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• 1. [Article] The State of the Portland MSA Housing Market

  On its surface, the rapid increase of home prices in the Portland Metropolitan Statistical Area (MSA) resembles the overheated moments before the housing bubble burst in 2007. OnPoint Community Credit ...

  Citation × Citation Citation Abstract Copy Title: The State of the Portland MSA Housing Market Author: Portland State University. Northwest Economic Research Center Year: 2016 On its surface, the rapid increase of home prices in the Portland Metropolitan Statistical Area (MSA) resembles the overheated moments before the housing bubble burst in 2007. OnPoint Community Credit Union, concerned that history may already be repeating itself, asked the Northwest Economic Research Center (NERC) to investigate speculation within the Portland housing market, provide a forecast of home prices, and summarize potential market headwinds and tailwinds. To accomplish this, NERC estimates the change in local home prices due to ‘fundamental’ drivers. Using population and income to estimate a fundamental home price index (HPI), this analysis compares the fundamental HPI with the actual level of the Case-Shiller HPI to indicate that home values within the Portland MSA are, within a margin of error, correctly valued. This method indicates that increasing growth in income and migration significantly contributes to rising home prices. This comparison also shows a period of undervaluation following the burst of the last bubble, which helps to explain the price growth of the past few years (the ‘expansion phase’ of the recovery). This analysis uses Error-Correction (EC), General Autoregressive Moving Average (GARMA), and Ordinary Least Squares (OLS) models to forecast the inflation-adjusted Case Shiller HPI to the end of the year. The inherent strengths and weaknesses of these models necessitate a discussion of their assumptions and consequent limitations. Encouragingly, each of the models describes the same basic story: that average home sale prices will increase at a decreasing growth rate from June to at least December 2016. Changes to land use and building height restrictions are among the external shocks to home prices not included in the model. Since predicting policy decisions is fraught with risk, real-world awareness of potential political outcomes should accompany all forecasts based on known factors. Due to data limitations, not all of the indicators NERC feels are important to HPI are explicitly included in the models. Instead, these indicators offer supporting evidence. Generally, they describe a tight housing market with high demand (as indicated by income, employment, and migration) and low supply (as indicated by housing permits and inventory levels). This analysis corroborates the model estimations and supports the forecasts. Title: The State of the Portland MSA Housing Market Author: Portland State University. Northwest Economic Research Center Year: 2016 On its surface, the rapid increase of home prices in the Portland Metropolitan Statistical Area (MSA) resembles the overheated moments before the housing bubble burst in 2007. OnPoint Community Credit Union, concerned that history may already be repeating itself, asked the Northwest Economic Research Center (NERC) to investigate speculation within the Portland housing market, provide a forecast of home prices, and summarize potential market headwinds and tailwinds. To accomplish this, NERC estimates the change in local home prices due to ‘fundamental’ drivers. Using population and income to estimate a fundamental home price index (HPI), this analysis compares the fundamental HPI with the actual level of the Case-Shiller HPI to indicate that home values within the Portland MSA are, within a margin of error, correctly valued. This method indicates that increasing growth in income and migration significantly contributes to rising home prices. This comparison also shows a period of undervaluation following the burst of the last bubble, which helps to explain the price growth of the past few years (the ‘expansion phase’ of the recovery). This analysis uses Error-Correction (EC), General Autoregressive Moving Average (GARMA), and Ordinary Least Squares (OLS) models to forecast the inflation-adjusted Case Shiller HPI to the end of the year. The inherent strengths and weaknesses of these models necessitate a discussion of their assumptions and consequent limitations. Encouragingly, each of the models describes the same basic story: that average home sale prices will increase at a decreasing growth rate from June to at least December 2016. Changes to land use and building height restrictions are among the external shocks to home prices not included in the model. Since predicting policy decisions is fraught with risk, real-world awareness of potential political outcomes should accompany all forecasts based on known factors. Due to data limitations, not all of the indicators NERC feels are important to HPI are explicitly included in the models. Instead, these indicators offer supporting evidence. Generally, they describe a tight housing market with high demand (as indicated by income, employment, and migration) and low supply (as indicated by housing permits and inventory levels). This analysis corroborates the model estimations and supports the forecasts. Close