Export-Output Causality and the Role of Exports
in Irish Growth: 1950-1997
Eleanor Doyle*
Department of Economics, University College Cork, Cork, Ireland
(address for correspondence)
and
Department of Economics, University of Birmingham, Edgbaston, B15 2TT.
Email: [email protected]
Abstract:
Sources of Irish growth are examined using the Granger causality
procedure recently developed by Toda and Yamamoto (1995) with
particular focus on the role of Irish exports. An augmented production
function is employed where the inclusion of variables in addition to
exports ensures that different impacts on exports and output are
controlled for and thus, a more accurate testing of the export-led-growth
hypothesis is possible. The most important sources of Irish growth are
identified as the terms of trade and demand in industrial countries i.e.
external sources. Bi-directional causality is found for exports and output
implying a virtuous circle of growth and exports.
[JEL F1 F4]
*The author is grateful for helpful comments and discussions with Peter Sinclair and
Nicholas Horsewood at the University of Birmingham. Any remaining errors are the
sole responsibility of the author. Financial support from the Arts Faculty Research
Fund under grant number R360/01 is gratefully acknowledged.
Export-Output Causality and the Role of Exports
in Irish Growth: 1950-1997
I. Introduction
Ireland has experienced growth rates far exceeding its European neighbours or
other developed countries in the 1990s, hence its description as the ‘Celtic Tiger’.1
Average GDP (GNP) growth over the four years to 1997 was 8.4% while the
European average was 2.3% (7.5%).
However, the reasons behind Ireland’s
phenomenal growth performance are far from clear. This study considers the role
played by trade, and exports in particular, to assess its importance in Irish growth.
The nature of the relationship between exports and economic growth is
ongoing, with various explanations propounded as to the importance of trade in
economic performance. As countries open up to trade, international communication
of ideas and technology becomes increasingly possible. This may have the effect of
intensifying competition, increasing the incentive for both imitation and innovation
and accelerating the rate of technical progress that can lead to efficiency gains
through more competitive cost structures and productivity improvement. Foreign
exchange constraints may be eased also since increased exports provide a source of
foreign exchange for countries that wish to purchase imports of final products or
inputs that embody domestically unavailable technology. Under the scenario where
increased exports lead to cost reductions and increased efficiency the underlying
causal direction is from export growth to output growth.
New trade theory has also contributed to the theoretical relationship between
exports and growth regarding effects on technical efficiency. Romer (1990),
Grossman and Helpman (1991) and Rivera-Batiz and Romer (1991) have developed
models where an expansion of international trade increases growth by increasing the
number of specialized production inputs. In models of imperfect competition and
increasing returns to scale, however, this outcome is ambiguous (Helpman and
Krugman, 1985) and indeed Grossman and Helpman (1991) also pointed out that
tariffs could be growth reducing. The impact of trade appears to depend on market
1
Morgan Stanley Dean Witter originally coined this term in August 1994.
1
competition, market contestability and whether the market structure is stable with
regard to trade disturbances or will be altered and lead to productivity improvements
and technical efficiency. Bidirectional causality is a possibility when productivity
increases that are made through the exploitation of scale economies lead to increased
exports (Kunst and Marin, 1989).
This occurs if the market structure changes
(brought about by increased trade) result in fewer firms and if scale economies allow
for increased competitiveness through further cost reductions. Hence a potential
feedback effect exists between export growth and output (Sharma et al, 1991).
Bhagwati (1988b) also considered the possibility for two-way causation between
growth and exports (or trade in general) arguing that increased trade, regardless of its
cause, stimulated increased output and in turn additional income facilitated more
trade, generating a process of a virtuous circle of growth and trade.
Marin (1992) included models of imperfect competition in his analysis of the
exports-output relationship and posited that exports lead to output growth (through
productivity enhancement) the smaller the country and the less entry that occurs. He
based this view on the fact that minimum efficient scale of production is large relative
to the home market so that the potential of exploitation of scale economies through
export expansion was high.
An export expansion is more likely to lead to
productivity improvements if the entry of new firms instigates greater competition
forcing inefficient firms to exit and increasing the incentive for incumbents to invest
in R&D.
The potential benefits of export growth for economic development have been
widely discussed (e.g. Keesing, 1967; Krueger, 1980; Bhagwati, 1988a; Greenaway
and Sapsford, 1994) and empirically tested for many less developed countries,
(Balassa, 1978; Feder, 1982; Bahmani-Oskooee and Alse, 1993). However, for more
industrialized or developed economies the potential benefits of export growth may be
less important because positive externalities enjoyed by LDCs are significantly higher
than for developed countries, whose infrastructural development is more advanced
(Afxentiou and Serletis, 1991). Benefits from increased competition are lessened
since advanced countries are more competitive and new technology will have less
impact because to retain competitiveness, continuous improvements in technology are
required. Such reasoning may provide some explanation for the principal focus of
recent export-output studies on LDCs.
2
Another causal explanation is manifest in Verdoorn's law which holds that
output growth has a positive impact on productivity growth. Kaldor (1967) attributed
this relationship to factors including economies of scale, learning curve effects,
increased division of labour, and the creation of new processes and subsidiary
industries. In this case productivity growth in the industrial sector is considered as the
principal determinant of output growth. Improved productivity and reductions in unit
costs make "it easier to sell abroad" (Kaldor, 1967: 42) implying a causal relationship
from output growth, via productivity growth, to export growth.
Empirical research mirrors the contradictory causality theories. The main
objective of this paper is to estimate if a causal relationship exists between Irish
exports and output, and in what direction. Recent econometric methods are employed
which generate improved test statistics in the causality test procedure. Since bias
might be introduced by focusing solely on output and exports, a number of additional
variables which potentially explain Irish growth are included in the analysis. The
results contribute to the ongoing debate on the direction of causality between output
and exports and on the wider debate relating to the causes of the variation in growth
rates between countries while also providing particular insight into the sources of
Ireland’s growth experience.
II. The Irish Dimension
Ireland represents an interesting application for the investigation of the nature
of causality, given its status as a small open economy (where exports in 1996
represented 76% of GDP in constant prices) and the path that Irish industrial and trade
policies have followed in recent decades. Unlike other larger economies, Ireland's
industrial and trade policies have largely been in tandem since the late 1950s.
Beginning in the mid 1950s the Irish government perceived that Irish industrialization
had reached a natural limit given the resources and size of the country.
The
publication of Economic Development in 1958 was the first unified policy
programme which laid out the policies deemed necessary for economic growth.
Further industrialization could only be ensured through targeting export markets,
which entailed a reorientation of the Irish development strategy away from a highly
protectionist import substitution policy to an export-oriented trade policy with foreign
3
direct investment (FDI) playing a central role (O'Sullivan, 1993). The aim of the
export-oriented trade policy was
to use imported private capital and technology to establish an extensive and
sophisticated industrial base, having a high export to sales ratio (to minimize
competition for domestic market shares with local firms), which would absorb some
of the surplus labour, reduce emigration, utilize natural resources more efficiently,
augment capital formation, stimulate economic growth, diversify merchandise exports
.….. to provide the impetus for the transformation of the Irish economy from its
excessive reliance on the agriculture … sector to a more vigorous and expanding
industrial base (O’Sullivan, 1993: 140).
Irish industrialization was late relative to other industrialized countries and the
reorientation away from primary products towards manufactures became apparent
only from the 1960s onwards. Industrial and trade policies were inextricably linked
as a result, as the focus switched from traditional exports from the agriculture sector
to exports from the industrializing sector. The extent of the reorientation is evident in
the decline in the share of agricultural exports in total Irish exports from 30% in 1960
to 2% by 1990 and the shift in the share of manufacturing exports from 30% to 69%
over the same period. Coupled with the changing composition of Irish exports was
the increasing importance of exports as a share of Irish output, increasing from 32%
of Irish GDP in 1960 to 68% in 1993.
Foreign Owned Industry’s Role in Irish Growth
Any discussion of the Irish export-output relationship should not ignore the
role of foreign-owned industry whose presence is most readily identified with the
high-technology industries of pharmaceuticals, office and data processing, electrical
engineering and instrumental engineering. Gross value added of the high-technology
sector as a percentage of total manufacturing output increased from 20% in 1980 to
39% by 1990 when it represented 58% of the net output of all overseas industry
(NESC, 1993). The high-technology sector is highly export-oriented and enjoys
higher export shares and levels of productivity - computed as net output per head compared to indigenous Irish industry.
However, aggregate figures on the strong economic performance reveal
important factors that matter in the relationship between Irish exports and output.
For example, a lack of linkages would mean that much of the growth in output and
productivity observed in foreign-owned industry stems not from any improvements in
Irish technology, marketing or other skills but from the expertise of associated firms
4
located elsewhere. Some research points to the lack of significant linkages between
overseas and domestic firms, for example
growth of foreign industries generally contributes proportionately less to the economy
than growth of indigenous industry (O’Malley, 1989: 179).
This view may seem valid given that imported inputs constituted 66% of gross output
for foreign-owned firms and 22% for indigenous firms (based on 1993 data in Barry
and Bradley, 1997). Interestingly, however, O’Malley (1995) employed a measure of
backward linkages per job2 and found that they were higher for foreign owned than
domestic industry. In addition, linkages in the foreign owned enterprises increased
over time while those in indigenous industry were in decline.
However, R&D expenditure in Irish subsidiaries is significantly lower than in
other comparable economies and the proportion of skilled workers compares
unfavourably with other more developed countries (Hitchens and Birnie, 1994). This
implies that the contribution of the foreign-owned sector in terms of spillovers into
the indigenous sector is less than what it could potentially be, limiting the
performance of the manufacturing sector generally and reducing the potential impact
of such an export-driven sector on the Irish economy. In addition, the financial
conduct of foreign-owned industry, evident in high and growing amounts of
repatriated profits, dividends and royalty payments, is indicative of their indifference
to improving the learning process in Irish subsidiaries (O'Sullivan, 1995). The strong
productivity performance of the foreign-owned sector (relative to Irish indigenous
industries and relative to advanced industrial countries) may reflect the success of low
rates of Irish corporation tax in attracting foreign direct investment into Ireland rather
than improvements in the productivity of the industries themselves.
Transfer pricing by multinational companies whereby artificially low prices on
inputs brought into Ireland and high output prices on exports from Ireland are
recorded, provides the opportunity to take advantage of the incentive to pay as much
tax on profits as possible in Ireland, where tax rates are lower.3 The extent to which
2
Rodriguez-Clare (1996) considered this the appropriate measure of linkage effects in multinational
firms.
3
A corporate tax rate of 10 % applies to the manufacturing sector (and will continue to apply until
2010). In 1990 this rate was extended to companies operating in the Irish Financial Services Centre
and the Shannon Zone until 2005.
5
transfer pricing is practised means that output measures are artificially inflated and
overstate the extent of productivity improvements.
Given the explicit Irish policy of encouraging foreign direct investment, and
the high share of Irish manufactured output produced by foreign-owned firms, it was
hoped to include FDI as an additional explanatory variable for Irish growth. Sachs
(1997) indicates three main channels i.e. technology transfer, increased investment
funds and additional marketing channels through which FDI can enhance output from
the perspective of the host country. Unfortunately, however, discussions with the
Irish Central Statistics Office, the Central Bank of Ireland, and the agency charged
with attracting Irish FDI (the Industrial Development Authority) revealed that no data
are available prior to 1958 and subsequent figures are not reliable. Lane and MilesiFerreti (1999) also point out that estimates of Irish FDI flows are undervalued and
should be corrected for real exchange rate shifts, inflation in the price of capital goods
and revaluation to take account of the replacement cost of capital of existing stocks.
They have undertaken such adjustment for FDI for the period 1976 to 1997 although
they focus on net figures (inflows less outflows) rather than inflows alone which
would be relevant in this research.
III. Evidence of the Export-Output Relationship
Many early studies of the links between exports and growth confirm a
statistical relationship between export growth and output growth, (Michaely, 1977;
Krueger, 1978; Balassa, 1978; and Feder, 1982).
The export-growth correlation
appeared to be particularly pronounced in the case of industrialized countries and
Michaely (1977) and Tyler (1981) considered a minimum level of development was
required for a significant relationship to be observed between output growth and
export growth. However, the empirical approach based on cross-country correlations
between exports and output (or productivity) yields no information for the causality
question as they deal with statistical and not causal relationships.
Studies that used Granger or Sims procedures to investigate causality do not
provide conclusive support for the export-growth relationship. Chow (1987) used the
Sims procedure to examine the causal relationship between export growth and output
growth for manufacturing industries and found bi-directional causality for Hong
Kong, Israel, Singapore, Taiwan and Brazil, uni-directional causality from export to
6
output growth for Mexico and no causality for Argentina. By comparison, Jung and
Marshall (1985) who used the technique of Granger causality tests found support for
the export-led growth hypothesis for just four out of thirty-seven developing countries
considered.4,5 A statistically significant relationship from output growth to export
growth was found for three countries. Six countries exhibited evidence of an exportreducing growth relationship, while a further three supported a growth-reducing
exports relationship.
More recent research has indicated that the existence of non-stationarity in the
time series considered can lead to spurious regression results and invalidate the
conclusions reached using Granger tests of causality. This casts doubt on the results
of the causality research carried out when the stationarity properties of the data were
not identified. Furthermore, it is only possible to infer a causal long-run relationship
between non-stationary time series when the variables concerned are cointegrated (on
cointegration see Engle and Granger, 1987).6 If cointegration analysis is omitted,
causality tests present evidence of simultaneous correlations rather than causal
relations between variables. As Ram (1985) points out
it is … important to be able to make a reasonably satisfactory transition from
statements about the correlation patterns to some judgements about the causal
structure (p. 416).
Axfentiou and Serletis (1991) tested real exports and GNP data (1950-1985)
for cointegration in their examination of export-output causality for sixteen developed
countries, including Ireland.
They concluded that exports and GNP did not
cointegrate, except in the cases of Norway, Iceland and the Netherlands. They found
evidence of bi-directional causality for the U.S., GNP to export causality for Norway,
Canada and Japan and no other significant causality results.
Granger (1988) has explained that for cointegrated time series, standard
Granger or Sims tests may provide invalid causal information due to the omission of
the error-correction terms from the tests. If the error-correction term is excluded from
causality tests when the series are cointegrated, no causation may be detected when it
4
Aggregate export and output data for Taiwan, Brazil and Mexico are included in Jung and Marshall's
analysis and provide no evidence of a causal relationship, despite Chow's findings at the level of
manufacturing industries. Neither Jung and Marshall nor Chow find a causal relationship for Argentina.
5
Darrat (1986) and Hsiao (1987) find a similar lack of support for the export-led growth hypothesis.
6
Granger tests of short-run causality can still be undertaken when series are not cointegrated.
7
exists i.e. when the coefficient on the error-correction term is statistically significant.
Hence, the use of error-correction modelling provides an additional channel through
which causality in the Granger sense may be assessed.
Research that incorporates cointegration and error-correction analysis yields
interesting results. Marin (1992) found that exports of manufactured goods Grangercause productivity (manufactured output per employee) for the developed economies
of the United Kingdom, Germany, the United States and Japan. These findings
contrast with those of Afxentiou and Serletis (1991), (who used aggregate data), in
each case apart from the United States. In a study using Portuguese data, Oxley
(1993) found evidence that output growth caused export growth.
Using similar
techniques of cointegration and error-correction modelling, Bahmani-Oskooee and
Alse (1993) found support for a bi-directional relationship between export growth and
output growth in the case of eight less developed countries.
In testing the export-led-growth hypothesis, it is inadequate to include output
and exports variables alone in a causality framework because omitted variables not
controlled for will also have impacts on output and exports, and hence, measured
causal impacts are inaccurate (Kwan and Kwok, 1995).
Ghartey (1993:1146)
includes the terms of trade (or capital stock) as an explanatory variable in a trivariate
model with exports and output for the Japanese economy in an attempt to “resolve any
occurrence of bidirectional causation” that could arise due to omitted variable bias.
Having found a feedback relationship between exports and output, the terms of trade
was included but did not have any explanatory power in the model. The terms of
trade was then replaced with a capital variable which provided no further
improvement. Bivariate analysis of the four variables of output, exports, terms of
trade and capital showed that terms of trade caused exports and no other causal
relationships were found.
Henriques and Sadorsky (1996) explained that the output/exports relationship
was complex because of the influence of (among other reasons) price fluctuations and
political intervention. Hence, inclusion of the terms of trade in causality analysis was
used to control for such factors. They focused on the ELG hypothesis for Canada
from 1877 to 1991. Using a VAR framework they found that the three variables of
interest were cointegrated. Their Granger causality tests suggested that the growthled exports hypothesis could not be rejected. They considered that this was
8
in accord with the development of a small open economy, since a small economy
developing efficiently in line with its comparative advantage will specialize and
hence turn to foreign markets for exports of goods that use its most abundant factor of
production most intensively (Henriques and Sadorsky, 1996: 552).
This view contrasts with Marin’s opinion that exports should lead to output growth
particularly for smaller countries due to the possibility of exploiting scale economies
through export expansion.
New growth theory provides indications of how standard production functions
can be augmented to include additional factors that may help in explaining growth
experience. For example, Jin and Yu (1996) constructed a six variable VAR in their
analysis of the ELG hypothesis for the United States. They found that no significant
causal relationships existed.
Further advances in the techniques used to examine the export-growth
relationship is evident in recent research by Shan and Tian (1998) who adopt the
methodology of Toda and Yamamoto (1995) and Zapata and Rambaldi (1997) in their
causality analysis.
Developments in econometrics have revealed that the F-test
procedure traditionally used for causality tests is not valid (i.e. it does not have a
standard distribution) if time series are I(1) first difference stationary, a feature shared
by a large proportion of macroeconomic variables (Enders, 1995: Gujarati, (1995);
Toda and Yamamoto, 1995; Zapata and Rambaldi, 1997).
Taking these developments into account, and using an improved methodology,
Shan and Tian (1998) employ a six variable VAR and find that for Shanghai internal
factors such as foreign direct investment, labour and investment contributed to rapid
output growth and that output growth contributed to export growth over the period
1990 to 1996. Shan and Sun (1998) also adopt the approach to analyse the export-led
growth hypothesis for China from 1987-1996. Using a six-variable VAR they found a
feedback effect indicating bidirectional causality between exports and real industrial
output (a proxy measure of output). The same methodology is used in this study and
is discussed in Sections IV and V.
IV. Granger Causality
The Granger approach to causality is based on the premise that predictability
is analogous with causality and that the relationship between cause and effect is
temporally such that an effect cannot arise before its cause. A time series X is said to
9
Granger-cause another series Y if the inclusion of lagged values of X improve the
forecast of Y (evident in a smaller mean square error) compared to the forecast
derived from the use of lags of Y alone. Here, exports are said to cause output with
respect to given information (including exports and output), if the prediction of output
is improved by using past values of exports, given that the relevant information is
totally contained in the present and past values of these variables. The rationale is
similar to test for causality from output to exports.
The simplest approach to test for a short-term causality relationship between
output and exports is to run two-way Granger-causality tests. As indicated above,
given economic theory on causality between exports and output there is no a priori
reason to exclude any one of the causal directions. The standard Granger-causality
test analyses bivariate weakly stationary stochastic processes. If the original series
are non-stationary they must be transformed into stationary variables which is carried
out by differencing the variables until they are stationary.
Since the data are
transformed to be stationary variables, it is possible that the causality structure may be
affected (Geweke, 1984). By differencing the data, any information about the long-run
relationship between the trend components of the original series is removed so that the
Granger-causality tests describe only short-run relationships between exports and output.
It is possible, however, that additional long-run relationships exist between the
variables. Standard Granger-causality tests augmented with error-correction terms
derived from the long-run cointegrating relationships can be used to assess the longterm effects. Such tests are undertaken on I(0) stationary variables to ensure that
valid inferences may be made from the tests (Engle and Granger, 1987).
Including the error-correction terms in the equations offers an extra channel
through which causality may be observed.
The error correction coefficients are
expected to capture the adjustments of ∆Xt and ∆Yt to their long-run equilibria, while
the coefficients on lagged exports and output are expected to capture the short-run
dynamics of the models (Jones and Joulfaian, 1991). Interestingly, in contrast to the
standard Granger test, the error-correction model allows for the finding that output
Granger causes exports once the coefficient on the relevant error-correction term is
significant and even if the coefficients on lagged exports are not significant.
10
This approach can be extended to include additional variables. Use of the
cointegration and error-correction approach becomes more elaborate and complex as
the number of cointegrating vectors may increase in line with an increase in the
number of variables used in analysis. Shan and Sun (1998) explain that when more
than two cointegration vectors are identified, the identification of the parameters
associated with causality is not “practically simple”. Thus the approach presented in
the following section offers an alternative that is more straightforward to employ and
yet produces robust results.
V. Augmented Production Function
To employ the causality approach of Toda and Yamamoto (1995) a VAR is
estimated based on an augmented production function:
Output = f (exports, imports, labour, capital, terms of trade, industrial countries’ GDP)
i.e. Y = f (X, M, L, K, ToT, YIC)
where:
•
•
•
•
•
•
•
Output is measured as real Irish GDP
Labour is total Irish employment
Capital is real gross fixed capital formation (real values are computed
based on the GDP deflator). (This measure of capital is used as no capital
stock series is available for Ireland).
Exports are real exports (computed using export unit values)
Imports are real imports (computed using import unit values)
The terms of trade variable is computed as the Irish export unit value index
divided by the import unit value index
Industrial countries’ GDP is the real value in Irish pounds of GDP of the
industrial countries (as defined by the IMF).
Data are taken from the International Financial Statistics produced by the IMF
for all variables except labour which is taken from the Review and Outlook published
by the Stationery Office of the Irish Government. The period analysed is from 1950
to 1997 and all monetary values are expressed in real Irish pounds (1990 prices). In
the empirical estimation all variables are in natural logarithms.
With regard to the selected variables in the production function, if the VAR
does not include all relevant variables the estimated causal relations will be
inaccurate. However, as in all empirical analysis the inclusion of all available and
relevant variables could lead to insufficient degrees of freedom for estimation. The
11
trade-off between these two issues gave rise to chosen variables which are considered
to be the most important explanatory variables in the context of Irish growth.
Based on Reizman et. al. (1996) imports are controlled for to avoid a spurious
causal relationship. The expansion of the export sector can itself directly accelerate
economic growth or give rise to the accumulation of foreign exchange that can be
spent on importing goods or services which has the effect of expanding a country’s
production possibilities, thus increasing income.
Regardless of the cause, both
sources of growth are described as export-led but the latter case has been identified as
the two-gap hypothesis (McKinnon, 1964; Findlay, 1973). Hence, for export-led
growth to occur, it is theoretically possible that unidirectional causality exists between
exports and output (income) or that there is a causal mechanism from exports to
imports to output (income).
Industrial countries’ GDP is included to take account of the effects of foreign
output shocks on Irish output. For Ireland this is particularly relevant as Barry and
Bradley explain:
The existence of FDI flows means that the supply sides of SOEs like Ireland are
closely integrated into the global economy, providing new and rather simpler
channels for the transmission of international shocks (1997: 1808).
Similarly, the terms of trade are particularly important for a small open economy such
as Ireland which is susceptible to changes in world prices.
Thus, foreign output and the terms of trade variables are linked to export
expansion while capital and labour variables are linked to output growth.
The
selection of these variables is hoped to provide the framework for a more accurate
testing of the exports-output relationship.
Sources of Growth: Geographical and Product-based Measures
As an extension to the causality tests based on aggregate exports and imports
an examination of Irish growth is conducted using Ireland’s main trading partners to
consider the extent to which Irish growth may be explained by its trade with particular
countries or regions. The focus is on the United Kingdom, Europe and the United
States which were Ireland’s main trading partners over the period from 1950 to 1997.
Their combined exports amounted to 84% (on average) of total Irish exports while the
corresponding figure for imports was 75%.
12
A further investigation of Irish growth based on trade in particular products is
carried out to consider if growth is explained by particular sectors e.g. manufacturing
(consisting of SITC Sections 5-8) and for each SITC Section 0 to 9.
Endogenous or Exogenous Independent Variables?
In the growth-accounting literature it is generally presumed that labour and
capital are exogenous sources of growth. This assumption is not necessarily correct
however (Sharma et al., 1991). The accelerator theory of investment proposes that
investment depends on the rate of output growth (or its lag) implying an opposite
relation. According to the Keynesian view of growth, bidirectional causality between
the variables has also been hypothesized where changes in the level of investment can
have a feedback effect on output through the multiplier process (Samuelson, 1939).
Modern economists would generally not support Malthus’s view that increases
in per capita income would lead to population growth (with a long lag) and prevent
improvements in the standard of living. Both population and labour force can be
considered as endogenous variables, however, and the nature of the relationship
between labour force and income is an empirical question. While this relationship is
not the focus of this research it is relevant because we cannot rule out a priori that
output growth causes labour force growth.
For imports, it is plausible that output growth can lead to increased imports
depending on a country’s income elasticity of imports. Since some imports are
required as intermediate inputs, particularly by small countries, and furthermore since
some imports embody technology (providing one channel for the international
diffusion of innovation), there is clearly reason also to consider an alternative causal
relationship from imports to output. On the basis that
imports may play the role of a confounding variable in causal ordering (i.e., imports
affect both income and exports) …. Failure to account for imports can … produce
misleading results (Reizman et al, 1996: 90).
the role of imports in economic growth is explicitly accounted for in the analysis here.
By omitting imports spurious rejection or non-rejection of the export-led growth
hypothesis is possible.
Given Ireland’s status as a small open economy it is difficult to envisage how
changes in Irish output might impinge on industrial countries’ GDP either directly or
13
indirectly. In the light of these issues, it is important to consider the endogenous
nature of the variables in the system before making causal inferences.
The Rybczynski Theorem
Although this study is directly concerned with the ELG hypothesis, the
assembled data can also provide the basis for considering a corollary of the
neoclassical Heckscher-Ohlin trade model – the Rybczynski theorem. This states
that, given constant prices, an increase in the supply of one productive factor leads to
an increase in the output of the product which uses that factor intensively. It is of
interest here because it provides a theoretical basis for relationships between
productive factors and exports. In the case where a country’s export sector were
capital intensive compared to the import-substitute sector, any increase in the supply
of capital (ceteris paribus) will cause an increase in exports and a decline in the
output of import substitutes. If the export sector were labour intensive, growth of the
capital stock would cause the export sector to contract and the import-substitute sector
to expand. Hence the factor intensity of the export sector in relation to the import
sector is the significant explanatory factor behind either a positive or negative
relationship between labour or capital growth and the export sector. To examine if
the Irish data are compatible with this hypothesis we can conjecture that both labour
and capital should not cause exports: no support for the Rybczynski theorem exists if
this conjecture is incorrect.
Granger Causality in a VAR Framework
The approach used here was introduced by Toda and Yamamoto (1995) and
extended by Zapata and Rambaldi (1997). In the context of VAR models the null
hypothesis of no causality is formulated as a set of zero restrictions on the coefficients
of the lags of a subset of the variables. However, the usual F-test statistic for Granger
non-causality based on estimation in levels has a non-standard asymptotic distribution
and depends on nuisance parameters if the process is I(1) (Sims, Stock and Watson,
1990). Methods to deal with Granger causality in I(1) systems have been developed
by Mosconi and Giannini (1992) and Toda and Phillips (1993) but they have involved
pretesting for cointegration ranks and “are not simple to implement” (Toda and
Yamamoto, 1995).
For cointegrated systems, an error correction model can be
transformed to its levels VAR form permitting a Wald type test for linear restrictions
14
on the resulting VAR model (Lutkepohl and Reimers, 1992, Toda and Phillips, 1993)
or alternatively a likelihood ratio test can be used (Mosconi and Giannini, 1992).
Toda and Yamamoto (1995) propose a method of testing for Granger causality
which is applicable whether the VAR process is stationary, integrated (of an arbitrary
order) or cointegrated (of an arbitrary order) with no need to address the cointegration
properties of the time series (a similar procedure is found in Dolado and Lutkepohl
(1996)). The method involves using a modified Wald test (denoted MWald) for
restrictions on the parameters of a VAR(k) (where k is the lag length in the system).
The test has an asymptotic χ2 distribution when a VAR(k + dmax) is estimated where
dmax is the maximum order of integration that occurs in the system. The test can be
carried out without any information on the cointegration properties of the system and
the test may be applied when no cointegration exists and/or the stability and rank
conditions are not satisfied. Rambaldi and Doran (1996) have proved that the method
can be applied by using a seemingly unrelated regression (SUR) form and they set out
the method clearly with the appropriate programme input for a range of alternative
econometrics packages.
To employ the method each variable is regressed on every other variable
lagged from one to k+dmax lags in a SUR system, and the restriction that particular
variables of interest are equal to zero is tested. Furthermore, since the variables
themselves are used and not their first-differences, all information contained in the
variables is used in assessing causality.
The VAR model considered here consists of seven variables. To test the
hypothesis of no Granger causality from exports to GDP amounts to testing if the all
of the coefficients on lagged exports are equal to zero. If the hypothesis cannot be
rejected, based on the significance of the MWald statistic for the group of lagged
export variables, Granger causality does not exist from exports to growth. Similarly,
testing for causality from growth to exports can be conducted (or for the other
variables in the system).
VI. Results
Results of ADF tests are presented below and indicate that the null hypothesis
of a unit root cannot be rejected for the levels of the variables. By comparison results
15
for the first differences reject the hypothesis of a unit root implying that the variables
are first difference stationary.
[Insert Table 1 about here]
The tests of Granger causality were carried out using a seven variable VAR.
The choice of the lag length (p) for the VAR may affect inferences made from the
causality tests: if p is too large degrees of freedom are wasted, and if p is too small,
the model is mis-specified.
To determine the optimal lag length of the VAR)
multivariate versions of the AIC and SBC criteria were used. Where the criteria
indicated different lag lengths, the SBC criterion was preferred given that it
has superior large sample properties … is asymptotically consistent whereas the AIC
is biased toward selecting an overparameterized model (Enders 1995: 88).
The SBC criterion was minimized for the first lag (k = 1), hence the order of the VAR
used was two (since dmax = 1). However, the test of causality was conducted using
several lag lengths to ensure that the results are not sensitive to this choice. Table 2
shows that the results are consistent for different lags implying that the results are
robust. This can be interpreted in the light of Leamer’s Extreme Bound Analysis
(1983) where he suggests the estimation of a range (bound) for the estimates from a
set of different combinations of free and doubtful variables where the smaller the
bound, the more robust the results.
[Insert Table 2 about here]
The test results indicate that the null hypotheses of no Granger causality from
exports to output and from output to exports can be rejected at the 99% and 95%
levels respectively for the VAR order of two, indicating a bidirectional causal
relationship between the variables. Additional lags in the VAR do not alter these
results. The lagged coefficients for both exports and output display positive signs
indicating that exports and output have a positive effect on each other in the Irish
economy. Therefore, the export-led growth hypothesis does not hold for Ireland since
a feedback effect exists in the system.
To test the exogeneity assumption for the exports variable within the VAR
system and in the context of the causality approach adopted, a restriction that all
coefficients on the lags of exports across all equations in the system were equal to
zero was tested. This follows Enders’ (1995: 316) concept of ‘block exogeneity’ as
16
employed by Shan and Sun (1998). The null hypothesis of exogeneity cannot be
accepted as an MWald statistic of 29.64 was estimated with a P-value of 0.0001.
Exports are, therefore, endogenous in the system and supports the finding that the
export-led growth hypothesis does not apply to the Irish economy.
Causality tests for the other sources of growth were similarly conducted. The
results reported in Table 3 indicate that the internal sources of growth i.e. capital and
labour did not play a role in explaining Irish output growth. Neither is support found
for the hypothesis that growth was stimulated by imports, through embodied
technology for example. External factors appear to explain Irish growth as both the
Terms of Trade and Output of industrial countries display statistically significant
causal effects at the 5% level. Because both labour and capital are found to cause
exports, no support for the Rybczynski theorem is evident.
[Insert Table 3 about here]
Table 4 presents results of tests for destination specific causes of growth. For
the destination analysis, the export and import variables were replaced by the
appropriate trade data for the UK, EU, EURO and US. The EU is defined to include
Belgium, France, Germany, Italy, the Netherlands the United Kingdom over the full
period, while the EURO measure omits trade with the United Kingdom.7
[Insert Table 4 about here]
For the United Kingdom the hypothesis of export-led growth is rejected and
again capital, labour and imports (from the UK) are not found to explain Irish growth.
The terms of trade appears to explain Irish growth while industrial countries’ GDP is
statistically significant at the 10% level. Support is found for the growth-led-exports
hypothesis.
The results for the EU are broadly similar to those for the UK which is not
very surprising given the proportion of total EU trade accounted for by the UK,
particularly in the early years covered for this analysis. Focusing just on Ireland’s
main European trading partners (EURO) leads to somewhat different results however.
Both the terms of trade and industrial countries’ GDP retain their importance as
7
Tests of stationarity were carried out for the additional variables and revealed them to be I(1). Both
AIC and SBC criteria were used to select the optimal VAR in the case of each system of variables.
These results are not shown here.
17
explanatory factors in Irish growth (and with higher P-values than for the EU). Again
neither capital nor labour appear to statistically significantly explain Irish growth,
although the P-value associated with capital at 0.1349 is considerably lower than the
corresponding value of 0.3312 found for the EU. The growth-led exports hypothesis
is not supported while the export-led-growth hypothesis is supported at the 10% level.
Imports play a more significant role in Irish growth, compared to the other results, as
the P-value is 0.1114.
In the case of the US, the terms of trade is a statistically significant variable
although industrial countries’ GDP is not. A P-value of 0.0005 indicates strong
support for the export-led-growth hypothesis for the US and a feedback effect is not
evident. Labour appears a significant explanation of Irish growth while capital is
insignificant. For no geographical area is support found for the Rybczynski theorem
as neither capital nor labour causes exports for the cases of trade with the UK, EU,
EURO-countries or the US.
Table 5 presents results for the product-based measures where exports and
imports denote those for each of the SITC Section classifications from 0 to 8, as
shown in the Data Appendix.8 The final columns in Table 5 denote the manufacturing
sector which is the sum of SITC Sections 5 to 8.
[Insert Table 5 about here]
Support is found for a uni-directional export-led growth hypothesis for only
one Section, i.e. Section 5 although even for this Section the P-value for a feedback
effect from output to exports is 0.1261. In the second Section (Section 4) where the
P-value of exports is significant at the 5% level a statistically significant feedback
effect also exists (P-value of 0.0120) from output to exports. Imports helps to explain
Irish growth for Section 8 only and while the two-gap hypothesis was tested for this
section (i.e. that exports leads indirectly to output via imports) it was not found to
hold. Capital does not appear to play a role in explaining growth for any section.
Labour appears to explain Irish growth when account is taken of trade in Section 8 at
the 1.5% level and Sections 2 and 6 at the 10% level. The terms of trade variable
8
It should be noted that the SITC classification was introduced in Ireland in 1963 and to compile a set
of consistent data back to 1950 it was necessary to reclassify the export and import data published for
Ireland between 1950 and 1961. This was aided by the publication of data for 1962 according to both
classifications. The method of re-classification is explained in the Data Appendix.
18
displays statistically significant P-values at the 5% level in Sections 4, 6 and 8 and at
the 10% level for Sections 0 and 5.
Industrial countries’ GDP appears with
significant P-values at the 5% level in Sections 2, 3 and 7 and at the 10% level for
Sections 0 and 1. The output-led-exports hypothesis is supported in Section 4 (5%
level) and in Section 0 (10% level).
For the manufacturing sector (SITC 5-8), the only statistically significant
variable in explaining Irish output is the Terms of Trade while the next most
significant P-value is for labour at 0.1292. The only support for the hypothesis
corresponding to the Rybczynski theorem is found for the sum of Sections five to
eight as labour is estimated to cause exports with a positive sign on the labour
variable.
If Irish exports are labour intensive relative to import-substitutes, an
increase in labour, ceteris paribus, causes an increase in exports.
While the
assumption of labour-intensive exports in the manufacturing sector would appear to
contradict recent estimates of the factor intensity of Irish exports (Neven, 1990), the
fact that the data period here begins in 1950 could be responsible for this result. Since
the reorientation of both the Irish industrial and trade structures occurred most
significantly following EEC entry in 1973, this result is not considered to be
implausible.
VII. Conclusions
The results of testing the export-led-growth hypothesis within the framework
of an augmented production function indicate bi-directional causality for exports and
output meaning that exports and output growth positively reinforced each other in the
course of Irish economic development from 1950 to 1997. A virtuous circle of
growth and exports may be said to exist for the Irish economy as any increase in Irish
output (exports) has feedback effects that lead to export (output) expansion. This is
further supported by the finding that exports are endogenous in the VAR system.
The finding of significance for the external factors in the augmented
production function indicate the reliance of the small open Irish economy on its
international markets for economic expansion and the need to maintain
competitiveness in these markets.
The lack of significance of capital in the
production function corresponds with O’Grada’s (1995: 216) view that
19
Ireland’s investment rate was consistently lower than [those] in other countries at a
similar stage of development …such investment … was not necessarily allocated
appropriately.
The poor explanatory power of labour is more surprising, however, and may indicate
the need to include an education-based measure of labour in future research as Irish
educational expenditure and rate of school attendance are high by international
standards (evident in Mankiw, Romer and Weil, 1992).
The results of the breakdown of Irish trade according to its main trading
partners highlight that no support for the export-led-growth hypothesis exists for UK
trade. In fact a one-way causal direction from Irish output to exports is found for the
UK. For trade with other European countries and the US support is found for the
export-led growth hypothesis at 10% and 5% significance levels respectively. To the
extent that non-UK exports have generated Irish growth this fuels the need to further
diversify trade away from the UK to take advantage of growth opportunities. The
view that the links between the Irish economy and that of the UK constrained Irish
economic development (e.g. Leddin and Walsh, 1998) is supported by the results
indicating that traditional Irish trade over-reliance on the UK market explains some of
Ireland’s poor growth performance in the past.
For the SITC Section level data exports appear as an explanatory factor in
Irish growth for two Sections (4 and 5), however, in 1997 the Sections represented
over one quarter of all Irish exports. Bi-directional causality was found for Section 4
while uni-directional causality was evident for Section 5. The most important sources
of growth remained the external factors although labour did appear as a significant
factor for 3 Sections.
While no conclusions can be made with regard to the direct role of FDI in
explaining Irish growth, it can be considered that given the two way causality found
for Ireland, any features of the economy which boost either output or exports can only
have a positive knock-on effect in terms of Irish economic development. Hence, the
encouragement of FDI, which heretofore has been focused on export-orientated
industry, would appear to have generated pro-growth effects in Ireland.
20
Data Appendix
The reclassification for trade data is shown in the tables below.
The
percentages indicated are derived based on data published for 1962 for both the old
and new (SITC) classifications and trade patterns in 1963.
As the pre 1963
classifications for exports and imports were different for Class III, separate reclassification was required for exports and imports.
[Insert Table 6 about here]
[Insert Table 7 about here]
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23
Table 1: Tests of Stationarity (ADF).
Y
1.68
X
1.97
M
0.47
K
-0.37
L
1.43
ToT
-2.91
YIC
-0.84
-3.13*
-6.06**
-4.52**
-3.61*
-4.15**
-6.92**
-5.05**
Levels
First
Differences
Note: The critical values of the ADF test statistic are –2.93 (-3.5) and –3.58 (-4.15) for 5%
and 1% significance levels respectively when testing with a constant (and trend) for the null
hypothesis of a unit root. 5% significance is denoted by *, 1% significance by **. Statistics
are taken from Enders (1995: 421) Table A.
Table 2: Granger Causality Test Results: Exports-GDP Relationship.
H0:
X does not cause Y
Y does not cause X
Test Statistics
P-value
MWald
P-value
MWald
Lag structure (VAR order)
1(2)
2(3)
3(4)
0.0055
0.0011
0.0003
7.7112
13.5402
18.8467
0.0433
0.0010
0.0236
4.0838
13.8273
9.4715
Table 3: Granger Causality Test Results: Sources of Growth (optimal VAR order).
H0:
P-values
MWald
Imports do not cause output
Capital does not cause output
Labour does not cause output
Terms of Trade do not cause output
Output (ICs) do not cause output
Capital does not cause exports
Labour does not cause exports
0.6180
0.3370
0.1950
0.0429
0.0360
0.0313
0.0522
0.2487
0.9218
1.6792
4.1002
4.3974
4.6367
3.7696
24
Table 4: Granger Causality Test Results: Geographical Trade and Growth.
UK
H0:
a
X→
/ Y
M →
/ Y
K→
/ Y
L→
/ Y
ToT →
/ Y
YIC →
/ Y
Y→
/ X
K→
/ X
L→
/ X
a
EU
EURO
US
P-value
MWald
P-value
MWald
P-value
MWald
P-value
MWald
0.1709
0.2399
0.1945
0.2063
0.0194
0.0967
0.0288
0.8776
0.7508
1.8747
1.3810
1.6829
1.5975
2.4682
2.7588
4.7772
0.0237
0.1008
0.8951
0.3710
0.3312
0.3199
0.0474
0.1038
0.0022
0.5444
0.4263
0.0174
0.8002
0.9442
0.9895
3.9319
2.6467
9.3685
0.3674
0.6329
0.0992
0.1114
0.1349
0.3221
0.0262
0.0358
0.6350
0.6891
0.9806
2.7186
2.5342
2.2355
0.9804
4.9441
4.4076
0.2253
0.1600
0.0006
0.0005
0.8199
0.8054
0.0215
0.0084
0.2010
0.9931
0.4603
0.1455
11.9571
0.0519
0.0607
5.2829
6.9514
1.6352
0.0000
0.5451
2.1190
→
/ denotes ‘do(es) not cause’ and Y denotes Irish output (GDP).
Table 5: Granger Causality Test Results: Product-based Trade and Growth.
0
H0:
X→
/ Y
M→
/ Y
K→
/ Y
L→
/ Y
ToT →
/ Y
YIC →
/ Y
Y→
/ X
K→
/ X
L→
/ X
1
→
/ Y
M→
/ Y
K→
/ Y
L→
/ Y
ToT →
/ Y
YIC →
/ Y
Y→
/ X
K→
/ X
L→
/ X
3
4
P-val.
MWald
P-val.
Mwald
P-val.
MWald
P-val.
MWald
P-val.
MWald
0.2339
0.4308
0.4767
0.4175
0.0681
0.0769
0.0768
0.3308
0.3451
1.4167
0.6205
0.5064
0.6571
3.3280
3.1297
0.1865
0.9457
0.8913
0.7576
0.4888
0.9342
0.3601
0.1317
0.0637
0.0952
0.4792
0.0068
0.8375
2.2728
3.4387
1.3794
0.1912
0.1351
0.7748
0.0908
0.2126
0.0512
0.8954
1.7069
2.2333
0.0819
2.8598
1.5535
3.8030
0.0173
0.7981
0.7618
0.5213
0.1610
0.1374
0.0432
0.5012
0.0655
0.0919
0.4114
1.9646
2.2073
4.0859
0.4524
0.0239
0.9420
0.7630
0.4843
0.0277
0.1762
0.0120
5.0995
0.0053
0.0909
0.4892
4.8463
1.8298
5.4134
2.1198
0.7797
0.0784
0.4456
0.5818
0.5220
0.4099
0.8447
0.5933
0.2852
0.6200
0.2458
0.9986
0.0000
0.2402
0.1454
0.3580
5
X
2
6
7
8
5+6+7+8
P-val.
MWald
P-val.
Mwald
P-val.
MWald
P-val.
MWald
P-val.
MWald
0.0520
3.7753
0.1359
2.2233
0.6568
0.1974
0.3789
0.7741
0.8709
0.0264
0.1757
1.8339
0.2111
1.5638
0.3203
0.9875
0.0103
6.5808
0.6402
0.2185
0.9207
0.0099
0.8616
0.0304
0.9966
0.0000
0.9408
0.0055
0.9705
0.0014
0.2372
1.3974
0.0644
3.4215
0.1995
1.6457
0.0153
5.8791
0.1292
2.3017
0.0964
0.0015
10.1338
0.2855
1.1406
0.0002
13.6505
0.0529
3.7468
0.4967
2.7634
0.4620
0.2973
1.0861
0.0305
4.6807
0.1477
2.0954
0.2323
1.4262
0.1261
2.3401
0.9936
0.0000
0.1313
2.2767
0.8582
0.0319
0.9824
0.0005
0.2227
1.4867
0.4656
0.5325
0.5994
0.2759
0.0207
5.3556
0.7929
0.0690
0.7923
0.0693
0.4935
0.4689
0.7925
0.0692
0.0058
7.6113
0.0423
4.1300
25
Table 6: Reclassifications of Data for 1950 to 1961: Exports.
Post 1963 Classification - SITC
0
Food and live animals
1
2
Beverages and tobacco
Crude materials, inedible except fuels
3
4
5
6
7
8
Mineral fuels, lubricants & rel. materials
Animal & veg. oils, fats and waxes
Chemicals and related products
Manufactures classified by material
Machinery & transport equipment
Miscellaneous manufactured articles
Corresponding Pre 1963 Classification
Class I: live animals + Class II: foodstuffs of animal
origin, cereals & feeding stuffs & misc. food
Class II: drink & tobacco
Class III: ores & metals + 30% of oils, fertilizers,
chemicals + 46% textiles + 30% hides, skins & leather
1.65% of total exports
Class III: 20% of oils, fertilizers, chemicals
Class III: 40% of oils, fertilizers, chemicals
Total exports less total of all other sections
Class III: vehicles + 4% of all Class III
Class III: Miscellaneous articles + Clothing & footwear
Table 7: Reclassifications of Data for 1950 to 1961: Imports.
Post 1963 Classification - SITC
0
Food and live animals
1
2
Beverages and tobacco
Crude materials, inedible except fuels
3
4
5
6
7
8
Mineral fuels, lubricants & rel. materials
Animal & veg. oils, fats and waxes
Chemicals and related products
Manufactures classified by material
Machinery & transport equipment
Miscellaneous manufactured articles
Corresponding Pre 1963 Classification
Class I: live animals + Class II: foodstuffs of animal
origin + cereals & feeding stuffs & misc. food
Class II: drink & tobacco
Class III: iron & steel + 55% textiles + 10% hides, skins
& leather
1% of total imports
Class III: 7.5% of oils, fats, resins & gums
Class III: chemicals perfumery, dyes and colours
Total exports less total of all other sections
Class III: vehicles + machinery & electrical goods
Class III: Miscellaneous articles + clothing & footwear
26