Journals should require authors to make their data available online before publication and encourage others to try to replicate the research they publish.
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My mentor, James Tobin, considered studying mathematics or law as a Harvard undergraduate but later explained that I studied economics and made it my career for two reasons. The subject was and is intellectually fascinating and challenging, particularly to someone with taste and talent for theoretical reasoning and quantitative analysis. At the same time it offered the hope, as it still does, that improved understanding could better the lot of mankind. I was an undergraduate math major (at Harvey Mudd, not Harvard) and chose economics for the much the same reasons. Mathematical theories and empirical data can be used to help us understand and improve the world. For example, during the Great Depression in the 1930s, governments everywhere had so Read More ›
A central part of John Maynard Keynes’ explanation of the Great Depression was his assertion that household income affects household spending. When people lose their jobs and income, they cut back on their spending, which causes other people to lose their jobs and their income — propelling the economy downhill. Keynes’ theory was based on logic and common sense. It was later tested empirically with household survey data and with national income data compiled by the National Bureau of Economic Research. Figure 1 shows U.S. after-tax personal income and consumer spending for the years 1929 through 1940. Since income and spending both tend to grow over time along with the population, the data were converted to annual percentage changes. The observed statistical Read More ›
For a while, there was a popular belief among finance professors that the stock market is “efficient” in the sense that stock prices are always correct — the prices that an all-knowing God would set. Thus, investors can buy any stock, even a randomly selected stock, and be confident that they are paying a fair price. This belief was based on seemingly overwhelming evidence that changes in stock prices are difficult to predict. Efficient market enthusiasts argued that if stock prices are always correct, taking into account all currently available information, then any changes in stock prices must be due to new information which, by definition, is impossible to predict. Therefore, the evidence that changes in stock prices are hard to Read More ›
Jacob Bernoulli made a now obvious observation about probability over three-and-a-half centuries ago: If nothing is known about the outcome of a random event, all outcomes can be assumed to be equally probable. Bernoulli’s Principle of Insufficient Reason (PrOIR) is commonly used. Throw a fair die. There are six outcomes, one for each face of the cube. The chance of getting five pips showing on the roll of a die is therefore one sixth. If a million lottery tickets are sold and you buy one ticket, the chances of winning are one in a million. This reasoning is intuitively obvious. The assumption about the die is wrong if the die is loaded. But you don’t know that. You know nothing. So Bernoulli’s PrIOR Read More ›
Elsewhere I have warned of the perils of making decisions based on data without theory. For example, the patterns discovered by data-mining computer algorithms are often nothing more than meaningless coincidences. It is also perilous to go to the opposite extreme—to make decisions based on theory without data. Once upon a time, for example, economists were fond of sketching labor demand and supply curves and assuming that the economy was at their intersection. That is, labor demand is equal to supply, so that everyone who wants to work is working. The unemployed have chosen to be unemployed because they value leisure more than income. True believers were fond of this theory and little troubled by reality. Between 1929 and 1933, Read More ›