1澳大利亚制造业

Economic Analysis and Policy 50(2016)
41–51
Contents lists available at ScienceDirect
Economic Analysis and Policy
journal homepage:
/locate/eap
Full length
article
Trade liberalisation,inward FDI and productivity within
Australia’s manufacturing sector
Christopher Turnbull a ,1,Sizhong Sun a ,2,Sajid Anwar b ,c ,∗
a
College of Business,Law and Governance,James Cook University,Townsville,QLD 4811,Australia b
School of Business,University of the Sunshine Coast,Maroochydore DC,QLD 4558,Australia c School of Commerce,University of South Australia,Adelaide,SA 5001,Australia
a r t i c l e i n f o Article history:Received 16September 2015Received in revised form 13February 2016Accepted 15February 2016Available online 20February 2016JEL classification:F14F21O11Keywords:
Trade liberalisation
FDI
Productivity
Manufacturing sector
Australia
a b s t r a c t
Using a simultaneous equations model,this paper aims to analyse the endogenous re-
lationship among trade liberalisation,inward foreign direct investment and productivity
within Australia’s manufacturing ing two-digit quarterly time-series data,from
1988to 2012,we find empirical support for trade liberalisation as a mechanism for im-
proving productivity within the domestic manufacturing sector.However,we find that in-
ward foreign direct investment has not had a statistically significant impact on productivity
within the sector.By drawing on these findings,among others,we make some recommen-
dations for Australia’s international trade,foreign investment and manufacturing industry
policies.
©2016Economic Society of Australia,Queensland.Published by Elsevier B.V.All rights reserved.1.Introduction
The manufacturing sector has long been a key pillar of the Australian economy,accounting for as much as 16%of domestic output in the early 1970s.However,the domestic economy has undergone significant structural change in recent decades,characterised by an expansion of the services sector,and a relative decline in manufacturing and agricultural output (Lowe,2012).According to the Reserve Bank of Australia (2001),structural change in the Australian economy has been predominantly driven by technological advancement and reduced protection from international competition.This paper focuses on the latter,paying particular attention to the impact of international competition on productivity within the domestic manufacturing sector.
The most notable channels through which domestic manufacturers have been exposed to foreign competition are imports and inward foreign direct investment (FDI).As depicted in Fig.1,both nominal and effective rates of assistance (NRA and ERA,respectively)afforded to the aggregated two-digit Australian and New Zealand Standard Industrial Classification ∗Corresponding author at:School of Business,University of the Sunshine Coast,Maroochydore DC,QLD 4558,Australia.Tel.:+61754301222.E-mail addresses:Chris.Turnbull@.au (C.Turnbull),Sizhong.Sun@.au (S.Sun),SAnwar@.au (S.Anwar).
1Tel.:+61261029979.
2Tel.:+61747811681.
/10.1016/j.eap.2016.02.004
0313-5926/©2016Economic Society of Australia,Queensland.Published by Elsevier B.V.All rights reserved.
42 C.Turnbull et al./Economic Analysis and Policy50(2016)41–51
Fig.1.Assistance afforded to two-digit manufacturing industries.Note:Estimates of ERA and NRA from after the year2000are available from the Productivity Commission upon request.
Source:Productivity Commission(2000).
(ANZSIC)manufacturing sector have declined substantially in recent decades.Moreover,microeconomic reforms and bilateral agreements have assisted Australia’s total stock of inward FDI to grow from around15%of GDP in1980to over 35%of GDP in2012.
Whilst much of the existing theory in international economics suggests that increased liberalisation of trade and FDI should result in improved host-nation productivity,productivity levels in Australian manufacturing have stagnated since the early2000s(Parham,2004).Consequently,this paper aims to explore the relationship among trade liberalisation, inward FDI and productivity within the aggregated two-digit ANZSIC manufacturing industries.Specifically,in exploring this relationship,the paper focuses on addressing the endogeneity issue that has been largely ignored in previous studies.
As a result of limited research exploring this issue in the Australian context,this paper aims to provide an important evaluation of the Australian international trade,foreign investment and manufacturing industry policy arrangements. Additionally,this paper also aims to update the existing literature by analysing current datasets and providing a useful starting point for further empirical research.
The remainder of this paper is structured as follows.Section2offers a brief background on international competition and the manufacturing industry in Australia.Section3provides a review of key literature.Section4outlines the methodology underpinning the empirical analysis.Section5identifies data sources and constructs variables.Empirical results are presented and discussed in Section6.Section7offers policy recommendations and concludes the paper.
2.The empirical setting
In the years following the Second World War,attitudes towards international competition in Australia have changed dramatically.Under the Menzies-led governments of the1950s and60s,protectionism was the cornerstone of industry policy.Specifically,the Menzies governments offered significant tariff protection to domestic manufacturing industries while concurrently attempting to attract FDI(Freedman and Stonecash,1997).Although protectionist policies achieved their aim of expanding the domestic manufacturing sector and providing an abundance of employment opportunities to Australians,by the late1960s calls to improve economic efficiency gained traction.
Over the following two decades the level of trade protection afforded to domestic industries declined substantially, assisted largely through a universal25%tariff reduction in1973.The ERA afforded to domestic manufacturers began to decline more rapidly through the late1980s and1990s following significant microeconomic reforms and,since the late 1990s,the ERA has remained relatively steady at around five percent,reflecting the sector’s exposure to increasingly higher levels of import competition(Productivity Commission,2000).
Whilst the microeconomic reforms undertaken in Australia throughout the1980s and90s helped to significantly reduce trade barriers,they also continued to attract FDI.According to Crotti et al.(2010),these reforms played an important role in attracting greater FDI in Australia;rising from15%of GDP in1980to over35%in2012.However,it is important to note that over the five years to2013,FDI in manufacturing averaged less than16%of total inward FDI in the Australian economy.
As the Australian economy has increased its openness to international competition,the manufacturing sector has undergone significant change.In the mid-late1980s,manufacturing was responsible for close to17%of total employment and produced nearly10%of domestic output.However,as in most developed economies,Australia’s manufacturing sector has been the victim of major structural change in recent decades.In2012,manufacturing’s share of total employment and domestic output had fallen to around eight and six percent,respectively.
C.Turnbull et al./Economic Analysis and Policy50(2016)41–5143
Although international competition,including imports and inward FDI,is thought to have played a major role in the relative decline of Australia’s manufacturing sector,a number of other factors have contributed to structural change.Most notable among these are rising costs of labour costs),increased consumer demand for services,and
the lasting strength of the Australian currency.the relative decline of manufacturing in Australia,the sector continues to produce around$100billion of each year.3
3.International Trade,FDI and Productivity Literature4
3.1.Trade liberalisation
A number of studies have considered the impact of trade liberalisation on various aspects of the Australia economy (for example employment,economic growth,and productivity).While many studies have explored the impact of trade liberalisation on the macro economy,a considerable proportion of the existing literature has focussed on productivity spillovers experienced by the domestic manufacturing sector(see for example Bloch and McDonald,2001,Chand,1999, Mahadevan,2002,Palangkaraya and Yong,2011,Paul and Marks,2009and Sanidas and Jayanthakumaran,2007).Given the traditionally important role of manufacturing in the Australian economy,it is not surprising that much of the research pertaining to trade liberalisation has focussed on this sector.
An early benchmark for research into the impact of trade liberalisation on Australian manufacturing productivity was provided by Chand(1999),who uncovered a negative and significant link between the NRA and multifactor productivity (MFP)growth among eight two-digit ANZSIC manufacturing industries.This negative impact,which provided strong empirical support for trade liberalisation,was identified by estimating an augmented Cobb–Douglas production function populated with annual time-series data from1968–69to1994–95.
Notably,the study found that a10%reduction in the NRA caused up to a five percent increase in the growth rate of MFP. Additionally,Chand(1999)highlighted the existence of inter-sectoral heterogeneity in the response to trade liberalisation;
a finding that is explained by the broad variety of industries that are considered part of the aggregated manufacturing sector. Although the significance of this problem was highlighted in the study,no attempt was made to address the functional form problems of the model,with the‘problem’industries instead dropped from the estimation.
Chand’s(1999)empirical analysis was based on the Cobb–Douglas production function,augmented with variables from new growth theory.The Cobb–Douglas production function,which measures technological progress using Solow(1957) residuals,has been commonly employed throughout the literature as a method of measuring productivity(see for example Driffield and Love,2005,Fadinger and Fleiss,2011,Hanel,2000,Mahadevan,2002and Singh,2011),though the framework is not without criticism.
Some studies,such as Fox and Kohli(1998)and Paul and Marks(2009),argue that the Cobb–Douglas framework is an inappropriate method of measuring productivity because it utilises an outdated functional form,aggregates outputs,and cannot easily incorporate the effects of an open economy.Whilst these arguments are widely acknowledged,more flexible functional form frameworks,such as Translog models,present their own problems,particularly in the significance of second order conditions(Mahadevan,2002;Murillo-Zamorano and Vega-Cervera,2001).
Mahadevan(2002),who also explored the aggregated two-digit ANZSIC manufacturing sector between1968–69and 1994–95,helped to somewhat alleviate the inadequacies of MFP by employing a Stochastic Frontier framework.Although the framework incorporated a model based on the Cobb–Douglas production function,it allowed MFP to be divided into sub-components of technological progress and technical efficiency.Borrowing the dataset utilised by Chand(1999),the model estimation was performed using Aitken’s generalised least squares regression.
Significantly,Mahadevan(2002)found that trade liberalisation,measured by both nominal and effective rates of assistance,positively impacted technological progress among domestic manufacturers,but had no significant impact on technical efficiency.The distinction between technological progress and technical efficiency is an important contribution to the literature,although it also presents some additional problems.Most notably,measures of technical efficiency remain subject to the functional form problems outlined by Fox and Kohli(1998).
Although firm and establishment-level studies are scarce in the Australian literature,due mainly to data limitations, a small number of studies have also explored the impact of trade liberalisation at the sub-industry level.Most notably, Bloch and McDonald(2001)and Palangkaraya and Yong(2011)provide detailed analyses of firm and establishment-level responses to trade liberalisation,respectively.Importantly,these studies suggest that trade liberalisation yields the greatest productivity gains in industries with a high level of domestic participation and in industries which are exposed to the greatest reductions in assistance,respectively.
3A detailed account of structural change in the Australian economy is provided in the Australian Department of Industry’s‘Australian Industry Report 2014’.
4The review presented in this section focuses predominantly on Australia.Of course,the literature on the determinants of FDI is vast.A more thorough review of related literature involving other countries can be found in Anwar and Nguyen(2014),Anwar and Cooray(2015),Kahouli and Maktouf(2015), along with a brief discussion in Section3.2of this paper.
44 C.Turnbull et al./Economic Analysis and Policy50(2016)41–51
3.2.Foreign investment
While numerous studies have focussed on the linkages between trade liberalisation and various aspects of the Australian economy,relatively few have considered the role of foreign investment.Some noteworthy exceptions include studies by Iyer et al.(2009),Crotti et al.(2010),and Kirchner(2012).
Iyer et al.(2009)examined the implications of outward orientation on Australia’s economic ing quarterly time-series data from1988to2003,the study explored the impact of five different measures of outward orientation on GDP ly,the study considered the role of imports,exports,FDI,foreign portfolio investment(FPI),and other foreign investment(OFI),ing a co-integrated vector autoregressive(VAR)model and Granger causality tests,Iyer et al.(2009)found both imports and FDI to have positive and significant effects on economic growth.Furthermore,the study provided evidence to suggest that FDI was the only form of foreign investment to Granger-cause economic growth in the long-run.
Although the empirical analysis performed by Iyer et al.(2009)focussed primarily on economic growth,its simultaneous consideration of both trade and investment provides a helpful starting point for studies exploring many other impacts of outward orientation.The main justification for this type of consideration is that trade and foreign investment channels are highly interrelated.Therefore,the exclusion of one of these variables could lead to under or overestimation of the other. Furthermore,measures of foreign investment should control for the heterogeneous impacts of FDI,FPI,and OFI(Iyer et al., 2009).The distinction of foreign investment type is further highlighted by Kirchner(2012)in uncovering the determinants of inward FDI flows to Australia.
Drawing on quarterly time-series data from1989to2004,Kirchner(2012)estimated a model for inward FDI in Australia. By employing a VAR model and Granger causality tests,the study found FDI to be positively related to economic growth and productivity growth but negatively related to foreign portfolio investment(Kirchner,2012).Additionally,FDI was found to Granger-cause productivity growth,although this finding was only marginally significant at the10%level.This conclusion, however,was based on a rather crude measurement of trade openness;computed as a ratio of total trade(both imports and exports)to GDP.Such a practice is criticised by many,including Iyer et al.(2009),who argue that imports and exports are not homogeneous in their impacts on growth and should therefore be considered separately.
Another important finding of Kirchner(2012)is the significance of distinguishing foreign investment into its sub-components,as indicated by Iyer et al.(2009).Moreover,the empirical evidence presented in the study suggests that international trade and FDI may be substitutes,or in other words,‘tariff-jumping’behaviour may occur in the Australian context.
A somewhat contrasting perspective of trade and investment is offered by Crotti et al.(2010),who explored the relationship between inward FDI and bilateral trade and investment ing panel data from1993and2003,the study analysed the impact of trade and investment accords on FDI flows to Australia from its six largest source countries:the US,the UK,Japan,the Netherlands,New Zealand,and Germany.Empirical results were estimated through both ordinary and generalised least squares regression of common constant and fixed effects models.Significantly,the study found Australia’s bilateral trade and investment agreements to have a positive impact on inward FDI flows.However,the study specifically highlighted the need for industry-level analyses to provide greater insight into the impacts of increased FDI,particularly on manufacturing and mining industries.
Although relatively few studies explore the productivity spillovers of FDI on Australia’s manufacturing sector,the broader literature related to productivity spillovers of FDI is vast.Notable examples of studies which have investigated the productivity spillovers of FDI in other countries include Javorcik(2004),Haskel et al.(2007),Suyanto and Salim(2010), and Suyanto and Salim(2013).
It is commonly believed that FDI from large multinational firms,which are typically exemplars of best-practice knowledge and technology,will result in positive productivity‘spillovers’for domestic firms.This is in addition to the productivity-enhancing benefits that FDI is hypothesised to deliver through heightened competition.However,the empirical evidence to support this hypothesis is mixed.5
Strong support for positive productivity spillovers hypothesis is offered by Haskel et al.(2007),who analysed UK manufacturing firms at the plant-level from1973to1992.Specifically,the study concluded that a robust and positive correlation existed between the productivity of a domestic plant and foreign activity within the same industry.This conclusion is corroborated by Javorcik(2004)who found evidence of positive productivity spillovers from FDI at the firm-level in Lithuania.However,the study found positive spillovers were only achieved by firms with a mixture of domestic and foreign ownership.
On the other hand,Suyanto and Salim(2013),who investigated FDI spillovers on productivity within the Indonesian pharmaceutical sector,found evidence that FDI had negative spillovers on the technical efficiency of domestic competitors, but positive spillovers for domestic suppliers.Heterogeneous impacts of FDI on domestic productivity are also found by Suyanto and Salim(2010),who found that spillover effects can manifest through different sources and vary according to firm-specific characteristics.
5Suyanto and Salim(2010)offer a more thorough explanation of how FDI can lead to positive productivity spillovers.
C.Turnbull et al./Economic Analysis and Policy50(2016)41–5145
3.3.Gaps in the existing literature
Based on the above preceding literature review,it is evident that the majority of existing studies offer support for trade liberalisation as a mechanism for improving productivity in the domestic manufacturing sector(Bloch and McDonald,2001; Chand,1999;Mahadevan,2002;Palangkaraya and Yong,2011;Paul and Marks,2009).In addition,recent studies have provided some insight into the determinants of inward FDI,as well as evidence to suggest that FDI has had a positive impact on Australia’s economic growth in recent decades(Crotti et al.,2010;Iyer et al.,2009;Kirchner,2012).Studies investigating the productivity spillover effects of FDI in other countries also help to provide context for this paper.
Notwithstanding the importance of these contributions,the lack of studies simultaneously exploring trade liberalisation, foreign investment and manufacturing productivity is a substantial gap in the existing literature.The significance of such an analysis is best explained by Iyer et al.(2009),who highlight the endogeneity of international trade and FDI.
Resultantly,this study aims to contribute to the existing literature by simultaneously considering trade liberalisation, inward FDI and domestic manufacturing productivity.Such an analysis is necessary given the significant degree to which trade and investment have been liberalised in Australia in recent decades and the concurrent lack of growth in MFP in the domestic manufacturing sector.Accordingly,the following analysis will provide valuable empirical evidence for policymakers to evaluate the suitability of Australia’s existing trade,investment,and industry policies.Additionally,the study will serve to update the existing literature and provide a platform for future research into industrial productivity in open economies.
4.Methodology
4.1.Model specification
A Simultaneous Equations Model(SEM)is employed to investigate the relationship among trade liberalisation,FDI and productivity within the Australian manufacturing sector.Following previous studies–see for example Anwar and Sun(2011) and Sun(2011)–the model is specified as follows:
uva t=β0+β1era t+β2fdi t+β3kl t+β4g t+β5sales t+β6m t+εt(1) fdi t=γ0+γ1uva t+γ2era t+γ3gni t+γ4w t+υt(2) era t=α0+α1uva t+α2fdi t+α3fpi t+α4gni t+ϕt(3) where uva is unassisted value added,constructed following Chand(1999);era is the effective rate of assistance;fdi is inward foreign direct investment;kl is the capital-to-labour ratio;g is government expenditure on fixed capital;m is imports of intermediate inputs;gni is gross national income;w is the weekly wage of employees;fpi is foreign portfolio investment; andε,ϕ,andυ,represent the error terms in the three equations,respectively.6
In the above SEM,Eq.(1)is formulated loosely following the growth accounting framework first introduced by Solow (1957),but is extended to include variables inspired by endogenous growth theory,which is explained in detail in Rivera-Batiz and Romer(1991).Instead of exploring economic growth,the framework is utilised to model unassisted value added (UVA)by manufacturing firms operating in Australia,as performed by both Chand(1999),and Mahadevan(2002).While the traditional capital and labour inputs have been incorporated through the capital-to-labour ratio(kl),Eq.(1)also includes trade liberalisation(era),foreign direct investment(fdi),public infrastructure(g),the size of the domestic manufacturing sector(sales)and imports of intermediate inputs(m).
In Eq.(2),inward FDI is modelled as a function of endogenous productivity(uva)and trade liberalisation(era)variables, and exogenous variables representing the size of the domestic economy(gni)and the domestic cost of production,namely the wage rate(w).
Finally,trade liberalisation is modelled in Eq.(3)through the ERA afforded to domestic manufacturers(era).The equation includes endogenous variables for productivity(uva)and inward FDI(fdi),and exogenous variables representing private investment in domestically producing firms(fpi)and the size of the domestic economy(gni).
4.2.Estimation and inference procedure
The empirical estimation is performed using the three-stage least squares(3SLS)regression technique for evaluating SEMs,as developed by Zellner and Theil(1962).After the estimation,autocorrelation plots are generated for each of the predicted residuals.Upon observing the autocorrelation plots,the presence of serial correlation is identified for each of the predicted residuals.With the existence of serial correlation,even though point estimates of coefficients remain consistent, they are not efficient.To account for this problem,we employ the block bootstrap technique to compute standard errors for our point estimates.
6Variables written in lower-case represent the logarithmic transformation of original variables.
46 C.Turnbull et al./Economic Analysis and Policy50(2016)41–51
Table1
Summary statistics of selected data series.
Unlike the standard bootstrap,the block bootstrap captures the dependence among time series by stratifying the data into sequential blocks.It is important to note,however,that the resulting estimates are sensitive to the selected block length. In our case we follow an approach outlined by Inoue and Shintani(2006)in selecting this block ly,we have chosen the block length(ℓ)to be approximatelyℓ=T1/3,where T is the number of observations in each series.Since each series contains95observations,we compute bootstrap standard errors using a block length of5observations.
5.Data sources and variable construction
The empirical analysis is performed using quarterly time-series data,from1988Q3to2012Q1,drawn from Australian Bureau of Statistics(ABS),Productivity Commission(PC)and OECD databases.Where necessary,series are seasonally adjusted and measured in constant prices.Additionally,all series are converted to their natural log form for scaling and ease of interpretation.
Data collected from the ABS include time-series for gross value added in manufacturing;the total flow of inward FDI to Australia;total expenditure on fixed capital in two-digit manufacturing industries;total government expenditure on fixed capital;income from sales of goods and services produced in the two-digit manufacturing industries;total imports of intermediate goods;total hours worked in the two-digit manufacturing industries;and gross national income(GNI).7 Additionally,data pertaining to the NRA and ERA for domestic manufacturing industries are obtained from the PC by request.Data for average weekly earnings in manufacturing are obtained from the OECD databases.A full description of the data,including sources,is provided in the Appendix.Summary statistics of the sample used in this paper are presented in Table1.
5.1.Endogenous variables
(i)Productivity
Productivity levels for the aggregated two-digit manufacturing sector are measured following the unassisted value-added(UVA)approach outlined by Chand(1999).Specifically,gross value-added for the aggregated manufacturing sector is deflated by the ERA afforded to the sector.Such a measure of productivity is justified as it captures value-added at border prices.
An alternate measure of productivity is available in the form of labour productivity.This measure is computed as manufacturing gross value added deflated by average weekly hours worked in the sector.
(ii)Foreign direct investment
Due to data constraints,total inward FDI in Australia is used as a proxy for FDI in domestic manufacturing industries. Specifically,FDI is measured as the quarterly closing position of Australia’s direct investment liabilities.
(iii)Trade liberalisation
Trade liberalisation is measured through the ERA afforded to the aggregated two-digit manufacturing industry.The ERA is the preferred proxy for trade liberalisation as it captures net assistance provided to industry.Most notably,the ERA considers non-border measures such as subsidies,special taxation arrangements,and other special provisions afforded to domestic industries,in addition to taxes and tariffs incurred on imported manufactures at the border.Additionally,the ERA captures any benefits achieved by providing assistance to domestic industries.
An alternate measure of trade liberalisation is available in the NRA afforded to the aggregated two-digit manufacturing industry.The NRA includes only the costs associated with ly,these include the degree to which consumers pay higher taxes and prices to support domestic industries.Both the ERA and NRA are regularly estimated by the PC,with estimates available in publications like the Trade and Assistance Review1999–2000,or upon request.8
7An appropriate proxy for R&D is not available,and is therefore excluded from the analysis.
8For the empirical analysis,the ERA and NRA are assumed constant across all four quarters of each financial year,as quarterly estimates are not available.。