Abstract
Forecasts of the future tendency of economic variables such as GDP, inflation rate and unemployment rate, arise many interests from business and government. Also, Modeling the land market at the national level can capture rich dynamic presenting in interdependent economies. In this paper, we studied a Vector Auto-regression (VAR) of Land Market Value and five US macroeconomic variables. We employed the VAR model for forecasting Land Market Value in USA and analyzed annual data on the main macroeconomic variables of interest going back to 1982. Most importantly, we explore the mutual influence between Land market value and selected macroeconomics variables to enable government and investor to make informed decision regarding real estate market.
Highlights
We can define land in many ways and different fields
What we studied in this paper is about the land market value
The Vector Auto-regression (VAR) forecasting model has been widely used in many area of finance in recent years and it increased the understanding of tendency of land market value
Summary
We can define land in many ways and different fields. We defined land as all naturally occurring resources whose supply is inherently fixed. All types of economic activity require land, either directly or indirectly. The direct use of land is obvious in industries such as farming and construction. All other forms of commerce require land as well because workers, equipment and buildings need to be located somewhere. What we studied in this paper is about the land market value. The Land Market Value, defined as the total value of land and quantity data are derived from data on housing values, is an important factor in the estimation of structure costs using price indexes for housing and construction costs (Calomiris et al, 2013)
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