Up to 5 pages, single-spaced, size 12 font, at least 1” margins, plus no limit on tables, graphs, and references cited, program appendix
This project requires SAS (Statistical Analysis System) software ability and statistical analysis ability with the results that need to be interpreted.
(1)
First you need to select an application of hedonics and implement it yourself. Then, find two or three papers in the literature that talking about the same application that you have chosen, and briefly discuss how your papers are similar and different. (I think you can google and find the articles that match the chosen application of hedonics)
(2)
For this part, it will need you to use SAS software to make the commands and discuss the data briefly, with special attention to any key variables.
I have uploaded a sample SAS program with some code in there, and the variable codesheet.doc. So you need to find some variables that you think are related to part (1).
(3)
Most of your paper should discuss methodology because the purpose of this project is to make the stuff we talk about in class come to life, and it will make you learn a new skill.
Pay particular attention to how you identify your parameter estimates.
Then discuss your results.
Next, see how robust your results are to regression technique or to excluding a set of variables.
I will require proper interpretation of the results. Here is an example: “The results suggest that a 1% rise in neighborhood income levels is associated with a 2.3 percentage point fall in public school dropout rates, all else constant.” To help you, I will give you a couple of files I have made.
Your project must include a table of means that includes variable name, mean, standard deviation, and source. It also must include the code you used to perform your analysis.
Applications of hedonics

1. Capitalization of taxes and public services

Hp = f(taxes, public services, control variables)

If parameter estimate of taxes is negative and of public services are positive, we say taxes and services are “capitalized” into house price

Oates (1969) found capitalization of both property taxes and school spending

But Linneman and Hamilton showed that we shouldn’t see capitalization

Long-standing debate over whether we should expect capitalization or not: Brasington(2002 JUE) summarizes the debate as a camp that emphasizes developer activity vs. camp that emphasizes competition over existing houses in existing jurisdictions; finds greater capitalization rates where there’s less developer activity, toward interior of urban area

Other interpretations of capitalization:

1) Inefficient service provision, in the sense of government using more resources than necessary to provide a set level of services (Epple et al. 1978, Hoyt 1990)
2) Allocative inefficiency – spend too much or too little on various services (Brueckner 1982, Taylor 1995)

2. Quantifying relative importance of non-market goods
House price and environmental quality
House price and public school quality
House price and crime rates
House price and being near lake, park, interstate, church, shopping mall, airport

3. Hedonic price indices

Estimate a hedonic
Hp^ = Bo^ + B1^x1 + … + Bn^xn

Plug in the sample means of x’s to get typical house’s estimated price in base year

(index = 100)

Then estimate hedonic for new time periods, plugging in OLD sample means for x’s with new B’s to track changes in house price over time, for return on investment in housing

Alternatives to hedonics to make index:
Repeat sales
Matching algorithm (McMillen, 2012)

4. Evaluating policy alternatives

All else equal, if some communities adopt a policy z while others adopt policy y, could see if z is better policy by sticking z-dummy into a hedonic and testing its sign

Cross-sectional
Or change over time

5. Demand for nonmarket goods

Environmental quality (Zabel and Kiel, 2000; Bender et al. 1980, Beron et al. 2001, Nelson, 1978)

School quality (Yinger 2015, Brasington 2000)

Rooms (Palmquist 1984, Bajari and Kahn 2003)

Public safety (Bhattarai 2005)

Can find price elasticity, income elasticity, cross-price elasticity

6. Real estate applications

Atypicality discount
Motivated seller discount (moving)
For sale by owner vs. using real estate agent
Sheriff’s auction, guardian deed, survivorship deed

7. Testing for market segmentation

If B’s are different, markets are distinct
Goodman and Thibodeau

8. Quality of life indices, based on Roback (1982) model

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