Questions and Answers of Econometrics

R. Amatya estimated the following logit model of birth control for 1,145 continuously married women aged 35 to 44 in Nepal:Where:Di = 1 if the ith woman has ever used a recognized form of birth
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each:a. Binomial logitb. Binomial probitc.
Run 5-percent Dickey–Fuller tests for the following variables from the chicken demand equation, using dataset CHICK9 on the text’s website, and determine which variables, if any, you think are
Test for serial correlation in the estimated dynamic model you got as your answer to Exercise 3b.
Consider the following equation aimed at estimating the demand for real cash balances in Mexico (standard errors in parentheses):Where:Mt = the money stock in year t (millions of pesos)Rt = the
Write the meaning of each of the following terms without referring to the book (or your notes), and then compare your definition with the version in the text for each:a. Cointegrationb.
R. Bucklin, R. Caves, and A. Lo estimated the following double-log model to explain the yearly circulation of metropolitan newspapers (standard errors in parentheses):Where:Ci = yearly circulation of
A. Ando and F. Modigliani collected the following data on the income and consumption of non-self-employed homeowners:a. Run a regression to explain average consumption as a function of average
Of all the econometric problems we’ve encountered, heteroskedasticity is the one that seems the most difficult to understand. Close your book and attempt to write an explanation of
Let’s return to the analysis of the international pharmaceutical industry that we started in Exercise 9 of Chapter 5. That study was cross sectional and included countries as large as the United
Write the meaning of each of the follow terms without referring to the book (or your notes), and compare your definition with the version in the text for each.a. The Breusch–Pagan testb.
In a 1988 article, Josef Brada and Ronald Graves built an interesting model of defense spending in the Soviet Union just before the breakup of that nation. The authors felt sure that Soviet defense
Suppose that the data in a time-series study were entered in reverse chronological order. Would this change in any way the testing or adjusting for serial correlation? How? In particular:a. What
Consider the following equation for U.S. per capita consumption of beef:Where:CBt = the annual per capita pounds of beef consumed in the United States in year tln Yt = the log of per capita
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each.a. Durbin–Watson testb. First-order
Consider the following regression result paraphrased from a study conducted by the admissions office at the Stanford Business School (standard errors in parentheses):Where:Gi = the Stanford Business
In each of the following situations, determine whether the variable involved is a dominant variable:a. Games lost in year t in an equation for the number of games won in year t by a baseball team
A recent study of the salaries of elementary school teachers in a small school district in Northern California came up with the following estimated equation:Where:SALi = the salary of the ith teacher
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each.a. Dominant variableb. Imperfect
Richard Fowles and Peter Loeb studied the interactive effect of drinking and altitude on traffic deaths.8 The authors hypothesized that drunk driving fatalities are more likely at high altitude than
In 2003, Ray Fair analyzed the relationship between stock prices and risk aversion by looking at the 1996–2000 performance of the 65 companies that had been a part of Standard and Poor’s famous
For each of the following pairs of dependent (Y) and independent (X) variables, pick the functional form that you think is likely to be appropriate, and then explain your reasoning (assume that all
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each.a. Double-log functional formb.
Look back at Exercise 9 in Chapter 5, the equation on international price discrimination in pharmaceuticals. In that cross-sectional study, Schut and VanBergeijk estimated two equations in addition
Suppose that you run a regression to determine whether gender or race has any significant impact on scores on a test of the economic understanding of children.11 You model the score of the ith
For each of the following situations, determine the sign (and, if possible, comment on the likely size) of the expected bias introduced by omitting a variable:a. In an equation for the demand for
You’ve been hired by “Indo,” the new Indonesian automobile manufacturer, to build a model of U.S. car prices in order to help the company undercut U.S. prices. Allowing Friedmaniac zeal to
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each:a. expected biasb. irrelevant
Let’s return to the model of iPod prices on eBay that was developed in Exercise 7 in Chapter 3. That equation was:Where:PRICEi = the price at which the ith iPod sold on eBayNEWi = a dummy variable
Suppose that you estimate a model of house prices to determine the impact of having beach frontage on the value of a house. You do some research, and you decide to use the size of the lot instead of
Return to Section 5.2 and test the appropriate hypotheses with the results in Equation 5.4 for all three coefficients under the following circumstances:a. 5 percent significance and 6 degrees of
Return to Section 5.3 and test the hypotheses implied by Equation 5.5 with the results in Equation 5.6 for all three coefficients under thefollowing circumstances:a. 10 percent significance and 15
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each.a. Alternative hypothesisb.
In 2001, Donald Kenkel and Joseph Terza published an article in which they investigated the impact on an individual’s alcohol consumption of a physician’s advice to reduce drinking.10 In that
Edward Saunders published an article that tested the possibility that the stock market is affected by the weather on Wall Street. Using daily data from 28 years, he estimated an equation with the
Consider the following estimated regression equation (standard errors in parentheses):Where:Yt = the corn yield (bushels/acre) in year tFt = fertilizer intensity (pounds/acre) in year tRt = rainfall
Write the meaning of each of the following terms without referring to the book (or to your notes), and compare your definition with the version in the text for each:a. Biased estimatorb. BLUEc.
Your boss is about to start production of her newest box-office smash-to-be, Invasion of the Economists, Part II, when she calls you in and asks you to build a model of the gross receipts of all the
Use Stata or your own computer regression software to estimate Equation 3.4 using the data in Table 3.1. Can you get the same results?
Contrary to their name, dummy variables are not easy to understand without a little bit of practice:a. Specify a dummy variable that would allow you to distinguish between undergraduate students and
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each:a. Dummy variableb. Omitted
What’s wrong with the following kind of thinking: “I understand that R2 is not a perfect measure of the quality of a regression equation because it always increases when a variable is added to
Let’s return to the height-weight example on page 53 and recall what happened when we added a nonsensical variable that measured the student’s campus post office box number (MAIL) to the
Just as you are about to estimate a regression (due tomorrow), massive sunspots cause magnetic interference that ruins all electrically powered machines (e.g., computers). Instead of giving up and
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each:a. Degrees of freedomb. Estimatec.
Your friend has an on-campus job making telephone calls to alumni asking for donations to your college’s annual fund, and she wonders whether her calling is making any difference. In an attempt to
Return to the housing price model of Section 1.5 and consider the following equation:where: SIZEi = the size (in square feet) of the ith housePRICEi = the price (in thousands of $) of that housea.
Not all regression coefficients have positive expected signs. For example, a Sports Illustrated article by Jaime Diaz reported on a study of golfing putts of various lengths on the Professional
Use your own computer’s regression software and the weight (Y) and height (X) data from Table 1.1 to see if you can reproduce the estimates in Equation 1.19. There are two ways to load the data:
Write the meaning of each of the following terms without referring to the book (or your notes), and compare your definition with the version in the text for each:a. constant or interceptb.
Monte Carlo experiment: Consider the following model:Yi = ?1 + ?2X2i + ?3X3i + uiYou are told that ?1 = 262, ?2 = ?0.006, ?3 = ?2.4, ?2 = 42, and ui??N(0, 42).Generate 10 sets of 64 observations on
The following table gives data on the crime rate in 47 states in the United States for 1960. Try to develop a suitable model to explain the crime rate in relation to the 14 socioeconomic variables
Using the data in the following table, develop a suitable model to explain the behavior of gross real investment in the Greek economy for the period 1960?1995. Look up any textbook on macroeconomics
As noted in the text, there may be several structural breaks in the U.S. economic time series dataset introduced in Section 21.1. Dummy variables are a good way of incorporating these shifts in the
With the definitions of the variables given there, consider the following two models to explain Y:Model A: Yt = α1 + α2X3t + α3X4t + α4X6t + utModel B: Yt = β1 + β2X2t + β3X5t + β4X6t +
The following table gives data on the hourly compensation rate in manufacturing in U.S. dollars, Y (%), and the civilian unemployment rate, X (index, 1992 = 100), forCanada, the United Kingdom, and
The following table gives data on the hourly compensation rate in manufacturing in U.S. dollars, Y (%), and the civilian unemployment rate, X (index, 1992 = 100), forCanada, the United Kingdom, and
Consider the following simple macroeconomic model for the U.S. economy, say, for the period 1960?1999. Private consumption function: Private gross investment function: A money demand
Class Exercise: Consider the following demand-and-supply model for loans of commercial banks to businesses:Demand: Qdt = α1 + α2Rt + α2RDt + α4IPIt + u1tSupply: Qst = β1 + β2Rt + β3RSt +
From the quarterly data for the period 1950€“1960, F. P. R. Brechling obtained the following demand function for labor for the British economy (the figures in parentheses are standard
Since R2as a measure of goodness of fit is not particularly well suited for the dichotomous dependent variable models, one suggested alternative is the Ï‡2test described below:where Ni =
Triangular, or arithmetic, distributed-lag model.€ This model assumes that the stimulus (explanatory variable) exerts its greatest impact in the current time period and then declines by
Consider Eq. (17.13.4):To obtain the variance of Î²Ì‚i from the variances of aÌ‚i, we use the following formula:a. Using the preceding formula, find the variance of
Consider the following distributed-lag model:Assume that Î²i can be adequately expressed by the second-degree polynomial as follows:Î²i = a0 + a1i + a2i2How would you estimate
The inverted V distributed-lag model. Consider the k-period finite distributed-lag modelF. DeLeeuw has proposed the structure for the Î²€™s as in Figure 17.11, where the
Refer to Exercise 12.15. Since the d value shown there is of little use in detecting (first-order) autocorrelation (why?), how would you test for autocorrelation in this case?
Consider the following model:Yˆ—i = Î± + Î²0Xt + utwhere Yˆ— = desired, or long-run, business expenditure for new plant and equipment, Xt = sales, and
Suppose someone convinces you that the relationship between business expenditure for new plant and equipment and sales is as follows:where Yˆ— is desired expenditure and Xˆ—
Using the data given in Exercise 17.22, determine whether plant expenditure Granger-causes sales or whether sales Granger-cause plant expenditure. Use up to six lags and comment on your results. What
Assume that sales in Exercise 17.22 has a distributed-lag effect on expenditure on plant and equipment. Fit a suitable Almon lag model to the data.
Reestimate Eq. (17.13.16) imposing (1) near-end restriction, (2) far-end restriction, and (3) both end restrictions and compare your results given in Eq. (17.13.16). What general conclusion do you
The following table gives data on private fixed investment in information processing and equipment (Y, in billions of dollars), sales in total manufacturing and trade (X2, in millions of dollars),
The following table gives data on indexes of real compensation per hour (Y) and output per hour (X2), with both indexes to base 1992 = 100, in the business sector of the U.S. economy for the period
What is the connection, if any, between Granger causality tests and VAR modeling?
Consider the data on log DPI (personal disposable income) introduced in Section 21.1 (see the book’s website for the actual data). Suppose you want to fit a suitable ARIMA model to these data.
Repeat Exercise 22.11 for the LDNIDENDS.In exercise 22.11Consider the data on log DPI (personal disposable income) introduced in Section 21.1 (see the book’s website for the actual data). Suppose
In Section 13.9 you were introduced to the Schwarz Information criterion (SIC) to determine lag length. How would you use this criterion to determine the appropriate lag length in a VAR model?
Using the data on LPCE and LDPI introduced in Section 21.1 (see the book’s website for the actual data), develop a bivariate VAR model for the period 1970–I to 2006–IV. Use this model to
Consider the Koyck (or, for that matter, the adaptive expectations) model given in Eq. (17.4.7), namely,Suppose in the original model ut follows the first-order autoregressive scheme ut ˆ’
The article by Subhayu Bandyopadhyay and Howard J. Wall, “The Determinants of Aid in the Post-Cold War Era,” Review, Federal Reserve Bank of St. Louis, November/December 2007, vol. 89, number 6,
In studying the farm demand for tractors, Griliches used the following model:where T* = desired stock of tractorsX1 = relative price of tractorsX2 = interest rateUsing the stock adjustment model, he
Consider the lag patterns in the following figure. What degree polynomials would you fit to the lag structures and why? Bi i i Lag Lag Bi х х х х Time Time
Whenever the lagged dependent variable appears as an explanatory variable, the R2 is usually much higher than when it is not included. What are the reasons for this observation?
Whenever the lagged dependent variable appears as an explanatory variable, the R2 is usually much higher than when it is not included. What are the reasons for this observation?
Refer to the VAR regression results given in the following table. From the various F tests reported in the three regressions given there, what can you say about the nature of causality in the three
Continuing with Exercise 20.20, can you guess why the authors chose to express the three variables in the model in percentage change form rather than using the levels of these variables?
Using the Canadian data given in the following table, find out if M1 and R are stationary random variables. If not, are they cointegrated? Show the necessary calculations. Observation M1 GDP
Continue with the data given in Table 17.5. Now consider the following simple model of money demand in Canada:ln M1t = β1 + β2 lnGDPt + β3 ln Rt + uta. How would you interpret the parameters of
Refer to the ARCH(2) model given in Eq. (22.11.4). Using the same data we estimated the following ARCH(1) model:How would you choose between the two models? Show the necessary calculations.
Table 22.7 gives data on three-month (TB3M) and six-month (TB6M) Treasury bill rates from January 1, 1982, to March 2008, for a total of 315 monthly observations. The data can be found on the
Since the number of lags to be introduced in a VAR model can be a subjective question, how does one decide how many lags to introduce in a concrete application?
If the primary object is forecasting, VAR will do the job.” Critically evaluate this statement.
In what sense is VAR atheoretic?
What are the differences between Box–Jenkins and VAR approaches to economic forecasting?
What happens if Box–Jenkins techniques are applied to time series that are nonstationary?
Outline the major steps involved in the application of the Box–Jenkins approach to forecasting.
What are the major differences between simultaneous-equation and Box–Jenkins approaches to economic forecasting?
What are the major methods of economic forecasting?
The following regressions are based on the CPI data for the United States for the period 1960 2007, for a total of 48 annual observations:1.2.3.WhereRSS = residual sum of squares.a. Examining the
From the data for the period 1971€“I to 1988€“IV for Canada, the following regression results were obtained:1.2.3.where M1 = M1 money supply, GDP = gross domestic product, both

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