The team meeting will be held in 3 days from the date of the assignment and because of the limitation of time the Chief economist has given you the following guidelines: (a) Is there a trend in total accidents? (b) Is there seasonality in total accidents? (c) Consider the following change in the time series model: y; = P1Yt-1+ Uz where ut follows a white noise process. What is the condition we need to impose on ø1 in order for the series yt to be weakly stationary? Why? P.T.O (d) Consider the following change in the time series model: y = Bo + B1xt-1 + B2xt-2 + Uz where y, is some outcome variable of interest, and x,-1 and x,-2 are strictly exogenous explanatory variables. How would you test for the presence of serial correlation in the residual u,? (e) Briefly explain how you would carry out econometric analysis of the model in (d) if u̟ is found to be stationary, but positively serially correlated.
The team meeting will be held in 3 days from the date of the assignment and because of the limitation of time the Chief economist has given you the following guidelines: (a) Is there a trend in total accidents? (b) Is there seasonality in total accidents? (c) Consider the following change in the time series model: y; = P1Yt-1+ Uz where ut follows a white noise process. What is the condition we need to impose on ø1 in order for the series yt to be weakly stationary? Why? P.T.O (d) Consider the following change in the time series model: y = Bo + B1xt-1 + B2xt-2 + Uz where y, is some outcome variable of interest, and x,-1 and x,-2 are strictly exogenous explanatory variables. How would you test for the presence of serial correlation in the residual u,? (e) Briefly explain how you would carry out econometric analysis of the model in (d) if u̟ is found to be stationary, but positively serially correlated.
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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Transcribed Image Text:The team meeting will be held in 3 days from the date of the assignment and because of the
limitation of time the Chief economist has given you the following guidelines:
(a) Is there a trend in total accidents?
(b) Is there seasonality in total accidents?
(c) Consider the following change in the time series model: y; = P1yt-1+ U¢
where ut follows a white noise process. What is the condition we need to impose on pl in order for
the series yt to be weakly stationary? Why?
P.T.O
(d) Consider the following change in the time series model: y; = Bo + B1xt-1+ B2xt-2 + Uţ
where y, is some outcome variable of interest, and xx-1 and x̟-2 are strictly exogenous explanatory
variables. How would you test for the presence of serial correlation in the residual u,?
(e) Briefly explain how you would carry out econometric analysis of the model in (d) if u, is found
to be stationary, but positively serially correlated.
![Question 2
You are an econometrician working in the Ministry of Finance in Trinidad and Tobago and using
a database consisting of 108 monthly observations on automobile accidents for Trinidad and
Tobago between January 2011 and December 2019, you estimate the following model:
log( totacc,) = Bo+Bit+B2feb, + Bzmar;.. + Bß 12 dec; + µ;
where totacc is the total number of accidents, t is time (measured in months), and feb;, mar,, dec,
are dummy variables indicating whether time period t corresponds to the appropriate month.
You obtain the following OLS results:
Number of obs
F( 12,
Source |
df
MS
108
95)
31.06
Model
1.00244071
12
.083536726
Prob > F
0.0000
R-squared
Adj R-squared
Residual
255496765
95
.00268944
0.7969
0.7712
Total
1.25793748
107
.011756425
Root MSE
.05186
ltotacc
|
Coef.
Std. Err.
P>|t|
[95% Conf. Interval]
.0027471
.0001611
17.06
0.000
.0024274
.0030669
feb
-.0426865
.0244475
-1.75
0.084
-.0912208
.0058479
mar
.0798245
.0244491
3.26
0.002
.031287
.1283621
.0184849
.0244517
0.76
0.452
-.030058
.0670277
аpr
may
jun
jul
.0320981
0.193
0.411
.0806483
.0687515
0244554
1.31
-.0164521
.0201918
.0244602
0.83
..0283678
.0375826
.024466
1.54
0.128
0109886
.0861538
aug
.053983
.0244729
2.21
0.030
.0053981
.102567 9
sep
.042361
.0244809
1.73
0.087
.0062397
0909617
oct
.0821135
0244899
3.35
0.001
.0334949
.130732
nov |
.0712785
0244999
0245111
.02264
.0474966
2.91
0.005
.1199171
dec
.0961572
3.92
0.000
.1448178
cons
10.46857
.0190028
550.89
0.000
10.43084
10.50629
The team meeting will be held in 3 days from the date of the assignment and because of the
limitation of time the Chief economist has given you the following guidelines:](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff5d93f92-43f2-4e21-9bbd-576203fb45e7%2F64af6b15-2ad6-4f1a-a044-2f9a1857b995%2Foscv8o3_processed.png&w=3840&q=75)
Transcribed Image Text:Question 2
You are an econometrician working in the Ministry of Finance in Trinidad and Tobago and using
a database consisting of 108 monthly observations on automobile accidents for Trinidad and
Tobago between January 2011 and December 2019, you estimate the following model:
log( totacc,) = Bo+Bit+B2feb, + Bzmar;.. + Bß 12 dec; + µ;
where totacc is the total number of accidents, t is time (measured in months), and feb;, mar,, dec,
are dummy variables indicating whether time period t corresponds to the appropriate month.
You obtain the following OLS results:
Number of obs
F( 12,
Source |
df
MS
108
95)
31.06
Model
1.00244071
12
.083536726
Prob > F
0.0000
R-squared
Adj R-squared
Residual
255496765
95
.00268944
0.7969
0.7712
Total
1.25793748
107
.011756425
Root MSE
.05186
ltotacc
|
Coef.
Std. Err.
P>|t|
[95% Conf. Interval]
.0027471
.0001611
17.06
0.000
.0024274
.0030669
feb
-.0426865
.0244475
-1.75
0.084
-.0912208
.0058479
mar
.0798245
.0244491
3.26
0.002
.031287
.1283621
.0184849
.0244517
0.76
0.452
-.030058
.0670277
аpr
may
jun
jul
.0320981
0.193
0.411
.0806483
.0687515
0244554
1.31
-.0164521
.0201918
.0244602
0.83
..0283678
.0375826
.024466
1.54
0.128
0109886
.0861538
aug
.053983
.0244729
2.21
0.030
.0053981
.102567 9
sep
.042361
.0244809
1.73
0.087
.0062397
0909617
oct
.0821135
0244899
3.35
0.001
.0334949
.130732
nov |
.0712785
0244999
0245111
.02264
.0474966
2.91
0.005
.1199171
dec
.0961572
3.92
0.000
.1448178
cons
10.46857
.0190028
550.89
0.000
10.43084
10.50629
The team meeting will be held in 3 days from the date of the assignment and because of the
limitation of time the Chief economist has given you the following guidelines:
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