With the introduction of the monetary union and the single currency in the Gulf Cooperation Council by 2010, the prospective supernational monetary agency will conduct a single and indivisible monetary and exchange policy. Its policies will be based on the GCC-wide economic and financial developments. In this dissertation, I present some empirical tools that can be utilized by the policymakers at the supernational monetary agency to conduct a sound monetary policy.

Policymakers at the GCC supernational monetary agency will be scrutinizing a large number of economic variables in order to obtain a clear signal about the current and future state of the GCC economies. Since economic data is controlled by different agencies, not all economic variables are released simultaneously. In contrast, policymakers will have to make a decision without all of the information available to them yet. To overcome this problem, the second chapter extracted a timely single coincident index that closely track the business cycle evolution of the GCC area by utilizing the Generalized Dynamic Factor Model (GDFM). As by product of utilizing GDFM, each variable in the dataset is classified as pro-cyclical or counter-cyclical with respect to the coincident indicator. The GDFM then categorizes the direction of each variable against the coincident indicator as lagging, coincident, or leading. Since common shocks from any factor models are statistical shocks, the proposed test by Bai and Ng (2006) was applied to the GCC dataset to test the economic meaningfulness of the statistically latent factors.

Recently, central banks have started to utilize large-scale models based on New Open Economy Macroeconomics (NOEM) approach, where the parameters have structural interpretation. Chapter 3 layout a Dynamic Stochastic General Equilibrium Model (DSGE) for a small open economy a with fixed exchange rate regime on the GCC area. It is a small open economy model with some nominal and real frictions. The model can be used by the policymakers at the prospective supernational monetary agency to examine the dynamic effects of exogenous shocks on endogenous macroeconomic variables and understand the sources of business cycle fluctuations in the GCC area. Also, the derived model can also serve as a tool for policymakers in assessing alternative scenarios in order to conduct a sound monetary policy at the regional level.

Finally, the need for producing accurate forecasts of the key macroeconomic variables has become crucial for both policymakers and economic agents. In a “rich-data environment,” where information is scattered over a large number of economic time series, it is not feasible to estimate the forecasting equation of any target variable with all relevant variables. Chapter 4 generates short-term forecasts of key macroeconomic variables for the GCC area in a “data-rich environment” by utilizing different factor models. The ultimate goal is to measure the efficiency gain from using the dynamic factor model of Forni et al. (2005) versus the static factor model of Stock and Watson (2002a, b). Since the previous two models are not comparable, I propose two approaches to make the forecasting equations of those two methods more comparable.