Download Dynamic Consumption Behavior: Evidence from Japanese

Dynamic Consumption Behavior:
Evidence from Japanese
Household Panel Data
Yukinobu Kitamura
Hitotsubashi University
Institute of Economic Research
August 5, 2005
1. Plan of my talk
1.
2.
3.
4.
Family Income and Expenditure Survey
2001-2002
Dynamic Consumption Behavior
Durability of Consumption
Liqudity Constraints
2 Durability of Consumption
Hayashi (1997, chapter5) shows the relationship between
expenditure xijt and consumption cij. Consumption is
a flow from accumulated expenditure in the past.
c ijt   j 0 xijt   j1 xijt1   j 2 xijt 2   j 3 xijt3     jM xijt M
(1)
where i is the agent, j is consumption good or item, t is
time, M is a certain time dimension.
However, expenditures on individual goods xijt are expressed as the flow of current and future consumption
cijt+n such that,
(2)
x ijt   j 0 cijt   j1cijt1   j 2 cijt 2   j 3cijt3     jM cijt N
3 Liquidity Constraints
1.
Households with debt. Although these households may not
borrow as much as they wish, they may not have had faced with
liquidity constraints in the past.
2.
Households without debt and seemingly without liquidity
constraints. They can borrow as much as they like but in fact they
do not borrow.
Households without debt and seemingly with liquidity constraints.
They may face with liquidity constraints at the moment.
3.
Distinction between 1. and 2.3. can be made according to debt
information at hand. Distinction between 2. and 3. requires some
assumptions to draw lines according to annual income and net
savings.
4 Empirical Model
Consumption function in empirical analysis is defined
such that,
conit    dispit 1  i  vt  uit
(3)
where con=log of real consumption, disp=log of real
disposable income, vt=monthly dummy.
The expenditure model is to convert consumption con
into expenditure x.
(4)
xit    xit 1  dispit 1  i  vt  uit
5 Empirical Results
AR(1) regression, coefficients of food, housing, traffic and
telecommunication, recreation exceed 0.5. There seem
to exist habit formation or sticky consumption. On the
other hand, coefficients of furniture, clothes, medical
expenditure, education are less than 0.2, habit formation
does not exist for these items.
AR(4) regression indicates smaller but stable coefficients
over four lags. Differences in coefficients across goods
are smaller and coefficients do not drop sharply after
some lags.
It implies that non durable consumption shows some
durability.
Autoregression Model
AR(1)
Dependent variable: xt
AR(4)
xt-1
xt-1
Estimated
z-statistics
Coefficient
xt-2
xt-3
xt-4
Estimated
Estimated
Estimated
Estimated
z-statistics
z-statistics
z-statistics
z-statistics
Coefficient
Coefficient
Coefficient
Coefficient
Clothes
0.6265
0.7766
0.6079
0.3556
0.0982
0.1168
4094.23
431.77
1271.40
1271.40
15.31
15.48
0.2474
0.3238
0.2892
0.0991
0.1716
0.1850
34.64
48.28
21.80
11.40
23.93
21.09
0.2107
0.2372
0.2076
0.3945
0.1469
0.1389
34.57
34.69
14.69
57.40
20.16
15.69
0.1952
0.2213
0.2127
0.0576
0.1249
0.1459
31.13
32.58
14.79
7.83
17.15
16.64
0.1917
0.1459
0.1898
0.2053
0.1338
0.1513
30.89
22.27
14.23
30.50
18.72
17.40
Medical expenditure
0.1800
22.70
0.2548
32.00
0.1807
22.35
0.1280
15.82
0.1527
19.26
Traffic and
Telecommunication
0.5250
1285.10
0.2329
36.19
0.1934
29.88
0.1966
30.05
0.1788
27.50
Education
0.1422
0.5244
0.6249
10.35
1196.91
177.90
0.2452
0.2476
0.2688
12.98
35.84
39.68
0.2073
0.1978
0.2109
13.57
28.19
30.60
0.2296
0.1554
0.1995
15.31
22.21
28.40
0.1716
0.1916
0.1925
11.64
27.41
27.68
Expenditure （all）
Food
Housing
Energy
Furniture
Recreation
Others
Expenditure Behavior by Items
(1) consumption has durability. This is
consistent with the fact that coefficients of
own lag are negative.
(2) coefficients of disposable income are
significant in many cases. Consumers
seem to face the disposable income
constraints.
Expenditure Behavior by Items
Panel A: Maximum Likelihood Method
Dependent Variable
△x
Expenditure (all)
Explanatory variables
disposable income t-1
own lag
Estimated
z-statistics
Coefficient
Estimated
z-statistics
Coefficient
-0.478
-106.78
0.011
6.11
food
housing
energy
furniture
-0.421
-88.36
0.006
5.14
-0.498
-59.24
-0.008
-0.91
-0.678
-164.03
0.002
1.08
-0.478
-95.82
0.026
4.46
clothes
-0.487
-87.64
0.059
8.07
medical expenditure
transportation and
telecommunication
education
recreation
others
-0.471
-85.96
0.008
1.49
-0.495
-105.96
0.019
4.89
-0.474
-54.19
0.023
1.37
-0.480
-97.27
0.007
1.65
-0.477
-97.40
0.009
2.28
Note: Other explanatory variables include monthly dummy for November,
December, January, May, July.
Expenditure Behavior by Items
Panel B: GMM (one-step)
Panel B：　GMM (one step)
Dependent Variable
△x
Expenditure (all)
Explanatory variables
disposable income t-1
own lag
Estimated
z-statistics
Coefficient
Estimated
z-statistics
Coefficient
-0.347
-55.69
-0.004
-1.91
food
housing
energy
furniture
-0.375
-59.47
-0.012
-8.56
-0.344
-28.43
-0.006
-0.64
-0.617
-120.11
0.009
3.69
-0.375
-57.52
-0.006
-0.78
clothes
-0.381
-51.83
0.052
5.69
medical expenditure
transportation and
telecommunication
education
recreation
others
-0.362
-49.93
-0.006
-0.83
-0.377
-60.10
0.015
3.20
-0.386
-33.84
0.053
2.63
-0.380
-59.77
-0.022
-4.45
-0.372
-58.54
-0.005
-0.94
Note: Additional instrumental variables are numbers of household members,
numbers of workers, age of household head.
Liquidity Constraints
(1) Households with debt (debtinc=1,debtass=1) and
households without debt and with low annual income
and net savings (debtinc=2,debtass=2) face the
disposable income constraint.
(2) For those households, parameter values, statistical
significance and implications remain, more or less, the
same.
(3) Households without debt and with high annual income
and net savings face the disposable income constraint in
MLE.
Expenditure Behavior by Annual Income
Panel A: Maximum Likelihood Method
debtinc = 0
Dependent　Variable: △x Estimated
z-statistics
Coefficient
△x_1
-0.461
-36.89
0.038
4.73
△disp_1
Nov2001
-0.049
-1.51
Dec2001
0.248
8.76
Jan2002
-0.111
-4.36
May2002
-0.050
-2.10
Jun2002
-0.044
-1.79
Jul2002
0.035
1.38
Nov2002
-0.089
-2.78
Dec2002
0.122
2.68
_cons
-0.036
-3.96
Diagnostic Test
4015
Number of observation
1076
Number of groups
1336.42
LR Chi2(10)
0.000
Prob>Chi2
LR test of sigma_u = 0
0.00
Chi2(01)
1.000
Prob>Chi2
debtinc = 1
Estimated
z-statistics
Coefficient
-0.476
-74.04
0.020
5.45
-0.002
-0.13
0.246
18.87
-0.070
-5.81
-0.048
-4.28
-0.012
-1.07
0.067
5.76
0.006
0.40
0.243
11.21
-0.054
-12.49
debtinc = 2
Estimated
z-statistics
Coefficient
-0.491
-67.89
0.006
2.69
0.014
0.77
0.214
14.78
-0.069
-5.19
-0.020
-1.58
-0.023
-1.80
0.038
2.86
0.001
0.04
0.228
9.51
-0.042
-8.69
15491
4066
5383.53
0.000
12399
3552
4328.46
0.000
0.00
0.00
1.000
1.000
Expenditure Behavior by Annual Income
Panel B: GMM (one-step)
Panel B：　GMM (one-step)
Dependent　Variable: △x
△x_1
debtinc = 0
Estimated
z-statistics
Coefficient
-0.2958
-16.05
0.0074
0.79
0.0035
0.49
debtinc = 1
Estimated
z-statistics
Coefficient
-0.3498
-39.48
-0.0067
-1.49
-0.0023
-0.70
debtinc = 2
Estimated
z-statistics
Coefficient
-0.3651
-36.65
-0.0038
-1.57
-0.0049
-1.30
2749
995
11093
3903
8706
3225
120.6
0.000
267.49
0.000
188.43
0.000
259.77
1615.78
1366.33
-24.41
-47.48
-40.87
0.000
0.000
0.000
-1.05
-6.07
-5.38
0.2923
0.000
0.0000
△disp_1
_cons
Diagnostic Test
Number of observation
Number of groups
Sargan Test
.
Chi2(42)
Prob>Chi2
Wald Test
Chi2(2)
Arellano-Bond Test
for residual AR(1)=z
Prob>z
Arellano-Bond Test
for residual AR(2)=z
Prob>z
Note: Additional instrumental variables are numbers of household members, numbers of workers, age of
household head, squares of age of household head.
Expenditure Behavior by Net Savings
Panel A: Maximum Likelihood Method
debtass = 0
Dependent　Variable: △x Estimated
z-statistics
Coefficient
△x_1
-0.483
-45.08
0.009
2.65
△disp_1
Nov2001
-0.046
-1.51
Dec2001
0.253
9.88
Jan2002
-0.095
-4.15
May2002
-0.060
-2.62
Jun2002
-0.036
-1.56
Jul2002
0.048
2.00
Nov2002
-0.042
-1.39
Dec2002
0.173
4.40
_cons
-0.042
-4.87
Diagnostic Test
5387
Number of observation
1622
Number of groups
1917.97
LR Chi2(10)
0.000
Prob>Chi2
LR test of sigma_u = 0
0.00
Chi2(01)
1.000
Prob>Chi2
debtass = 1
Estimated
z-statistics
Coefficient
-0.476
-74.04
0.020
5.45
-0.002
-0.13
0.246
18.87
-0.070
-5.81
-0.048
-4.28
-0.012
-1.07
0.067
5.76
0.006
0.40
0.243
11.21
-0.054
-12.49
debtass = 2
Estimated
z-statistics
Coefficient
-0.479
-62.01
0.008
3.09
0.021
1.18
0.207
14.21
-0.062
-4.68
-0.013
-1.08
-0.023
-1.84
0.038
2.90
-0.011
-0.62
0.222
8.90
-0.042
-8.57
15491
4066
5383.53
0.000
11027
3006
3679.43
0.000
0.00
0.00
1.000
1.000
Expenditure Behavior by Net Savings
Panel B: GMM (one-step)
Panel B：　GMM (one-step)
debtass = 0
Dependent　Variable: △x Estimated
z-statistics
Coefficient
△x_1
-0.3286
-20.73
-0.0021
-0.57
△disp_1
_cons
0.0061
0.88
Diagnostic Test
3573
Number of observation
1396
Number of groups
Sargan Test
112.48
LR Chi2(42)
0.000
Prob>Chi2
Wald Test
434.18
Chi2(2)
Arellano-Bond Test
-25.93
for residual AR(1)=z
0.000
Prob>z
Arellano-Bond Test
-3.27
for residual AR(2)=z
0.0011
Prob>z
debtass = 1
Estimated
z-statistics
Coefficient
-0.3498
-39.48
-0.0067
-1.49
-0.0023
-0.70
debtass = 2
Estimated
z-statistics
Coefficient
-0.3572
-33.95
-0.0048
-1.46
-0.0062
-1.67
11093
3903
7885
2824
267.49
0.000
175.62
0.000
1615.78
1178.93
-47.48
-40.19
0.000
0.000
-6.07
-3.79
0.000
0.0002
Note: Additional instrumental variables are numbers of household members, numbers of workers, age of household head,
squares of age of household head.
Policy Implications
Sensitivity of expenditure to disposable income turns
out to be significant for most cases.
This result implies, at least in the short run, policy
variables such as taxes and social security
contribution could affect consumption.
Provided the indebted households may face liquidity
constraints, such policies as income tax reduction
against the amount of mortgage, interest payment
deduction and property tax reduction against the
amount of mortgage might be used to relax such
constraints.