Errata for An Introduction to Modern Econometrics Using Stata
The errata for An Introduction to Modern Econometrics Using Stata are
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(1), (2)  Chapter 2, p. 25, first paragraph, second sentence 
For generate or replace, missing values are propagated;
any function of missing data produces missing data.

For generate or replace, missing values are propagated.
Most Stata functions of missing data return missing values.
Exceptions include sum(), min(), and max(); see
[D] functions for details.

(1)  Chapter 3, p. 45, second paragraph, last sentence 
For quarterly data, S.x generates x_{t}
− x_{t−4}, and S2.x generates
x_{t} − xt − 8.

For quarterly data, S4.x generates x_{t}
− x_{t−4}, and S8.x generates
x_{t} − x_{t−8}.

(1),(2),(3),(4)  Chapter 3, p. 67, dofile example and paragraph that follows it 
. use http://www.statapress.com/data/imeus/census2b, clear
(Version of census2a for data validation purposes)
. duplicates list state
Duplicates in terms of state
++
 obs: state 

 16 Kansas 
 17 Kansas 
++
. assert r(sum) == 0
assertion is false
r(9);
end of dofile
r(9);
The return item r(sum) is set equal to the total number of duplicate
observations found (here, 2), so the identification of duplicates implies
that you need to correct the dataset. The duplicates command could
also be applied to numeric variables.
 . use http://www.statapress.com/data/imeus/census2b, clear
(Version of census2a for data validation purposes)
. duplicates list state
Duplicates in terms of state
++
 obs: state 

 16 Kansas 
 17 Kansas 
++
. duplicates report state
Duplicates in terms of state

copies  observations surplus
+
1  48 0
2  2 1

. assert r(unique_value) == r(N)
assertion is false
r(9);
end of dofile
r(9);
The return item r(unique_value) is set equal to the number of unique observations found. If that value falls short of the number of observations, r(N), duplicates exist. The identification of duplicates in this supposedly unique identifier implies that the dataset must be altered before its further use. The duplicates command could also be applied to numeric variables to detect the same condition.

(1)  Chapter 4, p. 73, equation (4.5) 
(1)  Chapter 4, p. 77, unnumbered equation 
(1), (2), (3)  Chapter 4, p. 79, first full paragraph after equation, first line 
... a model, R^{2} cannot fall and will probably rise,

... a model, R^{2} cannot fall and will probably rise,

(1), (2), (3)  Chapter 4, p. 79, first full paragraph after equation, fifth line 
zero. Algebraically, ... (N  1)/(N  k) < 1 for any X

zero. Algebraically, ... (N  1)/(N  k) > 1 for any X

(1), (2)  Chapter 4, p. 85, last paragraph, fourth sentence 
A rule of thumb states that there is evidence of collinearity if the mean VIF is greater than unity or if the largest VIF is greater than 10.

A rule of thumb states that there is evidence of collinearity if the largest VIF is greater than 10.

(1)  Chapter 4, p. 96, last paragraph, first sentence 
We cannot reject the hypothesis that the coefficients on ldist
and stratio are equal at the 5% level, whereas we can reject
the test that the ratio of the lnox and stratio
coefficients equals 10 rejected at the 1% level.

Whereas we cannot reject the hypothesis that the coefficients on
ldist and stratio are equal at the 5% level, we can
reject the hypothesis that the ratio of the lnox and
stratio coefficients equals 10 at the 1% level.

(1), (2), (3)  Chapter 4, p. 104, second to last unnumbered equation 
(1), (2), (3)  Chapter 4, p. 104, last unnumbered equation 
(1), (2), (3)  Chapter 4, p. 105, top of page 
Plugging in our consistent estimators yields the bounds
Substituting for
and using the variance of predicted value presented in the text
yields a prediction interval for the predicted value

Plugging in our consistent estimators yields the bounds
Substituting for
and using the variance of predicted value presented in the text
yields a prediction interval for the predicted value
.

(1), (2), (3)  Chapter 4, p. 105, second block of Stata code 
. scalar tval = invttail(e(df_r), 0.975)
. generate double uplim = xb + tval * stdpred
(406 missing values generated)
. generate double lowlim = xb  tval * stdpred
(406 missing values generated)

. scalar tval = invttail(e(df_r), 0.025)
. generate double uplim = xb + tval * stdpred
(406 missing values generated)
. generate double lowlim = xb  tval * stdpred
(406 missing values generated)

(1), (2), (3)  Chapter 4, p. 113, equation (4.13) 
(1), (2)  Chapter 6, p. 136, equation (6.6) 
(1), (2), (3)  Chapter 6, p. 140, first unnumbered equation 
(1)  Chapter 6, p. 145, equation (6.10) 
(1), (2)  Chapter 6, p. 160, Exercise 3, first sentence 
Use the sp500 dataset, applying tsset date.

Use the sp500 dataset installed with Stata (sysuse sp500),
applying tsset date.

(1)  Chapter 7, p. 176, last paragraph, first sentence 
The deseasonalized series has a smaller standard deviation than the
original the seasonality has been removed.

The deseasonalized series has a smaller standard deviation than the
original as the fraction of the variation due to the seasonality has been removed.

(1)  Chapter 8, p. 196, paragraph after equation 8.10 
For an exactly identified equation, W = i_{N}.

For an exactly identified equation, W = I_{N}.

(1)  Chapter 8, p. 196, next paragraph 
Hansen (1982) showed that this process involves choosing W =
s^{1}, where S is the ...

Hansen (1982) showed that this process involves choosing W =
S^{1}, where S is the ...

(1)  Chapter 8, p. 196, footnote 10 
Aside from some conditions that guarantee 1/\sqrt(N),
z'u is a vector of wellbehaved random variables.

Aside from some conditions that guarantee 1/\sqrt(N)
Z'u is a vector of wellbehaved random variables.

(1), (2)  Chapter 9, p. 222, second paragraph, fifth sentence 
De Hoyos and Sarafidis (2006) describe some new tests for contemporaneous
correlation, and their command xtscd is available from SSC.

De Hoyos and Sarafidis (2006) describe some new tests for contemporaneous
correlation, and their command xtcsd is available from SSC.

(1)  Subject index, p. 337, letter M 
maximization likelihood optimization

maximum likelihood estimation

(1), (2)  Subject index, p. 341, letter X 
xtscd command

xtcsd command
