This paper investigates the importance of housing variables in predicting the six recent recessions using factor analysis model. It shows that housing variables have great predictive power in forecasting the downturn of the economy, but little predictive power when the economy is steady or is expanding. The explanation is that housing variables match consumers' expectations of future income and employment, and consequently predict future economic downturn. By using Granger-Causality test and vector autoregression (VAR) model, combination of factor analysis and VAR model, and hard thresholding method to identify the importance of each housing variable, the results show that housing price indexes are not important in forecasting the economy, but that measures of housing volumes improve predictions. Moreover, the housing volume measures with one-unit of structure tends to play a greater role in the prediction.
","abstract_html":"<p>This paper investigates the importance of housing variables in predicting the six recent recessions using factor analysis model. It shows that housing variables have great predictive power in forecasting the downturn of the economy, but little predictive power when the economy is steady or is expanding. The explanation is that housing variables match consumers' expectations of future income and employment, and consequently predict future economic downturn. By using Granger-Causality test and vector autoregression (VAR) model, combination of factor analysis and VAR model, and hard thresholding method to identify the importance of each housing variable, the results show that housing price indexes are not important in forecasting the economy, but that measures of housing volumes improve predictions. Moreover, the housing volume measures with one-unit of structure tends to play a greater role in the prediction.</p>","abstract_has_math":false,"creators":["Xu, Wenxian"],"institution":null,"degree_name":"Ph.D. in Economics","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Walter J. Mayer","Joshua Hendrickson","Xin Dang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-01T08:00:00Z","date_published":"2014-01-01T08:00:00Z","updated_at":"2026-07-24T03:05:36Z","subjects":["Economic Fluctuations","Factor Analysis","Forecast","Housing","Economics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://egrove.olemiss.edu/etd/486","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Walter J. Mayer","Joshua Hendrickson","Xin Dang"]},{"key":"dc:creator","label":"Author","values":["Xu, Wenxian"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-06-20T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D. in Economics"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Economic Fluctuations","Factor Analysis","Forecast","Housing","Economics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://egrove.olemiss.edu/etd/486"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This paper investigates the importance of housing variables in predicting the six recent recessions using factor analysis model. It shows that housing variables have great predictive power in forecasting the downturn of the economy, but little predictive power when the economy is steady or is expanding. The explanation is that housing variables match consumers' expectations of future income and employment, and consequently predict future economic downturn. By using Granger-Causality test and vector autoregression (VAR) model, combination of factor analysis and VAR model, and hard thresholding method to identify the importance of each housing variable, the results show that housing price indexes are not important in forecasting the economy, but that measures of housing volumes improve predictions. Moreover, the housing volume measures with one-unit of structure tends to play a greater role in the prediction.
"]},{"key":"dc:title","label":"Title","values":["The Importance Of Housing Variables In Predicting Economic Fluctuations"]}]}],"canonical_facts":{"dc:contributor":["Walter J. Mayer","Joshua Hendrickson","Xin Dang"],"dc:creator":["Xu, Wenxian"],"dc:date.available":["2019-06-20T07:00:00Z"],"dc:description.abstract":["This paper investigates the importance of housing variables in predicting the six recent recessions using factor analysis model. It shows that housing variables have great predictive power in forecasting the downturn of the economy, but little predictive power when the economy is steady or is expanding. The explanation is that housing variables match consumers' expectations of future income and employment, and consequently predict future economic downturn. By using Granger-Causality test and vector autoregression (VAR) model, combination of factor analysis and VAR model, and hard thresholding method to identify the importance of each housing variable, the results show that housing price indexes are not important in forecasting the economy, but that measures of housing volumes improve predictions. Moreover, the housing volume measures with one-unit of structure tends to play a greater role in the prediction.
"],"dc:identifier":["https://egrove.olemiss.edu/etd/486"],"dc:subject":["Economic Fluctuations","Factor Analysis","Forecast","Housing","Economics"],"dc:title":["The Importance Of Housing Variables In Predicting Economic Fluctuations"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D. in Economics"]},"updated_at":"2026-07-24T03:05:36Z"}