## _wp11294

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---

### Introduction and key conclusions
- Context and motivation
  - Inflation differentials across the Gulf Cooperation Council (GCC) countries tightened toward the end of the 1990's but widened after the 2003 upsurge in oil prices as fiscal policy became increasingly expansionary and contributed to rising domestic demand.
  - Minimizing inflation differentials across the GCC is a key convergence criterion for the planned GCC monetary union.
- Principal findings
  - After controlling for cyclical factors, convergence has increased even during the recent oil boom.
  - Inflation dynamics in the GCC are largely driven by the oil cycle, mainly through the credit and fiscal channels.
  - For a successful monetary union, closer coordination of fiscal policies is critical; avoiding procyclical fiscal policy will require a strong medium-term framework to reduce the risk of overheating and avoid increased divergence of inflation rates.

### Data and stylized facts
- GCC composition and data coverage
  - GCC comprises Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE).
  - Monthly CPI data used: January 1991–June 2010 (source: International Monetary Fund (2010b)).
  - Annual data used: 1991–2009 (various IMF databases).
  - Monthly data starting in January 1995 used for CPI index, NEER index, credit to the private sector, rent weight in CPI, and oil revenues (to proxy monthly fiscal activity).
- Macro-variable patterns highlighted (1991–2009)
  - Figures and pairwise differentials reported for: Inflation Rate, Non-oil real GDP growth, Credit growth, Non-oil fiscal balance, NEER growth.
  - Pairwise differentials computed for all 15 country pairs (ordered by GDP weights).

### Convergence of inflation rates (unit-root and stationarity testing)
- Definitions and testing approach
  - Pairwise price-level deviations: x_ijt = ln(CPI_it) - ln(CPI_jt).
  - Inflation differentials: Δx_ijt = π_it - π_jt.
  - Tests: Augmented Dickey-Fuller (ADF) and KPSS stationarity tests to examine absolute convergence (stationarity of pairwise inflation differentials).
- Main empirical results (1991M1–2010M6)
  - 15 pairwise combinations tested.
  - ADF tests: for all 15 pairwise combinations the null of a unit root can be rejected when investigating absolute convergence (0 = α_ij).
  - Two pairwise combinations could not reject the null of non-stationarity under the ADF when allowing for α_ij ≠ 0: Saudi Arabia with the U.A.E., and Qatar with Oman.
  - KPSS tests for these two combinations show that the stricter null of stationarity cannot be rejected for them.
  - Overall evidence points to absolute convergence in the GCC pairwise inflation differentials over the period 1991 to 2010.

### Econometric model and identification strategy
- Structural framework
  - Country inflation specification: p_it driven by a long-run equilibrium price p*_it, country-specific effect α_i, and short-run macro variables z_it (equation (7)).
  - Error term: u_it = f_t' θ_i + ε_it, where f_t are unobserved common shocks and θ_i are idiosyncratic loadings (equation (8)).
- Pairwise-differential formulation
  - Under convergence to a common long-run price level (p*_it = p*_jt), pairwise inflation-differential model reduces to a stationary equation where short-run deviations are explained by deviations in macro variables z_it - z_jt plus idiosyncratic errors (equations (11) and (12)).
- Methodological distinctions
  - Follows Pesaran (2007) and Pesaran et al. (2009) by estimating pairwise inflation differentials directly rather than deviations from a union average.
  - Advantages: relaxes uniform-response assumption to common shocks; avoids imposing equal weights N^{-1} to construct union aggregates; explicitly estimates effects of differences in countries' macro variables (φ and β) on inflation differentials.

### GMM estimation methodology and diagnostics
- Estimation strategy
  - Dynamic panel issues (lagged dependent variables, simultaneity) make standard fixed/random effects inconsistent.
  - First-difference transformation yields an equation with moving-average error structure.
  - Difference GMM (Anderson–Hsiao; Arellano–Bond) used; system GMM (Arellano–Bover; Blundell–Bond) employed to improve efficiency where lagged levels are weak instruments.
- Validity and robustness checks
  - Hansen test of over-identifying restrictions used to test instrument validity.
  - Arellano–Bond style test used to examine absence of serial correlation in transformed errors.
  - Robust two-step standard errors computed with Windmeijer (2005) correction for small sample bias.

### Key empirical findings (summary)
- Evolution of differentials
  - Inflation differentials across the GCC widened over 1991–2009, with a sharp increase between 2003 and 2009, especially for those associated with Qatar and the U.A.E.
  - The lagged price level coefficient is consistently negative and significant across monthly and annual estimations, indicating convergence in GCC inflation rates.
  - Convergence was faster during the oil boom (2003–09) than over the full sample (1991–2009).
- Main drivers (signs as predicted by theory)
  - Positive contributors (widen the inflation gap): non-oil output growth differentials, rent weight (share of rent in CPI), credit growth differentials, government expenditure growth.
  - Negative contributors (close the inflation gap): NEER growth, improvements in non-oil fiscal balances.

### Quantified effects (preserve reported magnitudes)
- Monthly-data estimations (1995M1–2010M6; 2003M1–2010M6 subsample)
  - A ten percentage point increase in oil revenue differentials leads to about a five percent increase in the inflation gap between countries.
  - Rent weight is significant and positive; post-2003 the coefficient on rent weight is roughly twice as large as in the full monthly sample.
  - Credit growth differentials: a 10 percent increase in credit growth implies about a 1 percentage point rise in the inflation gap for the full monthly sample; in the 2003–2010 subsample a 10 percent increase in credit growth leads to about a 1.5 percent increase in inflation differentials.
  - Nominal effective exchange rate coefficient is of expected (negative) sign but insignificant in monthly regressions reported.
- Annual-data estimations (1991–2009; preferred specification equation (20))
  - A 10 percent increase in NEER growth leads to almost an 8 percent decrease in inflation differentials (regression [2.5]).
  - A 10 percent increase in non-oil output growth differentials increases inflation differentials by about 3 percent (regression [2.5]).
  - A 10 percent difference in rent weights leads to a 2.4 percentage point difference in inflation rates (regression [2.5]).
  - A 10 percent credit growth differential widens the inflation gap by about 1 percent (regression [2.5]).
  - A tightening in non-oil fiscal balances by 10 percent reduces the inflation gap by 0.3 percent (regression [2.5]).
- Annual-data estimations for the subsample 2003–09 (Table 11)
  - A 10 percent increase in non-oil output growth or rent weight increases inflation differentials by about 4 percent.
  - A 1 percentage point increase in NEER reduces inflation differentials by almost 1 percent.
  - Every 10 percent increase in credit growth corresponds to a 2 percent increase in inflation differentials.
  - Replacing fiscal balances with government expenditure: a 10 percent increase in government expenditure growth differential widens the inflation gap by 3 percent; government expenditure effects are much larger in the 2003–09 subsample.

### Interpretation and transmission channels
- Oil cycle transmission
  - Oil cycle affects inflation differentials mainly through credit and fiscal channels: higher oil revenues enabled larger government spending on infrastructure and social services, contributing to overheating and heterogeneous inflation outcomes depending on utilization of oil wealth.
  - Rapid credit growth, particularly in Qatar and the U.A.E., amplified domestic demand and widened inflation differentials post-2003.
- Structural factor — rent weight in CPI
  - Higher rent weight (reflecting supply bottlenecks in housing markets) is associated with larger inflation differentials; supply constraints include inadequate past investment, shortages in commercial and residential space, opening real estate to foreign investors, and inflows of expatriate labor.
- NEER channel
  - Appreciation in the NEER is associated with closing inflation gaps; NEER growth has a pronounced negative effect in annual regressions and in the 2003–09 subsample.

### Robustness and specification diagnostics
- Estimation method: two-step system GMM with Windmeijer (2005) small sample robust correction.
- Instruments and serial correlation diagnostics
  - Hansen and second-order serial correlation test statistics are generally well above conventional significance levels across regressions, supporting instrument validity and absence of second-order serial correlation.
  - First-order serial correlation is present (as expected given differenced equations); second-order serial correlation is not detected at conventional levels.
- Robustness checks
  - Results are robust to using monthly vs. annual data.
  - Results are robust to replacing non-oil fiscal balance growth with government expenditure growth.
  - Splitting the sample (full vs. post-2003 subsamples) — magnitudes generally increase post-2003.

### Policy implications and recommendations
- Fiscal policy coordination and countercyclicality
  - Given oil-driven inflation dynamics operating mainly through credit and fiscal channels, closer coordination of fiscal policies across GCC countries is critical for a successful monetary union.
  - Avoiding procyclical fiscal policy is a key challenge; a strong medium-term fiscal framework is recommended to reduce overheating risks and prevent divergence of inflation rates.
  - Strengthening public financial management is a prerequisite for credible fiscal frameworks and for monitoring compliance.
- Macroprudential and structural policies
  - Implement countercyclical macroprudential policies during booms to contain excessive credit growth and limit its contribution to widening inflation differentials.
  - Invest in the expansion of commercial and residential housing supply to alleviate rent-driven inflation pressures and accommodate growing domestic and expatriate populations.
- Monetary union readiness
  - Absolute convergence of pairwise inflation differentials over 1991–2010 supports the pursuit of a monetary union, but heterogeneity in short-run responses implies the need for coordination mechanisms and country-specific safeguards; fiscal coordination and robust fiscal frameworks are essential to sustain price convergence.

*Content summarized from IMF working paper section: 4. Government Expenditure and Oil Revenue (right-scale), 1991–2009, and related sections of the provided IMF working paper excerpt.*

### Introduction ...........................................................................................................

### Introduction

### Document structure and major sections
- Introduction ....................................................................................................................3
- II. Literature Review ........................................................................................................6
- III. Econometric Model and Methodology .......................................................................7
  - A. Convergence of Inflation Rates .........................................................................8
  - B. Econometric Model ..........................................................................................11
  - C. GMM Methodology .........................................................................................13
- IV. Macroeconomic Trends ..........................................................................................15
  - A. Determinants of Inflation Differentials ..........................................................18
- V. Empirical Results ..................................................................................................20
  - A. Analysis Using Monthly Data ..........................................................................20
  - B. Analysis Using Annual Data ............................................................................22
- VI. Concluding Remarks .............................................................................................27
- References ..................................................................................................................28

### Tables (listed in source)
- Table 1. List of the GCC Countries and the Pairwise Combinations ................................................9
- Table 2. Definitions and Sources of Variables Used in the Regression Analyis .............................10
- Table 3. Unit Root and Stationary Test on Pairwise Inflation Differentials, 1991M1–2010M6 ....10
- Table 4. Inflation Differentials Summary Statistics, 1991–2009 ....................................................17
- Table 5. Inflation Differentials Summary Statistics, 1991–2002 ....................................................17
- Table 6. Inflation Differentials Summary Statistics, 1993–2009 ....................................................18
- Table 7. GCC Direction of Trade, 1991–2009 ................................................................................19
- Table 8. Share of Food and Rent in the CPI Basket ........................................................................19
- Table 9. GCC Inflation Differentials, 1995M1–2010M6 ................................................................21
- Table 10. GCC Inflation Differentials, 1991–2009 ...........................................................................23
- Table 11. GCC Inflation Differentials, 2003–09 ...............................................................................26

### Figures (listed in source)
- Figure 1. GCC Countries Macro Variables, 1991–2009 .....................................................................4
- Figure 2. Pairwise Differentials in GCC Countries Macro Variables, 1991–2009 .............................5
- Figure 3. Pairwise Inflation Differentials, 1991–2009 ........................................................................6

*Source: _wp11294 - Introduction (PDF) — table of contents and lists of tables and figures.*

### 4.    Government  Expenditure  and  Oil Revenue (right-scale), 1991–2009 ..............................16

### _wp11294 - 4.    Government  Expenditure  and  Oil Revenue (right-scale), 1991–2009 ..............................16

### Introduction and key conclusions
- Context and motivation
  - Inflation differentials across the Gulf Cooperation Council (GCC) countries tightened toward the end of the 1990's but widened after the 2003 upsurge in oil prices as fiscal policy became increasingly expansionary and contributed to rising domestic demand.
  - Minimizing inflation differentials across the GCC is a key convergence criterion for the planned GCC monetary union.
- Principal findings (from the paper)
  - After controlling for cyclical factors, convergence has increased even during the recent oil boom.
  - Inflation dynamics in the GCC are largely driven by the oil cycle, mainly through the credit and fiscal channels.
  - For a successful monetary union, closer coordination of fiscal policies is critical; avoiding procyclical fiscal policy will require a strong medium-term framework to reduce the risk of overheating and avoid increased divergence of inflation rates.

### Data and stylized facts
- GCC composition and data coverage
  - GCC comprises Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE).
  - Monthly CPI data used: January 1991–June 2010 (source: International Monetary Fund (2010b)).
  - Annual data used: 1991–2009 (various IMF databases).
  - Monthly data starting in January 1995 used for CPI index, NEER index, credit to the private sector, rent weight in CPI, and oil revenues (to proxy monthly fiscal activity).
- Macro-variable patterns highlighted (1991–2009)
  - Figures and pairwise differentials reported for: Inflation Rate, Non-oil real GDP growth, Credit growth, Non-oil fiscal balance, NEER growth.
  - Pairwise differentials computed for all 15 country pairs (ordered by GDP weights).

### Convergence of inflation rates (unit-root and stationarity testing)
- Approach
  - Define pairwise price-level deviations x_ijt = ln(CPI_it) - ln(CPI_jt) and inflation differentials Δx_ijt = π_it - π_jt.
  - Test for absolute convergence (stationarity of pairwise inflation differentials) using Augmented Dickey-Fuller (ADF) tests and KPSS stationarity tests.
- Main empirical results (1991M1–2010M6)
  - 15 pairwise combinations tested.
  - ADF tests: for all 15 pairwise combinations the null of a unit root can be rejected when investigating absolute convergence (0 = α_ij).
  - Two pairwise combinations could not reject the null of non-stationarity under the ADF when allowing for α_ij ≠ 0: Saudi Arabia with the U.A.E., and Qatar with Oman.
  - KPSS tests for these two combinations show that the stricter null of stationarity cannot be rejected for them.
  - Overall evidence points to absolute convergence in the GCC pairwise inflation differentials over the period 1991 to 2010.

### Econometric model and identification strategy
- Structural framework
  - Country inflation specification: p_it driven by a long-run equilibrium price p*_it, country-specific effect α_i, and short-run macro variables z_it (equation (7)).
  - Error term has multi-factor structure u_it = f_t' θ_i + ε_it, where f_t are unobserved common shocks and θ_i are idiosyncratic loadings (equation (8)).
- Pairwise-differential formulation
  - Under convergence to a common long-run price level (p*_it = p*_jt), pairwise inflation-differential model reduces to a stationary equation where short-run deviations are explained by deviations in macro variables z_it - z_jt plus idiosyncratic errors (equations (11) and (12)).
- Methodological distinction from union-average approaches
  - The paper follows Pesaran (2007) and Pesaran et al. (2009) and estimates pairwise inflation differentials directly, rather than deviations from a union average as in Honohan and Lane (2003).
  - Advantages of pairwise approach emphasized:
    - Relaxes the assumption of uniform response of all countries to common shocks.
    - Avoids imposing arbitrary equal weights N^{-1} on country variables to construct union aggregates.
    - Explicitly estimates the effects of differences in countries' macro variables (φ and β) on inflation differentials.

### GMM estimation methodology
- Dynamic panel issues and solution
  - Inclusion of lagged dependent variables and simultaneity of short-run determinants makes standard fixed/random effects inconsistent.
  - First-difference transformation yields equation (16) with moving-average error structure.
  - Difference GMM (Anderson–Hsiao; Arellano–Bond) moment conditions used, but lagged levels can be weak instruments when variables are persistent.
  - System GMM estimator (Arellano–Bover; Blundell–Bond) employed to improve efficiency, adding level equations instrumented by lagged differences.
- Validity and robustness checks
  - Hansen test of over-identifying restrictions used to test instrument validity.
  - Arellano–Bond style test used to examine absence of serial correlation in transformed errors.
  - Robust two-step standard errors computed with Windmeijer (2005) correction for small sample bias.

### Literature linkages and novel contribution
- Relation to existing literature
  - Builds on euro-area literature (Honohan and Lane (2003), Andersson et al. (2009)) but departs from the union-average deviation approach.
  - Complements country-specific GCC studies (Hasan and Alogeel (2008), Kandil and Morsy (2009), Basher and Elsamadisy (2010)) by addressing convergence properties and endogeneity in a panel pairwise framework.
- Novelty
  - First paper (to the authors' knowledge) to study convergence properties of GCC inflation rates using pairwise differentials and to model determinants of those differentials with a GMM system estimator addressing endogeneity.

### Policy implications and recommendations
- Fiscal policy coordination
  - Given oil-driven inflation dynamics operating mainly through credit and fiscal channels, closer coordination of fiscal policies across GCC countries is critical for a successful monetary union.
  - Avoiding procyclical fiscal policy is a key challenge; a strong medium-term fiscal framework is recommended to reduce overheating risks and prevent divergence of inflation rates.
- Monetary union readiness
  - Absolute convergence of pairwise inflation differentials over 1991–2010 supports the pursuit of a monetary union, but heterogeneity in short-run responses implies the need for coordination mechanisms and country-specific safeguards.

*Italic: Content summarized from IMF working paper section: 4. Government Expenditure and Oil Revenue (right-scale), 1991–2009, pages 3–15 of the provided PDF content.*

### 2009. Tables 4, 5, and 6 provide summary statistics for inflation differentials and highlight

### _wp11294 - 2009. Tables 4, 5, and 6 provide summary statistics for inflation differentials and highlight

### Key empirical findings
- Inflation differentials across the GCC widened over 1991–2009, with a sharp increase between 2003 and 2009, especially for those associated with Qatar and the U.A.E.
- Evidence of convergence in inflation rates:
  - The lagged price level coefficient is consistently negative and significant across monthly and annual estimations, indicating convergence in GCC inflation rates.
  - Convergence was faster during the oil boom (2003–09) than over the full sample (1991–2009).
- Main drivers of inflation differentials (signs as predicted by theory):
  - Positive contributors (widen the inflation gap): non-oil output growth differentials, rent weight (share of rent in CPI), credit growth differentials, government expenditure growth.
  - Negative contributors (close the inflation gap): NEER growth (nominal effective exchange rate growth), improvements in non-oil fiscal balances.

### Quantified effects (estimated elasticities and marginal impacts)
- Monthly-data estimations (1995M1–2010M6; 2003M1–2010M6 subsample):
  - A ten percentage point increase in oil revenue differentials leads to about a five percent increase in the inflation gap between countries.
  - Rent weight is significant and positive; post-2003 the coefficient on rent weight is roughly twice as large as in the full monthly sample.
  - Credit growth differentials: a 10 percent increase in credit growth implies about a 1 percentage point rise in the inflation gap for the full monthly sample; in the 2003–2010 subsample a 10 percent increase in credit growth leads to about a 1.5 percent increase in inflation differentials.
  - Nominal effective exchange rate coefficient is of expected (negative) sign but insignificant in monthly regressions reported.
- Annual-data estimations (1991–2009, Table 10; preferred specification equation (20)):
  - A 10 percent increase in NEER growth leads to almost an 8 percent decrease in inflation differentials (regression [2.5]).
  - A 10 percent increase in non-oil output growth differentials increases inflation differentials by about 3 percent (regression [2.5]).
  - A 10 percent difference in rent weights leads to a 2.4 percentage point difference in inflation rates (regression [2.5]).
  - A 10 percent credit growth differential widens the inflation gap by about 1 percent (regression [2.5]).
  - A tightening in non-oil fiscal balances by 10 percent reduces the inflation gap by 0.3 percent (regression [2.5]).
- Annual-data estimations for the subsample 2003–09 (Table 11):
  - A 10 percent increase in non-oil output growth or rent weight increases inflation differentials by about 4 percent.
  - A 1 percentage point increase in NEER reduces inflation differentials by almost 1 percent.
  - Every 10 percent increase in credit growth corresponds to a 2 percent increase in inflation differentials.
  - Replacing fiscal balances with government expenditure: a 10 percent increase in government expenditure growth differential widens the inflation gap by 3 percent; government expenditure effects are much larger in the 2003–09 subsample, consistent with intensified oil windfalls and fiscal spending.

### Interpretation and transmission channels
- Oil cycle operates through credit and fiscal channels to drive inflation differentials:
  - Higher oil revenues enabled larger government spending on infrastructure and social services, contributing to overheating and heterogeneous inflation outcomes depending on utilization of oil wealth.
  - Rapid credit growth, particularly in Qatar and the U.A.E., amplified domestic demand and widened inflation differentials post-2003.
- Structural factor — rent weight in CPI:
  - Higher rent weight (reflecting supply bottlenecks in housing markets) is associated with larger inflation differentials. Supply constraints include inadequate past investment, shortages in commercial and residential space, opening real estate to foreign investors, and inflows of expatriate labor.
- Nominal exchange rate (NEER) channel:
  - Appreciation in the NEER is associated with closing inflation gaps; NEER growth has a pronounced negative effect in annual regressions and in the 2003–09 subsample.

### Robustness and specification
- Estimation method: two-step system GMM with Windmeijer (2005) small sample robust correction.
- Instruments and serial correlation diagnostics:
  - Hansen and second-order serial correlation test statistics are generally well above conventional significance levels across regressions, supporting instrument validity and absence of second-order serial correlation.
  - First-order serial correlation is present (as expected given differenced equations), second-order serial correlation is not detected at conventional levels in reported regressions.
- Results are robust to:
  - Using monthly vs. annual data.
  - Replacing non-oil fiscal balance growth with government expenditure growth.
  - Splitting the sample (full vs. post-2003 subsamples) — magnitudes generally increase post-2003.

### Policy implications and recommendations
- Countercyclical macroprudential policy:
  - Implement countercyclical macroprudential policies during booms to contain excessive credit growth and limit its contribution to widening inflation differentials.
- Fiscal policy coordination and countercyclicality:
  - Fiscal policy is a key driver of inflation differentials; coordination of fiscal policy across countries in a monetary union is important.
  - Policies to reduce fiscal procyclicality are recommended to ensure convergence of inflation rates.
  - A strong medium-term expenditure framework could anchor expectations and limit procyclical fiscal responses to shocks.
  - Strengthening public financial management is a prerequisite for credible fiscal frameworks and for monitoring compliance.
- Structural policies — housing supply:
  - Invest in the expansion of commercial and residential housing supply to alleviate rent-driven inflation pressures.
  - Consider adequacy of housing to accommodate a growing domestic population and imported labor given the weight of rents in CPI baskets.
- Monetary union considerations:
  - While a single central bank would coordinate monetary policy under a proposed monetary union, fiscal policy coordination and robust fiscal frameworks are essential to sustain price convergence.

*Source: Authors' calculations and estimations reported in the provided IMF working paper excerpt.*

### References

### _wp11294 - References

### Panel data and econometric methods
- Alonso-Borrego, C. and M. Arellano (1999). Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data. Journal of Business and Economic Statistics, Vol. 17 (1), pp. 36–49.
- Anderson, T.W. and C. Hsiao (1982). Formulation and Estimation of Dynamic Models Using Panel Data. Journal of Econometrics, Vol. 18(1), pp. 47–82.
- Arellano, M. and S. Bond, (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. The Review of Economic Studies, Vol. 58(2), pp. 277–97.
- Arellano, M. and O. Bover (1995). Another Look at the Instrumental Variable Estimation of Error-components Models. Journal of Econometrics, Vol. 68(1), 29–51.
- Blundell, R. and S. Bond (1998). Initial Conditions and Moment Restriction in Dynamic Panel Data Models. Journal of Econometrics Vol. 87(1), pp. 115–43.
- Windmeijer, F. (2005). A Finite Sample Correction for the Variance of Linear Efficient Two-step GMM Estimators. Journal of Econometrics, Vol. 126(1), pp. 25–51.
- Kapetanios, G., M.H. Pesaran, and T. Yamagata (2011). Panels with Non-Stationary Multifactor Error Structures. Forthcoming in Journal of Econometrics.
- Kwiatkowski, D., and P.C.B. Phillios, P. Schmidt, and Y. Shin (1992). Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root? Journal of Econometrics, Vol. 54(1–3), pp. 159–178.

### Convergence, PPP, growth, and macroeconometrics
- Pesaran, M. H. (2007). A Pair-wise Approach to Testing for Output and Growth Convergence. Journal of Econometrics, Vol. 138(1), 312–355.
- Pesaran, M. H., R.P. Smith, T. Yamagata, and L. Hvozdyk (2009). Pairwise Tests of Purchasing Power Parity. Econometric Reviews, Vol. 28(6), pp. 495–521.
- Durlauf, S. and D. Quah (1999). The New Empirics of Growth. In J. Taylor and M. Woodfern (Eds.), Handbook of Macroeconomics, pp. 235–308. New York: North-Holland.
- Garratt, T., K. Lee, M.H. Pesaran, and Y. Shin (2006). Global and National Macroeconometric Modelling: A Long-Run Structural Approach. Oxford: Oxford University Press.

### Inflation, price level differentials, and regional studies
- Andersson, M., K.Masuch, and M. Schiffbauer (2009). Determininants of Inflation and Price Level Differentials Across the Euro Area Countries. ECB Working Paper Series 1129 (Frankfurt: European Central Bank).
- Busetti, F., L. Forni, A. Harvey, and F. Venditti (2007). Inflation Convergence and Divergence within the European Monetary Union. International Journal of Central Banking, Vol. 3(2) pp. 95–121.
- Honohan, P. and P.R. Lane (2003). Divergent Inflation Rates in EMU. Economic Policy, Vol. 18(37) pp. 357–94.
- Licheron, J. (2007). Explaining Inflation Differentials in the Euro Area: Evidence from a Dynamic Panel Data Model. Économie Internationale, Vol. 112, pp.73–97.
- Rabanal, P. (2009). Inflation Differentials Between Spain and the EMU: A DSGE Perspective. Journal of Money Credit and Banking, Vol. (41), pp. 1141–1166.
- Basher, S.A. and E.M. Elsamadisy, (2010). Country Heterogeineity and Long-Run Determinants of Inflation in the Gulf Arab States. Central Bank of Qatar, Working Paper (Doha).
- Hasan, M. and H. Alogeel (2008). Understanding the Inflationary Process in the GCC Region: The Case of Saudi Arabia and Kuwait. IMF Working Paper, WP/08/193 (Washington; International Monetary Fund).
- Kandil, M.E. and H. Morsy (2009). Determinants of Inflation in the GCC. IMF Working Paper WP/09/82.

### Data sources and institutional publications
- International Monetary Fund, (2010a). Direction of Trade Statistics (Washington).
- __________ (2010b). World Economic Outlook (Washington).
- __________ (2010c). Regional Economic Outlook: Middle East, and Central Asia (Washington).
- __________(2010d). International Financial Statistics, (Washington).
- United States Department of Energy, (2010). Energy Information Administration.

*Source: _wp11294 - References*

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