## _wp03228

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---

### I. INTRODUCTION
- Objective: investigate the importance of institutions and agglomeration vis-à-vis initial conditions and factor endowments as determinants of FDI for 25 transition economies in Central Europe and the former Soviet Union during 1990–98.
- Natural-experiment rationale: nearly thirty centrally planned economies began transition nearly simultaneously but with substantial variation in inherited institutions, initial conditions, income levels, and reform paths.
- Contextual facts:
  - Between 1990 and 1994, transition economies received 2.1 percent of global FDI inflows; Latin America received about 10 percent; Asia received about 20 percent (UNCTAD, 2002).
  - Between 1995 and 1999, transition economies received 3.2 percent of global FDI inflows; Latin America about 12 percent; Asia about 16 percent (UNCTAD, 2002).
  - CEEB per capita concentration: between 1990 and 1994, the CEEB received 95 percent of total per capita FDI to transition countries; between 1995 and 1998 the CEEB share declined but was still 84 percent.
- Contribution: expands prior work by including an array of institutional measures and covering 25 transition economies rather than focusing only on corruption or more advanced CEEB countries.

### II. LITERATURE REVIEW — conceptual determinants of FDI
- Typology of FDI drivers:
  - Market-seeking (horizontal): market size and market growth; tariffs and transport costs.
  - Resource-/asset-seeking: natural resource abundance and low-cost labor for export-oriented vertical FDI.
  - Efficiency-seeking: economies of scale and scope; proximity and integration (e.g., EU accession).
- Agglomeration economies: new investors follow prior investors to capture knowledge spillovers, specialized labor pools, and intermediate-input linkages (references: Marshall, Krugman; Wheeler and Mody; Head, Ries, and Swenson).
- Institutions: good legal institutions, lower corruption, efficient bureaucracy promote investment and growth (Mauro; La Porta and others; Wei).
- Key hypothesis: institutions and agglomeration may be as important, or more so, than classical determinants (market size, factor costs, natural resources) in attracting FDI to transition economies.

### III. DATA AND ESTIMATION
- Sample and period:
  - Panel of 25 transition countries between 1990 and 1998; complete panel size = 225 (= 25x9), data used for estimation are unbalanced.
  - Economies covered include: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovak Republic, Slovenia, Ukraine, Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyz Republic, Moldova, the Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.
- Dependent variable:
  - Per capita FDI stock in real millions of U.S. dollars (deflated by the GDP deflator), constructed from WDI FDI inflows.
- Key explanatory variable groups and definitions:
  - Classical comparative-advantage variables:
    - Market size: RGDPCH (real per capita GDP, chain method; base year 1996) [Penn World Table 6].
    - Labor cost: WAGEN (gross nominal wage) [UNECE Economic Survey of Europe].
    - Education: EDU (general secondary school enrolment, %) [UNICEF].
    - Natural resources: NATRES dummy (=0 poor, =1 moderate, =2 rich) [De Melo and others (1997)].
    - Distance: DISB (distance in km from Brussels to capital).
    - Infrastructure: TELEPHON (main telephone lines per 1,000 people) [WDI].
  - Macroeconomic policy and reform:
    - Inflation: INFAV (annual average inflation rate, %).
    - External liberalization: CLIE (cumulative external liberalization index).
    - FDI restrictions: RES (index of FDI restrictions) [Garibaldi and others (2001)].
    - Trade dependence: TRADDEP (trade as share of GDP in 1989).
  - Institutions:
    - Rule of law: RULELAW (strength and impartiality of legal system) [ICRG].
    - Quality of bureaucracy: BUROQUAL (autonomy, recruitment/training, ease of regulations) [Campos (2000)].
  - Agglomeration:
    - Lagged FDI stock (one-year lag) used as aggregate measure of agglomeration/existing FDI.
- Estimation strategy:
  - Partial-adjustment model where current FDI stock adjusts toward an equilibrium Y* determined by X variables.
  - Model includes lagged dependent variable; OLS is inconsistent due to correlation with time-invariant country effects.
  - First-differencing yields equation estimated by instrumental variables / generalized method of moments (GMM) following Arellano and Bond (1991).
  - Valid instruments: lagged levels of dependent variable (Y_{t-s}, s ≥ 2); if X strictly exogenous, lagged X can be instruments.
  - Sargan test for over-identifying restrictions and Arellano-Bond SOC test for second-order autocorrelation are used for instrument validity and error autocorrelation checks.
  - Fixed-effects models reported alongside GMM due to potential small-sample bias in GMM.
- Treatment of time-invariant variables: multiplied by a time trend to avoid dropping out in first differencing.

### IV. RESULTS — main econometric findings
- Dynamic (lagged FDI stock) and adjustment:
  - FE: Lagged FDI stock δ = 0.81 (0.05)*** → partial adjustment coefficient α = 0.19 and a roughly five-year adjustment to steady state.
  - GMM: δ = 0.75 (0.07)*** and δ = 0.79 (0.06)***; GMM partial-adjustment α ranges 0.21 to 0.25.
- Classical comparative-advantage variables:
  - Market size: coefficient 0.01 (elasticity interpretation in text: 1% increase in real GDP → 0.1% increase in per capita FDI); becomes insignificant in GMM.
  - Labor cost: negative and significant; examples: -0.13 (0.06)** (FE), -0.17 (0.07)** and -0.13 (0.06)** (GMM).
  - Natural resources: positive and robust; examples: 13.49 (4.25)*** (FE), 18.22 (5.59)*** and 14.61 (4.96)*** (GMM).
  - Education and telephone lines: statistically insignificant in pooled regressions (telephone lines show some significance in GMM).
- Policy, reform, and institutional variables:
  - External liberalization: large positive effect; examples: 40.48 (20.37)* (FE), 41.71 (20.86)** (GMM).
  - Rule of law: positive and significant in FE and one GMM; examples: 6.35 (3.74)* (FE); 7.27 (4.28)* (GMM).
  - Quality of bureaucracy: strongly positive and significant; examples: 28.62 (13.04)** (FE); 27.64 (13.32)** (GMM).
  - Trade dependence: positive and highly significant; examples: 1.12 (0.26)*** (FE); 1.18 (0.30)*** (GMM).
  - Restrictions on FDI: negative and significant; examples: -8.45 (3.23)** (FE); -8.86 (3.40)*** (GMM).
- Specification tests:
  - GMM column II: Sargan p-value = 0.001 (reject over-identifying restrictions); SOC test does not show second-order serial correlation.
  - GMM column III (market size and labor cost treated as predetermined): Sargan p-value = 0.906 (cannot reject validity of instruments).
- Heterogeneity: non-CIS (CEEB) vs. CIS country group results
  - Non-CIS (manufacturing-oriented) — selected exact coefficients:
    - Lagged FDI stock 0.54 (0.12)*** (GMM).
    - External liberalization 313.73 (131.64)** (GMM).
    - Rule of law 31.27 (14.06)** (GMM).
    - Quality of bureaucracy 56.38 (22.19)** (GMM).
    - Restrictions on FDI -20.38 (7.49)*** (GMM).
    - Natural resources: insignificant for non-CIS.
    - Distance from Brussels: positive and significant (e.g., 0.05 (0.02)**).
  - CIS (resource-oriented) — selected exact coefficients:
    - Natural resources 51.20 (10.46)*** (GMM); 51.20 (9.20)*** (FE).
    - Telephone lines 3.22 (1.06)*** (GMM); 3.22 (0.93)*** (FE).
    - External liberalization 142.35 (34.17)*** (GMM).
    - Rule of law 26.82 (7.70)*** (GMM).
    - Quality of bureaucracy 44.51 (20.14)** (GMM).
    - Trade dependence 4.99 (1.19)*** (GMM).
    - Restrictions on FDI -23.00 (7.74)*** (GMM).
    - Distance from Brussels: negative and significant (e.g., -0.018 (0.008)** (GMM)).
    - Agglomeration effect: not present for CIS in GMM.
- Robustness and interpretation notes:
  - Some variables (market size, labor cost) lose significance when reform, policy, and institutional variables are included; potential endogeneity addressed by treating them as predetermined in some GMM specifications.
  - Positive coefficient on inflation may reflect endogeneity with reform variables (disinflation often preceded liberalization).
- Selected pooled exact coefficients and standard errors (Tables):
  - Pooled FE: Lagged FDI stock 0.81 (0.05)***; Natural resources 13.49 (4.25)***; Quality of bureaucracy 28.62 (13.04)**; Trade dependence 1.12 (0.26)***; Restrictions on FDI -8.45 (3.23)**.
  - Pooled GMM (column III): Lagged FDI stock 0.79 (0.06)***; Natural resources 14.61 (4.96)***; Quality of bureaucracy 27.64 (13.32)**; Trade dependence 1.18 (0.30)***; Restrictions on FDI -8.86 (3.40)***.

### V. CONCLUSIONS — synthesis and policy implications
- Principal conclusion: institutions and agglomeration economies are the most important determinants of FDI location among transition economies and outweigh many traditional economic variables.
- Additional findings:
  - Natural resources and low labor costs also attract FDI at the region level; natural resources particularly important for CIS countries.
  - Poor quality of the bureaucracy and weak rule of law deter FDI.
  - Greater trade openness (trade dependence) and progress in external liberalization (CLIE) strongly increase FDI inflows.
  - Restrictions on FDI effectively deter inward FDI.
- Policy recommendations:
  - Strengthen institutions: improve rule of law and bureaucracy quality to lower non-economic transaction costs and attract more FDI.
  - Continue external liberalization and trade reforms to complement FDI inflows and reduce bureaucratic discretion that fosters corruption.
  - For CIS/resource-rich countries: leverage natural-resource-driven FDI to expand into other sectors (e.g., manufacturing) and invest in basic infrastructure (telephone lines) while sustaining institutional reforms to maintain FDI as resource rents evolve.
  - Recognize agglomeration dynamics in non-CIS countries: policies that facilitate early entrants and clustering in manufacturing can amplify future FDI.
- Caution: determinants differ between non-CIS (manufacturing-oriented) and CIS (resource-oriented) countries; tailored policy mixes are needed.

### APPENDIX I — Selected summary statistics (exact figures)
- FDI stock per capita: Obs 188; Mean 164; Std. Dev. 295; Min 0; Max 1771.
- Lagged FDI stock: Obs 163; Mean 131; Std. Dev. 250; Min 0; Max 1572.
- Market size: Obs 165; Mean 6955; Std. Dev. 3249; Min 1012; Max 15170.
- Labor cost: Obs 151; Mean 167; Std. Dev. 217; Min 0.02; Max 1247.
- Education: Obs 225; Mean 19; Std. Dev. 8; Min 4.4; Max 51.
- Natural resources: Obs 225; Mean 0.52; Std. Dev. 0.75; Min 0; Max 2.
- Distance Brussels: Obs 225; Mean 2222; Std. Dev. 1387; Min 719; Max 522.
- Telephone lines: Obs 219; Mean 162; Std. Dev. 88; Min 0; Max 374.
- Inflation: Obs 225; Mean 434; Std. Dev. 1304; Min -0.8; Max 15606.
- External liberalization: Obs 225; Mean 2.74; Std. Dev. 2.45; Min 0; Max 9.5.
- Rule of law: Obs 171; Mean 4.47; Std. Dev. 0.75; Min 3; Max 6.
- Quality of bureaucracy: Obs 225; Mean 2.45; Std. Dev. 1.63; Min 0.83; Max 8.33.
- Trade dependence: Obs 211; Mean 19; Std. Dev. 12; Min 0; Max 41.
- Restrictions to FDI: Obs 223; Mean 1.66; Std. Dev. 0.94; Min -0.03; Max 3.37.

*Content derived from _wp03228 - References (IMF working paper PDF) — sections I–V, Tables 1–4, Appendix I as supplied.*

### 1. Definitions of Variables ............................................................................................

### _wp03228 - 1. Definitions of Variables ............................................................................................

### 1. Definitions of Variables
- Listed on page 22.

### 2. Determinants of FDI: Fixed Effects Model and GMM
- Listed on page 23.

### 3. Determinants of FDI: GMM
- Listed on page 24.

### 4. Determinants of FDI: Fixed Effects Model
- Listed on page 25.

### Appendices
- I. Summary Statistics — listed on page 26.
- II. Correlation Matrix — listed on page 27.

*Source: _wp03228 - 1. Definitions of Variables (PDF chapter/section).*

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

### _wp03228 - References..............................................................................................................

### I. INTRODUCTION
- Objective: investigate the importance of institutions and agglomeration vis-à-vis initial conditions and factor endowments as determinants of FDI for 25 transition economies in Central Europe and the former Soviet Union during 1990–98.
- Natural-experiment rationale: nearly thirty centrally planned economies began transition nearly simultaneously but with substantial variation in inherited institutions, initial conditions, income levels, and reform paths.
- Contextual facts:
  - Between 1990 and 1994, transition economies received 2.1 percent of global FDI inflows; Latin America received about 10 percent; Asia received about 20 percent (UNCTAD, 2002).
  - Between 1995 and 1999, transition economies received 3.2 percent of global FDI inflows; Latin America about 12 percent; Asia about 16 percent (UNCTAD, 2002).
  - CEEB per capita concentration: between 1990 and 1994, the CEEB received 95 percent of total per capita FDI to transition countries; between 1995 and 1998 the CEEB share declined but was still 84 percent.
- Key prior findings and gaps: prior work often focused on corruption only or on the more advanced CEEB countries; this paper adds an array of institutional measures and covers a broader set of 25 transition economies.

### II. LITERATURE REVIEW — conceptual determinants of FDI
- Types of FDI and their main host-country drivers:
  - Market-seeking (horizontal): driven by market size and market growth; tariffs and transport costs matter.
  - Resource-/asset-seeking: driven by natural resource abundance and low-cost labor for export-oriented vertical FDI.
  - Efficiency-seeking: driven by economies of scale and scope; proximity and integration (e.g., EU accession) matter.
- Agglomeration economies: new investors follow prior investors to capture knowledge spillovers, specialized labor pools, and intermediate-input linkages (Marshall, Krugman; Wheeler and Mody; Head, Ries, and Swenson).
- Institutions: good legal institutions, lower corruption, efficient bureaucracy promote investment and growth (Mauro; La Porta and others; Wei).
- Hypothesis emphasized: institutions and agglomeration may be as important, or more so, than classical determinants (market size, factor costs, natural resources) in attracting FDI to transition economies.

### III. DATA AND ESTIMATION
- Sample and period:
  - Panel of 25 transition countries between 1990 and 1998; complete panel size = 225 (= 25x9), data used for estimation are unbalanced.
  - Economies covered include: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovak Republic, Slovenia, Ukraine, Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyz Republic, Moldova, the Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.
- Dependent variable:
  - Per capita FDI stock in real millions of U.S. dollars (deflated by the GDP deflator), constructed from WDI FDI inflows.
- Key explanatory variable groups and variable definitions (see Table 1):
  - Classical comparative-advantage variables:
    - Market size: RGDPCH (real per capita GDP, chain method; base year 1996) [Penn World Table 6].
    - Labor cost: WAGEN (gross nominal wage) [UNECE Economic Survey of Europe].
    - Education: EDU (general secondary school enrolment, %) [UNICEF].
    - Natural resources: NATRES dummy (=0 poor, =1 moderate, =2 rich) [De Melo and others (1997)].
    - Distance: DISB (distance in km from Brussels to capital).
    - Infrastructure: TELEPHON (main telephone lines per 1,000 people) [WDI].
  - Macroeconomic policy and reform:
    - Inflation: INFAV (annual average inflation rate, %).
    - External liberalization: CLIE (cumulative external liberalization index).
    - FDI restrictions: RES (index of FDI restrictions) [Garibaldi and others (2001)].
    - Trade dependence: TRADDEP (trade as share of GDP in 1989).
  - Institutions:
    - Rule of law: RULELAW (strength and impartiality of legal system) [ICRG].
    - Quality of bureaucracy: BUROQUAL (autonomy, recruitment/training, ease of regulations) [Campos (2000)].
  - Agglomeration:
    - Lagged FDI stock (one-year lag) used as aggregate measure of agglomeration/existing FDI.
- Estimation strategy:
  - Partial-adjustment model where current FDI stock adjusts toward an equilibrium Y* determined by X variables.
  - Model includes lagged dependent variable; OLS is inconsistent due to correlation with time-invariant country effects.
  - First-differencing yields equation estimated by instrumental variables / generalized method of moments (GMM) following Arellano and Bond (1991).
  - Valid instruments: lagged levels of dependent variable (Y_{t-s}, s ≥ 2); if X strictly exogenous, lagged X can be instruments.
  - Sargan test for over-identifying restrictions and Arellano-Bond SOC test for second-order autocorrelation are used for instrument validity and error autocorrelation checks.
  - Fixed-effects models reported alongside GMM due to potential small-sample bias in GMM.

### IV. RESULTS — main econometric findings
- Sample-wide findings (Tables 2; fixed-effects and two GMM specifications):
  - Lagged FDI stock (δ):
    - FE: 0.81 (0.05)*** — implies partial adjustment coefficient α = 0.19 and a roughly five-year adjustment to steady state.
    - GMM columns: δ ranges 0.75 (0.07)*** and 0.79 (0.06)***; GMM partial-adjustment α ranges 0.21 to 0.25.
  - Classical variables:
    - Market size: coefficient 0.01 (elasticity interpretation in text: 1% increase in real GDP → 0.1% increase in per capita FDI); becomes insignificant in GMM.
    - Labor cost: negative and significant; labor-cost coefficient examples: -0.13 (0.06)** (FE), -0.17 (0.07)** and -0.13 (0.06)** (GMM).
    - Natural resources: positive and robust; e.g., 13.49 (4.25)*** (FE), 18.22 (5.59)*** and 14.61 (4.96)*** (GMM).
    - Education and telephone lines: statistically insignificant in pooled regressions (though telephone lines show some significance in GMM).
  - Policy, reform, and institutional variables:
    - External liberalization: large positive effect; examples: 40.48 (20.37)* (FE), 41.71 (20.86)** (GMM).
    - Rule of law: positive and significant in FE and one GMM (e.g., 6.35 (3.74)* (FE); 7.27 (4.28)* (GMM)).
    - Quality of bureaucracy: strongly positive and significant (e.g., 28.62 (13.04)** (FE); 27.64 (13.32)** (GMM)).
    - Trade dependence: positive and highly significant (e.g., 1.12 (0.26)*** (FE); 1.18 (0.30)*** (GMM)).
    - Restrictions on FDI: negative and significant (e.g., -8.45 (3.23)** (FE); -8.86 (3.40)*** (GMM)).
  - Specification tests:
    - GMM column II: Sargan p-value = 0.001 (reject over-identifying restrictions), SOC test does not show second-order serial correlation.
    - GMM column III (market size and labor cost treated as predetermined): Sargan p-value = 0.906 (cannot reject validity of instruments).
- Group-wise results: non-CIS (CEEB) vs. CIS countries (Tables 3 and 4)
  - Non-CIS (manufacturing-oriented) findings:
    - Agglomeration effect present: Lagged FDI stock 0.54 (0.12)*** (GMM).
    - External liberalization, rule of law, quality of bureaucracy, and fewer FDI restrictions are significant drivers.
    - Natural resources insignificant for non-CIS.
    - Distance from Brussels: positive and significant in FE and GMM (e.g., 0.05 (0.02)** in FE and GMM) — note the positive sign reported for distance in non-CIS group.
  - CIS (resource-oriented) findings:
    - Natural resources strong driver: NATRES 51.20 (10.46)*** (GMM); 51.20 (9.20)*** (FE).
    - Telephone lines significant: 3.22 (1.06)*** (GMM); 3.22 (0.93)*** (FE).
    - Trade dependence strongly significant: 4.99 (1.19)*** (GMM); 4.99 (1.05)*** (FE).
    - Distance from Brussels: negative and significant in CIS (e.g., -0.018 (0.008)** (GMM); -0.01 (0.007)** (FE).
    - Agglomeration effect not present for CIS in GMM.
    - External liberalization, rule of law, quality of bureaucracy, and restrictions on FDI also matter for CIS.
- Robustness and interpretation notes:
  - Some variables (market size, labor cost) lose significance in the presence of reform, policy, and institutional variables; potential endogeneity concerns addressed by treating them as predetermined in some GMM specifications.
  - Positive coefficient on inflation is surprising and may be due to endogeneity with reform variables (disinflation often preceded liberalization).
  - Time-invariant variables were transformed (multiplied by a time trend) because they drop out in first differencing.
- Summary of quantitative magnitudes (selected exact coefficients and standard errors from Tables):
  - Pooled FE: Lagged FDI stock 0.81 (0.05)***; Natural resources 13.49 (4.25)***; Quality of bureaucracy 28.62 (13.04)**; Trade dependence 1.12 (0.26)***; Restrictions on FDI -8.45 (3.23)**.
  - Pooled GMM (column III): Lagged FDI stock 0.79 (0.06)***; Natural resources 14.61 (4.96)***; Quality of bureaucracy 27.64 (13.32)**; Trade dependence 1.18 (0.30)***; Restrictions on FDI -8.86 (3.40)***.
  - Non-CIS GMM: Lagged FDI stock 0.54 (0.12)***; External liberalization 313.73 (131.64)**; Rule of law 31.27 (14.06)**; Quality of bureaucracy 56.38 (22.19)**; Restrictions on FDI -20.38 (7.49)***.
  - CIS GMM: Natural resources 51.20 (10.46)***; Telephone lines 3.22 (1.06)***; External liberalization 142.35 (34.17)***; Rule of law 26.82 (7.70)***; Quality of bureaucracy 44.51 (20.14)**; Trade dependence 4.99 (1.19)***; Restrictions on FDI -23.00 (7.74)***.
- Appendix summary statistics (selected exact figures):
  - FDI stock per capita: Obs 188; Mean 164; Std. Dev. 295; Min 0; Max 1771.
  - Lagged FDI stock: Obs 163; Mean 131; Std. Dev. 250; Min 0; Max 1572.
  - Market size: Obs 165; Mean 6955; Std. Dev. 3249; Min 1012; Max 15170.
  - Labor cost: Obs 151; Mean 167; Std. Dev. 217; Min 0.02; Max 1247.
  - Education: Obs 225; Mean 19; Std. Dev. 8; Min 4.4; Max 51.
  - Natural resources: Obs 225; Mean 0.52; Std. Dev. 0.75; Min 0; Max 2.
  - Distance Brussels: Obs 225; Mean 2222; Std. Dev. 1387; Min 719; Max 522.
  - Telephone lines: Obs 219; Mean 162; Std. Dev. 88; Min 0; Max 374.
  - Inflation: Obs 225; Mean 434; Std. Dev. 1304; Min -0.8; Max 15606.
  - External liberalization: Obs 225; Mean 2.74; Std. Dev. 2.45; Min 0; Max 9.5.
  - Rule of law: Obs 171; Mean 4.47; Std. Dev. 0.75; Min 3; Max 6.
  - Quality of bureaucracy: Obs 225; Mean 2.45; Std. Dev. 1.63; Min 0.83; Max 8.33.
  - Trade dependence: Obs 211; Mean 19; Std. Dev. 12; Min 0; Max 41.
  - Restrictions to FDI: Obs 223; Mean 1.66; Std. Dev. 0.94; Min -0.03; Max 3.37.

### V. CONCLUSIONS — synthesis and policy implications
- Principal conclusion: institutions and agglomeration economies are the most important determinants of FDI location among transition economies and outweigh many traditional economic variables.
- Additional findings:
  - Abundance of natural resources and low labor costs also attract FDI at the region level, with natural resources particularly important for CIS countries.
  - Poor quality of the bureaucracy and weak rule of law deter FDI.
  - Greater trade openness (trade dependence) and progress in external liberalization (CLIE) strongly increase FDI inflows.
  - Restrictions on FDI effectively deter inward FDI.
- Policy implications:
  - Strengthen institutions: improve rule of law and bureaucracy quality to lower non-economic transaction costs and attract more FDI.
  - Continue external liberalization and trade reforms to complement FDI inflows and reduce bureaucratic discretion that fosters corruption.
  - For CIS/resource-rich countries: leverage natural-resource-driven FDI to expand into other sectors (e.g., manufacturing) and invest in basic infrastructure (telephone lines) while sustaining institutional reforms to maintain FDI as resource rents evolve.
  - Recognize agglomeration dynamics in non-CIS countries: early FDI can create self-reinforcing clustering benefits—policies that facilitate early entrants and clustering in manufacturing can amplify future FDI.
- Heterogeneity caution: determinants differ between non-CIS (manufacturing-oriented) and CIS (resource-oriented) countries; tailored policy mixes are needed.

*Italicized attribution: Content derived from _wp03228 - References (IMF working paper PDF) — sections I–V, Tables 1–4, Appendix I as supplied.*

### APPENDIX II

### APPENDIX II

### References

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*APPENDIX II*

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