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A paper on green innovation that drew sharp rebuke for using questionable and undisclosed methods to replace missing data will be retracted, its publisher told Retraction Watch.

Previous work by one of the authors, a professor of economics in Sweden, is also facing scrutiny, according to another publisher. 

As we reported earlier this month, Almas Heshmati of Jönköping University mended a dataset full of gaps by liberally applying Excel’s autofill function and copying data between countries – operations other experts described as “horrendous” and “beyond concern.”

Heshmati and his coauthor, Mike Tsionas, a professor of economics at Lancaster University in the UK who died recently, made no mention of missing data or how they dealt with them in their 2023 article, “Green innovations and patents in OECD countries.” Instead, the paper gave the impression of a complete dataset. One economist argued in a guest post on our site that there was “no justification” for such lack of disclosure.

Nearly 100 years ago, Muriel Bristol refused to drink a cup of tea that had been prepared by her colleague, the great British statistician Ronald Fisher, because Fisher had poured milk into the cup first and tea second, rather than tea first and milk second. Fisher didn’t believe she could tell the difference, so he tested her with eight cups of tea, half milk first and half tea first. When she got all eight correct, Fisher calculated the probability a random guesser would do so as well – which works out to 1.4%. He soon recognized that the results of agricultural experiments could be gauged in the same way – by the probability that random variation would generate the observed outcomes.

If this probability (the P-value) is sufficiently low, the results might be deemed statistically significant. How low? Fisher recommended we use a 5% cutoff and “ignore entirely all results which fail to reach this level.”

His 5% solution soon became the norm. Not wanting their hard work to be ignored entirely, many researchers strive mightily to get their P-values below 0.05.

Last year, a new study on green innovations and patents in 27 countries left one reader slack-jawed. The findings were no surprise. What was baffling was how the authors, two professors of economics in Europe, had pulled off the research in the first place. 

The reader, a PhD student in economics, was working with the same data described in the paper. He knew they were riddled with holes – sometimes big ones: For several countries, observations for some of the variables the study tracked were completely absent. The authors made no mention of how they dealt with this problem. On the contrary, they wrote they had “balanced panel data,” which in economic parlance means a dataset with no gaps.

“I was dumbstruck for a week,” said the student, who requested anonymity for fear of harming his career. (His identity is known to Retraction Watch.)