000, “Financial Contagion in Five Small Open Economies: Does the Exchange Rate Regime Really Matter?” International Finance, Vol. 3, No. 1, pp. 25–51.
- Derviz, Alexis, 2003, “Components of the Czech Koruna Risk Premium in a Multiple-Dealer FX Market,” Czech National Bank Working Paper, No.4 (Prague: Czech National Bank). Available via the Internet: http://www.cnb.cz/en/pdf/wp4-2003.pdf
- Schardax, Franz, 2002, “Exchange Rates and Long-Term Interest Rates in Central Europe: How Do Monetary and Fiscal Policy Affect Them?” Focus on Transition, Vol. 7, No. 2, pp. 58–71.

*References list from _wp0435 - References.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2004/_wp0435.pdf_