Chapter 5Case study: Nurses. The text describes implicit functions for the demand and supply of Registered Nurses in a “Findings” box on page 110. With that discussion as a backdrop, I would like for us to estimate a regression that predicts the number of nurses using some characteristics of potential influence. We are not doing an official supply curve, as that would be much more involved.10 points More detailed directionsand comments:With the case study, wewill extend our use of econometrics to capitalize on the textbook’s use of an “econometric approach”in Figure 5-2 on page 109.Our exercise will usemultiple regression,which we haven’t covered yet. Therefore,Iextend my tutorial on simple regression (there are 2 resources for this, a video entitled Intro to Regression video for the Econ of Healthcare and a journal tutorial calledIntro to Regression video part 2) with another called Multiple Regression Overview.See the excel file entitledNurses (student), which contains several variables on RNs and LPNs fora single year by state. 1Generate: 1a. Generate a correlation matrix, paying close attention to the interaction between the # of RNs and annual salaries of RNs and theannual salaries of LPNs. Are the signs consistent with the theory presented in the “Findings”box on p. 110? 1b.Estimate asample, multiple regression equationusing the # of RNs as the left-hand side variable and 1) annual salaries of RNs and 2) annual salaries of LPNs on the right-hand side. Arethe signs on the sample slope coefficients, consistent withthe theory presented in the “Findings”box on p. 110? 1c. Try the regression again using hourly wages for each on the right-hand side. Do you see any difference in the signs on the coefficients? 1d. What are some things you would do differently in this exercise if more time and resources were available? 1e. How would you use these results in a practical manner as a hospital manager, health care professional, etc.?

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