This study source was downloaded by 100000839564890 from CourseHero com on 06 10 2023 06 07 17 GMT 05 00 https www coursehero com file 90250185 ECON2271 Week 4 Exercisesdocx ECON2271 Business EconometricsStudent Activities for week 4To do list for week 4 1 Make sure you re OK with the lecture material from weeks 1 2 and 3 use the suggested textbook references to read up further a necessary 2 Complete the pre lab exercises next page which relate to Topic 2 what we ve done to date 3 Attend your scheduled lab in the trading room to complete the lab exercises 4 Attempt Quiz 2 on LMS AFTER your lab session The Quiz can be found in the Assessments area on LMS and will be open from 3 30pm on Wednesday until 10 00am on Friday Here is a list of learning outcomes for the first two weeks for your reference Topic 2 i Univariate Regression For the general econometric model Y b0 b1X u Students able to distinguish between model variables and parameters Students able to interpret meaning of model parameters and error term Students able to test simple hypotheses comparing means using dummy regression Students able to explain the basic premise of OLS Students able to evaluate goodness of fit using R squared and F stat Students able to estimate simple univariate regression model and interpret key regression output correctly Topic 2 ii Univariate Regression For the general econometric model Y b0 b1X u Understand meaning of OLS estimates being BLUE Understand the key factors which may prevent OLS estimates being blue specifically Understand the assumptions about Y and its relationship with X Understand key assumptions about disturbances e or u Recognise the logarithmic function and know how to specify a lin log function of Y which is linear in the model parameters i e a linearized function Able to interpret model estimates for the lin log function 1 This study source was downloaded by 100000839564890 from CourseHero com on 06 10 2023 06 07 17 GMT 05 00 https www coursehero com file 90250185 ECON2271 Week 4 Exercisesdocx Lab Preparation Exercises1 I want to find out whether men and women s physical health is different In order to do so I estimate a very simple dummy variable model with physical health PH and gender a dummy variable where 1 female and 0 male The output and most basic summary statistics for the variables are provided below except I have blanked out some of the vital information Complete the table and interpret the results What do you think you can conclude from this 2 This study source was downloaded by 100000839564890 from CourseHero com on 06 10 2023 06 07 17 GMT 05 00 https www coursehero com file 90250185 ECON2271 Week 4 Exercisesdocx 2 I have two alternative model specifications for the relationship between life satisfaction LS and income Income is measured in annual equivalised household income and is measured in tens of thousands of dollars INC in specification i and in dollars INCOME in specification ii i LSi b0 b1 INCi uiii LSi b0 b1ln INCOMEi 1 uiStata provides these estimates cons 7 773985 0172347 451 07 0 000 7 740203 7 807767 inc 0246917 0024233 10 19 0 000 0199418 0294415 ls Coef Std Err t P t 95 Conf Interval Total 37161 1064 17 502 2 12324914 Root MSE 1 4529 Adj R squared 0 0058 Residual 36941 9488 17 501 2 11084789 R squared 0 0059 Model 219 157596 1 219 157596 Prob F 0 0000 F 1 17501 103 82 Source SS df MS Number of obs 17 503 reg ls inc gen inc income 10000 cons 6 445769 1408791 45 75 0 000 6 169632 6 721906 lninc 1369685 0131442 10 42 0 000 1112046 1627324 ls Coef Std Err t P t 95 Conf Interval Total 37161 1064 17 502 2 12324914 Root MSE 1 4527 Adj R squared 0 0061 Residual 36931 9594 17 501 2 1102771 R squared 0 0062 Model 229 146996 1 229 146996 Prob F 0 0000 F 1 17501 108 59 Source SS df MS Number of obs 17 503 reg ls lninc gen lninc ln income 1 a What are the assumptions underpinning each specification b How can these results help you determine which model specification is correct c Provide an interpretation of the estimated model parameters for both models d Calculate the predicted life satisfaction score for someone with an income of 0 10 000 and 100 000 using both sets of model estimates Do a simple back of the envelope plot and compare 3 This study source was downloaded by 100000839564890 from CourseHero com on 06 10 2023 06 07 17 GMT 05 00 https www coursehero com file 90250185 ECON2271 Week 4 Exercisesdocx 4 This study source was downloaded by 100000839564890 from CourseHero com on 06 10 2023 06 07 17 GMT 05 00 https www coursehero com file 90250185 ECON2271 Week 4 Exercisesdocx 3 Some people tell me people get happier as they get older but my economist friend thinks this is rubbish In order to figure out who is right if any I get some data on life satisfaction LS andage for a large sample of Australians I then estimate the model LSi b0 b1 AGEi uiStata provides these estimates cons 7 793649 0280274 278 07 0 000 7 738713 7 848586 age 002595 0005782 4 49 0 000 0014617 0037284 ls Coef Std Err t P t 95 Conf Interval Total 37161 1064 17 502 2 12324914 Root MSE 1 4563 Adj R squared 0 0011 Residual 37118 385 17 501 2 12092937 R squared 0 0011 Model 42 7214775 1 42 7214775 Prob F 0 0000 F 1 17501 20 14 Source SS df MS Number of obs 17 503 reg ls age a What Stata command will produce the results you see b How can you interpret these results c Generate a prediction for the life satisfaction of someone aged 15 40 and 70 d Using the Excel spreadsheet provided generate predicted and residual life satisfaction for all individuals in the sample using the estimated model parameters See if you can generate the SSE model SS and SSR residual SS for these estimates and thereby verify the R squared statistic 5 This study source was downloaded by 100000839564890 from CourseHero com on 06 10 2023 06 07 17 GMT 05 00 https www coursehero com file 90250185 ECON2271 Week 4 Exercisesdocx 4 I talk to my psychologist friend about my life satisfaction age model She laughs and tells me I should estimate my model twice once for people below age 40 and once for people 40 and above When I get back to my office Stata provides the output below How can you make sense of this What do you think my psychologist friend wanted me to discover cons 6 676103 0745929 89 50 0 000 6 529885 6 822321 age 0206362 001235 16 71 0 000 0182153 0230571 ls Coef Std Err t P t 95 Conf Interval Total 22168 2435 9 560 2 31885392 Root MSE 1 5011 Adj R squared 0 …