It sounds like Michel Thomas's method, too. I'd second the effectiveness of the method (Michel Thomas's, at least; idk if they are the same entirely) for learning how to learn a language, but I also agree that immersion is needed for going beyond casual conversational level.
canihasaccount
joined 1 year ago
Would you say you're fluent in a language as a result of this?
Average monthly salary in the cities is listed at the bottom of that link I gave. The two cities differ in monthly salary by $14 dollars on average, per the available data. Those same submissions show that the cost of living is ~20% higher in San Diego than Austin.
Austin is cheaper than San Diego, even excluding taxes:
No, it isn't; performance != ability, and it's not clear that cognitive performance declines at all--hence the word "may."
My claim is that
Cognitive performance may also decline in remote settings
Nothing more.
The RCT is free to access (if you haven't downloaded more than three NBER papers; if you have, open the page in a different browser). Scroll down on the page I linked and download it via the button.
Statistically, you can control for variables in OLS regression--that's literally exactly what the model does when you include more than one variable--and, provided that you got your doctorate in anything that uses statistics, I am sure you know that.
Seasonality is one of the more basic economics concepts. The influence of weather and seasonal illness trends on productivity has been shown in a number of studies (e.g., productivity declines during the flu season). The authors didn't "show" it because it would be like showing gravity in a physics paper. Some things can be assumed. Also, productivity didn't have a trend, as was stated in the text that I quoted.
You completely ignored the log transformed results, which the authors note were better fit by the regression than the untransformed data, and which showed less productivity in work from home regardless of whether seasonality was controlled.
Personally, I think people should be able to work from home all they want. Productivity isn't the only important thing in life, nor is it the only important thing to businesses (e.g., retention of top employees is important). I am wholly against WebMD and all other companies requiring employees to return to the office. All I was doing in my comments was trying to clarify the data on WFH and productivity. There are good reasons to continue to allow WFH, but increased productivity is not one.
I'm going to finish my course prep. You can have the final word here; I don't have time to continue debating anymore.
First, the RCT is a much stronger study. I'm not sure why you're picking a fight with a correlational paper when there is a causal manipulation that I linked first.
Second, did you actually read the paper? 1B isn't the graph of productivity; 1C is. You can't just look at a graph, either--you need statistics.
"For Output, figure 1B, there is no visible monotonic or linear trend, so a seasonal time correction might be more appropriate here. Moreover, average output appears to be slightly lower during WFH.
For Productivity, figure 1C, the graph is more volatile, which is not surprising for a ratio. There is no clear linear time trend before WFH, but some variation from month to month, so a seasonal correction might be more appropriate. Productivity drops visibly during WFH. Finally, figure 1D plots the log of Productivity, which drops considerably after the start of WFH.
To quantify the WFH effect, and to control for employee and team time-invariant variables (via employee and team fixed effects), we now turn to the regression analyses. Informally, the estimates give us average differences in outcomes before and during WFH for the same employee, controlling for team effects (since employees sometimes switch teams) and time trends.
Table 4 reports WFH effect estimates based on OLS regressions for all three outcome variables, plus the natural logarithm of Productivity, in each case with linear and seasonal time trend corrections. All estimates are in line with the visible effects in the raw data in figure 1.
...
Columns 5 and 6 show that both WFH effect estimates on Productivity are negative, but only the estimate with seasonal time trend is significantly different from zero. We prefer that specification, since both the plot and the linear time trend coefficient indicate that a linear trend is not as appropriate. According to this specification, productivity decreased by 0.26 output percentage points per hour worked. Given an average WFO productivity of 1.36, this estimate corresponds to a 19% drop in output per hour worked. This is economically significant: if employees worked a fixed 40 hours per week, this would imply a drop in output of 10.2 output percentage points in a week. In other words, if employees had not increased time worked during WFH, on average they would have completed only 90 of 100 assigned tasks.
Columns 7 and 8 explain the log of Productivity, which strongly increases the fit of the regression. The WFH effect is negative and significantly different from zero at all significance levels, irrespective of time controls."
Klay Thompson being in the top 10 for guards while Sabonis isn't in the top 10 for frontcourt is a crime against humanity
I haven't heard of any ultra-rich person who wants to reduce the population. A population decline will lead to stock price declines as the majority of the population ages (automated 401k investments buy and thus increase stock prices, withdrawals from 401k sell and thus decrease stock prices; an older population means less investment and greater withdrawal). Do you have a source for your decrease surplus population claim?
The general rule of thumb is that five words, even with paraphrasing, of unquoted or uncited text is plagiarism:
Not sure what working with China is the best idea, given their track record of retractions
https://www.nature.com/articles/d41586-021-00733-5