2. Consider the following two periods panel data model:Wageit = Bo + SoD2 + ß₁ Educit + B₂ Expit +B3Female; + ai + uit, t = {1,2},where D2 is a dummy variable which equals to one in period 2 and zero in period 1.(a) Can we estimate the above model by OLS? Explain why.(b) Explain whether the OLS regression controls for individual-specific unobservedheterogeneity (i.e., a fixed effect a;)?(c) Write down the first differenced model. State which coefficients can be esti-mated by OLS?(d) Explain whether the first differenced model controls for individual-specific un-observed heterogeneity (i.e., a fixed effect a;)?(e) Write down the demeaned model. State which coefficients can be estimated byOLS?(f) Show that the models in (c) and (e) are actually equivalent.

This panel data analysis involves a two-period model that examines the factors influencing wages ()…

2. Consider the following two periods panel data model: Wage it = Bo + do D2 + ß₁Educit + ß₂Expit + ß3Female; + ai + Uit, t = {1, 2}, where D2 is a dummy variable which equals to one in period 2 and zero in period 1. (a) Can we estimate the above model by OLS? Explain why. (b) Explain whether the OLS regression controls for individual-specific unobserved heterogeneity (i.e., a fixed effect a;)?

2. Consider the following two periods panel data model: Wage it = Bo + do D2 + ß₁Educit + ß₂Expit + ß3Female; + ai + Uit, t = {1, 2}, where D2 is a dummy variable which equals to one in period 2 and zero in period 1. (a) Can we estimate the above model by OLS? Explain why. (b) Explain whether the OLS regression controls for individual-specific unobserved heterogeneity (i.e., a fixed effect a;)?

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
3. Wine Participant magazine has collected average price per bottle for the prestigious Chateau Le Thundebird bordeaux for different vintages (years). The data appears in the table below. year of bottling price a) draw the scatter diagram showing how wine price varies by vintage year b) use the most appropriate regression equation to determine the relationship between year of bottling (age) and price. c) what is the explanatory power (RSQ) of that equation d) determine the predicted price of a bottle of this wine for the 2017 vintage. 2009 36 2010 40 2011 51 2012 60 2013 68 2014 72 2015 70 2016 65 2018 51 2019 44 2020 39
The following result perspective in RapidMiner shows a multiple linear regression model. Based on the diagram, the model for our dependent variable Y is Predicted Y= (Insulation *0.420)+(Temperature *0.071)+(Avg_Age*0.065)+(Home_Size *0.311)+7.589 Attribute Insulation Temperature Avg Age Home Size (Intercept) O True O False Coefficient 3.323 -0.869 1.968 3.173 134.511 Std. Error 0.420 0.071 0.065 0.311 7.589 Std. Coefficient 0.164 -0.262 0.527 0.131 ? Tolerance 0.431 0.405 0.491 0.914 ? t-Stat 7.906 -12.222 30.217 10.210 17.725
A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+BOIL+yEXP+8FDI Where FR = yearly foreign reserves ($000's), OIL = annual oil prices, EXP = yearly total exports ($000's) and FDI = annual foreign direct investment ($000's). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Сoef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 ** S = 2.45 R-sq 96.3% R-sq (adj) 95.3% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values *', ***', '?'and ??' d) Hence test whether B is significant. Give reasons for your answer. e) Perform the F…
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Data on 220 reported crimes is collected from district X in 2016. Suppose CS denotes the total cost to the state of offering crime protection services to this district (in thousand dollars), LEOP denotes the number of law enforcement officers on patrol, DTP denotes the damage to public and private property (in thousand dollars), CCTV denotes the number of CCTV cameras installed in the district, and Prison denotes the number of prison inmates The following table shows the results of a few regressions of the total cost to the state. Dependent variable: total cost to the state (in thousand dollars) Regressor (1) (2) (3) (4) 12.32 17.99 14.55 18.1 LEOP (0.52) (0.84) (2.25) (0.82) 0.73 0.59 0.75 DTP (0 12) (0.04) 0.73 (0.06) CCTV (0.13) 2.11 2.12 (0.39) 288.5 (4 14) Prison (0.5) 182.5 191.6 219.95 Intercept (11.52) (6.68) (5.26) 0.64 0.75 0.12 0.75 R 220 220 220 220 Heteroskedasticity-robust standard errors are given in parentheses under coefficients. Which of the following statements…
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The model developed from sample data that has the form of Yhat = bo +bjX is known as the multiple regression model with two predictor variables. (True or False) O True O False
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
https://drive.google.com/file/d/1-aOh_O4aiPAqBldOcC70gIxAYx5PCMnx/view?usp=sharing
Hormone replacement therapy (HRT) is thought to increase the risk of breast cancer. The accompanying data on x percent of women using HRT and y breast cancer incidence (cases per 100,000 women) for a region in Germany for 5 years appeared in the paper *Decline in Breast Cancer Incidence after Decrease in Utilization of Hormone Replacement Therapy." The authors of the paper used a simple linear regression model to describe the relationship between HRT use and breast cancer incidence. HRT Use Breast Cancer Incidence 46.30 103.30 40.60 105.00 39.50 100.00 36.60 93.80 30.00 83.50 (a) What is the equation of the estimated regression line? (Round your numerical values to four decimal places.) 9= (b) What is the estimated average change in breast cancer incidence (in cases per 100,000 women) associated with a 1 percentage point increase in HRT use? (Round your answer to four decimal places.) cases per 100,000 women (c) What breast cancer incidence (in cases per 100,000 women) would be…
What is Instrumental Variables Regression?