Research Reports

An Optimal Investment Model for Georgia
Monday, 30 November, 2015

After the collapse of the Soviet Union in 1991, the newly independent state underwent serious turmoil, including civil war, deteriorated governance, depreciation of critical infrastructure, and endemic corruption. But after the Rose Revolution in 2003, the country began to implement major political and economic reforms. Foreign capital was injected into the county which helped deliver extremely high GDP growth rates (on average of 6% per year from 2003 to 2013).

Economic growth, however, was not socially inclusive. It mainly centered on Tbilisi (the capital city) while the rest of the country was left behind. High levels of poverty and unemployment persisted, and this led to a build-up of social tensions that ultimately resulted in a dramatic political regime shift in 2012.

The newly elected government promised development projects with a social agenda. As the debate crystallized and focused on welfare issues, funds that arrived from abroad, such as remittances, donations (e.g., Brussels Pledge Commitment), and others, were channeled by the government to achieve specific social-economic goals. These mainly include: promoting aggregate GDP growth, income and welfare equality, employment creation (fighting unemployment), export promotion, and a few others.1 In addition, the focus also centers on various regional dimensions (e.g., administrative regions, East-West), urbanity dimension (i.e., urban versus rural), and household income levels.

Policymakers in Georgia, and across the globe, have always tried to decide on how to optimally allocate limited funds, i.e., finding which sectors or households should receive funds to maximize a social objective. This, however, is a difficult task because of the lack of information and also because of the complex characteristics of the economy. For example in Georgia, around 60% of employment is based on the agricultural sector. However, GDP growth is fastest among the service sectors that are mainly located in the capital city, Tbilisi.

To consider these issues, we develop an economy-wide general equilibrium model to simulate various alternative investments strategies. The model incorporates a Development Fund, which has a certain size of assets and is tasked with channeling different proportions of the funds to various sectors in the economy. Our aim is to find the optimal allocation strategy that maximizes the social-economic targets (as previously discussed).

The model is calibrated to the Georgian economy using a newly developed social accounting matrix (SAM) of 2013, and searches among more than 42,750 alternative investment scenarios. We find that “You can’t always get what you want2”, i.e., not all social-economic objectives can be maximized simultaneously. For example, promoting the highest GDP growth would mean that investors should focus on the manufacturing sectors. But promoting the highest household welfare in rural households would mean investing in the agricultural sectors. Ultimately, policymakers will choose where to invest. The purpose of this CGE model is for them to make qualified judgments based on a unified modeling framework.

The paper is organized as follows. Section 2 provides background information on Georgia and reviews the level of foreign capital inflows into Georgia in the past decade. Section 3 reviews literature on rural and urban development, the benefits of infrastructure development, and the benefits and costs of FDI. These are all related to this study. Section 4 describes the theoretical economic model and its assumptions. Section 5 presents the newly developed social accounting matrix, which forms the basis of the model calibration.  Section 6 briefly summarizes how the Ministry of Economy and Sustainable Development (MoESD) in Georgia can use this tool for various other issues not covered in this paper. The section also refers to the accompanied instruction manual for this model. Finally, Section 7 summarizes the results of the model. Our focus is on results at an aggregate level, but a similar analysis can be done at a micro-regional level. Finally, Section 8 provides a brief conclusion.