Explain the unadjusted and the adjusted monthly data

Assignment Help Business Economics
Reference no: EM133065687

Let's practice time-series forecasting of new home sales (SEE DATA BELOW). Look at the monthly data on the "Reg Sold" tab. 

Only keep the dates beginning in January 2004, so delete the earlier observations, and use the data through September 2021. Keep only the US data, both the seasonally unadjusted monthly (column B) and the seasonally adjusted annual (column G). Make a new column of seasonally adjusted monthly by dividing the annual data by 12. Make a column called "t" where t will go from 1 (Jan. 2004) to 213 (September 2021); make a t2 column too (since, if you look at the data, you can see sales are U-shaped; hence the quadratic). Also make a column "D" that is a dummy variable equal to one during the spring and summer months of March through August.

Determine the correlation between the unadjusted and the adjusted monthly data (=CORREL(unadjust., adjust.) in Excel), and produce scatterplots (with straight lines) of both. Do you think making a seasonal adjustment will be useful, given what you observe at this point?

Run four regressions: 1) seasonally unadjusted monthly as the dependent, and t and t2 as the independents, 2) seasonally unadjusted monthly as the dependent, and t, t2, and D as the independents, 3) seasonally adjusted monthly as the dependent, and t and t2 as the independents, and 4) seasonally adjusted monthly as the dependent, and t, t2, and D as the independents. Discuss your findings, and determine which of the four models is the best for forecasting new home sales. When interpreting your p-values, remember that, say, 1.0E-08 is 1.0 * 10^-8, which is 0.00000001. State the equation that would be used to forecast sales.

Date

US NSA month

US SA year

Jan-04

89

1165

Feb-04

102

1159

Mar-04

123

1276

Apr-04

109

1186

May-04

115

1241

Jun-04

105

1180

Jul-04

96

1088

Aug-04

102

1175

Sep-04

94

1214

Oct-04

101

1305

Nov-04

84

1179

Dec-04

83

1242

Jan-05

92

1203

Feb-05

109

1319

Mar-05

127

1328

Apr-05

116

1260

May-05

120

1286

Jun-05

115

1274

Jul-05

117

1389

Aug-05

110

1255

Sep-05

99

1244

Oct-05

105

1336

Nov-05

86

1214

Dec-05

87

1239

Jan-06

89

1174

Feb-06

88

1061

Mar-06

108

1116

Apr-06

100

1123

May-06

102

1086

Jun-06

98

1074

Jul-06

83

965

Aug-06

88

1035

Sep-06

80

1016

Oct-06

74

941

Nov-06

71

1003

Dec-06

71

998

Jan-07

66

891

Feb-07

68

828

Mar-07

80

833

Apr-07

83

887

May-07

79

842

Jun-07

73

793

Jul-07

68

778

Aug-07

60

699

Sep-07

53

686

Oct-07

57

727

Nov-07

45

641

Dec-07

44

619

Jan-08

44

627

Feb-08

48

593

Mar-08

49

535

Apr-08

49

536

May-08

49

504

Jun-08

45

487

Jul-08

43

477

Aug-08

38

435

Sep-08

35

433

Oct-08

32

393

Nov-08

27

389

Dec-08

26

377

Jan-09

24

336

Feb-09

29

372

Mar-09

31

339

Apr-09

32

337

May-09

34

376

Jun-09

37

393

Jul-09

38

411

Aug-09

36

418

Sep-09

30

386

Oct-09

33

396

Nov-09

26

375

Dec-09

24

352

Jan-10

24

345

Feb-10

27

336

Mar-10

36

381

Apr-10

41

422

May-10

26

280

Jun-10

28

305

Jul-10

26

283

Aug-10

23

282

Sep-10

25

317

Oct-10

23

291

Nov-10

20

287

Dec-10

23

326

Jan-11

21

307

Feb-11

22

270

Mar-11

28

300

Apr-11

30

310

May-11

28

305

Jun-11

28

301

Jul-11

27

296

Aug-11

25

299

Sep-11

24

304

Oct-11

25

316

Nov-11

23

328

Dec-11

24

341

Jan-12

23

335

Feb-12

30

366

Mar-12

34

354

Apr-12

34

354

May-12

35

370

Jun-12

34

360

Jul-12

33

369

Aug-12

31

375

Sep-12

30

385

Oct-12

29

358

Nov-12

28

392

Dec-12

28

399

Jan-13

32

446

Feb-13

36

447

Mar-13

41

444

Apr-13

43

441

May-13

40

428

Jun-13

43

470

Jul-13

33

375

Aug-13

31

381

Sep-13

31

403

Oct-13

36

444

Nov-13

32

446

Dec-13

31

433

Jan-14

33

443

Feb-14

35

420

Mar-14

39

405

Apr-14

39

403

May-14

43

451

Jun-14

38

418

Jul-14

35

402

Aug-14

36

456

Sep-14

37

470

Oct-14

38

476

Nov-14

31

442

Dec-14

35

497

Jan-15

39

515

Feb-15

45

540

Mar-15

46

480

Apr-15

48

502

May-15

47

502

Jun-15

44

480

Jul-15

43

506

Aug-15

41

518

Sep-15

35

456

Oct-15

39

482

Nov-15

36

504

Dec-15

38

546

Jan-16

39

505

Feb-16

45

517

Mar-16

50

532

Apr-16

55

576

May-16

53

571

Jun-16

50

557

Jul-16

54

628

Aug-16

46

575

Sep-16

44

558

Oct-16

46

575

Nov-16

40

571

Dec-16

39

561

Jan-17

45

578

Feb-17

51

601

Mar-17

61

643

Apr-17

56

604

May-17

57

627

Jun-17

56

612

Jul-17

48

553

Aug-17

45

550

Sep-17

50

622

Oct-17

49

625

Nov-17

50

718

Dec-17

45

658

Jan-18

48

610

Feb-18

54

644

Mar-18

66

680

Apr-18

61

658

May-18

62

680

Jun-18

56

598

Jul-18

52

600

Aug-18

47

582

Sep-18

46

584

Oct-18

43

546

Nov-18

44

618

Dec-18

38

566

Jan-19

49

628

Feb-19

57

675

Mar-19

68

721

Apr-19

64

689

May-19

56

619

Jun-19

66

711

Jul-19

55

636

Aug-19

57

677

Sep-19

56

706

Oct-19

55

703

Nov-19

50

700

Dec-19

49

733

Jan-20

59

756

Feb-20

63

730

Mar-20

59

623

Apr-20

52

582

May-20

64

704

Jun-20

79

839

Jul-20

85

972

Aug-20

81

977

Sep-20

77

971

Oct-20

78

969

Nov-20

61

865

Dec-20

63

943

Jan-21

77

993

Feb-21

70

823

Mar-21

83

873

Apr-21

74

796

May-21

65

733

Jun-21

61

683

Jul-21

63

712

Aug-21

57

702

Sep-21

65

800

Reference no: EM133065687

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