JOURNAL
OF COMPARATIVE
ECONOMICS
16, l-26
(1992)
Effects of Rationing on the Consumption Behavior of
Chinese Urban Households during 1981-l 987’
ZHI WANG
University of Minnesota, St. Paul, Minnesota 55108
AND
WEN S. CHERN
The Ohio State University. Columbus, Ohio 43210
Received March 4, 199 1; revised August 19, 199 1
Zhi, and Chern, Wen S.-Effects of Rationing on the Consumption Behavior
of Chinese Urban Households during 198 l- 1987
Wang,
This paper investigates the impacts of housing, fuel, and food grain rationing on
consumption behavior of Chinese urban households. Four versions of the Almost
Ideal Demand System with different rationed goods were estimated using pooled time
series for 198 1-1987 and cross sectional data by income group from household expenditure surveys. The results show that rationing on housing and grain have had
significant impacts on the demand for unrationed goods. If the current rationing
system remains unchanged, Chinese urban households would continue to increase
their demand for nonstaple food. This would yield a considerable pressure on food
supply. Moreover, a reform in housing allocation and grain rationing would
significantly reduce the distortion of consumer behavior in China. J. Comp.
Econom., March 1992,16(l), pp. l-26. University ofMinnesota, St. Paul, Minnesota
55108; and The Ohio State University, Columbus, Ohio 43210. o 1992
Academic Press, Inc.
Journal ofEconomic Literature Classification Numbers: 012, D2 1, P50.
’ This study was supported by the Centrally Planned Economies Branch, Agricultural and
Trade Division, Economic Research Service, U.S. Department ofAgriculture, under the Cooperative Agreement 58-3AEGS-00080, and by The Ohio Agricultural Research and Development
Center. The authors express their gratitude to Francis Tuan and Kenneth Gray of ERS/USDA
for their programatic support and to J. C. Brada and an anonoymous referee for their helpful
comments on an earlier version of the paper.
1
0147-5967192 $3.00
Copyright @ 1992 by Academic Press, Inc.
411rights of reproduction in any form reserved.
WANG
AND
CHERN
I. INTRODUCTION
Consumer behavior under rationing has become one of the major foci of
economic inquiry in recent years. A large volume of theoretical literature has
been published in the past decade (Neary and Roberts, 1980; Lee, 1986;
Chetty and Jha, 1986; Podkaminer, 1989). The impetus has come not only
from the increasing demand for the improvement of public policy making in
developing and centrally planned countries, where rationing is a regular
feature ofthe economy (Ray, 1989), but also from theorists ofgeneral equilibrium models in which market equilibria depend upon the properties of supply and demand functions under quantity constraints (Deaton, 198 1).
China’s history of rationing of basic foods for more than 30 years provides
a unique opportunity for economists to study the impacts of quantity constraints on the behavior of consumers. Since the Chinese government began
its economic reform in 1979, the country has been moving gradually toward
a market-oriented economy. However, rationing of many necessities such as
housing remains intact in most urban areas.
Byrd (1987) developed a general equilibrium approach to analyze rationing, multiple pricing, and parallel markets for China. The basic assumption
of his model was that each individual consumer maximizes his utility in a
segmented market where a concessional sector characterized by a planned
fixed price and quantity rationing operates simultaneously with a commercial sector where the price is determined by the forces of demand and supply.
The consumer voluntarily decides whether and to what extent to participate
in the open free market based on a given ration and income level, as well as
on market prices. Byrd showed that if there exists a functioning parallel
market, consumer behavior is similar to what it would be in the absence of
rationing. Sicular (1988) further extended this proposition by means of a
general equilibrium model that focuses on the interactions between markets
and state planning in the context of China’s agricultural sector. She showed
that, in the presence of parallel markets, if at the equilibrium, when excess
demand in the free market is equal to zero, all state-planned prices are
strictly less than market prices, then rationing will cause lump-sum transfers
among economic agents and only influence consumer choice decision indirectly through its effects on income redistribution and equilibrium market
prices. Unfortunately, these studies provided only theoretical analyses and
contained no empirical verification of the effects of rationing.
There are several empirical studies of consumer behavior in China. Van
der Gaag ( 1984) estimated a Linear Expenditure System for food, clothing,
housing and services by using pooled provincial household budget data for
both rural, Hebei province, and urban, Beijing, residents in 198 1 and 1982,
but he did not consider any effects of rationing. Chow (1988) introduced the
theory of consumer behavior under rationing developed by Tobin and
RATIONING
CHINESE
HOUSEHOLDS
3
Houthakker (195 l), and interpreted theoretical results against the practices
in China. He then estimated a logarithmic Engel curve for food, clothing,
housing, and all other items using rural household budget data.
The purpose of this paper is to investigate and quantify the impacts of
housing, foodgrain, and fuel rationing on the consumption of other consumer goods and services by Chinese urban households during the recent
period of economic reforms, 198 l- 1987, and to explain the observed consumer behavior in the Chinese urban market. Special attention is paid to
nonstaple food and household appliances. Our hypothesis is that the observed excess demand for these two categories of commodities in the Chinese
urban consumer market is caused by the spillover effects of rationing. Attempts are made to test this hypothesis through econometric means.
This paper is organized as follows. Section II contains a brief description of
the consumption behavior of Chinese urban households since 1979. In Section III, a linear approximate Almost Ideal Demand System with rationing
(LA/AIDSR), is specified following Deaton (198 1) and Deaton and Muellbauer ( 1980). Related formulas for expenditure and price elasticities of unrationed goods and comparative statics for changing rationed level and price
are also derived. In Section IV, the data, stochastic assumptions, and estimation procedures are discussed. In Section V, the LA/AIDSR models are estimated by pooled cross-sectional and time-series survey data of Chinese urban households from 198 1 to 1987. Test results for homogeneity and symmetry, the estimated own price and total expenditure elasticities of
unrationed goods, the coefficients of ration level, and related comparative
statics are presented and analyzed. The policy implications of its estimation
results are also discussed. The paper ends with a summary (Section VI).
II. OBSERVED BEHAVIOR OF CHINESE URBAN
HOUSEHOLDS
DURING
198 1- 1987
A study published by the Chinese Academy of Social Sciences (1988)
points out that there have been two striking trends in the consumption behavior of Chinese urban households since 198 1. One is the growing demand for
appliances such as color TVs, washing machines, and refrigerators. The
other is the increasing demand for nonstaple food, especially for meats, edible oil, milk, and eggs. The study indicates that Chinese urban consumers
seem to eat too well relative to their income level. For example, although
China’s per capita GNP was only $465 in 1986, the per capita consumption
of meat and eggs by its urban residents already exceeded the level observed in
South Korea at a per capita GNP above $1,200. Furthermore, the Chinese
consumption level was about the level observed in the USSR at a per capita
GNP of $1,200. From 198 1 to 1987, the ownerships of washing machines,
refrigerators, and color TVs per 100 urban households increased 9.5, 89.5,
4
WANG
AND CHERN
and 57.7 fold, respectively. This accumulation of durable goods increased
the household budget share of articles for cultural life and daily use to nearly
17%, which is 8 percentage points higher than in countries where per capita
GNP was above $1,500 in 1986.
Furthermore, the relatively strong demand for nonstaple food and consumer durables may be sustainable or even strengthened by the preferences
of Chinese urban consumers. A survey published in the same study by the
Chinese Academy of Social Sciences showed that among 12 future consumption objectives, 37.5% of respondents ranked “to improve the quality of
food” as the most important, while 19.3% chose “to increase education expenditure for children,” and 14.3% chose “to purchase durable goods.” The
survey also showed that 20.6% respondents in the middle income group
ranked “to purchase durable goods” as most important, while 45.3% in the
high income group chose “to improve the quality of food,” which is 15%
higher than those in low income group. These survey results indicate that as
income increases, Chinese urban households will take improving food quality as their priority concern in consumption.
Although the dramatic increase in household income is an important factor, it is not sufficient to explain such strong demand for improving food
quality and consumer durables as occurred in recent years. If there are no
market distortions such as rationing, Engel’s Law should prevail. The law
stipulates that, as income increases, food’s expenditure share should decrease.’ In China, because the food expenditure share has remained very
high despite dramatic increases in household income during recent years, it
may not be too unreasonable to attribute this unusual consumer behavior to
the rationing system.
Figure 1 shows annual budget allocation by an average urban household in
China in 1987. The per capita income was $272.1 in U.S. dollars at an
exchange rate of 3.72 Rmb per dollar. Even though food still accounted for
the largest share of consumer expenditures, 47.74%, the major component of
food expenditure was for nonstaple food 31.3%. The budget allocation
clearly shows that under the current rationing system, Chinese urban households allocate very small expenditure shares to living necessities such as
grain, fuel, and housing. In China, the low budget shares for grain have been
caused more by the low prices of rationed staples than by stringent rationing.
As for fuel and housing, there have been both low prices and rationed quantities. Thus, the rationing system remains an important factor affecting the
’ Chenery and Syrquin (1975) studied consumption data for 101 countries, including those in
Eastern Europe, They found that the Engel coefficient decreased as per capita gross national
product (GNP) increased. This law was also confirmed by Houthakker (1957) in his study of
household expenditure patterns for both high income and low income countries.
RATIONING
CHINESE
HOUSEHOLDS
busing
---__-
_---_
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Water 6 Ekbicky
-------S*m,
Fee0 ----___-___---Transpcr~~o”
_-- ----_ --_-Chi,,j are
-------------O,hsrs
-------___-------
7.57
31.30
0.87
574
13.69
11.37
5.60
0.84
1.00
1.38
4.15
x
K
K
K
Y
n
n
x
K
K
x
0.87
1.32
1.28
1.03
0.42
3.57
$4
n
x
*
x
Y
FIG. I. Average annual household budget allocation on a per capita basis, Chinese urban
households, 1987. Source: State Statistical Bureau of PRC, China Statistical Year Book 1988, p.
722.
consumption behavior of urban households, despite the significant infusion
of free market forces into the Chinese economy since 1979.
In many industrialized nations such as the United States, housing usually
constitutes about 30% of household expenditures. In China, rationing of
housing is an in-kind subsidy for people working in the state sector, thus rent
accounted only for 0.87% of average total household expenditures in 1987.
This share will become even smaller as household incomes increase and the
government decontrols prices of other commodities. For instance, even
though per capita living space of urban residents increased from 5.6 square
meters in 1982 to 8.5 square meters in 1987, the expenditure share of housing declined from 1.5 to 0.87%.
Rationing distorts consumer behavior since consumers cannot purchase
their desired quantities at government controlled prices. Since consumers
incur smaller than desired expenditures for rationed goods and services,
rationing may lead to increased demand for other commodities that can be
purchased freely. Such phenomena are called spillovers between rationed
and unrationed good markets in the economics literature. The distortion or
spillover becomes more serious when a reforming centrally planned economy does not decontrol important consumer goods such as housing as household incomes increase suddenly as has happened in China.
Podkaminer (1982, 1986, 1988) analyzed disequilibrium in the consumer
markets in Poland, and he found that Polish consumer markets suffer from
relative price distortion. Food appeared to be overpriced as compared with
the market equilibrium price, and the observed food shortage was caused by
the spillovers from markets for rationed, but underpriced cars, housing, and
services. Collier ( 1986) studied the East German consumer market by using
6
WANG
AND CHERN
a direct utility function estimated from West German family budget data.
He also found similar evidence, i.e., overconsumption
of food, especially
tobacco and alcohol, and underconsumption
of housing. It would be reasonable to expect a similar distortion in the Chinese urban nonstaple food market because of similar patterns of government subsidization.
III. DEMAND
MODEL
SPECIFICATION
The consumer choice problem with some goods under strict rationing can
be formulated as:3
Max WL
x,1
s.t. p,x, + p,xr < I, and x, = z,
(1)
where z is a vector of ration levels, x,, and x,, p, and p, are subvectors of
unrationed and rationed goods and their prices, respectively.
Based on the duality theorem, this utility maximization problem can be
solved by minimizing the following expenditure function,
ECU, P,, or, 4 = P$n PP + POX,; Vz, 4
2 VI,
(2)
where V(z, x,) = Max U(x,, x,), E( . ) is the constrained expenditure function, which gives the minimum expenditure for reaching U at pu and p,, in
the presence of rationing constraints x, = z (Deaton, 198 1). Assuming that
the consumer buys exactly the ration level z of rationed goods, the expenditure for rationed goods, p,z is a constant and can be subtracted from (2)
without affecting the optimal x,. Thus, the expenditure functional under
rationing can be rewritten as
E(u, P,, P,, 4 = P,Z + ~~{PA,;
W, A) 2 U> = PG + C(U, z>PA
(3)
The function C( - ) has all the conventional properties of an expenditure
function, including the derivative property for the unrationed demands
(Deaton, 198 1). For empirical estimation, a suitable function form of C( * )
needs to be specified. Deaton (1981) suggested a flexible function form
3 China has evolved into a mixed economy because the parallel consumer goods markets have
expanded since 1979. In this mixed economy, only housing is still under strict rationing. For
other rationed goods, such as foodgrains and fuel, state stores, and a free market usually co-exist.
Therefore, dual pricing has become a common feature of the Chinese urban consumer market.
In order to model consumer behavior in this dual market system, a suitable theoretical framework should be the one proposed by Byrd ( 1987). Unfortunately, there are not enough data to
estimate a complete demand system under the dual market structure. No data on state ration
levels and the proportion of rationed goods in total household expenditure are published. For
the purpose of empirical estimation, the model (1) is thus used as an approximation.
RATIONING
CHINESE
I
HOUSEHOLDS
known as the PIGLOG class used for the Almost Ideal Demand System
(AIDS). The resulting expenditure share equation can be expressed as
Wi = (Yi+ 2 nikzk +
k=l
i
Yijln pj + Piln{ (I - $J pkZk)/P}
j=m+l
k=l
k= I,...,
ln P = (YO
+ 5
k=l
i
+
(ori
m,andi,j=m+
pj + 0.5 i:
njkzk)h
j=m+l
j=m+l
l,...,
n (4)
5 rij In pi In Pj (5)
i=m+l
where the W:s are the budget shares as a proportion of the total non-rationed
expenditure, zk’s are the quantities of rationed goods, Pi is the price for jth
unrationed good, pk is the price for kth rationed good, Z is total expenditure,
P is the general price index for unrationed goods, subscripts i and j refer to
non-rationed goods, k refers to rationed goods, and n > m. The parameters
CX~,
nik, rij, and pi can be required to satisfy the theoretical properties of utility
maximization by imposing the following restrictions: for adding up,
5
(yi = 1, i
i=m+l
nik = 0,
i=m+l
ril = 0, and i
c
i=m+l
pi = 0;
i=m+l
(7)
for homogeneity,
i
rij = 0;
(8)
j=m+l
and for symmetry,
rij = rjp
(9)
As usually done in empirical application, Stone’s price index is used as a
proxy for the true price index given in equation (5). Stone’s price index is
defined as
In p* =
i
Wjln pi
(10)
j=m+l
Substituting
estimation,
(10) into (4), we obtain the following
final specification
for
(11)
j=m+l
where pit is the random error for tih observation in ith share equation. This
model is a linear approximation of the original AIDS with rationing. There-
8
WANG
AND CHERN
fore, it can be appropriately termed the linear approximate AIDS with rationing or, simply, LA/AIDSR. In this model, the effects of rationing on
consumer behavior are captured by two terms. One is the income effect (I C pkzk); the other is the ration level z. The coefficients of the latter term
provide a quantitative measure of the effect of the kth rationed good on the
budget share of ith unrationed commodity.
The total expenditure elasticities can be derived from equation (11) by
calculating the partial derivative of Wi with respect to I. The result is straightforward:
ei= 1+ Pi/wi{l/(l - 5 Pkzk)}.
k=l
(12)
Green and Alston ( 1989) suggest several ways of computing own-price and
cross-price elasticities in the AIDS model. They argue that the underlying
assumption for the commonly used AIDS price elasticity formula e0 = -6, +
pi/ Wi is very restrictive.4 Following Green and Alston, we derive the price
elasticity formula in the rationing case under the assumption that all other
prices and total non-rationed expenditure are held constant, but allow W
and the overall non-rationed price level, P, to change. The price elasticities
can be computed as
eu = -6, + r,ilW, - gJWi{
Wj
+ C wjn p,(eU + a&},
(13)
where&=
1 fori=jandOfori#j.
Equation (11) can be used to derive the effects of changes in the price of
rationed goods & and ration level z,. The results are given below.
(a) When rationed price pk changes, the rationed price elasticity of the
demand for unrationed goods can be computed as
eik= -@i/w{pkzk/(I
- k=l
5 Pkzk)}.
(14)
This elasticity should be negative for normal goods, since the expenditure
of unrationed goods (I - C pkzk) is always positive and a change in pk has
only an income effect. An increase in pk would force consumers to pay more
for the given ration level zk and reduce the demand for unrationed goods.
(b) When the ration level zk changes, its impacts can be evaluated by
the following two sets of elasticities?
4 The assumption is a In P/a In p, = 0, implying that the general price level is constant,
independent of each individual commodity’s price.
’ When driving (16), we assume that all budget shares of unrationed goods are constant, i.e.,
let dW, = 0.
RATIONING
CHINESE
HOUSEHOLDS
WZik = d In BJa In zk = nikzkjwi - pi/wi{pkz~(~
9
- 5 p$k))
(15)
k=l
and
Pzik= a In pi/a In zk = pi/rii{pkzd(I
- 5 &ZJ> - &kZJrii.
k=l
(16)
Equation ( 15) shows that a change in the ration level zk has a substitution
effect n,$,J Wi besides an income effect. An increase in zk would reduce the
demand for substitutes and increase the demand for complements of the
rationed good. The sign of this elasticity is ambiguous in general, because the
income and substitution effects work in opposite directions when the unrationed goods are normal and net substitutes for the rationed goods6
IV. DATA
AND
ESTIMATION
PROCEDURES
The data used in estimation were obtained from the surveys of urban
household income and expenditures conducted by the State Statistical
Bureau of the PRC from 198 1 to 1987. The surveys were carried out by local
agencies. The families selected in the surveys were drawn from a very large
population frame based on proportionate stratification, one out of ten thousand households. Every family selected had to sign an agreement with the
government to guarantee their accuracy in recording their daily income and
expenditures, and in auditing all records monthly and quarterly. Initial data
contain per capita annual expenditures for 11 categories of goods and services.7 Unfortunately, only sample means by income groups are published.
These data were obtained from Chinese Urban Household Budget Surveys,
published by the State Statistical Bureau in 1988 and 1989 in Chinese. We
6 A further clarification should make this assertion clearer. In China, an increase in the ration
level represents an increase in state subsidy because of the low prices of rationed goods. In the
cases of grain and fuel, an increase. in their ration level would reduce the need to pay higher
prices for buying additional quantities of these rationed goods in the free or black markets. In the
case of housing, an increase in the rationed living space is not always accompanied with an
increase in the rent paid to the government. Therefore, in general, an increase in ration level
would result in an increase in disposable income for buying nonmtioned goods in China.
’ These 11 expenditure categories include (1) food grain, (2) nonstaple food, (3) tobacco,
liquor, and tea, (4) other food, (5) clothing, (6) durables and articles for daily use, (7) durables
and articles for cultural life and recreation, (8) medicine and medical articles, (9) fuel, (10)
housing rent, and (11) services. These categories are aggregated from the original data for 11
items of commodity expenditures and 12 items of non-commodity expenditures. The expenditures on commodities refer to the total expenses by the sample households for purchasing
commodities from state-run stores, factories, catering industries, canteens, free markets, and
directly from peasants.
10
WANG
AND CHERN
organized these data into six consistent income groups, and thus we have 42
observations for each expenditure item over this 7-year period.
The price data are retail price indexes for the 11 categories of commodities
and services sold in state commercial departments in cities and towns from
198 1 to 1987 with 1978 as the base year. Only one price series is available for
all income groups. The price data were obtained from China Statistical Year
Book 1989 and China PriceStatistical YearBook (various issues), published
by the State Statistical Bureau. The price indexes of housing rent were only
available after 1983. Since there was no rent increase before 1983, we assumed the same index during 198 1- 1983. Since there are high collinearities
among price indexes for several commodity groups, the ill-condition of the
(XX) matrix caused problems in estimating an 1 l-commodity model. For
this reason, some closely related expenditures were further aggregated into
eight categories for estimation. They are (1) food grains, (2) nonstaple
and other food, (3) tobacco, liquor, and tea, (4) clothing, (5) articles for
cultural life and daily use, mostly durables, (6) fuel, (7) services, and (8)
housing rent.’
The sample period of 198 l- 1987 was chosen not only because of data
availability but also because of theoretical considerations. This period can be
characterized by relatively small changes in relative prices and large changes
in income (total expenditures), a situation best suitable for estimating a
stable demand structure following the assumption of a neoclassical representative consumer (Varian, 1982). The inclusion of later years, such as 1988
and 1989, would not ensure the stability in the demand structure because of
dramatic increases in the prices of nonstaple food and consumer durables in
these years.
Among these categories, housing was under strict rationing in the sample
period. Fuel and food grains were also subject to formal rationing. However,
urban households in many cities could purchase additional grain and fuel
from free markets at market prices. A portion of nonstaple food such as beef,
edible oil, fresh eggs, and sugar was also rationed in most cities, at least
during part of the sample period. However, since the rationed amount of
these nonstaple food items was usually small, many urban households purchased significant additional amounts in free markets. Since no information
is available for the ration and free market portion of food grains, fuel, and
some nonstaple food items in the household expenditure surveys, we have to
treat them as either rationed goods or unrationed goods. The approximation
of this treatment may be justified by the shares sold on the free market
during the sample period.
Table 1 shows the free market shares in retail quantities/values of food
* All data used in this study are available upon request from the authors.
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grain, fuel and some nonstaple food items during 1978-1987. The shares for
grain and fuel are rather small, around 5 to 7% and the rationed quantities
accounted for the major portion of urban consumption. Therefore, we may
consider these two categories of goods as if they were under strict rationing in
the empirical model. But nonstaple food items are different. Table 1 shows
that the free market shares of the selected nonstaple food items were rather
high, around 50% for most items in most recent years. Furthermore, a large
portion of nonstaple foods such as vegetables and fruits was no longer subject
to any rationing. As mentioned earlier, Sicular (1989) has showed that in a
dual market system, the equilibrium conditions for the consumer’s decisions
are likely to be determined by the free market prices rather than by state
plans. Therefore, it should be a reasonable approximation to treat the category of nonstaple food as an unrationed commodity in the empirical model.
If the disturbance term pir in Eq. (11) satisfies the usual assumptions,
ordinary least squares (OLS) can be applied to each expenditure share equation separately. However, since we use the pooled cross-sectional, six income
levels, and time-series ( 198 l-l 987) grouping for mean value only data, this
regularity assumption may not hold. The findings of previous consumer
budget studies carried out by Cramer ( 1964), and Prais and Aitchison ( 1954)
suggest the existence of heteroscedasticity in such data and the variance of
pu,‘sto be inversely proportional to the number of people within each income
group. Therefore, the weighted least squares (WLS) estimator using group
size as the weighing factor is chosen to estimate each expenditure share
separately.
The commonly used estimator for a set of expenditure share equations is
Zellner’s seemingly unrelated regressor (SUR), which gains efficiency when
contemporaneous correlation exists. However, in our LA/AIDSR model,
the explanatory variables are the same for all expenditure share equations.
Thus SUR is identical to WLS when no cross-equation restrictions are imposed (Johnston, 1984). For imposing cross-equation restrictions such as
symmetry, we still need use the SUR procedure to estimate all share equations simultaneously.
As discussed earlier, among the eight categories of expenditure used for
estimation, housing, fuel, and food grain were subject to various degrees of
rationing during the sample period. For evaluating the validity of the model
specification, the LA/AIDSR model is estimated for four alternative cases of
assumed rationed goods: (1) housing only, (2) housing and fuel, (3) housing
and grain, (4) housing, fuel, and grain. Together with the unrationed LA/
AIDS model, a total of five complete demand systems is estimated. Each
expenditure share equation is first estimated separately without any restriction by the WLS. Then, the homogeneity condition is imposed. The validity
of this restriction is formally tested. The symmetry conditions are further
imposed using the SUR. One expenditure share equation is dropped from
RATIONING
CHINESE
HOUSEHOLDS
13
each system and its parameters are obtained from the adding-up conditions.
Therefore, totally 15 complete demand systems are estimated. For each
unrationed good such as nonstaple food, we have 15 alternative sets of estimates. The major findings from these estimates are summarized in the next
section.
V. ESTIMATION
RESULTS
Testingfor TheoreticalPropertiesof a Demand System
Testing theoretical properties of demand can provide useful information
for validating the consistency of the observed data with the utility maximization hypothesis and with various specifications of rationing. Since the dependent variables are expenditure shares in the LA/AIDSR, the adding-up conditions are automatically satisfied. The results of F tests for homogeneity are
presented in Table 2. The F-statistics show that the homogeneity conditions
are rejected at the 5% significance level in 21 out of 32 equations under 5
alternative specifications of rationing. Based on the Euler’s theorem, the
necessary condition for homogeneity is that the sum of expenditure and
price elasticities is equal to zero. We also check this condition for all estimated equations, and the results are also presented in Table 2. As one can see
from these results, the models with rationing perform much better than the
unrationed model, especially for nonstaple food and articles for cultural life
and daily use. For these two expenditure share equations, the estimated
F-values are dramatically reduced when rationing of housing is imposed.
The homogeneity condition can not be rejected when rationing of foodgrains is also imposed. In the model with three rationed goods, the computed
F-statistics was further reduced for these two equations. Although the sums
of price and expenditure elasticities are all not equal to zero, the values are
implausibly large in the specification where no group of goods was considered to be under rationing. It is noted that the sums of the elasticities are
considerably smaller and approximately equal to zero in most goods in the
specifications where one, two, or three groups of goods are considered under
rationing. For example, the sum of price and expenditure elasticities is
- 16.52 for nonstaple food and 24.99 for articles for daily use and durables in
the model without any rationing goods, while they are only 0.25 and -0.38
in the models with housing, grain, and fuel as rationing goods.
Table 3 presents the results of asymptotic Wald tests for imposing both
homogeneity and symmetry restrictions. The results reveal that these restrictions are also rejected in all five systems with different specifications of rationing. However, similar to the homogeneity test, the computed x2 statistics
are substantially reduced when various rationing regimes are imposed. Taking into consideration the degrees of freedom and the asymptotic nature of
the test, the models with (1) housing and fuel (2) housing, grain, and fuel as
-1.55
1.16
-0.65
-
102.25
12.82
70.51
1.57
24.99
0.75
-15.99
-1.32
9.97
0.7
43.21
-
4.66
1.62
6.97
6.12
Fvalue
-0.59
1.22
-1.83
-
-1.04
0.34
0.7
Sum of
elasticities
1.54
1.27
28.08
-
6.29
2.39
5.51
Fvalue
Housing & grain
’ All elasticities are calculated at sample means. The 5% critical value of F,.32 = 4.17.
Services
Fuel
Housing
USe
-0.62
14.5
-25.53
-0.8
0.76
0.59
12.66
54.46
3.59
57.08
-16.52
1.73
Sum of
elasticities
Grain
Nonstaple food
Clothing
Tea, tobacco, and
liquor
Articles for daily
Fvalue
Sum of
elasticities
Housing
Expenditure
groups
None
-1.57
1.22
-
-0.72
-0.8
0.75
0.69
21.62
119.71
-
12.47
0.08
13.26
14.84
Fvalue
Housing and fuel
Sum of
elasticities
Alternative rationing specifications
SUM OF EXPENDITURE AND PRICE ELASTICITIESAND PSTATISTICS FORHOMOGENEITY”
TABLE 2
-0.38
1.26
-
-1.29
0.25
0.82
Sum of
elasticities
3.53
75.91
-
0.63
1.75
13.17
Fvalue
Housing, grain
and fuel
s
3
e
RATIONING
CHINESE
HOUSEHOLDS
15
TABLE 3
TESTS FOR HOM~GENEW
AND S~MMETFCY
Alternative rationing specifications
Item
None
Housing
Housing
and grain
Housing
and fuel
Housing, grain
and fuel
D.F.”
Wald-statistic
21
326.4
15
355.0
10
149.7
10
70.5
6
74.2
Note. 5% critical value of xi, = 32.67, xf5 = 25, &, = 18.31, xi = 12.59.
’ Degrees of freedom.
rationed goods would be more likely to satisfy these theoretical restrictions
than the other three models. While the model with housing and grain as
rationing goods yields the best results in single equation homogeneity tests,
in general we can only conclude from these test results that the demand
systems with rationing perform better and are more consistent with the
theory of utility maximization in fitting the budget data from Chinese urban
households during 198 1-1987. However, these results can not provide undisputable evidence for judging which rationing scheme is the best among
the four LA/AIDSR models estimated in this study. In order to enhance the
accuracy and creditability of these tests, it would be necessary to analyze the
reasons that may have caused the rejection of homogeneity and symmetry
conditions, such as preference changes, and to properly consider these factors in the model formulation.
Price and Expenditure
Elasticities
Since not all regression results can be presented in this paper, we will focus
our analysis on these results directly related to the evaluation of the effects of
rationing. However, it is worthwhile mentioning that the models fit the data
very well as the computed R2’s are greater than 0.95 for all expenditure share
equations, and in most cases they are as high as 0.99. In addition, most
regression coefficients, especially the &‘s, are statically significant at the 5%
significance level.
Total expenditure and the uncompensated price elasticities of unrationed
goods are calculated using equations (12) and (13). Table 4 presents the
estimated elasticities for all the five demand systems with different rationing
specifications under the three cases of (1) unconstrained, (2) homogeneity
imposed, and (3) both homogeneity and symmetry imposed. A careful comparison of the elasticities reveals four important facts. First, the expenditure
elasticities are all very robust among alternative rationing specifications. The
Fuel
Housing
SXViCeS
Grain
Nonstaple food
Tea, tobacco, and
liquor
Clothing
Articles for daily
use
Expenditure
groups
- 14.42
-1.83
-0.79
1.76
-9.5
-0.95
4.89
-3.03
I .04
I .27
1.56
0.93
0.27
0.95
Price
0.1
0.97
EXpelI.
1.67
0.93
0.19
0.94
1.04
1.15
0.19
0.89
Expen.
-0.77
0.34
15.62
-0.7 I
Price
1.71
0.84
0.1
2.39
0.99
1.17
0.47
0.85
EXpelI
-5.31
0.44
0.32
-29.43
-0.79
-1.91
-1.27
-0.82
Price
and
1.64
0.94
-0.1
-
I .08
1.39
0.3 I
0.86
Expen.
Price
-6.63
-0.94
4.67
-
-0.76
-1.38
1.96
-0.74
Unconstrained
specifications
Alternative
rationing
ELASTICITIES’
AND EXPENDITURE
Homogeneity
symmetry
OWN PRICE
-6.23
-0.92
4.48
-0.54
Homogeneity
No rationing
ESTIMATED
TABLE 4
1.63
0.95
-0.1
-
1.08
1.39
0.31
0.87
Expen.
1.96
-0.61
price
-9.07
-0.65
5.6 I
-
-0.82
-0.66
Homogeneity
Housing
-2.42
1.35
-6.5 1
-0.57
-5.85
-
-0.6
1.17
1.76
0.8
1.99
-
-1.13
-0.58
Price
and
0.43
0.86
Expen.
symmetry
Homogeneity
!z
i
s
1
5
Q
’ All elasticities
Grain
Nonstaple
food
Tea, tobacco,
and liquor
Clothing
Articles for
daily “se
Services
Fuel
-0.79
-1.41
-1.42
1.25
-
1.05
1.39
I .66
0.89
-
are computed
-1.15
1.65
0.82
0.31
-8.96
-3.02
-
-1.08
-0.39
-0.18
0.13
at sample
1.57
0.96
-
1.09
1.35
0.87
0.28
Price
Expen.
Expen.
Price
Homogeneity
and fuel
Unconstrained
Housing
means.
1.56
1.04
-
1.05
I .33
0.86
0.27
Expen.
-3.49
0.89
-
-2.05
-1.9
-0.64
-0.49
Price
Homogeneity
and symmetry
1.87
0.89
1.27
-2.95
-1.16
4.28
-2.95
-1.16
4.28
-0.72.1 1
-3.44
-0.81
6.52
-0.75
2.68
1.73
1.13
1.01
1.03
0.98
8.82
-1.04
0.71
-0.73
-0.48
-0.72.1 I
0.96
1.06
Price
-0.86
0.7
Expen.
-0.92
-0.97
Price
0.67
-0.92
Expen.
Homogeneity
and symmetry
-
Price
and grain
Homogeneity
Housing
4-Continued
-----
Expen.
Unconstrained
TABLE
1.51
0.73
-
0.93
I .34
0.75
-
Expen.
-4.5 I
0.4
-
-0.75
-0.84
-0.8
-
Price
Unconstrained
1.47
0.86
_
1.01
1.21
0.78
-
Expen.
-5.12
-0.81
_
-1.06
0.89
-0.75
-
Price
1.46
1.01
-
1.09
1.14
0.76
-
Expen.
-1.65
-0.84
-
-0.82
-1.22
-0.9
-
Price
Homogeneity
and symmetry
fuel and grain
Homogeneity
Housing,
8
E;
CA
cg
g
E
8
2
2
c!
8
!z
18
WANG
AND CHERN
articles and durables group has the highest expenditure elasticities among
unrationed goods, clothing has the second highest, while nonstaple food has
the lowest elasticities. Second, the estimated price elasticities are very sensitive to alternative specifications. This result may be attributed to the fact that
price data used in the estimation cover a very short time period and may not
contain sufficient variations to produce robust estimates. Third, after imposing the theoretical restrictions of demand, the estimates of price elasticities
are improved substantially. For example, in the model without any constraint or with only the homogeneity constraint, the price elasticities for
articles and durables are unreasonably large (-9.5 and -6.23), while they
were reduced to a more reasonable range after imposing both homogeneity
and symmetry conditions. One possible explanation is that the imposition of
homogeneity and symmetry reduces the number of parameters to be estimated in the model. Thus, there are more degrees of freedom in estimation.
Finally, among the five estimated complete demand systems, the system
with three rationed goods provides more plausible estimates of price and
expenditure elasticities, especially when all theoretical restrictions are imposed. The restriction-free system with no rationed goods produces the most
unrealistic elasticities, as the price elasticity is as high as - 14.42 for foodgrain
and has a positive (wrong) sign for clothing and fuel. The results show that
the LA/AIDSR model performs much better than its unrationed version in
estimating consumer behavior parameters in the Chinese economy with a
rationing system.
Rationing Eflectson UnrationedGoods
The estimated coefficients njk of ration level z;k and their t-ratios in the
four demand systems with rationing under three types of restrictions are
presented in Table 5. As mentioned in Section III, changes in the ration level
have an income effect and a substitution effect. If the unrationed goods are
normal and net substitutes for the rationed goods, the signs of these two
effects should be opposite. Furthermore, in the LA/AIDSR models, the adding-up condition requires that the sum of the coefficients of the ration level
across all expenditure share equations equals zero. Therefore, the estimated
&‘s can be positive or negative. Table 5 shows that the estimated coefficients
of the housing ration level are positive in 10 out of 12 expenditure share
equations of nonstaple food, 4 rationing specifications and 3 types of restriction, and in the 2 cases with a negative sign the coefficients are nearly zero
and have a very small t-ratio. These results indicate that as the ration level of
housing increases, Chinese urban consumers would increase their expenditure share on nonstaple food.
It is interesting to note that although the model with housing and fuel as
rationed goods provides relatively better results based on homogeneity and
RATIONING
CHINESE
HOUSEHOLDS
19
symmetry tests, all the coefficients of ration level zik in this system
are not
significantly different from zero, while in the model with either three rationed goods or only housing and grain as rationed goods these coefficients
are significantly different from zero in most cases. In particular, in the two
equations that we are most interested in, i.e., the expenditure shares of nonstaple food and articles for daily use, the t-ratios for the estimated coefficients
of the ration level are very high. These statistical results suggest that rationing
may have been one of the major factors affecting consumer behavior in
Chinese urban nonstaple food and durable good markets.
The results in Table 5 also indicate that an increase in the rationed quantity of grain would reduce the expenditure shares of nonstaple food, tobacco,
liquor, and tea, but would increase the expenditure shares of clothing and
durables. This pattern of rationing effects seem to be reasonable because the
increases in the amount of rationed grain would have substitution effects for
nonstaple food and tobacco, liquor, and tea, resulting in a larger proportion
of budget being available for clothing, durables, and articles for daily use.
The effects of rationing can also be evaluated by comparative statics analysis, i.e., by calculating the cross price elasticity of an unrationed good with
respect to the prices of rationed goods (a In xi/a In &), and the expenditure
share elasticity with respect to rationed quantities (a In w,/a In zk), and the
price flexibility with respect to the rationed quantity (a In pi/d In zk). All these
elasticities were calculated for the four rationing systems using Eqs. (14),
( 15), and ( 16). In order to save space, only the estimates from the model with
homogeneity and symmetry constraints are reported in Table 6, where EP,
WZ, and PZ denote eib d In wi/a In zk, and a In pi/d In zk, respectively. The
subscripts r, f, and g refer to the rationed goods of housing, fuel, and grain,
respectively.
Consider first the estimated EPs, the cross-price elasticities of unrationed
goods with respect to the prices of rationed goods. In all four demand systems under rationing, these elasticities are negative in all categories except
the food group. These results indicate that when the prices of rationed goods
increase, the demand for unrationed goods will be depressed. This is clearly
because the income effect will reduce the purchasing power of Chinese urban
households for unrationed goods when the prices of rationed goods increase.
It is rather difficult to explain the positive sign of ejk for nonstaple food.
Because nonstaple food obviously cannot be considered an inferior good in
the Chinese urban consumer market. Carefully comparing the absolute
value of cross price elasticities between nonstaple food and the three rationed
goods, we find that the cross-price elasticity between nonstaple food and
food grain is much greater than the others. Therefore, a possible explanation
is that there is a substantial substitution effect between nonstaple food and
grain. Consequently, increases in the price of rationed grain would result in
an increase in demand for nonstaple food. But this explanation would con-
Fuels
Articles and
durable
Services
Tea, tobacco,
and liquor
Clothing
Nonstaple food
Grain
Expenditure
groups
0.28
(0.87)
0.23
(0.4)
-0.027
(-0.44)
-0.6
(-2.92)
0.053
(0.14)
-0.003
(-0.034)
0.078
(1.66)
Housing
Housing
0.28
(0.87)
0.166
(0.3 1)
-0.034
(-0.59)
-0.58
(-2.97)
0.105
(0.31)
-0.023
(-0.37)
0.08
(1.59)
Homogeneity
W-S)
Unconstrained
(WW
-0.037
(-0.12)
-0.14
(-2.18)
-0.39
(-1.9)
0.4 I
(1.82)
0.094
(0.56)
-0.45
b
(2.1)
0.52
Housing
Homogeneity and
symmetry (SUR)
GOODS
IN
LA/AIDSR
MODELS”
-
Housing
-
Grain
Housing
-
-
-
Fuel
-0.44
-0.26
(-6.63) (-2.46)
-0.06
-0.016
(-3.16) (-0.63)
0.24 -0.26
(4.91) (-3.36)
0.49
0.47
(7.71) (4.66)
-0.24
0.07
b
b
-
-
Grain
Homogeneity and
symmetry (SUR)
Fuel
Homogeneity (WLS)
-0.26
-0.3
1.34 -0.41
-0.4
1.29
(-1.57)
(1.71)
(2.62) (-3.58) (-2.49)
(4.12)
0.033
0.018
0.034 -0.029 -0.022
-0.019
(1.38) (0.69)
(0.39) (-1.5)
(-0.82) (-0.24)
-0.17
-0.36
-0.66
-0.1
-0.19
-0.67
(-2.74) (-5.38) (-2.37)
(1.55) (-2.18) (-2.82)
0.34
0.53
-0.92
0.43
0.58
-0.85
(2.85) (3.38) (-2.06)
(4.26)
(4.16) (-2.91)
0.05
0.12
0.2
-0.08
0.03
0.26
(2.44) (4.92)
(1.61) (-3.04)
(0.70)
b
-
-
-
1.08
(1.98)
-0.073
(-0.92)
-0.2
(-0.94)
-0.77
(-1.59)
-0.04
(-0.52)
-
Fuel
Grain
Housing
Unconstrained (WLS)
Housing, grain, and fuel
rationing specifications (estimated method)
(Q) FOR RATIONED
Alternative
COEFFICIENTS
Housing only
ESTIMATED
TABLE 5
Q
g
z
i2
u
-0.21
(- 0.03
1.22)
(1.81)
-0.14
(-1.56)
0.31
(1.88)
0.05
(1.85)
-0.035
(-0.86)
(-1.14)
0.38
(1.44)
-1.43
(-2.97)
-0.19
(-2.42)
-0.23
(-1.92)
(0.15)
0.02
(0.1)
-1.76
(-4.3)
0.035
(0.39)
-0.31
(-3.0)
1.99
(4.46)
0.01
-
-
1.56
-0.08
(2.99)
-
Housing
Grain
(-0.18)
0.0005
(0.006)
0.43
(3.38)
-0.039
(-1.39)
-0.006
(-0.2)
-0.38
(-2.73)
-0.004
-
Grain
Homogeneity
ww
(0.01)
-0.33
(-1.41)
-1.33
(4.59)
-0.079
b
-0.064
(-0.52)
$6)
0.007
-
Housing
-0.071
(-1.99)
b
(-2.04)
0.25
(4.52)
0.41
(6.31)
-0.18
(Ii:;;)
-0.038
-
Grain
Homogeneity and
symmetry (SUR)
(-0.49)
-0.57
(-2.94)
0.1
(0.3)
-0.013
(-0.24)
-
0.28
(0.85)
0.22
-0.029
(0.42)
Housing
(0.18)
-0.22
(1.42)
-0.3
(-1.1)
0.16
(3.58)
-
-0.12
(-0.44)
0.47
(1.09)
0.008
Fuel
Unconstrained
W-S)
’ The figures in parentheses are estimated t-ratios.
b The z-ratios are not estimated because the coefficients are derived from the adding-up conditions.
Fuel
Articles for
daily use
Services
Nonstaple
food
Tea, tobacco,
and liquor
Clothing
Grain
Housing
Unconstrained
ww
Housing and grain
TABLE 5--Continued
(-0.28)
-0.59
(-2.66)
0.04
(0.09)
0.011
(0.09)
-
0.26
(0.77)
(:::8)
-0.02
Housing
0.47
(1.72)
-0.13
(-1.76)
-
(0.8)
(-2.3)
0.11
0.14
(0.63)
(%)
-0.1
Fuel
Homogeneity
VW
Housing and fuel
(0.26)
-0.36
(-1.32)
0.32
(1.1)
-0.39
b
-
(Z7)
(I::&
0.05
Housing
-
b
-0.06
(-0.93)
-0.14
(-1.36)
0.15
(1.18)
0.19
0.024
(0.22)
(-%)
Fuel
Homogeneity and
symmetry (SUR)
2
g
g
Q
3
g
4
g
are computed
-0.ooo1
Fuel
r?All elasticities
-0.ooo4
0.0002
-0.0087
-0.0016
0.0036
Tea, tobacco,
and liquor
Clothing
Articles for daily use
Services
food
Wz,
EPr
Foodgrain
Nonstaple
-1.8
0.081
-0.0
0.0025
I5
SetiCeS
Fuel
at sample
-0.2232
0.0068
-0.132
-0.5108
-0.0597
0.2583
-0.179
0.167
-0.0039
-0.0067
-0.177
0.298
-0.004
Clothing
Articles for daily use
1
0.009 I
0.0017
wzr
-0.002
and
food
EPr
Housing
Tea, tobacco,
liquor
Foodgrain
Nonstaple
groups
Expenditure
means.
-0.025
-0.2545
I .705
0.037 1
0.0227
14.671
pz.
Housing
-0.1681
-0,256,
-0.1545
0.045
0.4638
0.3917
0.0097
Pz,
ESTIMATED
I
-0.0034
0.0017
-0.078
-0.0143
-0.0009
0.03 I8
EP.
and grain
-0.0001
_
-0.0017
-0.0055
-0.001
_
0.0028
EPr
Emcrs
-0.3079
0.752
1.2607
-0.9986
- 1.8382
-0.4437
w
0.1876
-
-0.2626
-0.3211
-0.020
0.1809
Wz,
I
6
1.151
- 1.450
-4.209
0.62 I
0.187
-24.63
Pz,
-1.1213
_
-1.3264
-0.5 126
0.1040
_
-4.9519
pz,
rationing
RATIONING
Alternative
OF CHANGING
TABLE
-0.0006
-0.004
-0.0067
-0.OMJ5
-
0.0087
0.0016
EPr
-0.0006
-
-0.0153
-0.049
-0.01
0.0253
EPs
Housing,
14
0.0594
-0.162
0.1275
-0.323
-
0.2273
-0.001
-1.2716
_
0.6847
1.3165
-0.48
_
-0.4296
Wz,
0.0566
-0.194
0.05 19
0.1706
-
-0.6019
0.0048
Housing
7.6001
-
3.4588
2.1014
2.4866
11.7594
Pz,
grain, and fuel
AND PRICES
specifications
LEVEL
_
-0.0008
-0.0052
-0.0088
-0.0007
-
0.0114
0.002 1
EPr
and fuel
-0.0001
_
-0.0022
-0.0072
-0.0015
0.0037
17
-0.09 1
-0.082
0.07 1
0.188
-
0.0276
-0.0295
Wz,
0.0610
-0.1258
-0.2072
-0.02
-0.0413
-
Wz,
-0.086
-0.097
0.0289
-0.099
-
-0.073
0.0869
pzr
-0.3048
_
-0.6353
0.3307
0.112
1.1306
-
pzr
8
z
g
e
w
RATIONING
CHINESE HOUSEHOLDS
23
tradict the assumption of foodgrain being under strict rationing. In such an
assumption, consumers would buy exactly the rationed amount, and thus
there can only be income effects but no substitution effects from changes in
the price of a rationed good. This is one of the few caveats and limitations for
using this model to study consumer behavior in an economy with a parallel
market.
Consider next WZ, the expenditure share elasticity with respect to rationed quantities. In general, the magnitudes of these elasticities are larger
than the rationed price elasticities EP, implying that the demands for unrationed goods are more sensitive to rationed quantities than rationed prices.
In analyzing the impact of the changes in the ration level for housing on the
expenditure share of nonstaple food, this elasticity is positive in the models
with either housing and grain as rationed goods or with three rationed goods
(Table 6). When this elasticity is negative in the other two specifications, the
magnitudes are very small. For the elasticities of durable and articles for
daily use, it is negative in the two rationing specifications with both housing
and grain as rationed goods. These results indicate that when the ration level
of housing increases, Chinese urban households would increase their expenditure shares on nonstaple food and decrease their share on durable appliances. On the other hand, the results show that the rational quantities of
grain and fuel all have positive elasticities with respect to durable goods. In
fact, the magnitudes of the elasticity of rationed grain level exceed unity in
the two specifications with both housing and grain as rationed goods. Since
housing and grain rationings are in-kind subsidies to urban households in
China, an increase in either or both of these goods will also increase the
marginal purchasing power of Chinese urban consumers for nonstaples and
durable goods.’
Finally, we examine the price flexibilities with respect to the rationed
quantity, PZ. It measures the effects of changes in ration level on the prices of
unrationed goods, if all budget shares are held constant. The estimated price
flexibilities are somewhat sensitive to rationing specification. For example,
in three out of the four specifications, housing rationed level has a positive
impact on the prices of nonstaple food and durables and articles for daily
uses as the estimated price flexibilities are positive. In the specification with
three rationed goods, the rationed level of housing has negative impacts on
the prices of nonstaple food and durables. However, the ration level of the
two other rationed goods shows very strong impacts on the prices of nonsta-
9 As noted earlier, in China, an increase in the housing ration level, i.e., living space, did not
necessarily require an increase in rent. More often than not, an increase in rationed housing
would accomodate the need of family members such as adult children who, otherwise, would
have to pay rent and live elsewhere.
24
WANG
AND CHERN
ple food and durables. In fact, the estimated price flexibilities for grain ration
level are positive and greater than unity for all five nonrationed goods. The
sensitivity of the estimates of these elasticities may be caused by the restriction that these price flexibilities are defined conditional upon fixed budget
shares. Nevertheless, the results show strong effects of rationing on the prices
of nonrationed goods. These findings would support the hypothesis that
rationing may be one of the causes for the sharp increases in the prices of
nonstaple food and consumer durables in Chinese urban consumer markets
in recent years.
VI. CONCLUSIONS
AND
IMPLICATIONS
In this paper, a LA/AIDSR Model with different combinations of rationed
goods was estimated using the pooled time series ( 198 1- 1987) and cross-sectional data from the urban household expenditure surveys in China. The
hypothesis test for the theoretical properties of the demand function shows
that the models with rationing perform much better than the unrationed
model. The estimated own price and total expenditure elasticities show that,
among unrationed commodities, articles for daily uses, cultural life, and
recreation (mostly durables) have the largest elasticities, clothing is second,
while nonstaple food has the smallest elasticities. Comparing the alternative
specifications of rationing schemes, in general the model with housing, grain,
and fuel as rationed goods is found to produce more plausible estimation
results than other specifications.
The estimated coefficients of the housing ration level indicate that rationing of housing has had significant impacts on the demands for nonstaple
food and durables. The comparative statics for changes in ration level reveal
that increases in the ration quantities of housing, grain, and fuel will simultaneously push up both the prices of and demands for nonstaple food and
durables. These results imply that rationing is one of the fundamental reasons for the concurrence of raising prices of and excess demand for nonstaple
food and consumer durables in China during 198 1-1987. The excess demand for nonstaple food would have a considerable pressure on food supply
for the state economy. Therefore, it would be beneficial if the distortions of
relative prices particularly in the housing and grain sectors are removed. In
particular, reforms by gradually eliminating grain and housing subsidies and
expanding a free market for grain and housing in urban areas would not only
depress the excess demand for these two categories of unrationed goods but
may also help to reduce inflationary pressure in China.
This study represents the first major attempt to estimate a complete demand system incorporating rationing in China. Since a dual market system
has become a common feature of Chinese economy, the estimated effects of
rationing obtained from our model are only approximations. A model for
RATIONING
CHINESE HOUSEHOLDS
25
analyzing consumer behavior under partial rationing in a mixed economy
would have been more appropriate. However, such a model requires separate household expenditure data on rationed and free market goods for estimation; these are not currently available.‘0
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