Time Series Analysis and Forecasting of the US Housing Starts using Econometric and Machine Learning Model

Sudiksha Joshi

Papers from arXiv.org

Abstract: In this research paper, I have performed time series analysis and forecasted the monthly value of housing starts for the year 2019 using several econometric methods - ARIMA(X), VARX, (G)ARCH and machine learning algorithms - artificial neural networks, ridge regression, K-Nearest Neighbors, and support vector regression, and created an ensemble model. The ensemble model stacks the predictions from various individual models, and gives a weighted average of all predictions. The analyses suggest that the ensemble model has performed the best among all the models as the prediction errors are the lowest, while the econometric models have higher error rates.

Date: 2019-05
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ets, nep-pay and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1905.07848

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