S670 Mini-project 1: House prices and population growth Solved

For your initial submission, you may work in groups of any reasonable size, and submit one report per group. However, your final submission will be in groups of no more than 2 people. Register your group using the “Mini-project 1 initial groups” tab on Canvas (or ask me or a TA to do it.)

A researcher for a thinktank wants to learn about how house prices in the U.S. have changed over the last few decades, and whether changes in prices are related to population in some way.She has taken an introductory statistics course using R, but that was a long time ago, so she is outsourcing the exploratory data analysis to YOU.

Questions
The researcher’s major research question is: How have house prices in U.S. states changed over the last few decades, and are changes in prices are related to population in some way? This question may be difficult to answer, at least straight away. So she has brainstormed a series of questions he would like you to address, which can be divided into groups:

1.    House prices over time: How have house prices in the U.S changed since 1975, after adjusting for inflation (i.e. relative to the CPI?) How have changes in prices varied by state? Which states have seen the biggest increases in real house prices, and which have seen the biggest decreases? Have changes in prices within each state mostly followed the same basic pattern, and are there outliers to that pattern? Do the typical patterns vary between the four regions (Northeast, Midwest, South, and West)?

2.    Population density and changes in house prices: Does present-day population density explain changes in house prices by state since 1975? Are there outliers to the relationship, and if so, is there a principled reason to drop them? What does the relationship look like after dropping or downweighting outliers? Does the relationship vary by region? If so, how?

3.    Changes in population and changes in house prices: Is there a relationship between changes in population and changes in house prices? To answer this, look at changes in each state over three time periods: 1990 to 2000, 2000 to 2010, and 2010 to the present. Analyze the three time periods separately. Has the relationship changed over the three time periods? Are there variations by region?

4.    Conclusion: What does all of this tell you about the relationship between house prices and population? Is there a plausible cause-and-effect story you can tell that’s consistent with the data and with common sense?

Data
•    Freddie Mac House Price Index (http://www.freddiemac.com/research/indices/ house-price-index.html): This tracks the average house price in each state (plus Washington, D.C. and a national average) since 1975. For each state, the index value is fixed at 100 in December 2000. Figures are seasonally-adjusted but not adjusted for inflation. The data is in the spreadsheet State and US SA.xls.

•    state abbrevs.txt (on Canvas): This contains the names, the two-letter code, and the Census region (Northeast, Midwest, South, or Midwest) for each state in the U.S.

•    Consumer Price Index, on Canvas in cpi.csv. This tracks how prices in general have changed in the U.S. The data in the spreadsheet is the “All Urban Consumers (Current Series),” seasonally adjusted, from www.bls.gov/cpi/data.htm.

•    Census Data: You’ll need to get population data for each state in 2018, 2010, 2000, and 1990 from the Census and American Community Survey. We recommend you do this using the tidycensus R package. See https://walkerke.github.io/tidycensus/articles/ basic-usage.html for a description of how to use the package.

To use the package, you’ll need a Census Data API key. To sign up for one, enter your email at https://api.census.gov/data/key_signup.html and they’ll send you a key (you’ll have to wait a few minutes for it to activate.) The main population variable is P001001 in the 2010 and 2000 Censuses, and P0010001 in the 1990 Census. If you can’t get the data this way, you can always get it directly from data.census.gov.