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To put it pithily: it uses proxies of both dependent and independent variables, which increases the noise of both, in a study to determine signal-to-noise ratio

To put it pithily: it uses proxies of both dependent and independent variables, which increases the noise of both, in a study to determine signal-to-noise ratio.

viraptor 3y ago
Which proxies do you think are bad / why? The moment you go more coarse than documenting every single worker's perfect timesheet and working out their direct individual output, you're introducing some kind of proxy. What you wrote applies to every economics statistical analysis so far.
- ororroro 3y ago
  > The researchers examined productivity trends in 43 industries — including chemical manufacturing, retail trade, and accommodation and food services — and assigned a “teleworkability” score based on the occupational mix of each industry and the share of jobs that can be done remotely. They never actually measured the amount of work hours being done remotely. They never measured the number of employees working remotely. They just had some guy make up "remote-ability" numbers for each sector and then carefully pretended to be doing science. Meanwhile all these sectors have seen unrelated changes to operating environment that have not been controlled for. It's BS on BS on BS. Overall I am not even convinced their remote work metric would correlate with hours worked remotely.
- Eridrus 3y ago
  Actually, this does not apply to good economics papers. Good economics papers have much stronger ways to identify both the independent and dependent variables using microdata from public and private sources. Getting access logs for whether people logged in from home or the office is really not a crazy stretch. Measuring the dependent variable "productivity" is actually much harder since firm-level productivity (aka earnings) has a whole host of other things that impact it besides worker-level productivity and we all know how hard it is to measure developer productivity.

To put it pithily: it uses proxies of both dependent and independent variables, which increases the noise of both, in a study to determine signal-to-noise ratio.

viraptor 3y ago

Which proxies do you think are bad / why? The moment you go more coarse than documenting every single worker's perfect timesheet and working out their direct individual output, you're introducing some kind of proxy. What you wrote applies to every economics statistical analysis so far.

ororroro 3y ago
> The researchers examined productivity trends in 43 industries — including chemical manufacturing, retail trade, and accommodation and food services — and assigned a “teleworkability” score based on the occupational mix of each industry and the share of jobs that can be done remotely. They never actually measured the amount of work hours being done remotely. They never measured the number of employees working remotely. They just had some guy make up "remote-ability" numbers for each sector and then carefully pretended to be doing science. Meanwhile all these sectors have seen unrelated changes to operating environment that have not been controlled for. It's BS on BS on BS. Overall I am not even convinced their remote work metric would correlate with hours worked remotely.
Eridrus 3y ago
Actually, this does not apply to good economics papers. Good economics papers have much stronger ways to identify both the independent and dependent variables using microdata from public and private sources. Getting access logs for whether people logged in from home or the office is really not a crazy stretch. Measuring the dependent variable "productivity" is actually much harder since firm-level productivity (aka earnings) has a whole host of other things that impact it besides worker-level productivity and we all know how hard it is to measure developer productivity.