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FRED API: Get US Economic Data using Python
Python tutorial on how to extract economic data
What indicators help us to predict where a real estate housing market is headed? Is it possible to get this data all from a single source? If so, how? This article will look at main factors that affect the real estate market and how to obtain these data points using FRED’s API.
4 Key Factors That Drive the Real Estate Market
For real estate investors, it is important to understand trends within a given market. This can help present areas of opportunity or signal warning signs for a given market.
Per Investopedia, there are four key factors that drive the real estate market. the four factors are:
- Demographics — age, income, migration patterns, population growth
- Interest rates — influence a person’s ability to purchase property
- Economy — unemployment, manufacturing, GDP
- Government policies/subsidies — tax credits, deductions, subsidies
Each of these data points are hosted on a variety of government sites available to the public. To merge all of these sources into one table would be a HUGE undertaking.
Luckily FRED does all the heavy lifting for us! :)
What is FRED?
What is FRED? Short for Federal Reserve Economic Data, FRED is an online database consisting of hundreds of thousands of economic data time series from scores of national, international, public, and private sources.
FRED contains data sets reported by the Board of Governors, Bureau of Economic Analysis, Bureau of Labor Statistics, and Census — among others.
Data is browsable by (1) source (the institution or company that produces the data), (2) release (the document associated with the data’s publication), (3) category (a list of data topics as organized by the FRED staff), (4) latest update (the most recently updated data), and (5) tags.
