It Matters How You Get There: McFadden and the Metro
If you live in the city like me, public transportation is a way of life. It helps you go from point A to point B without having to own a car. Since moving to DC, I have discovered many alternative modes of transportation. I have the option to walk without having to pay a dime. I can also take the bus or metro rail system for a low fare rate, relatively quickly* (*see Metro complaints). This array of choices is an example of economic choice theory, which our Nobel Prize laureate of the week, Daniel McFadden, studied extensively.
Daniel McFadden is a professor of Economics at University of California, Berkeley. McFadden’s work in economic choice theory won him, along with James Heckman, a Nobel Prize in 2000. His focus was on discrete choice (as compared to continuous choice). Simply stated, a discrete choice requires an individual to choose between two or more particular alternatives. Continuous choice is where the individual chooses how much of any particular item he or she wants.
Looking at public transportation, a discrete choice is deciding which mode of transportation to take whereas continuous choice is how much transportation we should take. McFadden’s study of choices looked at a variety of factors, adding insights from psychology and basic economic choice theory. He examined the constraints with psychological factors such as perception, memory, motivation, attitude, and process.
Depending on these factors, we choose the option that seems best to us. We evaluate according to what we think is most important (our preferences) and how much time or money we have (our constraints). Some people value convenience above all, others might value money.
McFadden actually studied public transportation in San Francisco Bay Area in 1972. He applied his discrete choice theory to help plan public transportation. In his Nobel Prize lecture, McFadden said that after overestimating willingness to walk and underestimating willingness to drive, they were able to estimate correctly that 15% of commuters would take the BART, San Francisco’s new public transportation. Using his theory about discrete choices, he and his team were able to correctly estimate how residents would respond to a new transportation option, depending on their preferences and constraints.
While we face choices, like which public transportation to take or what to eat for dinner, the outcome of these decisions are generally insignificant. If we incorrectly evaluate our preferences and constraints, generally the worst that could happen is we show up late for work. However, choices can have major effects when applied on a greater scale, such as government policy. Applying discrete choice theory and looking at the multiple factors surrounding each policy or initiative can save time, money, and most importantly, headaches. Economic choice is not just about how much policy we should have, but which policy is best.
McFadden’s work also influenced the study of Behavioral Economics, an increasingly popular field in economics adjusting for errors committed by human beings in economic interactions (see Alex’s blog on the 2017 Nobel laureate, Richard Thaler). McFadden, like the Behavioralists, applied insights from psychology to standard economic theory to improve the theory of choice. He added that according to individuals’ perceptions, experiences, and attitude, individuals will maximize utility subject to their preferences and constraints. Using this new and improved theory of choice, McFadden was able to more accurately analyze the discrete choice of the individual, especially seen in his work for San Francisco transportation.
The next time you are debating between driving, riding the Metro or bus, or walking, think of McFadden and all of the relevant factors he explored when making your choice. Then, after ranking your preferences, build an Excel table taking into account all the relevant factors and your budget for time and money. Then send your results to McFadden and he will reply with the best mode of transportation.
