The study - a new National Bureau of Economic Research working paper that sought to determine whether USA cultural preferences have changed across various groups over time - found that there's a 69% chance to correctly predict that a household is "high-income" based on the ownership of the said device. This is correct, two mobile computing devices have become an indicator as to how rich you really are, according to a paper published by the National Bureau of Economic Research.
The researchers say that knowing someone owns an iPhone gives them a 69 percent chance to infer correctly that the owner was "high-income". "Across all years in our data, no individual brand is as predictive of being high-income as owning an Apple iPhone in 2016". Economists found that almost seven out of ten times, a person with an iPhone has a higher income than others. After all, iPhones were only introduced in 2007. In 2004, the second batch of data showed Land O' Lakes Regular butter was the clearest indication you were earning good money. For instance, in 1992, there was a 62.2% chance that if you were using Grey Poupon dijon mustard, you had some cash.
In 2016, the list is dominated by technology-related entries, including iPhone ownership on top of the list, followed by iPad ownership, being on the Verizon Wireless network, owning an Android phone, used Kikkoman, HP printer ownership, being on the AT&T network, and Samsung TV ownership.
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During the debate surrounding the issue, Hunt said it would likely be his "last big job in politics". You will either own or have permission to use anything you provide.
The iPhone is a luxury product that is usually priced higher than competing smartphones. The most recent data was taken in 2016. And it found that in 2016, the previous year it analyzed, there was a 69.1% chance of accurately guessing that a person was wealthy if he or she owned an iPhone. The data included bi-annual questionnaires and information obtained from face-to-face interviews such as household income.
The researchers also used a machine learning algorithm to look at how different groups have had their preferences diverge over time.
"This take-away runs against the popular narrative of the U.S. becoming an increasingly divided society", the researchers write.
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