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Determinants of house prices in Lebanon: an ARDL approach

Show simple item record Nseir, Albert 2022-09-15T11:50:25Z 2022-09-15T11:50:25Z 2022-07
dc.identifier.citation Nseir, A. (2022). Expanding retail messaging at PowerMeMobile (Master's thesis, Notre Dame University-Louaize, Zouk Mosbeh, Lebanon). Retrieved from
dc.description MSFRM -- Faculty of Business Administration and Economics, Notre Dame University, Louaize, 2022; "A Thesis presented in partial fulfillment of the requirements for the degree of the Master of Science in Financial Risk Management"; Includes bibliographical references (pages 67-75).
dc.description.abstract Purpose: The purpose of this thesis is to investigate the variables affecting house prices in Lebanon in the long run and the short run. Design/ Methodology/ Approach: To answer the above question, data collected is a monthly one covering second half of the year 2013 until February 2021. The dependent variable is average housing price, while independent variables include employment index, construction permits, non-resident deposits, interest rate, CPI, and coincident indicators. The autoregressive distributed lag (ARDL) model is applied for the long run and the error correction model (ECM) is applied for the short run. Findings: The results show that, in the long run, the employment index (EI), which is a proxy of employment, affected house prices. In the short run, EI, construction permits, and interest on USD loans (USD) affected house prices in Lebanon. Research Limitations and Implications: There are various limitations concerning the thesis. First, average house prices do not necessarily represent housing since real estate is both residential and commercial. Second, average house prices differ from median house prices which are a more fair representation of housing whose data is not available. Third, there are no large datasets in Lebanon and data used in the thesis was limited to being less than 100 observations. There are also several implications. Findings will help policymakers determine which variables affect housing and how they could structure their policies based on the information. Real estate develepors will know when to build housing units and how to build and price them. It can also help the average house buyer determine the right time to buy a house.
dc.format.extent xiii, 75 pages : color illustrations
dc.language.iso en en_US
dc.publisher Notre Dame University-Louaize en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri *
dc.subject.lcsh Housing--Prices--Lebanon
dc.subject.lcsh Average
dc.subject.lcsh Long-term business financing--Lebanon
dc.subject.lcsh Short-term business financing--Lebanon
dc.title Determinants of house prices in Lebanon: an ARDL approach en_US
dc.type Thesis en_US
dc.rights.license This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 United States License. (CC BY-NC 3.0 US)
dc.contributor.supervisor Naimy, Viviane, Ph.D. en_US
dc.contributor.department Notre Dame University-Louaize. Graduate Division en_US

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