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Tobin Pre-Doctoral Fellowship

Research in Household Finance and Real Estate

POSITION FILLED

FACULTY SUPERVISOR(S):

Paul Goldsmith-Pinkham and Cameron LaPoint

 

PROJECT DESCIRPTION:

Paul Goldsmith-Pinkham and Cameron LaPoint are looking to recruit a highly skilled and intellectually curious individual to join the Tobin Pre-Doctoral Fellowship Program to work on several research projects at the intersection of household finance, real estate, and urban economics.

 

The prospective fellow will evenly split their time between two sets of projects.

 

The first set of projects, supervised by Paul Goldsmith-Pinkham, revolves around housing markets and applied econometrics.

 

One example of the research on housing will involve questions of housing risk and transactions. This involves several potential projects, but the first will involve questions of the risk associated with selling a home. Namely, how often do potential transactions fall through? How costly is it? What do sellers do to avoid it? We will use housing listing and transaction data to study this aspect of the real estate market. Another example will use housing data linked to migration data to understand movements between home ownership and renting throughout the lifecycle and the business cycle.

 

Sample tasks in this set of projects will involve data merges based on geography, clean-up of existing datasets to construct a new panel dataset, and statistical regression analysis. There are also a number of projects regarding applied econometric questions, such as analysis of network data and instruments, which will involve simulations and analytic work.

 

The second set of projects, supervised by Cameron LaPoint, analyzes the real estate financing choices of elderly homeowners and policies for encouraging investments towards green property retrofitting. Research in behavioral economics has documented that consumers make suboptimal financial decisions, but what fraction of these mistakes can be explained by cognitive impairments like Alzheimer’s and dementia among the elderly population? This project seeks to isolate financial mistakes among elderly homeowners which lead to severe property tax and mortgage delinquencies, or even the loss of a home. Such mistakes might include missing payments, a lack of take-up of local tax forbearance policies, and failure to use subsidized loan products like government-sponsored reverse mortgages to cover existing debts.

 

The research on environmental property retrofitting involves evaluating state-level subsidized loan programs against alternative nudges to encourage homeowners to make upgrades such as solar panels or disaster proofing. Which borrowers and types of properties are more likely to benefit from these loan programs, and do these policies have the potential to amplify existing inequalities through spillovers to home values in surrounding neighborhoods?

 

Sample tasks under this project set include assigning coordinates to property addresses, fuzzy merging based on names and address information between datasets and constructing a new database of mortality and loan records linked to home transactions. The research agenda will inform policy debates related to property tax and mortgage payment collection, decarbonizing the real estate sector, and precision public health initiatives for treatment of early onset Alzheimer’s and dementia cases.

 

REQUISITE SKILLS AND QUALIFICATIONS:

Applicants should be completing or have completed a bachelor's or master's degree. Applicants need not hold an Economics degree, but a working knowledge of economics/finance principles is necessary to carry out the research underlying these projects.

 

As many of the research tasks will involve extensive work merging large datasets and spatial mapping techniques, we are especially interested in candidates with prior experience using statistical software such as Stata and programming languages such as R. Additionally, experience using geocoding tools like ArcGIS/Google API, webscraping, and interests or coursework in applied econometrics are a big plus.

 

Preference will be given to applicants with a strong interest in pursuing a PhD in Economics or a related discipline.

 

SPECIAL APPLICATION INSTRUCTIONS:

Applicants interested in this position should include several coding samples in their application file (ideally in R or Stata), and/or a link to a GitHub account, if available. As part of the application review process, short-listed candidates may also be asked to complete a sample exercise. 

 

LINK TO APPLY