Exam (elaborations)

Solutions for Essentials of Econometrics, 5th Edition Gujarati (All Chapters included)

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Course
Economists

Institution
Economists

Complete End of Chapters Solutions for Essentials of Econometrics, 5th Edition by Damodar N. Gujarati ; ISBN13: 9781071850398. (Full Chapters included Chapter 1 to 12)....Chapter 1. The Nature and Scope of Econometrics. Chapter 2. Basic Ideas of Linear Regression: The Two-Variable Model. Chapter ...

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Uploaded on February 26, 2024
Number of pages 229
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Type Exam (elaborations)
Contains Questions & answers

solutions
manual
end of chapter
essentials
econometrics
5th edition
gujarati
9781071850398
excercises
problems
solutions manual
5e

Institution Economists
Course Economists

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Essentials of Econometrics
5th Edition by Damodar N. Gujarati

Complete Chapter Solutions Manual
are included (Ch 1 to 12)

** Immediate Download
** Swift Response
** All Chapters included
** Exercises and Problems

, CHAPTER
1
THE NATURE AND SCOPE OF ECONOMETRICS

QUESTIONS
1.1. (a) Other things remaining the same, the higher the tax rate is, the lower
the price of a house will be.
(b) Assume that the data are cross-sectional, involving several residential
communities with differing tax rates.
(c) Yi = B1 + B2 X i
where Y = price of the house and X = tax rate
(d) Yi = B1 + B2 X i + ui
(e) Given the sample, one can use OLS to estimate the parameters of the
model.
(f) Aside from the tax rate, other factors that affect house prices are
mortgage interest rates, house size, buyers’ family income, the state of the
economy, the local crime rate, etc. Such variables may be included in a more
detailed multiple regression model.
(g) A priori, B2 < 0. Therefore, one can test H0 : B2 ≥ 0 against H1 : B2 < 0.

(h) The estimated regression can be used to predict the average price of a
house in a community, given the tax rate in that community. Of course, it
is assumed that all other factors stay the same.
1.2. Econometricians are now routinely employed in government and business
to estimate and / or forecast (1) price and cost elasticities, (2) production
and cost functions, and (3) demand functions for goods and services, etc.
Econometric forecasting is a growth industry.
1.3. The economy will be bolstered if the increase in the money supply leads to
a reduction in the interest rate which will lead to more investment activity
and, therefore, to more output and more employment. If the increase in the
money supply, however, leads to inflation, the preceding result may

1

, not occur. The job of the econometrician will be to develop a model to
predict the effect of the increase in the money supply on inflation, interest
rate, employment, etc.
1.4. As a matter of fact, on October 1, 1993 the Federal Government did increase
the gasoline tax by 4 cents. Since gasoline and cars are complementary
products, economic theory suggests that an increase in the price of gasoline
will not only lead to a decline in the demand for gasoline but also in the
demand for cars, ceteris paribus. The Ford Motor Companymay be advised
to produce more fuel-efficient cars to stave off a serious decline in the
demand for its cars. An automobile demand function will provide numerical
estimates of the effect of gasoline tax on the demandfor automobiles.
1.5.
There are many alternative designs possible. However, to keep things
simple, and discuss just a basic idea of the design, we could think of using
an econometric model known as Autoregressive Distributed Lag (ARDL)
of the form:
∆yt = α + β∆yt −1 + θ 0 ∆gt + θ1∆gt −1 + γ 0 ∆τ tp + +γ 1∆τ tp−1 + δ 0 ∆τ tc + δ1∆τ tc−1 + ut

where
Yt − Yt −1
yt = = real GDP growth rate in year t;
Yt −1

Gt − Gt −1
gt = = real government infrastructure investment growth rate in
Gt −1
year t;
τ tp = personal income tax rate in year t;

τ tc = corporate income tax rate in year t;
∆yt = yt − yt −1 = change in real GDP growth rate in year t;

∆g t = g t − g t −1 = change in real government infrastructure investment growth
rate in year t;
∆τ tp = τ tp − τ tp−1 = change in personal income tax rate in year t;
∆τ tc = τ tc − τ tc−1 = change in corporate income tax rate in year t.

Expected signs and magnitudes of the parameters the regression model:

2

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