Prediction on Land Market Value Based on the Real Estate Market in USA

Abstract

The Land Market Value, defined as the total value of land price 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. In this study, we gather and analyze 34 years' national data on past and present real estate transaction. According to the characteristics of raw data, we try to develop the potential Decomposition, Smoothing, ARIMA and other advanced forecasting models with appropriate transformations. Specifically, we employ an innovation space state underlying certain forecasting model. For regression analysis, we involves GDP, CPI, Construction Cost Index, population, unemployment rate, inflation rate and Purchasing Manage Index in multivariate statistical model. Most importantly, we obtain how to add value to business and apply skills set to real estate in a real world environment. The goal in providing crucial statistical method is to enable government and investors to make informed decisions regarding real estate.