## Appendix 1: Lags of BoP and merchandise trade data in selected EMs

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---

### Data on reporting lags (merchandise trade and Balance of Payments)
- Header: (Lag, in months, unless specified otherwise)Frequency
- Merchandise Trade — Balance of Payments (listed by country):
  - Brazil: 25 daysmonthly — 25 daysmonthly
  - China: 2quarterly — 8 daysmonthly
  - Colombia: 3quarterly — 1.5monthly
  - Indonesia: 3quarterly — 1monthly
  - Romania: 1.5monthly — 1.5monthly
  - Russia: 3quarterly — 2monthly
  - South Africa: 3quarterly — 1monthly
  - Thailand: 3quarterly — 1.5monthly
  - Turkey: 2monthly — 1monthly

### Implications (as reflected in the source appendix)
- Reporting lags for merchandise trade and BoP data vary substantially across selected EMs, with mixed frequency indicators (days, months, quarterly) reported in the source.
- The heterogeneity in timeliness underscores the motivation for constructing more timely coincident proxies for capital flows in the main paper.

### Appendix 2: EM sample coverage of the capital tracker and the EPFR

- Coverage panels and time spans:
  - Capital tracker (1995Q2-2011Q2)
  - EPFR: Equity 1/ (2001Q1-2011Q3)
  - EPFR: Bonds 2/ (2004Q2- 2011Q3)

- Countries included in all three series (grouped as in source):
  - Asia:
    - China
    - India
    - Indonesia
    - Korea
    - Malaysia
    - Pakistan
    - Philippines
    - Sri Lanka
    - Thailand
    - Vietnam
  - Latin America:
    - Argentina
    - Brazil
    - Chile
    - Colombia
    - Mexico
    - Peru
    - Venezuela
  - Emerging Europe:
    - Bulgaria
    - Czech Republic
    - Hungary
    - Kazakhstan
    - Luthania
    - Poland
    - Romania
    - Russia
    - Turk ey
    - Ukraine
  - Other EMs / Middle East & Africa:
    - Israel
    - Lebanon
    - South Africa
    - Tunisia

- Additional country listings (as shown in the source):
  - Appearing in the Capital tracker but with gaps or absent from EPFR panels in the source listing:
    - Costa Rica
    - Ecuador
    - El Salvador
    - Uruguay
  - Appearing in EPFR Equity and/or Bonds lists in the source:
    - Costa Rica
    - Croatia
    - Ecuador
    - El Salvador
    - Latvia
    - Uruguay

- Exclusions noted in source footnotes:
  - Footnote 1/ (EPFR: Equity exclusions): "Costa Rica, Croatia, Ecuador, El Salvador, Latvia and Uruguay (6 countries) are excluded due to unavailabilty of data."
  - Footnote 2/ (EPFR: Bonds exclusions): "Costa Rica, Croatia, Ecuador, El Salvador, Esttonia, Jordon, Latvia, Morocco and Uruguay (9 countries) are excluded due to unavailabilty of data."

*Source: Appendix 1 and Appendix 2 content from _wp1255 — Coincident Indicators of Capital Flows, Yanliang Miao and Malika Pant, February 2012.*

### Appendix 1: Lags of BoP and merchandise trade data in selected EMs ................................ 21

### Appendix 1: Lags of BoP and merchandise trade data in selected EMs

### Context
- This content unit is titled "Appendix 1: Lags of BoP and merchandise trade data in selected EMs".
- It is an appendix within the paper "Coincident Indicators of Capital Flows".
- Located on page 21 of the source PDF.

### Document metadata
- Authors: Yanliang Miao and Malika Pant
- Division: Emerging Markets Division, Strategy, Policy, and Review Department
- Date: February 2012

### Role within the paper
- Serves as an appendix focused on lags of balance of payments (BoP) and merchandise trade data for selected emerging markets (EMs).
- Intended to provide supporting empirical detail complementing the main text of "Coincident Indicators of Capital Flows".

*Source: _wp1255 - Appendix 1: Lags of BoP and merchandise trade data in selected EMs (page 21) — Coincident Indicators of Capital Flows, Yanliang Miao and Malika Pant, February 2012.*

### Executive Summary

### _wp1255 - Executive Summary

### Timeliness problem and motivation
- Balance of payments capital flows data typically become available "3 to 6 months" after the period in question.
- Heightened volatility in global financial markets and capital flows increases the need for real time information for policy deliberation and calibration.
- Goal: provide more timely coincident proxies for capital flows that improve upon simple proxies used in the literature.

### Proposed coincident composite indicators
- Two coincident composite indicators are proposed:
  - A timely proxy for net capital inflows based on the difference between the trade balance and the change in international reserves, augmented with other regional and global coincident correlates of capital flows.
    - Note: a simple version using only the trade balance and change in reserves has been widely used; the paper finds it typically over-predicts capital flows by "about 30 percent".
  - A real time proxy for gross bond and equity inflows based on Emerging Portfolio Fund Research (EPFR) data, augmented with regional and global correlates in an error correction model.

### Key empirical sample and data coverage
- Main sample: "40 major EMs" with continuous quarterly BoP coverage from "1995Q2 to 2011Q1".
  - Regions in the sample: 10 in Asia, 11 in Latin America, 13 in Emerging Europe, and six Other EMs.
- EPFR coverage:
  - Equity flows coverage goes back to "2001Q1".
  - Bond flows coverage starts at "2004Q2".
- For EMs as a whole, EPFR reported flows cover about half of BoP reported portfolio equity inflows and around an eighth of BoP reported portfolio bond inflows for the sample of 34 EMs.

### Performance of existing simple tracker
- The commonly used tracker = merchandise trade balance minus change in international reserves.
- Empirical finding: the simple tracker is highly correlated with actual net capital flows but typically more volatile and overshoots actual flows.
- OLS result (aggregate all EMs, 1995Q2-2011Q1): a one dollar increase in the tracker is associated with an increase of "about 70 cents" in actual capital flows (i.e., tracker overestimates by "30 percent").
  - Regional one-dollar responses: Emerging Europe "75 cents", Asia "51 cents", Latin America "96 cents", Other EMs "80 cents".
- Reported R Squares for simple regressions (net inflows on capital tracker): All EMs "0.78"; Asia "0.68"; Emerging Europe "0.66"; Latin America "0.64"; Other EMs "0.78".

### Construction of the coincident composite indicator for net capital inflows
- Augmentations to the tracker:
  - Reassess weight on the capital tracker (coefficient estimated rather than constrained to 1).
  - Include global/regional push and pull predictors: VIX index, US 10 year bond price index, EUR/USD exchange rate, and regional MSCI equity indices.
- Estimation equation (levels): Y = α + β·X + γ·Z  (where Y = net capital flows; X = regional aggregate capital tracker; Z = controls listed above).
- Key regression outputs (OLS, 1995Q2-2011Q1, regional aggregates):
  - Coefficient on Capital flows tracker (estimated):
    - All EMs "0.49"
    - Asia ex-China EMs "0.55"
    - Emerging Europe "0.51"
    - Latin America EMs "0.92"
    - Other EMs "0.72"
  - R Squared (with controls): All EMs "0.84"; Asia ex-China "0.76"; Emerging Europe "0.81"; Latin America "0.64"; Other EMs "0.82".
- Composite indicator constructed as the fitted value from the estimated equation: Fitted(net flows) = X·β̂ + Z·γ̂.
- Empirical performance:
  - Panel plots (2006Q1–2011Q1, four-quarter moving averages) show the composite indicator outperforms the simple capital tracker in approximating underlying net flows across All EMs and regions.
  - Robustness checks:
    - Re-estimating on samples truncated by one to four quarters shows stability of estimated coefficients and composite indicator.
    - Panel estimations with country fixed effects confirm the less-than-one-to-one relationship between the tracker and underlying flows.

### EPFR-based proxies for gross portfolio inflows (bond and equity)
- EPFR provides weekly/monthly country flows for registered funds and captures primarily institutional investors.
- EPFR flows are gross (liabilities side) and are only a subset of total portfolio flows; coverage differs between bonds and equities.
- Time series properties:
  - ADF tests indicate bond flows to most regions and all EMs and equity flows to certain regions contain a unit root.
  - Regressions of BoP gross bond/equity flows on EPFR flows show cointegration, enabling an error correction modeling approach.
- Error Correction Model (ECM) setup:
  - Long-run relation: ε = Y − β·X  (where Y = BoP portfolio inflows, X = EPFR flows).
  - Short-run ECM (changes): ΔY = a + b·(ε_{t-1}) + c1·ΔX + c2·ΔZ + ...
  - Controls used in ECM: VIX, US 3-month T-bill rate, and regional MSCI (for equities only).
- ECM empirical results (regional aggregates):
  - Bond flows (ECM for 2004Q2-2011Q1):
    - D(EPFR: Bond flows) coefficients by region: All EMs "6.27"; Asia EMs "8.24"; Emerging Europe "6.91"; Latin America EMs "3.78"; Other EMs "13.66".
    - Error correction term (t-1) coefficients: All EMs "-0.72"; Asia "-0.48"; Emerging Europe "-1.02"; Latin America "-0.81"; Other EMs "-1.02".
    - R Square (bond ECM): All EMs "0.77"; Asia "0.50"; Emerging Europe "0.70"; Latin America "0.68"; Other EMs "0.57".
    - Long-term EPFR: Bond flows (t-1) coefficients: All EMs "7.47"; Asia "7.9"; Emerging Europe "7.88"; Latin America "5.96"; Other EMs "9.64".
  - Equity flows (ECM for 2001Q1-2011Q1):
    - D(EPFR: Equity flows) coefficients by region: All EMs "1.14"; Asia EMs "0.77"; Emerging Europe "1.31"; Latin America EMs "1.22"; Other EMs "1.54".
    - Error correction term (t-1) coefficients: All EMs "-0.78"; Asia "-0.71"; Emerging Europe "-0.82"; Latin America "-0.78"; Other EMs "-0.88".
    - R Square (equity ECM): All EMs "0.84"; Asia "0.58"; Emerging Europe "0.75"; Latin America "0.83"; Other EMs "0.58".
    - Long-term EPFR: Equity flows (t-1) coefficients: All EMs "1.85"; Asia "1.59"; Emerging Europe "1.23"; Latin America "1.96"; Other EMs "2.38".
- Interpretation:
  - The BoP bond flows respond more strongly (larger multipliers) to EPFR bond flows than BoP equity flows respond to EPFR equity flows, reflecting more limited coverage of EPFR bond flows.
  - Speed of adjustment (error correction coefficient) is generally faster for equity than bond, reflecting greater liquidity in equity markets.
- Composite EPFR indicators (fitted values from ECMs) outperform simple proportional rescaling of EPFR series in approximating BoP bond and equity flows.

### Out-of-sample real-time forecasting and application
- Real-time exercise: sequentially rerun models up to 2010Q1 to forecast 2010Q2, then move forward quarterly to produce one-quarter-ahead forecasts for the period "2010Q3 to 2011Q1".
- Findings:
  - Out-of-sample one-step-ahead forecasts almost always overlap with composite indicators constructed using the full sample coefficients, confirming coefficient stability.
  - One-step-ahead forecasts are closely aligned with subsequently released realized flows, corroborating the usefulness of the composite indicators.
  - Based on information available at "end 2011Q3", the EPFR based models project an ongoing sharp decline of bond and equity flows into emerging markets.

### Main conclusions
- The conventional assumption of a one-to-one relationship between the capital tracker (trade balance minus reserve change) and net capital flows does not hold empirically; the tracker typically overestimates flows.
- A composite coincident indicator that reweights the tracker and incorporates timely global and regional controls (VIX, US 10 year bond price index, EUR/USD, regional MSCI) produces a better real-time proxy for net capital inflows.
- EPFR high-frequency bond and equity flow data, combined with controls in an ECM framework, provide timely and effective coincident proxies for gross portfolio bond and equity inflows, with strong fit (R-squares of "0.77" for bonds and "0.84" for equities for All EMs).
- Both types of composite indicators are simple enough for frequent monitoring and can significantly improve timeliness of information for surveillance and policy calibration.

*Source: _wp1255 - Executive Summary (IMF staff calculations and analysis).*

### Appendix 1: Lags of BoP and merchandise trade data in selected EMs

### Appendix 1: Lags of BoP and merchandise trade data in selected EMs

### Data on reporting lags (merchandise trade and Balance of Payments)
- Header: (Lag, in months, unless specified otherwise)Frequency
- Merchandise Trade — Balance of Payments (listed by country):
  - Brazil: 25 daysmonthly — 25 daysmonthly
  - China: 2quarterly — 8 daysmonthly
  - Colombia: 3quarterly — 1.5monthly
  - Indonesia: 3quarterly — 1monthly
  - Romania: 1.5monthly — 1.5monthly
  - Russia: 3quarterly — 2monthly
  - South Africa: 3quarterly — 1monthly
  - Thailand: 3quarterly — 1.5monthly
  - Turkey: 2monthly — 1monthly

### Appendix 2: EM sample coverage of the capital tracker and the EPFR

### Coverage panels and time spans
- Capital tracker (1995Q2-2011Q2)
- EPFR: Equity 1/ (2001Q1-2011Q3)
- EPFR: Bonds 2/ (2004Q2- 2011Q3)

### Countries included in all three series (grouped as in source)
- Asia:
  - China
  - India
  - Indonesia
  - Korea
  - Malaysia
  - Pakistan
  - Philippines
  - Sri Lanka
  - Thailand
  - Vietnam
- Latin America:
  - Argentina
  - Brazil
  - Chile
  - Colombia
  - Mexico
  - Peru
  - Venezuela
- Emerging Europe:
  - Bulgaria
  - Czech Republic
  - Hungary
  - Kazakhstan
  - Luthania
  - Poland
  - Romania
  - Russia
  - Turk ey
  - Ukraine
- Other EMs / Middle East & Africa:
  - Israel
  - Lebanon
  - South Africa
  - Tunisia

### Additional country listings (as shown in the source)
- Appearing in the Capital tracker but with gaps or absent from EPFR panels in the source listing:
  - Costa Rica
  - Ecuador
  - El Salvador
  - Uruguay
- Appearing in EPFR Equity and/or Bonds lists in the source:
  - Costa Rica
  - Croatia
  - Ecuador
  - El Salvador
  - Latvia
  - Uruguay

### Exclusions noted in source footnotes
- Footnote 1/ (EPFR: Equity exclusions): "Costa Rica, Croatia, Ecuador, El Salvador, Latvia and Uruguay (6 countries) are excluded due to unavailabilty of data."
- Footnote 2/ (EPFR: Bonds exclusions): "Costa Rica, Croatia, Ecuador, El Salvador, Esttonia, Jordon, Latvia, Morocco and Uruguay (9 countries) are excluded due to unavailabilty of data."

*Appendix 1 and Appendix 2 content from the source document.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2012/_wp1255.pdf_