Develop a suitable ARIMA model to forecast the labor force participation rate for females and males separately. What considerations would you take into account in developing such a model? Show the...

Using seasonally adjusted employment data from the Bureau of Labor Statistics website from 1939
to 2009 (quarterly, obtained through taking three-month averages from monthly data), we take the
log of employment and find that it is nonstationary:
. dfuller lnemp, trend

Dickey-Fuller test for unit root Number of obs = 283

---------- Interpolated Dickey-Fuller ---------
Test 1% Critical 5% Critical 10% Critical
Statistic Value Value Value
------------------------------------------------------------------------------
Z(t) -1.574 -3.989 -3.429 -3.130
------------------------------------------------------------------------------
MacKinnon approximate p-value for Z(t) = 0.8026
We find that series is stationary after taking first differences:
. dfuller d.lnemp, trend

Dickey-Fuller test for unit root Number of obs = 282

---------- Interpolated Dickey-Fuller ---------
Test 1% Critical 5% Critical 10% Critical
Statistic Value Value Value
------------------------------------------------------------------------------
Z(t) -6.536 -3.989 -3.429 -3.130
------------------------------------------------------------------------------
MacKinnon approximate p-value for Z(t) = 0.0000
The co
elogram with 50 lags looks like this:
. co
gram d.lnemp, lags(50)

-1 0 1 -1 0 1
LAG AC PAC Q Pro
Q [Autoco
elation] [Partial Autocor]
-------------------------------------------------------------------------------
1 0.7483 0.7506 160.14 0.0000 |----- |------
2 0.4019 -0.3583 206.51 0.0000 |--- --|
3 0.2052 0.1727 218.63 0.0000 |- |-
4 0.0924 -0.1128 221.1 0.0000 | |
5 0.0542 0.1176 221.95 0.0000 | |
6 0.0799 0.0426 223.81 0.0000 | |
7 0.0284 -0.1948 224.05 0.0000 | -|
8 -0.0751 -0.0273 225.7 0.0000 | |
9 -0.0755 0.1405 227.38 0.0000 | |-
10 -0.0851 -0.2196 229.52 0.0000 | -|
11 -0.1692 -0.1118 238 0.0000 -| |
12 -0.2049 0.0325 250.5 0.0000 -| |
13 -0.1523 0.0690 257.42 0.0000 -| |
14 -0.0670 0.0462 258.77 0.0000 | |
acer aspire
Text Box
Develop a suitable ARIMA model to forecast the labor force participation rate for females and males separately. What considerations would you take into account in developing such a model? Show the necessary calculations and explain the various di-agnostic tests you use in your analysis.
acer aspire
Text Box
Qn. ID: 2247823
acer aspire
Text Box
Solution:
15 0.0262 -0.0211 258.98 0.0000 | |
16 0.0921 0.0284 261.54 0.0000 | |
17 0.0668 -0.0189 262.89 0.0000 | |
18 0.0150 -0.0193 262.96 0.0000 | |
19 0.0015 -0.0413 262.96 0.0000 | |
20 0.0265 0.0844 263.18 0.0000 | |
21 0.0629 0.0482 264.39 0.0000 | |
22 0.0519 -0.1486 265.23 0.0000 | -|
23 -0.0029 -0.0516 265.23 0.0000 | |
24 -0.0319 0.1060 265.54 0.0000 | |
25 0.0072 0.1127 265.56 0.0000 | |
26 0.0341 -0.0614 265.93 0.0000 | |
27 0.0027 -0.0753 265.93 0.0000 | |
28 -0.0497 0.0248 266.71 0.0000 | |
29 -0.0977 -0.0391 269.74 0.0000 | |
30 -0.1254 -0.0902 274.75 0.0000 -| |
31 -0.0871 0.0634 277.18 0.0000 | |
32 -0.0326 0.0443 277.52 0.0000 | |
33 0.0076 0.0748 277.54 0.0000 | |
34 0.0570 -0.0097 278.59 0.0000 | |
35 0.1188 0.0812 283.18 0.0000 | | ...