All Theses and Dissertations

Degree

Master of Science in Economics

Faculty / School

School of Economics and Social Sciences (SESS)

Department

Department of Economics

Date of Award

Spring 2021

Advisor

Dr. Qaiser Munir

Committee Member 1

Dr. Qaiser Munir, Institute of Business Administration, Karachi

Project Type

Thesis

Access Type

Restricted Access

Pages

v, 23

Abstract

Providing housing for low-income families has been a key agenda item for governments in developing countries such as Pakistan. Several mechanisms have been employed to provide easier access to housing, such as low interest loans as well as incentivizing real estate developers to increase housing supply through amnesty schemes. The primary objective of this paper is to explore the non-linear impact of nominal interest rates on housing prices in Pakistan. The policy rate set by the State Bank of Pakistan shall be used as a proxy for nominal interest rates while housing price data is extracted from a monthly index set by Zameen.com. As opposed to the prevalent approach in the literature of implementing a linear regression model, we employ a nonlinear autoregressive distributed lag model (NARDL) suggested by employ Shin, Yu and Greenwoord-Nimmo (2014) for the period of January 2011 to June 2020. We then examine causality using Hatemi-J’s (2012) asymmetric causality testing approach. The advantage of NARDL is that it works efficiently even in small sample sizes and stationary testing is not mandatory. Using the asymmetric causality approach allows us to check for the direction of causality between the variables. Our results suggest a long run co-integration relationship between nominal interest rates and housing prices. Real estate prices will increase regardless of a positive or a negative interest rate shock. However, the increase would be greater in case of a negative shock. Negative asymmetric causality was found running from nominal interest rates to housing prices. Asymmetric positive causality could not be established. Positive causality was established from nominal interest rates to plot prices, subsequently suggesting an asymmetric relationship between the two variables. Our findings suggest that policy makers could use interest rates as a secondary tool for controlling real estate price appreciation.

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