## _wp10154

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---

### I. Introduction
- Purpose:
  - Investigate determinants of competitiveness using the real effective exchange rate (REER) as the measure of competitiveness.
  - Identify which capital and foreign exchange flows lead to REER appreciation and which do not.
- Definitions and scope:
  - REER used: the IMF REER Index (from IMF Information Notice System (INS) database).
  - Capital flows considered (financial account): foreign direct investments (FDI), portfolio investments, other investments (debts).
  - Foreign exchange flows considered (current account): remittances, aid, income.
- Sample and methodology overview:
  - Panel of 57 countries covering 6 regions: Africa, Central and Eastern European Countries (CEEC), South and East Asia, Latin America, Middle East and North Africa (MENA), and the Gulf Cooperation Council (GCC).
  - Sample period: 1980 to 2007.
  - Main estimator: Generalized Method of Moments (GMM).

### II. Related literature and theoretical framework
- Theoretical framework:
  - Surge in capital flows → higher real wages → higher prices of nontradables relative to tradables → REER appreciation (spending effect; Dutch Disease).
- Empirical evidence (select findings cited in source):
  - Athukorala and Rajapatirana (2003): non-FDI capital flows → REER appreciation; FDI tends to depreciate REER.
  - Elbadawi and Soto (1994): short-term capital and portfolio → no effect; long-term flows and FDI → appreciating effect (Chile).
  - Amuedo-Dorantes and Pozo (2004): doubling transfers → REER appreciation by 22 percent (panel of 13 Latin American countries).
  - Elbadawi (1999): 10 percent increase in aid → REER rise of 1 percent (panel of 62 developing countries).
  - Rajan and Subramanian (2005): aid flows have systematic adverse effects on competitiveness via REER overvaluation; remittances may have no effect where directed toward tradable sectors.
- Gaps highlighted:
  - Limited multi-flow, multi-region analyses; mixed and sometimes contradictory results across flows, countries, and methods.

### III. Empirical framework, data, and variables
- Baseline specification (variants used):
  - REER_{i,t} = α1 + α2 Capital Flows_{i,t} + α3 Policy_{i,t} + α4 Control_{i,t} + ε_{i,t}
  - Log-level GMM specification used for estimation:
    - Ln REER_it = α0 + α1 Ln REER_{i,t-1} + α2 Capital Flows_it + α3 Ln GCON_it + α4 Ln OPEN_it + α5 Ln PROD_it + α6 Ln TOT_it + ε_it
- Data sources:
  - Capital and foreign exchange flows: International Financial Statistics (IFS).
  - Control and policy variables: World Economic Outlook (WEO).
  - REER indices: IMF INS database.
- Variable definitions (selected):
  - NKF = Net capital flows = sum of income, remittances, aid, FDI, portfolio investments, other investments.
  - FDI, PORT, DEBT, INCOME, AID, REMIT defined as flows/GDP (current USD) per Appendix 2.
  - Controls: GCON (public consumption/GDP), OPEN ((exports+imports)/GDP), PROD (real GDP per capita), TOT (terms of trade index, 2000=1).
- Estimation approach:
  - System GMM (Arellano and Bover (1995), Blundell and Bond (1998)); one-step GMM preferred for small-sample bias considerations.
  - Instruments: lagged levels for first-differenced equations and vice versa; Hansen (Sargan) and serial correlation tests applied.

### IV. Key empirical findings (aggregate sample)
- Aggregate NKF (Table 1, column 1) — reported estimates:
  - Constant: 0.603 (0.437)
  - LagREER: 0.785*** (0.049)
  - LNGDP: 0.134*** (0.031)
  - LTOT: 0.158** (0.074)
  - LGCON: -0.104** (0.049)
  - LOPEN: -0.051* (0.031)
  - NKF: 0.006*** (0.001)
  - Sargan p-value: 0.139
  - Serial correlation p-value: 0.654
  - No. of countries: 57
  - No. of observations: 1347
- Interpretation (aggregate):
  - NKF has a positive and significant impact on REER → increase in NKF leads to REER appreciation.
  - LTOT and PROD increases → REER appreciation.
  - OPEN and GCON increases → REER depreciation.

### V. Disaggregated flows (aggregate sample estimates and interpretation)
- Disaggregated coefficients (Table 1, column 2; estimates and standard errors):
  - Constant: 0.311 (0.610)
  - LagREER: 0.751*** (0.057)
  - LNGDP: 0.094*** (0.030)
  - LTOT: 0.224** (0.111)
  - LGCON: -0.064 (0.047)
  - LOPEN: -0.024 (0.027)
  - FDI: 0.002 (0.002)
  - DEBT: 0.003** (0.001)
  - PORT: 0.006*** (0.002)
  - INCOME: 0.009** (0.004)
  - AID: 0.006*** (0.002)
  - REMIT: 0.008* (0.004)
  - Sargan p-value: 0.242
  - Serial correlation p-value: 0.888
  - No. of countries: 57
  - No. of observations: 1313
- Aggregate-sample interpretations:
  - All disaggregated flows except FDI have a significant positive impact on REER: DEBT, PORT, INCOME, AID, REMIT.
  - FDI is not significant in the overall sample (coefficient: 0.002 (0.002)).
  - Suggested mechanism for FDI non-significance: part of FDI finances imports of machinery/capital goods and increases productive capacity, which can exert downward pressure on REER over time.

### VI. Regional results (summary of Table 2 and regional patterns)
- NKF:
  - Positive and significant impact on REER in all regions except CEEC (CEEC: NKF negative and nonsignificant).
  - MENA: significance at 10 percent reported for NKF.
- FDI:
  - Generally nonsignificant (negative but not significant) in Latin America, South and East Asia, CEEC, MENA.
  - Nonsignificant positive in GCC.
  - Significant positive only in Africa (suggesting loss of competitiveness).
- DEBT:
  - Significant positive impact in all regions except CEEC (CEEC coefficient negative and nonsignificant).
- PORT:
  - Positive and significant impact on REER in South and East Asia, Latin America, GCC, and CEEC (CEEC at 10 percent).
  - No significant impact in Africa.
  - MENA: significant but negative impact (portfolio inflows associated with privatization-driven modernization and import of machinery → REER depreciation).
- INCOME:
  - Significant positive impact in Latin America and MENA; no impact in Africa, CEEC, South and East Asia.
- AID:
  - Positive and significant in CEEC, GCC, South and East Asia, and Africa; not significant in MENA and Latin America.
- REMITTANCES:
  - Positive and significant in GCC, South and East Asia, and Africa.
  - Positive and nonsignificant in MENA.
  - Negative and nonsignificant in Latin America.
  - Negative and significant in CEEC.
- Comparative magnitudes (entire sample ranking reported in source):
  - Income has the strongest impact on REER appreciation, followed by remittances, aid, portfolio investments, and debt.
  - FDI is the only variable with no significant impact on REER appreciation in the overall sample.

### VII. Regional stylized facts on flows (1980–2007)
- NKF/GDP:
  - GCC: massive capital outflows reaching almost 27 percent of GDP; 1991 a recurrent outlier.
  - MENA: NKF/GDP oscillated on average between 10 and 20 percent.
  - Africa: second highest NKF/GDP over the period; CEEC joined by end of period.
  - South and East Asia and Latin America: NKF/GDP oscillated between +/- 5 percent.
- Current account components:
  - INCOME:
    - GCC reached almost 18 percent of GDP in the early 1980s.
    - In most other regions income was negative.
  - AID:
    - Africa received the highest ratios, reaching more than 6 percent in 1993.
  - REMIT:
    - All regions except GCC have increasing or stable remittances.
    - GCC remittances outflows between 5 and 10 percent of GDP.
    - MENA: more than 5 percent of GDP since early 1990s; Africa ~3 percent.
- Financial account components:
  - FDI/GDP < 2 percent in the 1980s; picked up in early 1990s.
  - Since late 1990s CEEC were on average highest receivers of FDI.
  - PORT:
    - GCC: increasing portfolio investment outflows since 1996, reaching more than 16 percent of GDP.
    - Other regions: portfolio inflows since early 1990s but never exceeded 2 percent of GDP.
  - DEBT:
    - Africa principal recipient in 1980s–1990s reaching almost 9 percent of GDP.
    - CEEC debt flows increased continuously since 2002, reaching almost 10 percent of GDP in 2007.

### VIII. Policy implications and recommendations (as inferred in source)
- Main policy message:
  - Policymakers should account for heterogeneous effects of different inflows on competitiveness when designing strategies to attract capital and foreign exchange.
- Specific implications:
  - Income, remittances, aid, portfolio investments, and debt are more likely associated with REER appreciation (potential competitiveness loss) and thus may require policy measures to manage absorption and composition of spending.
  - FDI appears less likely to cause REER appreciation in most regions and may be preferable for balancing capital attraction and competitiveness (exception: Africa where FDI is associated with REER appreciation).
  - Policy design should consider:
    - Expenditure composition of inflows (imports vs. domestic nontradables vs. tradable investment).
    - Exchange rate regime and sterilization of central bank interventions.
    - Presence of excess capacity and supply responses in nontradable sectors.
    - Sectoral allocation of inflows (tradable vs. nontradable; capital goods vs. consumption).
    - Accumulation in reserves versus domestic spending.
- Research implications:
  - Disparate regional results call for further investigation into factors explaining heterogeneity: shocks/crises, policy responses, level of development, institutional quality, and financial market sophistication.

### IX. Conclusion (source summaries)
- Contributions:
  - Comparative multi-flow, multi-region panel analysis on 57 developing countries (1980–2007) using GMM.
- Core findings:
  - Aggregated capital flows (NKF) → positive impact on REER in all regions except CEEC.
  - Disaggregated: INCOME strongest driver of REER appreciation; REMIT, AID, PORT, and DEBT also associated with appreciation; FDI generally not associated with REER appreciation (Africa is an exception).
  - Cross-regional heterogeneity substantial, implying differentiated policy responses.

*Source: _wp10154 - Appendix 2 provides the definition and data sources for the variables used in the paper.*

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

### _wp10154 - References .............................................................................................................

### I. Introduction
- Purpose:
  - Investigate determinants of competitiveness using the real effective exchange rate (REER) as the measure of competitiveness.
  - Identify which capital and foreign exchange flows lead to REER appreciation (potentially undermining competitiveness) and which do not.
- Definitions and scope:
  - REER used: the IMF REER Index (from IMF Information Notice System (INS) database).
  - Capital flows considered (financial account): foreign direct investments (FDI), portfolio investments, other investments (debts).
  - Foreign exchange flows considered (current account): remittances, aid, income.
  - Terminology note: the paper refers to remittances, aid, and income as “foreign exchange” flows although they appear in the current account.
- Sample and methodology overview:
  - Panel of 57 countries covering 6 regions: Africa, Central and Eastern European Countries (CEEC), South and East Asia, Latin America, Middle East and North Africa (MENA), and the Gulf Cooperation Council (GCC).
  - Sample period: 1980 to 2007.
  - Main estimator: Generalized Method of Moments (GMM) to address omitted variable and endogeneity biases.
- Key headline finding:
  - FDI does not lead to REER appreciation in almost all regions and leads to REER depreciation in the CEEC and MENA.

### II. Capital flows and the REER nexus: related literature
- Theoretical framework:
  - Salter (1959), Swan (1960), Corden (1960) and Dornbusch (1974) paradigm: surge in capital flows raises real wages → higher domestic demand → higher prices of nontradables relative to tradables → REER appreciation (spending effect). This is associated with “Dutch Disease effects” (Corden and Neary, 1982).
- Empirical findings summarized:
  - FDI vs. other capital flows:
    - Athukorala and Rajapatirana (2003): non-FDI capital flows → REER appreciation (greater in Latin America than East Asia); FDI tends to depreciate REER.
    - Lartey (2007): FDI causes REER appreciation in Sub-Saharan Africa but less than aid flows.
    - Elbadawi and Soto (1994) for Chile: short-term capital flows and portfolio investment have no effect on equilibrium REER; long-term capital flows and FDI have significant appreciating effect.
  - Portfolio investment and other investments (debt): limited attention; mixed or little-evidenced effects.
  - Income flows:
    - Largely neglected in literature; impact depends on whether income is spent domestically or reinvested abroad, exchange rate regime, and sterilization of interventions.
  - Remittances:
    - Amuedo-Dorantes and Pozo (2004): doubling transfers → REER appreciation by 22 percent in a panel of 13 Latin American countries.
    - Lopez et al. (2007) and Lartey et al. (2008): remittances can lead to REER appreciation; effect stronger under fixed exchange rate regimes.
    - Rajan and Subramanian (2005): remittances have no effects on external competitiveness; argue remittances directed toward tradable sectors explains null effect.
  - Aid:
    - Rajan and Subramanian (2005): aid flows have systematic adverse effects on competitiveness via REER overvaluation.
    - Elbadawi (1999): a 10 percent increase in aid → REER rise of 1 percent (panel of 62 developing countries).
    - Elbadawi et al. (2008): post-conflict countries receive larger aid but exhibit moderate REER overvaluation.
    - Prati and Tressel (2006), Arellano et al. (2009), Gupta et al. (2005) and others: mixed evidence; effect depends on use of aid (imports vs. domestic spending), sterilization, excess capacity, and composition of expenditures.
    - IMF (2005): absence of exchange rate appreciation in five African countries after aid surges; attributed to authorities restricting aid absorption.
  - Country and regional studies: mixed results across studies for aid and remittances (examples: Sri Lanka, Ghana, Cape Verde, Tanzania).
- Gaps identified in literature:
  - Limited multi-flow, multi-region analyses; ambiguous and sometimes contradictory results across flows, countries, regions, and econometric methods.

### III. Capital flows and other REER determinants (empirical framework and data)
- Empirical model:
  - Baseline specification: REER_{i,t} = α1 + α2 Capital Flows_{i,t} + α3 Policy_{i,t} + α4 Control_{i,t} + ε_{i,t}
    - i indexes country, t indexes time.
  - Variants of equation (1) depend on error term assumptions and exogeneity of independent variables.
- Data sources:
  - Capital and foreign exchange flows: balance of payments data reported in the International Financial Statistics.
  - Control variables and policy variables: World Economic Outlook (WEO) database.
  - REER indices: IMF INS database.
- Sample details reiterated:
  - 57 developing countries (Appendix 1).
  - Six regions analyzed separately: Africa, CEEC, South and East Asia, GCC, Latin America, MENA.
  - Sample period: 1980 to 2007.
  - Year 2000 used as a common base year for REER comparisons across countries.
- Stylized REER regional patterns (1980s–2000s):
  - General: REER depreciated from 1980 to early 1990s across regions.
  - Post-1990s:
    - Latin America, GCC, and Africa: REER stabilized.
    - Asia: REER depreciation during the Asian crisis.
    - MENA: strong appreciation during the first Gulf war in 1991.
    - CEEC: continuous REER appreciation since early-1990s economic transformation.
- Econometric approach:
  - GMM estimator used to tackle omitted variable and endogeneity biases common in REER–capital flow literature.
- Research objective restated:
  - Identify the degree to which each type of inflow affects the REER and compare impacts across different regions.

### IV. Key empirical findings and implications (as presented)
- Aggregate headline:
  - Aggregated capital flows tend to appreciate REER, but disaggregated analysis reveals heterogeneous effects by flow type and region.
- Principal flow-specific finding highlighted:
  - FDI:
    - Does not lead to REER appreciation in almost all regions.
    - Leads to REER depreciation in the CEEC and MENA.
    - Policy implication: supports policies that encourage FDI as a means to improve competitiveness and mitigate negative effects of aggregated capital inflows on REER appreciation.
- Other flows: evidence and considerations summarized from literature (as context for interpretation):
  - Remittances: strong evidence in many studies of REER appreciation (e.g., doubling transfers → 22 percent appreciation in one panel), but some studies find no effect depending on expenditure patterns.
  - Aid: generally associated with REER appreciation in several studies (e.g., 10 percent aid increase → 1 percent REER rise), but results are conditional on how aid is spent, sterilization, excess capacity, and policy responses; mixed results across studies and samples.
  - Portfolio and other investment flows: limited and mixed evidence; impact depends on whether flows finance tradable-sector modernization or finance nontradables/consumption/speculation.
  - Income flows: understudied; impact depends on domestic spending versus reinvestment abroad and on exchange rate and sterilization policies.
- Policy-relevant mechanisms emphasized:
  - The effect of a given inflow on REER depends crucially on:
    - The expenditure composition of the inflow (imports vs. domestic nontradables vs. tradable investment).
    - Exchange rate regime and sterilization of central bank interventions.
    - Presence of excess capacity and supply responses in nontradable sectors.
    - Sectoral allocation (tradable vs. nontradable, capital goods vs. consumption).
- Empirical contribution claim:
  - The paper fills a gap by providing a comprehensive multi-flow, multi-region panel analysis using GMM on a large sample of developing countries.

*Source: _wp10154 - References .............................................................................................................*

### Appendix 2 provides the definition and data sources for the variables used in the paper.

### _wp10154 - Appendix 2 provides the definition and data sources for the variables used in the paper.

### B. Capital and Foreign Exchange Flows Variables
- Definition and aggregation:
  - Net capital flows (NKF) = sum of six variables: income, remittances, aid (current account) and FDI, portfolio investments, other investments (financial account).
  - The sum of these six variables equals the inverse sign of the balance of goods and services after subtracting the change in reserves (to obtain total capital and foreign exchange flows without central bank intervention).
- Regional patterns (1980–2007):
  - GCC exhibited massive capital outflows reaching almost 27 percent of GDP; 1991 is a recurrent outlier for the GCC.
  - MENA: NKF/GDP oscillated on average between 10 and 20 percent.
  - Africa: second highest NKF/GDP over the period, joined by CEEC by end of period.
  - South and East Asia and Latin America: NKF/GDP oscillated between +/- 5 percent.
- Current account components:
  - Income:
    - GCC reached almost 18 percent of GDP in the early 1980s.
    - In most other regions income was negative (higher interest paid on debt than returns on investments).
  - Aid (public official current transfers, AID, % of GDP):
    - Africa received the highest ratios, reaching more than 6 percent in 1993.
    - Ordering by received aid ratios: Africa, MENA, CEEC (since 1992), Latin America, South and East Asia.
  - Remittances (private unilateral transfers, % of GDP):
    - All regions except GCC have increasing or stable remittances.
    - GCC remittances outflows between 5 and 10 percent of GDP (foreign labor effect).
    - MENA: more than 5 percent of GDP since early 1990s; Africa ~3 percent; then South and East Asia, Latin America, CEEC.
- Financial account components:
  - FDI:
    - FDI/GDP < 2 percent in the 1980s; picked up in early 1990s.
    - Since late 1990s CEEC were on average highest receivers of FDI, followed by Latin America, MENA (share increasing), South and East Asia, Africa, GCC.
  - Portfolio investments (PORT, % of GDP):
    - GCC: increasing portfolio investment outflows since 1996, reaching more than 16 percent of GDP (sovereign wealth funds investing oil revenues).
    - Other regions: increasing portfolio inflows since early 1990s but never exceeded 2 percent of GDP.
    - Episodes of massive outflows: Asia (1997–1998), Latin America (2003–2004), CEEC (2005). MENA and Africa experienced outflows but not exceeding 1 percent of GDP.
  - Other net investments (DEBT, proxy for net borrowing, % of GDP):
    - GCC outlier in 1991; prior to 1991 GCC had negative DEBT ratios (lending abroad).
    - 1980s–1990s: Africa was principal recipient of DEBT reaching almost 9 percent of GDP; other regions < 5 percent.
    - Since then: Asian countries started lending (exports of debt capital reaching 5 percent of GDP), followed by Latin America in some years, and Africa experienced massive debt outflows in 2006.
    - CEEC debt flows increased continuously since 2002, reaching almost 10 percent of GDP in 2007.

### C. Control Variables (definitions and theoretical impacts)
- Government Consumption (GCON):
  - GCON = logarithm of public consumption expenditure as a percent of GDP.
  - Theoretical impact on REER ambiguous:
    - If public spending biased toward nontradables → REER appreciation.
    - In non-industrialized countries, higher public wages may raise private spending on tradables → REER depreciation.
    - Increased government spending could deteriorate fiscal balance → downward pressure on exchange rate.
- Trade Openness (OPEN and IMP):
  - OPEN = typically (exports + imports)/GDP; impact on REER mixed.
  - Alternative proxy to avoid misinterpretation for oil exporters: IMP = imports/GDP.
- Productivity (PROD):
  - PROD = real GDP per capita (proxy for Balassa-Samuelson effect).
  - Higher per capita incomes expected to be associated with real appreciation.
- Terms of Trade (TOT):
  - Shocks to TOT may induce REER movements; increases in export prices relative to import prices can lead to REER appreciation.

### IV. Empirical Methodology
- Model specification:
  - All variables logged except capital and foreign exchange flows (which can be negative).
  - Estimated equation (as specified in source):
    - Ln REER_it = α0 + α1 Ln REER_{i,t-1} + α2 Capital Flows_it + α3 Ln GCON_it + α4 Ln OPEN_it + α5 Ln PROD_it + α6 Ln TOT_it + ε_it
  - Sample: i = 1,...,57 developing economies (Appendix 1); t = 1980 to 2007 (T=27).
  - Different capital and foreign exchange flows are incorporated alternatively according to regression specification.
- Estimator choice and rationale:
  - Use Generalized Method of Moments (GMM), specifically system GMM (Arellano and Bover (1995), Blundell and Bond (1998)):
    - Corrects for omitted variable and endogeneity biases.
    - Deals with dynamics of REER and potential unit roots.
    - First-differences eliminate country fixed effects; lagged levels used as instruments; equations in first differences and levels jointly estimated.
    - Validity of instruments tested using Hansen (Sargan) test and serial correlation test.
  - Prefer one-step GMM results because two-step estimates are biased in small samples.
  - Note: differencing prevents pinning down long-run relationships among levels; Blundell and Bond procedure provides consistent short-run dynamic estimates.

### V. Interpretation of Results (summary of empirical findings)
- Aggregate NKF (column 1, Table 1):
  - NKF has a positive impact on REER → increase in NKF leads to REER appreciation (possible loss of competitiveness).
  - LTOT and PROD increases → REER appreciation.
  - OPEN and GCON increases → REER depreciation.
  - Reported estimates (Table 1, column 1):
    - Constant: 0.603 (0.437)
    - LagREER: 0.785*** (0.049)
    - LNGDP: 0.134*** (0.031)
    - LTOT: 0.158** (0.074)
    - LGCON: -0.104** (0.049)
    - LOPEN: -0.051* (0.031)
    - NKF: 0.006*** (0.001)
    - Sargan p-value: 0.139
    - Serial correlation p-value: 0.654
    - No. of countries: 57
    - No. of observations: 1347
- Disaggregated flows (column 2, Table 1 and Tables 2–3):
  - In column 2 (Table 1) coefficients (estimates):
    - Constant: 0.311 (0.610)
    - LagREER: 0.751*** (0.057)
    - LNGDP: 0.094*** (0.030)
    - LTOT: 0.224** (0.111)
    - LGCON: -0.064 (0.047)
    - LOPEN: -0.024 (0.027)
    - FDI: 0.002 (0.002)
    - DEBT: 0.003** (0.001)
    - PORT: 0.006*** (0.002)
    - INCOME: 0.009** (0.004)
    - AID: 0.006*** (0.002)
    - REMIT: 0.008* (0.004)
    - Sargan p-value: 0.242
    - Serial correlation p-value: 0.888
    - No. of countries: 57
    - No. of observations: 1313
  - Key interpretations:
    - All capital flows except FDI have a significant positive impact on REER (debt, portfolio, income, aid, remittances consistent with NKF coefficient).
    - FDI has no significant impact on REER in overall sample → short-run appreciation effect may be diluted over time as part of FDI finances imports of machinery/capital goods and increases production, potentially putting downward pressure on prices and REER.
- Regional results (Table 2 highlights):
  - NKF positive and significant impact on REER in all regions except CEEC (for MENA significance at 10 percent).
  - CEEC: NKF coefficient negative and nonsignificant; explanation: large share of FDI relative to other flows counteracts appreciation.
  - FDI: generally nonsignificant (negative but not significant) in Latin America, South and East Asia, CEEC, MENA; nonsignificant positive in GCC; significant positive only in Africa (suggesting loss of competitiveness).
  - DEBT: significant positive impact in all regions except CEEC (CEEC coefficient negative and nonsignificant).
  - PORT:
    - Positive and significant impact on REER in South and East Asia, Latin America, GCC, and CEEC (CEEC at 10 percent).
    - No significant impact in Africa.
    - MENA: significant but negative impact (portfolio inflows associated with privatization-driven modernization and import of machinery → REER depreciation).
  - INCOME: significant positive impact in Latin America and MENA; no impact in Africa, CEEC, South and East Asia.
  - AID: positive and significant in CEEC, GCC, South and East Asia, and Africa; not significant in MENA and Latin America.
  - REMITTANCES:
    - Positive and significant in GCC, South and East Asia, and Africa.
    - Positive and nonsignificant in MENA.
    - Negative and nonsignificant in Latin America.
    - Negative and significant in CEEC.
- Comparative magnitudes (entire sample ranking):
  - Income has the strongest impact on REER appreciation, followed by remittances, aid, portfolio investments, and debt.
  - FDI is the only variable with no significant impact on REER appreciation in the overall sample.

### VI. Conclusion and Policy Implications
- Main contributions:
  - First attempt to compare impacts of different types of capital and foreign exchange flows on competitiveness across 57 developing countries (1980–2007).
- Main findings:
  - Aggregated capital flows (NKF) → positive impact on REER in all regions except CEEC.
  - Disaggregated: income strongest driver of REER appreciation; remittances, aid, portfolio, and debt also associated with appreciation; FDI not associated with REER appreciation (with exception of Africa).
  - Cross-regional heterogeneity:
    - Portfolio, debt, aid, and income generally point to REER appreciation, except portfolio in MENA (negative).
    - Remittances show disparate effects across regions (positive for GCC, South and East Asia, Africa; negative in CEEC; mixed in others).
    - FDI generally not causing REER appreciation and may support competitiveness by not appreciating REER in most regions.
- Policy implications (inferred from findings in source):
  - Policymakers seeking to attract capital and foreign exchange flows to finance current account deficits and enhance investment should consider the heterogeneous effects of different flows on competitiveness:
    - Income, remittances, aid, portfolio investments, and debt are more likely to be associated with REER appreciation (potential competitiveness loss).
    - FDI appears less likely to cause REER appreciation and may be preferable when balancing capital attraction and competitiveness (but Africa shows an exception).
  - Regional policy design should account for the nature, size, and channels of flows, the degree of financial market development, and possible use of inflows (e.g., accumulation in reserves vs. spending on imports).
- Research implications:
  - Disparate regional results call for further investigation into factors explaining heterogeneity: shocks/crises, policy responses, level of development, institutional quality, and financial market sophistication.

*Italic: Source — _wp10154 - Appendix 2 provides the definition and data sources for the variables used in the paper.*

### Appendix 1: List of Countries Included in our Sample

### Appendix 1: List of Countries Included in our Sample

### Sample composition by region
- Africa
  - Cameroun
  - Côte d'Ivoire
  - Ghana
  - Kenya
  - Mali
  - Mozambique
  - Nigeria
  - Senegal
  - South Africa
  - Tanzania
  - Zambia
- CEEC
  - Bulgaria
  - Croatia
  - Czech Rep.
  - Estonia
  - Hungary
  - Latvia
  - Lithuania
  - Poland
  - Romania
  - Slovak Rep.
  - Slovenia
- South and East Asia
  - China
  - India
  - Indonesia
  - Korea
  - Malaysia
  - Pakistan
  - Philippines
  - Singapore
  - Thailand
- Latin America
  - Argentina
  - Bolivia
  - Brazil
  - Chile
  - Colombia
  - Ecuador
  - Mexico
  - Peru
  - Uruguay
  - Venezuela
- MENA
  - Egypt
  - Iran
  - Jordan
  - Lebanon
  - Morocco
  - Sudan
  - Syria
  - Tunisia
  - Turkey
- GCC
  - Bahrain
  - Kuwait
  - Oman
  - Qatar
  - Saudi Arabia
  - UAE

### Notes on Appendix 1
- The list presents country coverage used in the sample, organized by regional grouping exactly as shown.

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### Appendix 2: List of Variables Included in the Regressions

### Variables, definitions, and sources
- REER
  - Real Effective Exchange Rate Index
  - Source: IMF Staff database
- GCON
  - Government Consumption = Public Consumption Expenditure / GDP (current, local currency)
  - Source: Authors’ Calculation based on WEO data
- PROD
  - Productivity = Real GDP per Capita
  - Source: WEO
- LIQ
  - Liquidity = Broad Money / GDP (current, local currency)
  - Source: Authors’ Calculation based on WEO data
- TOT
  - Terms of Trade (Price of Exports to the Price of Imports), Index 2000=1
  - Source: WEO
- OPEN
  - Degree of Openness = (Imports + Exports) / GDP  (Constant, Local Currency)
  - Source: Authors’ Calculation based on WEO data
- IMP
  - Degree of Openness = Imports / GDP  (Constant, Local Currency)
  - Source: Authors’ Calculation based on WEO data
- NKF
  - Net Capital Flows = Balance of goods and services [- (Exports . Imports) / GDP] - Change in Gross international reserves (including gold, in current US Dollars] / GDP (Current, Billion USD)
  - Source: Authors’ Calculation based on WEO data
- FDI
  - FDI = Foreign Direct investments / GDP (Current, USD)
  - Source: Authors’ Calculation based on IFS data
- PORT
  - Portfolio = Portfolio investments / GDP (Current, USD)
  - Source: Authors’ Calculation based on IFS data
- DEBT
  - Debt (Other Investments in the Financial Account)= Other investments / GDP (Current, USD)
  - Source: Authors’ Calculation based on IFS data
- INCOME
  - Income (Current Account) = Income / GDP (Current, USD)
  - Source: Authors’ Calculation based on IFS data
- AID
  - Aid = Official unrequited transfers (Current Account)  / GDP (Current, USD)
  - Source: Authors’ Calculation based on IFS data
- REMIT
  - Remittances = Other unrequited transfers (Current Account) / GDP (Current, USD)
  - Source: Authors’ Calculation based on WEO data

*Appendix 1 and Appendix 2, as presented in the source PDF.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2010/_wp10154.pdf_