Australia's imports of clothing products (2) represent a small
proportion of world imports of such products. However, Australia's
share of world imports of clothing products increased from 0.66 per cent
in 1965 to 2.9 percent in 2007. China, India, Indonesia, Fiji and
Vietnam are among the major suppliers of Australia's imports of
clothing products. The volume of Australia's imports of clothing
products from the rest of the world, in real terms increased sharply
from around US$182 million in 1965 to US$ 2,819 million in 2007, which
represents an annual average increase of about 35 per cent from 1965 to
2007. Imports of clothing products contribute an insignificant share of
Australia's total merchandise imports. During the period 1965 to
2007, average share of clothing products in Australia's total
annual imports has varied between 0.6 per cent and 2.4 per cent. (3) The
reduction of tariffs and quotas on clothing imports and the reduced
effective assistance for domestic (import competing) manufacturing of
clothing, especially since the early 1990's, gain prominence among
the factors that have contributed to the increased imports of clothing
products (Havrila and Gunawardana, 2008). For example, the nominal rate
of assistance to Australia's clothing industries decreased from 90
per cent 1984-85 to 19 per cent in 2000-01, while the effective rate of
assistance declined form 243 per cent in 1984-85 to 34 per cent in
2000-01 (IC, 1997 and PC, 2003, cited in Havrila, 2004, p. 26). Despite
these trends in imports of clothing products and changes in policies
towards the clothing sector, there has been no recent study that
rigorously analyses the determinants of Australia's import demand
for clothing products. This paper aims to fill this gap in research by
developing and estimating a model of Australia's import demand for
clothing products from the rest of the world. In so doing, we attempt to
answer the questions: what are the major determinants of
Australia's import demand for clothing products and what are the
magnitudes of price and income elasticities of Australia's import
demand for clothing products.
The remainder of the paper is structured as follows. In Section 2
presents a review of literature on import demand. A model of
Australia's import demand for clothing is developed in Section 3.
In Section 4, data and data sources are discussed. Section 5 focuses on
the econometric procedure. Section 6 provides a discussion of results.
Section 6 presents the conclusion.
2. REVIEW OF LITERATURE
International economic theory suggests that if an importing country
accounts for an insignificant share of world imports a change in imports
by that country (a "small country") is unlikely to influence
the demand and price in the world market. A small country's import
demand for a product is the difference between its domestic quantities
demanded and supplied on the domestic market at the world price. (4) A
shift in the importing country's domestic demand (due to changes in
consumer income, price of substitutes, tastes) and/or domestic supply
(due to the factors such as changes in weather, price of alternative
products, technical change, R&D) will also shift the import demand.
However, limitations of data on domestic consumption and production, as
well as the difficulty of estimating domestic demand and supply
functions, constrain the application of this approach to derive the
import demand functions and price and income elasticities of import
demand for traded commodities.
Thus, the empirical approach has been the estimation of import
demand models directly, and then to derive the elasticities. Empirical
literature points to numerous studies that estimated the import demand
functions in many different countries, both developed and developing,
using different data and different econometric techniques and obtaining
various results.5 Houthakker and Magee (1969), Leamer and Stern (1970),
Goldstein and Khan (1985) and Gafar (1988)) emphasised that the demand
for imports is directly influenced by the level of domestic income and
international competitiveness, shown by the prices of imported goods
relative to the prices of domestically produced goods. Thus, in most
empirical work (such as Khan and Ross, 1977; Kravis and Lipsey, 1978;
Arize and Afifi, 1987; Boylan and Cuddy, 1987; Wilkinson, 1992;
Athukorala and Menon, 1995; Menon, 1995; Carone et al, 1996;
Bahmani-Oskooe and Niroomand, 1998) a general form of the import demand
is usually specified as:
[M.sub.it] = f([P.sup.m/[P.sup.d], Y) (1)
where, M is the quantity of imports, [P.sup.m] is the import price
index, [P.sup.d] is the domestic price index and Y is the consumer
Leamer and Stern (1970), and George et al. (1977) argued for the
inclusion of a variable representing the level of foreign exchange
reserve, or 'a proxy for the restraints on imports'.
Silvapulle and Phillips (1985) tested this proposition, however, the
variable was found insignificant in explaining import demand, or had the
'wrong' sign. Some other studies, including Miljkovic et al.
(2002) reported a significant effect of exchange rates on Japanese
import demand for U.S. beef and pork. Other studies found that the
effect of the exchange rate was greater on export elasticities than on
import elasticities (Kabir, 1988).
Since the late 1970s, some researchers have advocated a split-price
specification (inclusion of [P.sup.m] and [P.sup.d] separately) instead
of the price ratio (Murray and Ginman, 1976; Haynes and Stone, 1983;
Arize, 1987; Gafar, 1988; Koo, Uhm et al., 1991; Deyak, et al., 1993a;
Deyak, et al., 1993b; Carone, 1996). They argue that this form of
specification could be useful in analysing changes in foreign prices and
changes in the exchange rate or domestic trade barriers that would
affect the import price only. In this specification, the relationship
between imports and the respective variables can be expressed
symbolically as in Equation 2. The definitions of the variables are as
in Equation 1.
[M.sub.it] = f([P.sup.m], [P.sup.d], Y) (2)
Athukorala and Menon (1995) estimated import demand functions for
Australian total manufactured imports as well as for nine subdivisions.
To capture the cyclical effect on demand, Athukorala and Menon (1995)
and Menon (1995) used the ratio of stocks to average sales volume to
measure the general scarcity of domestic supplies. The relative price in
the model was specified as the ratio of the tariff augmented import
price and the price of the domestic competing commodity. An important
finding relevant to this paper is that whereas the long-run price
elasticity estimates for eight categories were in the range of -0.37 to
-2.10 (for total imports -0.67), the estimate for clothing and footwear
was not statistically different from zero.
A number of studies estimated the effect of trade liberalisation on
the import demand elasticities and found various results. With regard to
liberalisation, Melo and Vogt (1984) argue that an increase in the
degree of import liberalisation and a country economic development would
lead to higher income and price elasticities of import demand. Mah
(1999) found a low and insignificant income elasticity of import demand
for Thailand. Santos-Paulino and Thirlwall (2004) tested the impact of
trade liberalisation on both imports and exports for 22 developing
countries and found that the effect on import was greater than on
exports. Income elasticities increased equally for imports and exports,
however, the price elasticity of demand for imports was greater than for
exports. Lopez (2005) observed that trade liberalisation positively
affected import demand and the long-run income and price elasticities
for imports were also significant. Estimated elasticities of import
demand by Harb (2005) for forty developed and developing countries were
higher for developing than for developed countries. Mehta and Parikh
(2005) report an increase of price elasticities after trade
liberalisation. Dutta and Ahmed (2000) examined a long-run import demand
function for Bangladesh, using cointegration and error correction model
and observed a long-run relationship among the variables. They also
specified a dummy variable to account for import liberalisation
policies. However, the results do not provide evidence of the
effectiveness of liberalisation policies. Similar findings were obtained
by Dutta and Ahmed (2006) for India.
Wijeweera et al. (2008) estimated import price and income
elasticities for Bangladeshi bilateral trade on the basis of
disaggregated data. They found that real income is not a significant
determinant of imports, implying that imported goods and services from
included countries are necessities, rather than luxuries. Similar
results were reported by Rehman (2007) for the aggregate import demand
function for Pakistan. Ho (2004) estimated both aggregated and
disaggregated import demand functions for Macao and concludes that the
disaggregate model is more appropriate the import demand in the
long-run. The results indicate that different final demand components
have different effects on import demand behaviour. Agbola and Damoense
(2005) estimated import demand for pulses in India, and provide evidence
that the response of import demand for pulses to key determinants differ
substantially from product to product.
The study by Chiarlone (2000) focused on the estimation of sectoral
import demand for Italy with European Union, Japan, Canada and the
United States. Chiarlone attempted to include considerations of
horizontal and vertical product differentiation as well as homogenous
trade flows, using dummy variables. The findings indicate the strong
response of imports to relative prices and income. The dummy variables
for product differentiation suggest that imports perform differently
with respect to various levels of product differentiation.
Based on the above review of empirical studies, it can be concluded
that import demand is more sensitive to changes in real income than it
is to import price changes.
3. A MODEL OF AUSTRALIA'S IMPORT DEMAND FOR CLOTHING PRODUCTS
Following the theoretical insights and the review of empirical
studies, a model of Australia's imports for clothing is specified
MDC = f(RPC, YC, ERAC) (3)
MDC = Australia's real imports of clothing
RPC = the relative price of imports of clothing (the ratio of
import price of clothing to domestic price of clothing)
YC = Australia's real income represented by private final
consumption expenditure for clothing
ERAC = the effective rate of assistance for clothing
An inverse relationship is expected between the level of imports
and the relative prices of imports, RPC. It is expected that a rise in
the relative price of imports (import prices, relative to the domestic
prices) would result in a decrease in the quantity of imports demanded.
As imports become more expensive, consumers are likely to turn to
relatively cheaper domestically produced products. On the other hand, if
the domestic price of clothing relative to price of imports rises,
imports become relatively cheaper, leading to an increase in the demand
for imported products. A hypothesised positive relationship between the
variable representing income, YC (private final consumption expenditure
for clothing) and import demand is based on the assumption that imported
clothing products are normal goods. Thus, with rising incomes, consumers
are assumed to increase the quantity demanded of imported clothing.
Given historically high level of protection of the clothing industries
relative to other industries (except motor vehicles), and extensive
trade policy reforms in the 1990s, it was decided to include the average
effective rate of assistance, (ERAC), to the clothing industries as an
explanatory variable in the model. Other things being constant, an
increase in the rate of assistance (ERAC) to Australia's domestic
clothing industries leads to a reduction in imports. Therefore, a
negative relationship is expected between ERAC and imports of clothing.
4. DATA AND SOURCES OF DATA
Econometric estimation in this paper is based on annual time series
data for the period from 1970 to 2005, at the 2-digit SITC level of
aggregation. Clothing products are categorised as SITC 84. A more
detailed, three-digit level of disaggregation is: 841 Clothing not of
fur and 842 Clothing made of fur. While it would have been desirable to
estimate the models at a more disaggregated level within each category,
it was not possible to obtain the data for all relevant variables at a
disaggregated level. The data on imports of clothing were obtained from
the International Economic Data Bank (IEDB) maintained by the Australian
National University (ANU) and dxtime (Australian Bureau of Statistics,
Time Series Plus Statistics). The effective rates of assistance data
were provided by the Productivity Commission in Canberra. The real
income variable used here is private final consumption expenditure
deflated by the CPI for clothing, which also includes private final
consumption expenditure on footwear and drapery. The data on private
final consumption expenditure was obtained from dxtime (Australian
Bureau of Statistics, Time Series Plus Statistics).
5. ECONOMETRIC PROCEDURE
The import demand model was estimated using the 'general to
specific' approach, that is sometimes referred to as the Hendry
method or the unrestricted error correction method or UECM (see Hendry
and Mizon 1978; Mizon and Hendry 1980; Hendry and Richard 1982; Hendry
1995). This procedure avoids the need for testing for unit roots and
two-stage estimation of the model. The procedure has been applied
successfully in the empirical studies of Athukorala and Jayasuriya
(1994), Gunawardana et al. (1995), Menon (1995), Athukorala and
Rajapatirana (2000), Gunawardana and Vojvodic (2006) and Gunawardana,
Havrila and Khorchurklang (2008). This approach minimises the likelihood
of arriving at spurious regression estimations. The economic theory
motivation is that, in the same model
both short-run responses and long-run adjustment of importers to
changes in economic variables can be derived. It is particularly
superior for small samples, as is the case in this analysis. First, the
unrestricted equations are estimated using the OLS method. Taking into
consideration the regression diagnostics, a more specific (parsimonious)
model is gradually derived. Banerjee et al. (1993, p. 167) suggest that
'lagging' variables and including them as regressors often has
the same effect as providing a cointegrated set of regressor variables
and maintain that such a possibility is enhanced in a dynamic model as
the probability of a cointegrated set being present is increased.
Following Banerjee et al., the models were estimated with different lag
structures. In order to evaluate the appropriateness of the regression
results, a set of standard diagnostic tests was considered. These
include testing for residual serial correlation (Godfrey 1978),
normality (Jargue and Bera 1980; Bera and Jarque 1981) functional form
misspecification (Ramsey 1969), and heteroskedasticity (White, 1980).
The import demand model is estimated using log-log form due to the
advantage that the estimated slope coefficients can be used to directly
derive the elasticity values with respect to specified variables. The
following log-log model is specified initially for Australia's
import demand for clothing:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4)
[MDC.sub.t] = Australia's real imports of clothing.
[RPC.sub.t] = the relative price of imports of clothing (the ratio
of import price of clothing to domestic price of clothing).
[YC.sub.t] = private final consumption expenditure for clothing.
[ERAC.sub.t] = the effective rate of assistance to clothing
[[epsilon].sub.t] = error term
L = logarithm
t = the time period.
The hypothesised signs of parameter estimates can be symbolised as
follows: [[empty set].sub.1]<0, [[empty set].sub.2]>0, [[empty
The UECM model was empirically estimated as:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
where [Delta] is the first difference operator. The coefficients
for the variables with [Delta] show the short-run relationships and the
coefficients for the variables in level form indicate long run
relationships with import demand.
6. DISCUSSION OF ESTIMATION RESULTS
The estimation results from a 'parsimonious' version of
the model in Equation 5 are shown in Table 1. The initial OLS estimation
was found to entail heteroskedasticity, hence the results shown in Table
1 are based on White heteroskedasticity-consistent standard errors and
covariance. The findings show that, with the exception of the effective
rate of protection, the short-run relationships in the demand for
imports of clothing are statistically significant. However, the long-run
relationships as well as the dynamic factor represented by the lagged
dependent variable are statistically significant. Signs of the estimated
coefficients are in accordance with theoretical expectations. The
derived values of the long-run elasticities are indicative of an
inelastic import demand for clothing with respect to relative price and
effective rate of assistance. Respective absolute values of elasticities
are 0.41 and 0.22. In contrast to the relative price and the effective
rate of assistance, import demand for clothing appears to be highly
responsive to changes in income represented by final consumption
expenditure. With a positive and greater than one (2.58) coefficient of
the long-run income elasticity, imported clothing can be classified as a
luxury good. One percent change in income is likely to result in 2.58
percent change in import demand for clothing. The results indicate that
the adjustment period of import demand to changes in relative price and
effective rate of assistance is around two years, whereas the adjustment
period of import demand to changes in income is about one year.
LMS --Lagrange multiplier test for serial correlation.
RESET --Ramsey's test for functional from misspecification.
JBN --Jarques-Bera test for the normality of residuals (based on
the [chi square] distribution).
HSC --Heteroscedasticity test based on the regression of squared
residuals on squared fitted values.
We now compare and contrast our findings with those of some of the
previous empirical studies of import demand. Houthakker and Magee (1969)
estimated the price and income elasticities of import demand for the
United States by country of origin and by commodity class (for 5 major
commodity classes). The results indicate generally higher income and
price elasticity estimates for the United States imports. The price and
income elasticities of import demand from Australia were -4.69 and 2.23
respectively. In comparison with the results in this study, while the
price elasticity coefficient is distinctly higher, the income elasticity
is rather close. The results in this study support the findings by
Wilkinson (1992) who concludes that imports are more responsive to
changes in economic activities than to the variation in relative prices.
The long-run elasticity estimates (for Australia's aggregate
imports) derived by Wilkinson are 1.9 with respect to economic activity
and 0.5 with respect to relative price. O'Regan and Wilkinson
(1997) derived the long-run price elasticity of import demand for
clothing of 0.81, that is, relatively higher than the estimate in this
study (0.41). Athukorala and Menon (1995) found that the long-run price
elasticity estimates for the combined clothing and footwear category was
not statistically different from zero. With regard to activity variable,
Athukorala and Menon derived a unit long-run elasticity (1) for
clothing. Menon (1995) examined the relationship between manufactured
imports to Australia and relative prices and domestic economic activity
over the period 1981 and 1992, based on quarterly data. The price
elasticity estimates for individual categories ranged from 0.24 to 1.75,
with almost two thirds of price elasticities of less than 1 and the
remainder between 1 and 2. The relative price elasticity for total
manufactured imports was estimated at 0.66. With respect to the activity
elasticities, Menon found that most of the estimates were between 1 and
2. The activity elasticity for total imports was 1.87. The import demand
for the category of textiles was found inelastic with respect to both
price and activity variable. The respective elasticity estimates were
-0.24 and 0.33. The import demand for apparel and clothing accessories
was found unitary elastic with respect to price, and inelastic with
respect to the activity variable (0.64). Thus, Menon's estimates
for clothing differ rather significantly from the findings in our study.
The purpose of this paper was to identify the significant factors
that determine Australia's import demand for clothing products and
to estimate the elasticities of import demand. The model estimated and
the hypotheses tested in this paper were developed on the basis of
economic theory and previous empirical studies. The 'general to
specific' unrestricted error correction modelling procedure was
applied to estimate the short run relationships and long-run
elasticities of import demand with respect to the specified variables.
Prior to deriving a 'parsimonious' version of the model, the
outcomes of the preliminary regressions and associated diagnostic tests
were taken into account and the empirical models were re-specified
accordingly. The findings of this study are expected to serve as an
important indicator to retailers of how the demand at retail for
imported clothing may change if various factors influencing the import
demand vary. According to the results, Australia's import demand
for clothing appears to be highly responsive to changes in
Australia's income. The value of the long-run elasticity of income
reveals that one percent increase in Australia's income is likely
to result in 2.58 percent increase of Australia's import demand for
clothing. However, the import demand for clothing is inelastic with
respect to the relative price and the effective rate of assistance, both
elasticities being less than one.
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Inka Havrila, Victoria University, Melbourne, Victoria, AUSTRALIA
Pemasiri J. Gunawardana, Victoria University, Melbourne, Victoria,
(1.) Some parts of this paper are derived from Havrila (2004).
(2.) Standard International Trade Classification (SITC) Category
84, Articles of Apparel and Clothing Accessories.
(3.) In this section, trade data for 1965 are from NAPES ANU
Database, while the trade data for 2007 are from World Trade
Organisation, International Trade Statistics, 2008.
(4.) A detailed derivation of import demand functions and
elasticities of import demand can be found in Kreinin (2002, Chapter 4,
Dr. Inka Havrila earned her Ph.D. from Victoria University,
Melbourne, Australia in 2004. Currently, she is a senior lecturer in
economics at the school of economics and finance and a research
associate of the centre of strategic economic studies, Victoria
University, Melbourne, Australia.
Dr. Pemasiri J. Gunawardana earned his Ph.D. from Latrobe
University, Melbourne, Australia in 1988. Currently he is a senior
lecturer in economics at the school of economics and finance and a
research associate of the centre of strategic economic studies, Victoria
University, Melbourne, Australia.
PARSIMONIOUS ESTIMATES OF IMPORT DEMAND MODEL FOR CLOTHING
(BASED ON WHITE HETEROSKEDASTICITY-CONSISTENT STANDARD ERRORS
Dependent variable = [[Delta]MDC.sub.t]
Regresssor Coefficient t-ratio Long-run t-ratio
Constant 1.93 1.20 - -
[[Delta]LRPC.sub.t] -0.43 -4.67 *** - -
[[Delta]LYC.sub.t] 1.02 1.82 * - -
[[Delta]LERAC.sub.t] -0.10 -0.56 - -
[LM DC.sub.(t-1)] -0.46 -3.37 *** - -
[LRPC.sub.(t-2)] -0.19 -2.54 ** -0.41 -1.31
[LYC.sub.(t-2)] 1.19 3.53 *** 2.58 5.04 ***
[LERAC.sub.(t-2)] -0.10 -2.83 *** -0.22 -2,04 ***
[R.sup.2] = 0.56 Adj. [R.sup.2] = 0.45 F = 4.17 *** DW = 1.91
AIC = -0.75 LL = 20.76 SBC = -0.39
LMS [F.sub.(1,25)] = 0.001 RESET [F.sub.(1,25)] = 0.0.032
JBN, [chi square](2) = 11.714 [HSC.sub.(1,32)] = 3.31
*** significant at the 1 % level; ** significant at the 5% level;
* significant at the 10% level.