Forecasts of growth in US durables spending: assessing the usefulness of disaggregated consumer survey data

Figures & data

Table 1. Consumer survey data: 1988Q1–2016Q4.

	DBA		HBA		CEB
	Good time	Bad time	Good time	Bad time	Better	Worse
Respondents	(1)	(2)	(3)	(4)	(5)	(6)
All survey respondents	69.6%	21.0%	73.8%	22.6%	27.0%	19.3%
Disaggregated by age:
18–34	72.7	20.7	74.5	23.1	28.4	16.2
35–54	69.5	21.9	75.8	21.5	27.0	20.1
55 and over	67.6	20.3	70.9	23.9	26.0	20.4
Disaggregated by education:
High school or less	67.5	22.9	66.4	29.5	23.5	19.5
Some college	70.3	20.9	75.6	21.1	27.0	19.3
College degree	71.2	19.5	80.4	16.5	30.4	19.1
Disaggregated by gender:
Female	67.4	23.0	71.4	24.8	23.5	19.1
Male	72.2	18.7	76.8	20.0	31.0	19.5
Disaggregated by income:
Bottom 33%	65.9	24.1	63.9	31.4	24.4	20.1
Middle 33%	71.3	20.5	76.2	20.9	26.5	19.1
Top 33%	73.0	18.4	82.4	15.3	30.2	18.4

Notes: Calculations utilize monthly MSC data (January 1988 – December 2016). The HBA and CEB of the groups in bold help improve Federal Reserve forecast accuracy.

Source: Author’s calculation.

Figure 1. Growth in real durables spending (real-time data): 1988Q1–2016Q4.

Source: Author’s calculation.

Figure 2. Federal reserve forecast errors.

Source: Author’s calculation.

Table 2. Federal Reserve forecast accuracy results.

			MAE		Directional accuracy
$(A_{t+f}–P{F}_{t+f})=\alpha +u_{t+f}$	f	α = ME	PFt+f	PNt+f	πAll	πUp	πDown	p-value
Row no.		(1)	(2)	(3)	(4)	(5)	(6)	(7)
1	0	1.435 (2.91)	3.854	11.65	0.92^a	0.89	0.95	0.297
2	1	2.029 (2.18)	7.396	10.33	0.74^a	0.67	0.80	0.094
3	2	1.003 (1.19)	7.061	9.843	0.74^a	0.74	0.74	0.994
4	3	1.073 (1.23)	6.955	9.836	0.77^a	0.73	0.80	0.371
5	4	1.010 (1.17)	7.582	10.57	0.73^a	0.72	0.75	0.756

Note: The correct t-values are in parentheses. ME estimates in bold are significantly different from zero. Superscript a indicates that the null hypothesis of no association between (A_t+f – R_t−1) and (PF_t+f – R_t−1) is rejected at the lower than 1% level of significance.

Source: Author’s calculation.

Table 3. Orthogonality test results.

$(A_{t+f}–P{F}_{t+f})\mathrm{}={\beta }_0+{\beta }_1{X}_{t-1}+u_{t+f}$
Row no.	X	f = 0	f = 1	f = 2	f = 3	f = 4
		(1)	(2)	(3)	(4)	(5)
35–54-year-old participants
1	DBA	0.587	0.737	0.292	0.101	0.437
2	HBA	0.176	0.001	0.031	0.013	0.037
Participants with a college degree
3	DBA	0.876	0.926	0.349	0.144	0.540
4	HBA	0.460	0.054	0.083	0.091	0.073
Male participants
5	DBA	0.638	0.944	0.304	0.131	0.346
6	HBA	0.140	0.002	0.046	0.022	0.055
Participants with the top 33% income
7	DBA	0.738	0.998	0.533	0.166	0.529
8	HBA	0.243	0.013	0.045	0.092	0.081

Notes: Numbers are the p-values of the calculated correct t-values for testing the null hypothesis that β₁ = 0. Those below 0.10 are in bold.

Source: Author’s calculation.

Table 4. Knowledge model (KM) estimates of growth in durables spending.

$g_t={\gamma }_0+{\gamma }_{1}HB{A}_{\mathrm{t}-1}+{\gamma }_{2}CE{B}_{\mathrm{t}-1}+v_t$
Row no.	Sample period	γ0	γ1	γ2	R^2
35–54-year-old participants
1	1978Q2–1987Q4	−41.26 (2.73)	0.072 (1.65)	0.362 (2.72)	0.219
2	1978Q2–2015Q3	−35.58 (4.84)	0.054 (2.01)	0.312 (4.76)	0.178
Participants with a college degree
3	1978Q2–1987Q4	−42.86 (2.96)	0.104 (1.85)	0.321 (2.86)	0.245
4	1978Q2–2015Q3	−30.50 (4.31)	0.067 (2.37)	0.233 (4.17)	0.153
Male participants
5	1978Q2–1987Q4	−47.96 (2.97)	0.101 (1.73)	0.370 (2.95)	0.239
6	1978Q2–2015Q3	−34.81 (4.54)	0.073 (2.54)	0.265 (4.34)	0.161
Participants with the top 33% income
7	1980Q1–1987Q4	−58.47 (3.21)	0.083 (1.69)	0.455 (3.12)	0.303
8	1980Q1–2015Q3	−37.17 (4.71)	0.073 (2.80)	0.277 (4.58)	0.175

Note: g_t is real-time growth in durables spending, HBA is consumer home-buying attitudes, and CEB is consumer expectations about future business conditions. Numbers in parentheses are the absolute t-values. Coefficient estimates in bold are significantly different from zero. The data on HBA and CEB are available starting 1980Q1 for participants with the top 33% income.

Source: Author’s calculation.

Table 5. Encompassing test results.

$A_{t+f}=\mathrm{}{\delta }_0+{\delta }_{1}P{F}_{t+f}+{\delta }_{2}P{K}_{t+f}+u_{t+f}$
Row no.	f	δ0	δ1	δ2	R^2
35–54-year-old participants
1	0	0.950 (0.89)	0.952 (16.6)	0.104 (0.74)	0.713
2	1	−0.444 (0.23)	0.418 (2.62)	0.685 (3.04)	0.153
3	2	−0.075 (0.03)	0.629 (2.15)	0.423 (1.61)	0.079
4	3	−1.147 (0.50)	0.901 (3.54)	0.398 (1.59)	0.122
5	4	1.371 (0.57)	0.352 (1.47)	0.415 (1.65)	0.053
Participants with a college degree
6	0	1.029 (0.97)	0.956 (17.0)	0.082 (0.65)	0.712
7	1	−0.432 (0.21)	0.419 (2.66)	0.622 (2.72)	0.133
8	2	0.136 (0.05)	0.588 (2.03)	0.383 (1.49)	0.071
9	3	−0.781 (0.35)	0.861 (3.37)	0.341 (1.50)	0.112
10	4	1.125 (0.47)	0.266 (1.11)	0.471 (1.86)	0.056
Male participants
11	0	0.797 (0.78)	0.952 (17.6)	0.123 (0.96)	0.714
12	1	−0.230 (0.13)	0.451 (2.93)	0.614 (2.58)	0.140
13	2	0.141 (0.06)	0.615 (2.12)	0.388 (1.59)	0.075
14	3	−0.712 (0.32)	0.896 (3.56)	0.326 (1.45)	0.113
15	4	1.480 (0.62)	0.340 (1.45)	0.395 (1.66)	0.051
Participants with the top 33% income
16	0	0.851 (0.95)	0.951 (17.7)	0.125 (1.10)	0.714
17	1	0.357 (0.21)	0.435 (2.83)	0.570 (2.81)	0.142
18	2	0.916 (0.21)	0.552 (1.88)	0.340 (1.44)	0.071
19	3	0.092 (0.05)	0.840 (3.14)	0.266 (1.29)	0.108
20	4	2.195 (1.09)	0.211 (0.87)	0.411 (1.83)	0.056

Notes: Coefficient estimates in bold are significantly different from zero.

Source: Author’s calculation.

Table 6. Mean absolute errors (MAE) of alternative forecasts.

Row no.	f	PFt+f	PKt+f	PCt+f	p-value
		(1)	(2)	(3)	(4)
35–54-year-old participants
1	0	3.854	7.518	4.989	–
2	1	7.396	7.212	6.744	0.051
3	2	7.061	7.367	7.016	0.838
4	3	6.955	7.403	6.814	0.476
5	4	7.582	7.317	7.105	0.021
Participants with a college degree
6	0	3.854	7.731	5.023	–
7	1	7.396	7.314	6.812	0.086
8	2	7.061	7.462	7.052	0.965
9	3	6.955	7.472	6.886	0.709
10	4	7.582	7.355	7.143	0.022
Male participants
11	0	3.854	7.590	5.043	–
12	1	7.396	7.331	6.806	0.087
13	2	7.061	7.404	7.056	0.961
14	3	6.955	7.480	6.890	0.737
15	4	7.582	7.415	7.122	0.026
Participants with the top 33% income
16	0	3.854	7.688	5.074	–
17	1	7.396	7.285	6.815	0.090
18	2	7.061	7.343	7.060	0.999
19	3	6.955	7.490	6.924	0.871
20	4	7.582	7.400	7.194	0.035

Notes: PF_t+f and PK_t+f are, respectively, the Federal Reserve and KM forecasts. PC_t+f is the combined forecasts. The p-values in column 4 are for testing the null hypothesis that the MAE of PC_t+f equals the MAE of PF_t+f. P-values below .10 are in bold.

Source: Author’s calculation.

Table 7. Accuracy results of the combined (PC_t+f) forecasts.

$(A_{t+f}–P{C}_{t+f})\mathrm{}=\alpha +u_{t+f}$ Row no.	f			Directional accuracy
		α = ME	MAE	πAll	πUp	πDown	p-value
		(1)	(2)	(3)	(4)	(5)	(6)
35–54-year-old participants
1	1	0.516 (0.61)	6.744	0.73^a	0.75	0.72	0.777
2	4	0.083 (0.11)	7.105	0.79^a	0.77	0.80	0.717
Participants with a college degree
3	1	0.212 (0.25)	6.812	0.74^a	0.78	0.70	0.339
4	4	−0.221 (0.28)	7.143	0.76^a	0.79	0.73	0.442
Male participants
5	1	0.414 (0.49)	6.806	0.72^a	0.73	0.72	0.961
6	4	−0.020 (0.03)	7.122	0.79^a	0.77	0.82	0.545
Participants with the top 33% income
7	1	0.655 (0.77)	6.815	0.74^a	0.76	0.72	0.602
8	4	0.222 (0.28)	7.194	0.78^a	0.75	0.80	0.562

Note: See Table 2 notes.

Source: Author’s calculation.