2/3 1. by by 2. 2. Explain why choosing a model by maximizing R² or minimizing ô is the same thing. 3. Suppose that the annual number of drunk driving arrests is determined log(arrests) Bo + B₁ log(pop) + B2age1625 + other factors Where age 16_25 is the proportion of the population between 16 and 25 years of age. Please interpretate B₁ and ₂. 4. 5. Ju Let arr86 be a binary variable equal to unity if a man was arrested during 1986, and zero otherwise. The population is a group of young men in California born in 1960 or 1961 who have at least one arrest prior to 1986. A linear probability model for describing arr86 is arr86-0.380-0.152pcnv+0.0046avgsen-0.0026totime-0.024ptime86- 0.038qemp86+0.17black+0.096hispan Where: pcnv: the proportion of prior arrests that led to a conviction avgsen: the average sentence served from prior convictions (in months) tottime: months spent in prison since age 18 prior to 1986 ptime86: months spent in prison in 1986 qemp86: the number of quarters(0 to 4) that the man was legally employed in 1986 black: 1 if the man is a black hispan: 1 if the man is a hispan the base group is white (1) Interpretate 0.17 and 0.096 (2) What is the predicted probability of arrest for a black man with no prior convictions, and he was employed all four quarters in 1986? Does this seem reasonable? oLey y be the number of extramarital affairs for a married woman from the U.S. population; we would like to explain this variable in terms of other characteristics of the woman-in particular, whether she works outside of the home, her husband, and her family. Is this a good candidate for a Tobit model?
2/3 1. by by 2. 2. Explain why choosing a model by maximizing R² or minimizing ô is the same thing. 3. Suppose that the annual number of drunk driving arrests is determined log(arrests) Bo + B₁ log(pop) + B2age1625 + other factors Where age 16_25 is the proportion of the population between 16 and 25 years of age. Please interpretate B₁ and ₂. 4. 5. Ju Let arr86 be a binary variable equal to unity if a man was arrested during 1986, and zero otherwise. The population is a group of young men in California born in 1960 or 1961 who have at least one arrest prior to 1986. A linear probability model for describing arr86 is arr86-0.380-0.152pcnv+0.0046avgsen-0.0026totime-0.024ptime86- 0.038qemp86+0.17black+0.096hispan Where: pcnv: the proportion of prior arrests that led to a conviction avgsen: the average sentence served from prior convictions (in months) tottime: months spent in prison since age 18 prior to 1986 ptime86: months spent in prison in 1986 qemp86: the number of quarters(0 to 4) that the man was legally employed in 1986 black: 1 if the man is a black hispan: 1 if the man is a hispan the base group is white (1) Interpretate 0.17 and 0.096 (2) What is the predicted probability of arrest for a black man with no prior convictions, and he was employed all four quarters in 1986? Does this seem reasonable? oLey y be the number of extramarital affairs for a married woman from the U.S. population; we would like to explain this variable in terms of other characteristics of the woman-in particular, whether she works outside of the home, her husband, and her family. Is this a good candidate for a Tobit model?
Essentials Of Investments
11th Edition
ISBN:9781260013924
Author:Bodie, Zvi, Kane, Alex, MARCUS, Alan J.
Publisher:Bodie, Zvi, Kane, Alex, MARCUS, Alan J.
Chapter1: Investments: Background And Issues
Section: Chapter Questions
Problem 1PS
Related questions
Question
Transcribed Image Text:2/3
1. by
by
2. 2.
Explain why choosing a model by maximizing R² or minimizing ô
is the same thing.
3.
Suppose that the annual number of drunk driving arrests is determined
log(arrests) Bo + B₁ log(pop) + B2age1625 + other factors
Where age 16_25 is the proportion of the population between 16 and 25 years of
age. Please interpretate B₁ and ₂.
4.
5.
Ju Let arr86 be a binary variable equal to unity if a man was arrested
during 1986, and zero otherwise. The population is a group of young men in
California born in 1960 or 1961 who have at least one arrest prior to 1986. A
linear probability model for describing arr86 is
arr86-0.380-0.152pcnv+0.0046avgsen-0.0026totime-0.024ptime86-
0.038qemp86+0.17black+0.096hispan
Where: pcnv: the proportion of prior arrests that led to a conviction
avgsen: the average sentence served from prior convictions (in months)
tottime: months spent in prison since age 18 prior to 1986
ptime86: months spent in prison in 1986
qemp86: the number of quarters(0 to 4) that the man was legally employed
in 1986
black: 1 if the man is a black
hispan: 1 if the man is a hispan
the base group is white
(1) Interpretate 0.17 and 0.096
(2) What is the predicted probability of arrest for a black man with no prior
convictions, and he was employed all four quarters in 1986? Does this seem
reasonable?
oLey y be the number of extramarital affairs for a married woman from
the U.S. population; we would like to explain this variable in terms of other
characteristics of the woman-in particular, whether she works outside of the home,
her husband, and her family. Is this a good candidate for a Tobit model?
AI-Generated Solution
AI-generated content may present inaccurate or offensive content that does not represent bartleby’s views.
Unlock instant AI solutions
Tap the button
to generate a solution
Recommended textbooks for you
Essentials Of Investments
Finance
ISBN:
9781260013924
Author:
Bodie, Zvi, Kane, Alex, MARCUS, Alan J.
Publisher:
Mcgraw-hill Education,
Essentials Of Investments
Finance
ISBN:
9781260013924
Author:
Bodie, Zvi, Kane, Alex, MARCUS, Alan J.
Publisher:
Mcgraw-hill Education,
Foundations Of Finance
Finance
ISBN:
9780134897264
Author:
KEOWN, Arthur J., Martin, John D., PETTY, J. William
Publisher:
Pearson,
Fundamentals of Financial Management (MindTap Cou…
Finance
ISBN:
9781337395250
Author:
Eugene F. Brigham, Joel F. Houston
Publisher:
Cengage Learning
Corporate Finance (The Mcgraw-hill/Irwin Series i…
Finance
ISBN:
9780077861759
Author:
Stephen A. Ross Franco Modigliani Professor of Financial Economics Professor, Randolph W Westerfield Robert R. Dockson Deans Chair in Bus. Admin., Jeffrey Jaffe, Bradford D Jordan Professor
Publisher:
McGraw-Hill Education