Whilst financial markets continue to chase macroeconomics for that elusive insight, the world of business still finds value in microeconomics. The latest to hop on the bandwagon is tech giants who have hitherto thrived on electronics, computer science and software engineers. The emergence of data science in new age technologies such as artificial intelligence and machine learning is likely driving this appetite for economists armed with an understanding of statistics as well as human behaviour in the Silicon valley as this piece in The Economist explains.
“Silicon Valley is increasingly turning to economics for insights into how to solve business problems—from pricing and product development to strategy. Job-placement data from ten leading graduate programmes in economics shows that tech firms hired one in seven newly minted PHDs in 2022, up from less than one in 20 in 2018 (see chart). Amazon is the keenest recruiter. The e-emporium now has some 400 full-time economists on staff, several times as many as a typical research university. Uber is another big employer—last year the ride-hailing firm hired a fifth of Harvard University’s graduating PHD class.
…For big tech, meanwhile, economists offer skills that computer scientists and engineers often lack. They tend to have a good grasp of statistics, as well as a knack for understanding how incentives affect human behaviour. Most important, economists are adept at designing experiments to identify causal relationships between variables. Machine-learning engineers usually think in terms of prediction problems, notes one Ivy League grad who recently started a job in tech. Economists can nail down the causal parameters, he says.
An e-commerce firm may want to estimate the effect of next-day shipping on sales. A ride-hailing firm may wish to know which sets of incentives lure drivers back to the city centre after they are hailed by customers attending a big concert or sporting event. In two periods between 2015 and 2017 Mr List and colleagues at Lyft, Arizona State University and Boston University manipulated the prices and wait times for Lyft rides across 13 American cities to estimate the value of time. The study, which found that Lyft users value their time at about $19 per hour, yielded a paper. It also led to a new feature on the Lyft app called “Wait & Save”, which lets riders opt for a longer wait time in exchange for a lower fare.”
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