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Modeling and Forecasting the Infrastructure Investments Needs in Lebanon

Authors: Latife Ghalayini; Fabienne Saade;

Modeling and Forecasting the Infrastructure Investments Needs in Lebanon

Abstract

The aim of this paper is to model and forecast the infrastructure investment needs in Lebanon. It divides the Lebanese infrastructure into ten main sectors, and it represents an analysis of each sector. The article collects data of the government expenditures on projects for each sector from the Lebanese council of development and reconstruction. The expenditure on each sector represents a different impact on the Lebanese growth and the Gross Domestic Product, the article analyses the impact in an assessment approach. Findings emphasis the importance of social infrastructure in promoting growth, especially Education sector. Furthermore, findings stress the high volume of expenditure on waste water and solid waste management sector. The article proceeds by modeling the infrastructure investment need using Dynamic OLS equilibrium. The study encloses ten Dynamic OLS models, one for each sector, having the investment needs as the dependent variable, and as independent variables the Lebanese Gross Domestic Product and the Lebanese population. Eventually, the paper forecasts the Lebanese infrastructure investment needs for each sector until the year 2025. Results emphasis the unfair low expenditure on Education and other social infrastructures, and the high expenditures on inefficient sectors such as the waste water and solid waste sector, and the electricity sector. The study eventually recommends a better distribution of infrastructure investments within the Lebanese expenditures.

Keywords

Lebanese Infrastructure, Education, Investment Needs, Government Expenditures, Dynamic OLS, Solid Waste

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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