## Section V concludes, summarizing the key findings.

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### Identification and descriptive statistics of terms-of-trade (ToT) cycles
- Sample and episodes:
  - Data cover 150 countries for the period 1960-2015.
  - Identified episodes: 59 ToT busts and 81 ToT booms.
  - Identified phases: 75 phases of high ToT and 91 phases of low ToT.
- Phase persistence and duration:
  - High ToT phases last, on average, 19 years.
  - Low ToT phases last, on average, about 10–12 years.
  - Terms-of-trade phases are highly persistent (high probability of remaining in a given state).
- Cross-group features:
  - EMDEs account for 63 and 75 percent of high and low phases, respectively.
  - On average, ToT are about 50-60 percent higher during the high phase of the cycle.
  - During high ToT phases, the real exchange rate is about 12 percent higher, and current account balances are about 1½ percentage points of GDP higher.
  - AEs exhibit a higher mean Low/High ToT ratio and smaller standard deviation than EMDEs.

### Dynamics of transitions and stylized facts
- Magnitude and dispersion:
  - Median ToT shift around regime switches is about 40 percentage points in EMDEs (both booms and busts) and about 20 percentage points in AEs.
  - Variance around these means is significantly larger for EMDEs.
- Timing of adjustment:
  - Much of the adjustment to a ToT shock occurs on impact, with a full adjustment visible within a 3–4 year horizon.
  - Real exchange rate responses tend to occur with a lag relative to the ToT shock.
- Symmetry:
  - Adjustment pattern is broadly symmetric between ToT booms and busts and materially similar between AEs and EMDEs once scaled by shock size.

### Quantitative response of external accounts and prices
- Current account response:
  - A one percent of GDP positive ToT income shock leads, on average, to a ½ percent of GDP improvement of the current account on impact.
  - Adjustment is approximately symmetric for positive and negative shocks; somewhat faster adjustment for negative shocks.
- Real exchange rate response:
  - Real exchange rates respond more strongly to ToT shocks in AEs—especially for ToT booms—than in EMDEs.

### Role of policies and buffers
- Exchange rate regime:
  - Economies with exchange rate flexibility display a significantly more muted current account impact in response to positive ToT shocks.
  - No statistically significant difference is found across regimes for the current account response to negative ToT shocks in the baseline results.
- International reserves:
  - Higher initial international reserves (above the sample median) are associated with more gradual external adjustment to ToT busts.
  - Reserves holdings do not play a statistically significant role for ToT booms.

### Domestic adjustment: supply and demand channels
- Decomposition findings:
  - The ToT income windfall (price effect) and net trade volumes jointly determine trade balance changes; the income windfall is sizable.
  - Domestic demand is the main driver of external adjustment; output responses are limited.
  - Domestic demand tends to respond more than one-to-one to ToT shocks to stabilize the current account.
- Trade volumes composition:
  - Import volumes play a dominant role in adjustment (imports contract significantly in ToT busts), while export volumes react only modestly.
  - For net commodity exporters, output and domestic demand show larger decelerations (accelerations) during busts (booms) than for importers.

### Recent ToT episode in historical perspective
- Recent bust (starting 2011, accelerating in 2014) is broadly comparable to past episodes, though often preceded by a short-run boom from the 2008-09 recovery.
- For AE commodity exporters, the recent weakening of ToT has been milder relative to past episodes.
- For EMDEs, current account weakening during the recent ToT bust is of the same order of magnitude as in previous episodes and broadly consistent with out-of-sample model forecasts.
- Exchange rate regime in recent bust:
  - Unconditional current account weakening has been similar for flexible and fixed regimes.
  - Controlling for the magnitude of the ToT shock, economies with fixed exchange rate regimes experienced stronger current accounts than expected (conditional out-of-sample forecast errors).

### Robustness and methodological notes
- Identification and estimation:
  - ToT regimes are identified via individual Markov regime-switching models distinguishing high and low ToT regimes.
  - The ToT shock measure, ∆ToT, accounts for trade openness and is expressed in percent of GDP.
  - Estimation uses annual data over t−4 to t+5 windows around each transition event and Arellano-Bond GMM.
- Robustness checks (selected estimates from Table A2):
  - Excluding large countries:
    - L.Y 0.623*** (0.023)
    - TOT shock 0.405*** (0.027)
    - L.TOT shock 0.091*** (0.029)
    - L2.TOT shock 0.092*** (0.028)
    - Number of observations 645; Number of countries 74; Adjusted R2 0.350; Sargan P value 0.000; Sargan Test 727.218
  - Large ToT shocks only (>20%):
    - L.Y 0.626*** (0.025)
    - TOT shock 0.437*** (0.030)
    - L.TOT shock 0.110*** (0.032)
    - L2.TOT shock 0.088*** (0.032)
    - Number of observations 496; Number of countries 56; Adjusted R2 0.360; Sargan P value 0.000; Sargan Test 561.131
  - Controlling for global financial conditions:
    - L.Y 0.604*** (0.027)
    - TOT shock 0.434*** (0.033)
    - L.TOT shock 0.248*** (0.039)
    - L2.TOT shock 0.231*** (0.037)
    - Number of observations 710; Number of countries 82; Adjusted R2 1.00; Sargan P value 0.000; Sargan Test 507.52
  - Controlling for global financial conditions and external demand:
    - L.Y 0.601*** (0.028)
    - TOT shock 0.398*** (0.036)
    - L.TOT shock 0.294*** (0.043)
    - L2.TOT shock 0.264*** (0.040)
    - Number of observations 710; Number of countries 82; Adjusted R2 0.070; Sargan P value 0.000; Sargan Test 448.413
- Notes:
  - 1/ Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

### Key policy-relevant implications and open questions
- Policy-relevant implications:
  - Exchange rate flexibility helps buffer positive ToT shocks via expenditure responses but is less effective in mitigating busts when financing constraints bind.
  - International reserves provide useful smoothing capacity during ToT busts by delaying adjustment pressures.
  - Domestic demand management is central to external adjustment following ToT shocks; import compression is a key margin of adjustment.
- Open questions for future research:
  - What channels drive domestic demand adjustment—expectations about shock persistence or borrowing constraints?
  - What roles do public sector versus private sector play in adjustment dynamics?
  - What are the distributional and policy implications of adopting different exchange rate regimes in the face of ToT shocks?

*Source: wp1729 - Section V concludes, summarizing the key findings.*

### Section V concludes, summarizing the key findings.

### Section V concludes, summarizing the key findings.

### Identification and descriptive statistics of terms-of-trade (ToT) cycles
- Sample and episodes:
  - Data cover 150 countries for which ToT series are available for the period 1960-2015.
  - Identified episodes: 59 ToT busts and 81 ToT booms.
  - Identified phases: 75 phases of high ToT and 91 phases of low ToT.
- Phase persistence and duration:
  - High ToT phases last, on average, 19 years.
  - Low ToT phases last, on average, about 10–12 years.
  - Terms-of-trade phases are highly persistent (high probability of remaining in a given state).
- Cross-group features:
  - EMDEs account for 63 and 75 percent of high and low phases, respectively.
  - On average, ToT are about 50-60 percent higher during the high phase of the cycle.
  - During high ToT phases, the real exchange rate is about 12 percent higher, and current account balances are about 1½ percentage points of GDP higher.
  - AEs exhibit a higher mean Low/High ToT ratio and smaller standard deviation than EMDEs (more stable ToT).

### Dynamics of transitions and stylized facts
- Magnitude and dispersion:
  - Median ToT shift around regime switches is about 40 percentage points in EMDEs (both booms and busts) and about 20 percentage points in AEs.
  - Variance around these means is significantly larger for EMDEs.
- Timing of adjustment:
  - Much of the adjustment to a ToT shock occurs on impact, with a full adjustment visible within a 3–4 year horizon.
  - Real exchange rate responses tend to occur with a lag relative to the ToT shock.
- Symmetry:
  - The adjustment pattern is broadly symmetric between ToT booms and busts and materially similar between AEs and EMDEs once scaled by shock size.

### Quantitative response of external accounts and prices
- Current account response:
  - A one percent of GDP positive ToT income shock leads, on average, to a ½ percent of GDP improvement of the current account on impact (i.e., only ½ of the price shock is offset by trade volume variation).
  - Adjustment is approximately symmetric for positive and negative shocks; somewhat faster adjustment for negative shocks.
- Real exchange rate response:
  - Real exchange rates respond more strongly to ToT shocks in AEs—especially for ToT booms—than in EMDEs, indicating greater buffering via exchange rate movements in AEs.

### Role of policies and buffers
- Exchange rate regime:
  - Economies with exchange rate flexibility display a significantly more muted current account impact in response to positive ToT shocks (flexibility facilitates offsetting adjustment in trade volumes).
  - No statistically significant difference is found across regimes for the current account response to negative ToT shocks in the baseline results, possibly reflecting financing constraints faced by fixed-regime countries.
- International reserves:
  - Higher initial international reserves (above the sample median) are associated with more gradual external adjustment to ToT busts (reserves allow smoothing/delay of adjustment).
  - Reserves holdings do not play a statistically significant role for ToT booms (no constraint on reserve accumulation).

### Domestic adjustment: supply and demand channels
- Decomposition findings:
  - The ToT income windfall (price effect) and net trade volumes jointly determine trade balance changes; the income windfall is sizable.
  - Domestic demand is the main driver of external adjustment; output responses are limited.
  - Domestic demand tends to respond more than one-to-one to ToT shocks to stabilize the current account.
- Trade volumes composition:
  - Import volumes play a dominant role in adjustment (imports contract significantly in ToT busts), while export volumes react only modestly.
  - For net commodity exporters, output and domestic demand show larger decelerations (accelerations) during busts (booms) than for importers—partly reflecting larger ToT shocks and production incentives for commodity exporters.

### Recent ToT episode in historical perspective
- Recent bust (starting 2011, accelerating in 2014) is broadly comparable to past episodes, though often preceded by a short-run boom from the 2008-09 recovery.
- For AE commodity exporters, the recent weakening of ToT has been milder relative to past episodes.
- For EMDEs, current account weakening during the recent ToT bust is of the same order of magnitude as in previous episodes and broadly consistent with out-of-sample model forecasts.
- Exchange rate regime in recent bust:
  - Unconditional current account weakening has been similar for flexible and fixed regimes.
  - Controlling for the magnitude of the ToT shock, economies with fixed exchange rate regimes experienced stronger current accounts than expected (conditional out-of-sample forecast errors), suggesting limited willingness or ability to finance larger deficits in the face of large ToT drops.

### Robustness and methodological notes
- Identification and estimation:
  - ToT regimes are identified via individual Markov regime-switching models distinguishing high and low ToT regimes.
  - The ToT shock measure, ∆ToT, accounts for trade openness and is expressed in percent of GDP (income shock measure).
  - Estimation uses annual data over t−4 to t+5 windows around each transition event and Arellano-Bond GMM given the short panel span.
- Robustness checks:
  - Excluding countries that may affect their own ToT (large relative to world markets), excluding small ToT shifts (|μH − μL| > .2 retained), including additional global financial controls, and controlling for contemporaneous trading-partner demand shifts do not overturn baseline results.

### Key policy-relevant implications and open questions
- Policy-relevant implications:
  - Exchange rate flexibility helps buffer positive ToT shocks via expenditure responses but is less effective in mitigating busts when financing constraints bind.
  - International reserves provide useful smoothing capacity during ToT busts by delaying adjustment pressures.
  - Domestic demand management is central to external adjustment following ToT shocks; import compression is a key margin of adjustment.
- Open questions for future research:
  - What channels drive domestic demand adjustment—expectations about shock persistence or borrowing constraints?
  - What roles do public sector versus private sector play in adjustment dynamics?
  - What are the distributional and policy implications of adopting different exchange rate regimes in the face of ToT shocks?

*Source: wp1729 - Section V concludes, summarizing the key findings.*

### References

### References

### Reference citations
- Adler, G. and N. Magud, (2015): “Four Decades of Terms-of-Trade Booms: A Metric of Income Windfall,” Journal of International Money and Finance, Vol 55, July, 162–192.
- Agenor, P. R. and J. Aizenman, (2004): “Savings and the Terms of Trade under Borrowing Constraints,” Journal of International Economics 63 (2004) 321– 340.
- Backus, D.K., (1993): “Interpreting Comovements in the Trade Balance and the Terms of Trade,” Journal of International Economics 34, 375-387
- Barone S., Descalzi R. y A. Díaz Cafferata (2009): “Terms of Trade Shocks and Current Account Adjustment in Latin American Countries” presentado en XXIV Jornadas Anuales de Economía. Banco Central del Uruguay. October 2009. Montevideo, Uruguay.
- Barone, S. and and R. Descalzi, (2010): “Credit Constraints and the Asymmetric Current Account Response to Terms-of-trade Shocks: An Empirical Application to Latin American Countries,” Anales Asociacion Argentina de Economia Politica, XLV Reunión Annual.
- Baxter, M. (1995): “International Trade and Business cycles”, in Grossman, G. and K. Rogoff (eds), Handbook of International Economics, Vol. III, Elsevier Science. B.V., The Netherlands.
- Bouakez Hafedh and Kano Takashi, (2008): "Terms of trade and current account fluctuations: The Harberger-Laursen-Metzler effect revisited," Journal of Macroeconomics, Vol. 30, No 1; 260-281.
- Cashin, P., and C. J. McDermott (1998): “Terms of Trade Shocks and the Current Account,” Working Paper 177, International Monetary Fund.
- Edwards, S. (1989): “Temporary Terms-of-Trade Disturbances, the Real Exchange Rate and the Current Account,” Economica, 56(223), 343–57.
- Hamilton, J. (1994), “Time Series Analysis,” Princeton University Press, Princeton, New Jersey.
- Harberger, A. C. (1950): “Currency Depreciation, Income, and the Balance of Trade,” Journal of Political Economy, 58(1), 47–60.
- International Monetary Fund (IMF), 2016 “External Sector Report”, Washington D.C.
- Independent Evaluation Office of the International Monetary Fund (2014): “IMF Forecasts: Process, Quality, and Country Perspectives,” Washington D.C.
- Kent, C. J., and P. Cashin (2003): “The Response of the Current Account to Terms of Trade Shocks: Persistence Matters,” Working Paper 143, International Monetary Fund.
- Laursen, S., and L. Metzler (1950): “Flexible Exchange Rates and the Theory of Employment,” Review of Economics and Statistics, 32(4), 281–299.
- Mendoza, E. G. (1995): “The Terms of Trade, the Real Exchange Rate, and Economic Fluctuations,” International Economic Review, 36(1), 101–37.
- Obstfeld, M. (1982): “Aggregate Spending and the Terms of Trade: Is There a Laursen-Metzler Effect?,” The Quarterly Journal of Economics, 97(2), 251–70.
- Obstfelf, M. and K. Rogoff (1995), “The Intertemporal Approach to the Current Account,” in Handbook of International Economics, vol.3, North Holland: Amsterdam, Chapter 34.
- Obstfeld Maurice and Rogoff Kenneth, (1996): “Foundations of International Economics”, MIT Press, Cambridge, Massachusetts.
- Ogaki, M., J. Ostry and C. Reinhart, (1996), “Saving Behavior in Low and Middle-Income Countries,” IMF Staff Papers 43, pp. 38-71.
- Ostry, J. and C. Reinhart, (1992), “Private Savings and Terms of Trade,” IMF Staff Papers 32, pp.495-517.
- Otto, G. (2003): “Terms of Trade Shocks and the Balance of Trade: There is a Harberger-Laursen-Metzler effect,” Journal of International Money and Finance, 22(2), 155–184.
- Phillips, S., L. Catão, L. A. Ricci, R. Bems, M. Das, J. di Giovanni, D. F. Unsal, M. Castillo, J. Lee, J. Rodriguez, and M. Vargas, (2013): “The External Balance Assessment (EBA) Methodology,” IMF Working Paper 13/272
- Sachs, J. D. (1981): “The Current Account and Macroeconomic Adjustment in the 1970s,” Brookings Papers on Economic Activity, 12(1), 201–282.
- Svensson, L. E. O., and A. Razin (1983): “The Terms of Trade and the Current Account: The Harberger-Laursen-Metzler Effect,” Journal of Political Economy, 91(1), 97–125.
- Vegh, Carlos A. (2013): “Open Economy Macroeconomics in Developing Countries,” The MIT Press, Cambridge, Massachusetts.

### Appendix: Figures (captions and sources)
- Figure A.1. ToT. Net commodity exporters vs. importers. (index, demeaned)
- Figure A.2. Real exchange rate: Net commodity exporters vs. importers. (index, demeaned)
  - Legend entries: Net Commodity Exporters; Net Commodity Importers; TOT Busts; TOT Booms; 75th percentile; 50th percentile; 25th percentile.
  - Sources: IMF, World Economic Outlook database; and IMF staff calculations.
- Figure A.3. Current account. Net commodity exporters vs. importers. (percent of GDP, demeaned)
- Figure A.4. Current account during ToT busts. Commodity exporters vs. importers: AEs vs. EMs. (percent of GDP, demeaned)
  - Legend entries: Net Commodity Exporters; Net Commodity Importers; Net Commodity Importers Advanced Economies Emerging Markets and Developing Economies; 75th per centile; 50th per centile; 25th per centile.
  - Sources: IMF, World Economic Outlook database; and IMF staff calculations.
- Figure A5. Exports/imports volumes & prices during ToT busts.
  - Panel A: volumes — Exports Volume (Percent change); Imports Volume (Percent change).
  - Panel B: Prices — Exports Deflator (Index: 2010 = 100, demeaned); Imports Deflator (Index: 2010 = 100, demeaned).
  - Legend entries: Advanced Economies; Emerging and Developing Economies; 75th per centile; 50th per centile; 25th per centile.
  - Sources: IMF, World Economic Outlook database; and IMF staff calculations.

### Table A.1. List of identified transitions
- Table A.1 enumerates identified Terms-of-trade Busts (transitions from High to Low ToT) and Terms-of-trade Booms (transitions from Low to High ToT).
- Each row records Country, Transition year 1/, Low/High ToT ratio (μL/μH) 2/.
- Example entries (as presented):
  - Albania 1991 0.40
  - Algeria 1987 0.44
  - Argentina 1982 0.62
  - Australia 2007 0.63
  - Brazil 1996 0.87
  - Canada 2005 0.87
  - Chile 1976 0.52
  - Colombia 1988 0.70
  - New Zealand 1968 0.82
  - Qatar 1986 0.33
  - United Kingdom 1974 0.87
  - Venezuela 2006 0.37
- Footnotes (verbatim):
  - 1 As identified by Markov switching procedure.
  - 2 Ratio of the (Markov regime switching) identified low vs. high terms of trade.

### Table A2. Robustness checks — key reported estimates and statistics
- Panel: Excluding large countries and countries with large share in world commodity markets (first column shown)
  - Variable estimates:
    - L.Y 0.623*** (0.023)
    - TOT shock 0.405*** (0.027)
    - L.TOT shock 0.091*** (0.029)
    - L2.TOT shock 0.092*** (0.028)
    - Constant -0.647*** (0.193)
  - Sample and fit:
    - Number of observations 645
    - Number of countries 74
    - Adjusted R2 0.350
    - Sargan P value 0.000
    - Sargan Test 727.218
- Panel: Large ToT shocks only (>20%) (first column shown)
  - Variable estimates:
    - L.Y 0.626*** (0.025)
    - TOT shock 0.437*** (0.030)
    - L.TOT shock 0.110*** (0.032)
    - L2.TOT shock 0.088*** (0.032)
    - Constant -0.283 (0.260)
  - Sample and fit:
    - Number of observations 496
    - Number of countries 56
    - Adjusted R2 0.360
    - Sargan P value 0.000
    - Sargan Test 561.131
- Panel: Controlling for global financial conditions (first column shown)
  - Variable estimates:
    - L.Y 0.604*** (0.027)
    - TOT shock 0.434*** (0.033)
    - L.TOT shock 0.248*** (0.039)
    - L2.TOT shock 0.231*** (0.037)
    - Constant 3.060*** (0.734)
  - Controls: Controls for Global Financial Conditions Yes
  - Sample and fit:
    - Number of observations 710
    - Number of countries 82
    - Adjusted R2 1.00
    - Sargan P value 0.000
    - Sargan Test 507.52
- Panel: Controlling for global financial conditions and external demand (first column shown)
  - Variable estimates:
    - L.Y 0.601*** (0.028)
    - TOT shock 0.398*** (0.036)
    - L.TOT shock 0.294*** (0.043)
    - L2.TOT shock 0.264*** (0.040)
  - Controls: Controls for Global Financial Conditions Yes; Control for External Demand Yes
  - Sample and fit:
    - Number of observations 710
    - Number of countries 82
    - Adjusted R2 0.070
    - Sargan P value 0.000
    - Sargan Test 448.413

- Notes (verbatim):
  - Sources: authors' estimations.
  - 1/ Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

*Content derived from "wp1729 - References" (source PDF: wp1729 - References).*

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_Source: https://www.imf.org/-/media/files/publications/wp/wp1729.pdf_