c. Which outcome measures in Table 4A show statistically signicant effects (at least the 5% level) of providing a recycling bin? [4 points] d. Which outcome measures in Table 4A show statistically signicant effects (at least the 5% level) of sending text messages? [4 points] e. Suppose that the covariate "percentage of visits turned in bag, baseline\" had been Iett out of the regression reported in Column 1. [Note: by "baseline," they mean, "before the experiment started." So, " percentage of visits turned in bag, baseline" just means "percentage of weeks in which the household turned in a bag in the weeks before the treatment began.\" The outcome variable in this regression, by contrast, is the same measure. but collected after the experiment started] What would you expect to happen to the results on providing a recycling bin? In particular: Would you expect an increase. decrease. or no change in the estimated ATE? Would you expect an increase or decrease in the standard error? Explain your reasoning. [4 points] t- In column 1 of Table 4A, would you say the variable "has cell phone." which was measured before the start of the experiment, is a "bad control" that should not be included in the regression? Explain your reasoning. [4 points] Problem 2 - Using Regression to Measure The impact of a "Work From Home" Policy on Employee Productivity [32 points] Managers fiercely debate whether to allow employees to work from home. For example. Marissa Mayer of Yahoo! touched off a firestorm when she famously reversed Yahool's work from home polig and forced all Yahoo! employees to come into work every day. Employees argued that they would be more productive from home. but data from other workplaces show that workers are sometimes dishonest about how much work they are actually getting done while working from home. Meanwhile, The New York Times editorial board continues to run data-free articles that opine on both sides of the work from home debate. In debates like these about firm management practices, rigorously measuring impact can cut through reasonable points made by both sides and begin to uncover the truth. Stanford Economist Nick Bloom and his colleagues worked with a call center rm in China to measure the impact of a new "Work from Home" (WFH) policy the rm implemented. The results are reported in an article that appeared in the Quarterly Journal of Economics. (You do not need to read that article.) Bloom and colleagues ran a 9-month long randomized controlled trial with a Chinese travel agency called "Ctrip"(j$) and evaluated the impact of WFH on employee performance and productivity. In this question, we will analyze the impact of the rm's WFH policy. You can download a version of the data that I've cleaned and over-Sit'hptied here. in the data: 0 Mb = the treatment indicator; 1 = randomly assigned to work from home; 0 = randomly assigned to have to come to the office perform_during = "the number of phone calls answered and number of orders taken". after the experiment began. This is the outcome. This is observed for both the treatment and the control group; the control group's working conditions did not change, but we track of their productivity after the experiment started, too. ' perform_before = "the number of phone calls answered and number of orders taken", the same measure as above. but recorded for a fixed time period before the experiment