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Principles Of Econometrics 4th Edition R Hill - Solutions

The labor supply of married women has been a subject of a great deal of economic research. A classic work6 is that of Professor Tom Mroz, who kindly provided his data to us. The data file is mroz.dat and the variable definitions are in the file mroz.def. The data file contains information on women
Supply and demand curves as traditionally drawn in economics principles classes have price (P) on the vertical axis and quantity (Q) on the horizontal axis.(a) Rewrite the truffle demand and supply equations in (11.11) and (11.12) with price P on the left-hand side. What are the anticipated signs
Estimate (11.11) and (11.12) byleast squares regression,ignoringthe factthatthey form a simultaneous system. Use the data in truffles.dat. Compare your results to those in Table 11.3. Do the signs of the least squares estimates agree with economic reasoning?
(a) Use your computer software for two-stage least squares or instrumental variables estimation, and the 30 observations in the file truffles.dat to obtain 2SLS estimates of the system in (11.11) and (11.12). Compare your results to those in Table 11.3.(b) Using the 2SLS estimated equations,
Consider the following simultaneous equations model. Assume that x is exogenous.y1 ¼ bx þ e y2 ¼ ay1 þ u(a) How would you estimate the parameter b? Is it identified?(b) How would you estimate the parameter a? Is it identified?
Suppose you want to estimate a wage equation for married women of the form lnðWAGEÞ ¼ b1 þ b2HOURS þ b3EDUC þ b4EXPER þ e where WAGE is hourly wage, HOURS is the number of hours worked per week, EDUC is years of education, and EXPER is years of experience. Your classmate observes that higher
and on graph paper accurately sketch the supply and demand equations. For these sketches, set the values of the exogenous variables DI, PS, and PF to be DI ¼ 3:5, PF ¼ 23, and PS ¼ 22.(b) What are the equilibrium values of P and Q from (a)?(c) Calculate the predicted equilibrium values of P and
Supply and demand curves as traditionally drawn in economics principles classes have price (P) on the vertical axis and quantity (Q) on the horizontal axis.(a) Take the estimates in Table
Can you suggest a method for using the reduced-form (11.4) and (11.5) to obtain an estimate of the slope of the supply function Q ¼ b1P þ es? In particular, suppose that the estimated reduced-form equations are P^ ¼ 18X and Q^ ¼ 5X. What is an estimated value of b1? (Hint: look at the
Consider a supply model for edible chicken, which the U.S. Department of Agriculture calls ‘‘broilers.’’ The data for this exercise are in the file newbroiler.dat, which is adapted from the data provided by Epple and McCallum (2006).7 The data are annual, 1950–2001, but in the estimations
The labor supply of married women has been a subject of a great deal of economic research. A classic work6 is that of Professor Tom Mroz, who kindly provided us his data. The data file is mroz.dat and the variable definitions are in the file mroz.def. The data file contains information on women who
A consulting firm run by Mr. John Chardonnay is investigating the relative efficiency of wine production at 75 California wineries. John sets up the production function Q ¼ b1 þ b2MGT þ b3CAP þ b4LAB þ e where Q is an index of wine output for a winery, taking into account both quantity and
The 500 values of x; y; z1; and z2 in ivreg2.dat were generated artificially. The variable y ¼ b1 þ b2x þ e ¼ 3 þ 1x þ e.(a) The explanatory variable x follows a normal distribution with mean zero and variance s2 x ¼ 2. The random error e is normally distributed with mean zero and variance
Using your computer software, and the 50 observations on savings (y), income (x), and averaged income (z) in savings.dat,(a) Estimate a least squares regression of savings on income.(b) Estimate the relation between savings and income (x) using the instrumental variables estimator, with instrument
The 25 values of x and e in ivreg1.dat were generated artificially. Use your computer software to carry out the following:(a) Create the value of the dependent variable y from the model y ¼ b1 þ b2x þ e ¼1 þ 1 x þ e by the method described in Section 10.1.3.(b) In the same graph, plot the
To examine the quantity theory of money, Brumm (2005) [‘‘Money Growth, Output Growth, and Inflation: A Reexamination of the Modern Quantity Theory’s Linchpin Prediction,’’ Southern Economic Journal, 71(3), 661–667] specifies the equation INFLAT ¼ b1 þ b2MONEY þ b3OUTPUT þ e where
The labor supply of married women has been a subject of a great deal of economic research. Consider the following supply equation specification HOURS ¼ b1 þ b2WAGE þ b3EDUC þ b4AGE þ b5KIDSL6 þ b6KIDS618þ b7NWIFEINC þ e where HOURS is the supply of labor, WAGE is hourly wage, EDUC is years
Using state level data, a researcher wishes to examine the relationship between the median rent paid (RENT) as a function of median house values (MDHOUSE in$1,000). The percentage of the state population living in an urban area (PCTURBAN)is used as an additional control.(a) The least squares
Consider the infinite lag representation of (9.95) that we write as INFt ¼ a þ 1 s¼0 bsWGWTHts þ et(a) Derive expressions that can be used to calculate a and the bs from u1; u3; d; and d0.(b) Estimate the rate of inflation when WGWTH remains at WGWTH ¼ 0. Use the estimates from (9.95) to test
If you have not already done so, use the data in infln_wage.dat to estimate (9.95).Given that WGWTH2010Q2 ¼ 0:6; WGWTH2010Q3 ¼ 0:5; WGWTH2010Q4 ¼ 0:7; and WGWTH2011Q1 ¼ 0:4, find 95% forecast intervals for inflation in 2010Q2, 2010Q3, 2010Q4, and 2011Q1. Does knowing wage growth tell you much
In this question we investigate the effect of wage changes on the inflation rate. Such effects can be from the demand side or the supply side. On the supply side, we expect wage increases to increase costs of production and to drive up prices. On the demand side, wage increases mean greater
Consider the infinite lag representation of (9.94) that we write as CONGWTHt ¼ a þ 1 s¼0 bsINCGWTHts þ et(a) Derive expressions that can be used to calculate the bs from u2; d0; and d1.(b) Find estimates for the one-, two-, and three-quarter delay and interim multipliers, and the total
If you have not already done so, use the data in consumptn.dat and the sample period 1960Q4 to 2009Q4 to estimate (9.94). Given that INCGWTH2010Q1 ¼0:6; INCGWTH2010Q2 ¼ 0:8; and INCGWTH2010Q3 ¼ 0:7, find 90% forecast intervals for consumption growth in 2010Q1, 2010Q2, and 2010Q3. Comment on
An important relationship in macroeconomics is the consumption function. The file consumptn.dat contains quarterly data from 1960Q1 to 2009Q4 on the percentage changes in disposable personal income and personal consumption expenditures. We describe these variables as income growth (INCGWTH) and
In (9.59) we obtained the following estimated equation for Okun’s Law DUdt ¼ 0:3780 þ 0:3501DUt1 0:1841Gt 0:0992Gt1ðseÞ ð0:0578Þ ð0:0846Þ ð0:0307Þ ð0:0368Þ(a) Use the data in okun.dat to reproduce these estimates.(b) Check the correlogram of the residuals. Are there any significant
(a) Show that (9.93) can be written as HOMESt ¼ d þ ð Þ u1 þ 1 HOMESt1 u1HOMESt2 þ u5DHOMESt5þ d1DIRATEt1 þ d3DIRATEt3 þ vt(b) If you have not already done so, estimate (9.93). Use this estimated equation and the result in part (a) to forecast the number of new one-family houses sold in
In this exercise we explore further the relationship between houses sold and the mortgage rate that was introduced in Exercise 9.6. To familiarize yourself with the variables, go back and read the question for Exercise 9.6. Then, use the data in homes.dat to answer the following questions:(a) Graph
You wish to compare the performance of an AR model and an exponential smoothing model for forecasting sales revenue one week into the future.(a) Using the data in ex9_13.dat, estimate an AR(2) model for SALES. Check to see if the errors are serially correlated.(b) Re-estimate the AR(2) model with
The file growth47.dat contains 250 quarterly observations on U.S. GDP growth(percentage change in GDP) from quarter 2, 1947, to quarter 3, 2009.(a) Estimate an AR(2) model for GDP growth and check to see if the residuals are autocorrelated. What residual autocorrelations, if any, are significantly
Consider further the ARDL(1,1) supply response model for sugar cane estimated in part (e) of Exercise 9.15.lnð Þ¼ AREAt d þ u1 lnð Þþ AREAt1 d0 lnð Þþ PRICEt d1 lnð Þþ PRICEt1 vt(a) Suppose the first two post-sample prices are PRICETþ1 ¼ 1 and PRICETþ2 ¼0:8. Use the estimated
Reconsider the sugar cane supply response problem that was introduced in Exercise 9.14. Using data in bangla.dat, estimate the following model with no lags lnð Þ¼ AREAt b1 þ b2 lnð Þþ PRICEt et(a) Find the correlogram for the residuals. What autocorrelations are significantly different from
One way of modeling supply response for an agricultural crop is to specify a model in which area planted (acres) depends on price. When the price of the crop’s output is high, farmers plant more of that crop than when its price is low. Letting AREA denote area planted, and PRICE denote output
The file ex9_13.dat contains 157 weekly observations on sales revenue (SALES)and advertising expenditure (ADV) in millions of dollars for a large midwest department store for 2005–2007. (Exercise 9.2 used data on this store for 2008–2009.) The weeks are from December 28, 2004, to December 25,
Increases in the mortgage interest rate increase the cost of owning a house and lower the demand for houses. In this question we consider an equation where the monthly change in the number of new one-family houses sold in the U.S. depends on last month’s change in the 30-year conventional
Reconsider the estimated equation and covariance matrix in Exercise 9.2. Suppose, as a marketing executive for the department store, that you have a total of $6 million to spend on advertising over the next three weeks, t ¼ 106, 107, and 108. Consider the following allocations of the $6
The file ex9_2.dat contains 105 weekly observations on sales revenue (SALES) and advertising expenditure (ADV) in millions of dollars for a large midwest department store in 2008 and 2009. The following relationship was estimated:SALES bt ¼ 25:34 þ 1:842 ADVt þ 3:802 ADVt1 þ 2:265 ADVt2(a)
Consider the following distributed lag model relating the percentage growth in private investment (INVGWTH) to the federal funds rate of interest (FFRATE):INVGWTHt ¼ 4 0:4FFRATEt 0:8FFRATEt1 0:6FFRATEt2 0:2FFRATEt3(a) Suppose FFRATE = 1% for t ¼ 1, 2, 3, 4. Use the above equation to forecast
In Exercise 7.7 we considered a model designed to provide information to mortgage lenders. They want to determine borrower and loan factors that may lead to delinquency or foreclosure. In the file lasvegas.dat are 1000 observations on mortgages for single-family homes in Las Vegas, Nevada during
This exercise is a continuation of Exercise 8.20. Estimates from 8.20(c) and 8.20(d)should be used to answer the following questions.(a) Forecast the wage of a married worker with 18 years of education and 16 years of experience. Use both the natural predictor and the corrected predictor. (See
Consider again the data in cps4_small.dat and the wage equation lnðWAGEÞ ¼ b1 þ b2EDUC þ b3EXPER þ b4EXPER2þ b5ðEXPEREDUCÞ þ e 8.7 EXERCISES 329(a) Plot the least squares residuals against EDUC and against EXPER. What do they suggest?(b) Test for heteroskedasticity using a Breusch-Pagan
(a) Using the data in cps4_small.dat estimate the following wage equation with least squares and heteroskedasticity-robust standard errors:lnðWAGEÞ ¼ b1 þ b2EDUC þ b3EXPER þ b4EXPER2þ b5ðEXPEREDUCÞ þ e Report the results.(b) Add MARRIED to the equation and re-estimate. Holding education
In Section 8.6.1 we estimated the linear probability model COKE ¼ b1 þ b2PRATIO þ b3DISP COKE þ b3DISP PEPSI þ e where COKE ¼ 1 if a shopper purchased Coke and COKE ¼ 0 if a shopper purchased Pepsi. The variable PRATIO was the relative price ratio of Coke to Pepsi, and DISP_COKE and
The file br2.dat contains data on 1080 houses sold in Baton Rouge, Louisiana during mid-2005. We will be concerned with the selling price (PRICE), the size of the house in square feet (SQFT ), and the age of the house in years (AGE). Define a new variable that measures house size in terms of
Consider the following model used to explain gasoline consumption per car in Germany and Austria for the period 1960–1978:lnðGASÞ ¼ b1 þ b2lnðINCÞ þ b3lnðPRICEÞ þ b4lnðCARSÞ þ e where INC is per capita real income, PRICE is the real gasoline price, and CARS is the per capita stock of
(a) Reconsider the wage equation that was estimated in Section 8.4.2. Instead of estimating the variances from two separate subsamples, one for metropolitan and the other for rural, estimate the two variances using the model s2 i ¼ expða1 þ a2METROiÞand one single combined sample. Are your
In the file cloth.dat there are 28 time-series observations on total cost (C) and output(Q) for two clothing manufacturing firms. It is hypothesized that both firms’ cost functions are cubic and can be written as firm 1: C1t ¼ b1 þ b2Q1t þ b3Q2 1t þ b4Q3 1t þ e1t firm 2: C2t ¼ d1 þ d2Q2t
Consider the following cost function where C denotes cost and Q denotes output.Assume that varðe1tÞ ¼ s2Q1t. We use a subscript t because the observations are time-series data. They are stored in the file cloth.dat.C1t ¼ b1 þ b2Q1t þ b3Q2 1t þ b4Q3 1t þ e1t(a) Find generalized least squares
In the file pubexp.dat there are data on public expenditure on education (EE), gross domestic product (GDP), and population (P) for 34 countries in the year 1980. It is hypothesized that per capita expenditure on education is linearly related to per capita GDP. That is, yi ¼ b1 þ b2xi þ ei where
(a) The purpose of this exercise is to test whether the variance specification s2 i ¼s2xi introduced in Section 8.4.1 has been adequate to eliminate heteroskedasticity in the food expenditure example in the text. Compute the squares of the residuals from the transformed model used to obtain the
(a) Using the estimates obtained in part (a) of Exercise 8.8 as the parameter values, and assuming normally distributed errors, find the probability that (i) your 1400-square-foot house sells for more than $115,000 and (ii) your 1800-square-foot house sells for less than $110,000.(b) After making
A sample of 200 Chicago households was taken to investigate how far American households tend to travel when they take vacation. Measuring distance in miles per year, the following model was estimated MILES ¼ b1 þ b2INCOME þ b3AGE þ b4KIDS þ e
(large data set) Use the data file cps4.dat for the following:(a) Estimate the model used in Table 7.4. (i) Test the null hypothesis that the interaction between BLACK and FEMALE is statistically significant. (ii) Test the null hypothesis that there is no regional effect.(b) Estimate the model used
This question extends the analysis of Exercise 7.10. Read the introduction to that exercise if you have not done so. Each city in the sample may have unique, unobservable characteristics that affect LNPRICE and LNUNITS. Following the discussion in Section 7.5.6, use the differenced data to control
Consider again the data in the file tuna.dat used in Exercise 6.24. Carry out the following data transformations:(a) Estimate each of the following three equations and explain the relationship between the estimated coefficients:SAL1 ¼ b1 þ b2APR1 þ b3APR2 þ b4APR3 þ e SAL1 ¼ a1 þ a2PR1 þ
Data on the weekly sales of a major brand of canned tuna by a supermarket chain in a large midwestern U.S. city during a mid-1990s calendar year are contained in the file tuna.dat. There are 52 observations on the variables. The variable SAL1 ¼ unit sales of brand no. 1 canned tuna, APR1 ¼ price
Use the data in cps4_small.dat to estimate the following wage equation:lnðWAGEÞ ¼ b1 þ b2EDUC þ b3EDUC2 þ b4EXPERþ b5EXPER2 þ b6ðEDUC EXPERÞ þ e(a) Find 95% interval estimates for:(i) The approximate percentage change in WAGE from an extra year of education for someone with 10 years of
In Chapter 5.7 we used the data in file pizza4.dat to estimate the model PIZZA ¼ b1 þ b2AGE þ b3INCOME þ b4ðAGE INCOMEÞ þ e(a) Test the hypothesis that age does not affect pizza expenditure—that is, test the joint hypothesis H0:b2 ¼ 0, b4 ¼ 0. What do you conclude?(b) Construct point
Re-estimate the model in Exercise 6.20 with (i) FERT omitted, (ii) LABOR omitted, and (iii) AREA omitted. In each case, discuss the effect of omitting a variable on the estimates of the remaining two elasticities. Also, in each case, check to see if RESET has picked up the omitted variable.
Reconsider the production function for rice estimated in Exercise 5.24 using data in the file rice.dat:lnðPRODÞ ¼ b1 þ b2 lnðAREAÞ þ b3 lnðLABORÞ þ b4 lnðFERTÞ þ e(a) Using a 5% level of significance, test the hypothesis that the elasticity of production with respect to land is equal
Reconsider the commuting time model estimated in Exercise 5.21 using the data file commute.dat:TIME ¼ b1 þ b2DEPARTS þ b3REDS þ b4TRAINS þ e Find a 95% interval estimates for the time Bill arrives at the University when:(a) He leaves Carnegie at 7:00 AM and encounters six red lights and one
The file stockton4.dat contains data on 1,500 houses sold in Stockton, CA during 1996 –1998. Variable descriptions are in the file stockton4.def.(a) Estimate the following model lnðSPRICEÞ ¼ b1 þ b2LIVAREA þ b3LIVAREA2 þ b4AGE þ b5AGE2þ b6BEDS þ b7ðLIVAREA BEDSÞ þ b8ðLIVAREA2
The file stockton4.dat contains data on 1500 houses sold in Stockton, CA during 1996–1998. Variable descriptions are in the file stockton4.def.(a) Estimate the following model and report the results lnðSPRICEÞ ¼ b1 þ b2LIVAREA þ b3LIVAREA2 þ b4AGE þ b5AGE2þ b6BEDS þ e(b) Using a 5%
Reconsider the data and model estimated in Exercise 6.15.(a) Add the variables LIVAREA2 and AGE2 to the model, re-estimate it, and report the results.250 FURTHER INFERENCE IN THE MULTIPLE REGRESSION MODEL(b) Does an F-test suggest that the addition of LIVAREA2 and AGE2 has improved the model? Use a
The file stockton4.dat contains data on 1500 houses sold in Stockton, California, during 1996 –1998. Variable descriptions are in the file stockton4.def.(a) Estimate the following model and report the results:
Following on from the example in Section 6,3, the file hwage.dat contains another subset of the data used by labor economist Tom Mroz. The variables with which we are concerned are What effects do changes in the level of education and age have on wages?(b) Does RESET suggest that the model in part
The file toodyay.dat contains 48 annual observations on a number of variables related to wheat yield in the Toodyay Shire of Western Australia, for the period 1950– 1997.Those variables are Y ¼ wheat yield in tonnes per hectare, t ¼ trend term to allow for technological change, RG ¼ rainfall
Using data in the file beer.dat, apply RESET to the two alternative models lnðQÞ ¼ b1 þ b2 lnðPBÞ þ b3 lnðPLÞ þ b4 lnðPRÞ þ b5 lnðIÞ þ e Q ¼ b1 þ b2PB þ b3PL þ b4PR þ b5I þ e Which model seems to better reflect the demand for beer?
Consider production functions of the formQ¼f(L,K), where Q is the output measure and L andKare labor and capital inputs, respectively. A popular functional form is the Cobb–Douglas equation lnðQÞ ¼ b1 þ b2 lnðLÞ þ b3 lnðKÞ þ e(a) Use the data in the file cobb.dat to estimate the
Use the sample data for beer consumption in the file beer.dat to(a) Estimate the coefficients of the demand relation (6.14) using only sample information. Compare and contrast these results to the restricted coefficient results given in (6.19).(b) Does collinearity appear to be a problem?(c) Test
In Exercise 5.25 we expressed the model Y ¼ aKb2Lb3Eb4Mb5 expfeg in terms of logarithms and estimated it using data in the file manuf.dat. Use the data and results from Exercise 5.25 to test the following hypotheses:(a) H0 :b2 ¼ 0 against H1 :b2 6¼ 0:(b) H0 :b2 ¼ 0, b3 ¼ 0 against H1 :b2 6¼ 0
In Section 6.1.5 we tested the joint null hypothesis H0 :b3 þ 3:8 b4 ¼ 1 and b1 þ 6 b2 þ 1:9 b3 þ 3:61 b4 ¼ 80 in the model SALES ¼ b1 þ b2PRICE þ b3ADVERT þ b4ADVERT2 þ e By substituting the restrictions into the model and rearranging variables, show how the model can be written in a
Table 6.5 contains output for the two models y ¼ b1 þ b2x þ b3w þ e y ¼ b1 þ b2x þ e obtained using N ¼ 35 observations. RESET applied to the second model yields F-values of 17.98 (for ^y2) and 8.72 (for ^y2 and ^y3). The correlation between x and w is rxw ¼ 0:975. Discuss the following
RESET suggests augmenting an existing model with the squares of the predictions^y2, or with their squares and cubes (^y2; ^y3). What would happen if you augmented the model with the predictions themselves ^y?
Consider the wage equation lnðWAGEÞ ¼ b1 þ b2EDUC þ b3EDUC2 þ b4EXPER þ b5EXPER2þ b6HRSWK þ e(a) Suppose you wish to test the hypothesis that a year of education has the same effect on ln (WAGE) as a year of experience. What null and alternative hypotheses would you set up?(b) What is the
Consider the wage equation lnðWAGEÞ ¼ b1 þ b2EDUC þ b3EDUC2 þ b4EXPER þ b5EXPER2þ b6ðEDUC EXPERÞ þ b7HRSWK þ e where the explanatory variables are years of education, years of experience and hours worked per week. Estimation results for this equation, and for modified versions of it
Consider the model y ¼ b1 þ x2b2 þ x3b3 þ e and suppose that application of least squares to 20 observations on these variables yields the following results cov ( bb) denotes the estimated covariance matrix:b1 b2 b3 24 35 ¼0:96587 0:69914 1:7769 24 35; bcovðbÞ ¼0:21812 0:019195 0:050301
Consider again the model in Exercise 6.1. After augmenting this model with the squares and cubes of predictions ^y2 and ^y3, we obtain SSE ¼ 696:5357. Use RESET to test for misspecification.
When using N ¼ 40 observations to estimate the model y ¼ b1 þ b2x þ b3z þ e you obtain SSE ¼ 979:830 and sy ¼ 13:45222. Find(a) R2(b) The value of the F-statistic for testing H0 :b2 ¼ b3 ¼ 0 (Do you reject or fail to reject H0?)
Consider the following aggregate production function for the U.S. manufacturing sector:Y ¼ aKb2Lb3Eb4Mb5 expfeg where Y is gross output, K is capital, L is labor, E is energy, and M denotes other intermediate materials. The data underlying these variables are given in index form in the file
The file rice.dat contains 352 observations on 44 rice farmers in the Tarlac region of the Philippines for the 8 years 1990 to 1997. Variables in the data set are tonnes of freshly threshed rice (PROD), hectares planted (AREA), person-days of hired and family labor (LABOR), and kilograms of
Lion Forest has been a very successful golf professional. However, at age 45 his game is not quite what it used to be. He started the pro-tour when he was only 20 and he has been looking back examining how his scores have changed as he got older. In the file golf.dat, the first column contains his
Reconsider the commuting time model estimated in Exercise 5.21 using the data file commute.dat TIME ¼ b1 þ b2DEPARTS þ b3REDS þ b4TRAINS þ e
Each morning between 6:30AM and 8:00AM Bill leaves the Melbourne suburb of Carnegie to drive to work at the University of Melbourne. The time it takes Bill to drive to work (TIME) depends on the departure time (DEPART), the number of red lights that he encounters (REDS), and the number of trains
In Section 5.6.3 we discovered that the optimal level of advertising for Big Andy’s Burger Barn, ADVERT0, satisfies the equation b3 þ 2b4ADVERT0 ¼ 1. Using a 5%significance level, test whether each of the following levels of advertising could be optimal: (a) ADVERT0 ¼ 1:75, (b) ADVERT0 ¼ 1:9,
Use the data in cps4_small.dat to estimate the following wage equation lnðWAGEÞ ¼ b1 þ b2EDUC þ b3EXPER þ b4HRSWK þ e(a) Report the results. Interpret the estimates for b2, b3, and b4. Are these estimates significantly different from zero?(b) Test the hypothesis that an extra year of
What is the relationship between crime and punishment? This important question has been examined by Cornwell and Trumbull4 using a panel of data from North Carolina. The cross sections are 90 counties, and the data are annual for the years 1981–1987. The data are in the file crime.dat.Using the
(a) Reconsider the model SAL1 ¼ b1 þ b2PR1 þ b3PR2 þ b4PR3 þ e from Exercise 5.16. Estimate this model if you have not already done so, and find a 95%interval estimate for expected sales when PR1 ¼ 90; PR2 ¼ 75, and PR3 ¼ 75.What is wrong with this interval?(b) Estimatethe alternative
Data on the weekly sales of a major brand of canned tuna by a supermarket chain in a large midwestern U.S. city during a mid-1990’s calendar year are contained in the file tuna.dat. There are 52 observations on the variables. SAL1 ¼ unit sales of brand no.1 canned tuna; APR1 ¼ price per can of
Reconsider the presidential voting data (fair4.dat) introduced in Exercise 2.14.(a) Estimate the regression model VOTE ¼ b1 þ b2GROWTH þ b3INFLATION þ e Report the results in standard format. Are the estimates for b2 andb3 significantly different from zero at a 10% significance level? Did you
The file br2.dat contains data on 1,080 houses sold in Baton Rouge, Louisiana, during mid-2005. We will be concerned with the selling price (PRICE), the size of the house in square feet (SQFT), and the age of the house in years (AGE). Define a new variable that measures house size in terms of
The file br2.dat contains data on 1,080 houses sold in Baton Rouge, Louisiana, during mid-2005. We will be concerned with the selling price (PRICE), the size of the house in square feet (SQFT), and the age of the house in years (AGE).(a) Use all observations to estimate the following regression
The file cocaine.dat contains 56 observations on variables related to sales of cocaine powder in northeastern California over the period 1984–1991. The data are a subset of those used in the study Caulkins, J. P. and R. Padman (1993), ‘‘Quantity Discounts and Quality Premia for Illicit
(a) The file lond_small.dat contains a subset of 500 observations from the bigger file london.dat. Use the data in the file lond_small.dat to estimate budget share equations of the form W ¼ b1 þ b2lnðTOTEXPÞ þ b3AGE þ b4NK þ e for all budget shares (food, fuel, clothing, alcohol,
When estimating wage equations, we expect that young, inexperienced workers will have relatively low wages and that with additional experience their wages will rise, but then begin to decline after middle age, as the worker nears retirement. This lifecycle pattern of wages can be captured by
An agricultural economist carries out an experiment to study the production relationship between the dependent variable YIELD ¼ peanut yield (pounds per acre) and the production inputs NITRO ¼ amount of nitrogen applied (hundreds of pounds per acre)PHOS ¼ amount of phosphorus fertilizer
What are the standard errors of the least squares estimates b2 and b3 in the regression model y ¼ b1 þ b2x2 þ b3x3 þ e where N ¼ 202, SSE ¼ 11.12389, r23 ¼0.114255, N i¼1ð Þ xi2 x2 2 ¼ 1210:178, and N i¼1ð Þ xi3 x3 2 ¼ 30307:57?
Suppose that from a sample of 63 observations, the least squares estimates and the corresponding estimated covariance matrix are given byTest each of the following hypotheses and state the conclusion:(a) b2 ¼ 0 (b) b1 þ 2b2 ¼ 5 (c) b1 b2 þ b3 ¼ 4 2 b 3 b b3 3 cov(b) = -2 27 40 10 3
This question is concerned with the value of houses in towns surrounding Boston. It uses the data of Harrison, D., and D. L. Rubinfeld (1978), ‘‘Hedonic Prices and the Demand for Clean Air,’’ Journal of Environmental Economics and Management, 5, 81–102. The output appears in Table 5.8.
The data set used in Exercise 5.3 is used again. This time it is used to estimate how the proportion of the household budget spent on transportation WTRANS depends on the log of total expenditure ln(TOTEXP), AGE, and number of children NK. The output is reported in Table 5.7.(a) Write out the
Consider the following model that relates the proportion of a household’s budget spent on alcohol WALC to total expenditure TOTEXP, age of the household head AGE, and the number of children in the household NK.The data in the file london.dat were used to estimate this model. See Exercise 4.10 for

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