index.rmd

---
title: "Estimating Neighborhood Rents with Scraped Data"
output: 
  html_document:
      includes:
        in_header: "header.html"
        after_body: "footer.html"
---

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This project is under construction and subject to change at any moment!

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### About

The goal of this research is to understand the dynamics of Seattle neighborhoods' median rent level using scraped rental housing listings from Craigslist. I use a series of data visualizations to describe the accumulated data and compare the Craigslist estimates against other indicators. After the data description, I model a panel of quarterly census tract estimates to explain the spatial and temporal dynamics observed so far. Models are trained on quarterly tract estimates observed through the prior quarter and forecast the current quarter's rent surface.

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### Contents

[Working paper](./manuscript/index.html) on estimating Seattle neighborhood rent indicators

[Results dashboard](./dashboard/index.html) for working paper's model diagnostics and forecasts

[GitHub repository](https://github.com/hesscl/smooth-sea/) with source code for manuscript and results dashboard

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### Powered By

[Helena](http://helena-lang.org) - Web automation for end users

[R Markdown](https://rmarkdown.rstudio.com) - Reproducible data analysis and manuscript creation

[flexdashboard](https://rmarkdown.rstudio.com/flexdashboard/index.html) - Easy interactive dashboards for R

[plot.ly](https://plot.ly/) - translate ggplot() objects to JavaScript htmlwidgets

[GitHub Pages](https://pages.github.com/) - Publish static web pages with repositories

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### Contact

Email Chris Hess at [hesscl@uw.edu](mailto://hesscl@uw.edu) for more information about this research.