Export market participation, spillovers, and foreign direct investment in Australian food manufacturing

Export Market Participation, Spillovers, and ForeignDirect Investment in Australian Food Manufacturing

Shauna PhillipsAgricultural and Resource Economics, Faculty of Agriculture, Food and NaturalResources, University of Sydney, NSW, 2006, Australia.E-mail: [email protected]

Fredoun Z. Ahmadi-EsfahaniAgricultural and Resource Economics, Faculty of Agriculture, Food and NaturalResources, University of Sydney, NSW, 2006, Australia.E-mail: [email protected]

ABSTRACT

Generating a more outward looking sector has been one of the principal aims of agrifoodpolicy in Australia for the past two decades. Australia’s proximity to fast-growing economiesof East Asia has been seen as a major source for export growth. Over the same time span, therehas been an increase in foreign ownership in the food sector. Using a firm-level data set for2005, we characterize the probability that a firm participates in exporting by a set of firmcharacteristics, including foreign ownership and spillovers from foreign-owned firms, and findthat foreign ownership neither increases nor decreases the probability that a firm will beinvolved in exporting. [EconLit citations: Q170, Q130]. r 2010 Wiley Periodicals, Inc.

1. INTRODUCTION

Over the past two decades, a central aim of Australian agrifood policy has beenmaking the sector more outward looking and internationally competitive. GivenAustralia’s proximity to the fast growing economies of East Asia, the sector is seento enjoy potential for export-led growth, providing a major motivation for sectoralgovernment policy (Beeson & Cloney, 1997; Pritchard, 2005). This was also a periodof financial market deregulation and substantial microeconomic reform in Australia,which facilitated mergers and acquisitions (M&A) in the sector. Although there haslong been a foreign presence in Australian food manufacturing, this presence grewrapidly with the wave in M&A activity (Beeson & Cloney, 1997; Department ofAgriculture, Fisheries, and Forestry [DAFF], 2005; Fagan, 1996 and referencestherein). National sentiment towards inbound foreign direct investment (FDI) issometimes unfavorable (Jones, 1992; Shears, 2005). In particular, there has beenconcern about the impact that foreign-owned firms may have upon the exportperformance of the sector. An assessment of the contribution to export performancethat foreign affiliates make is of interest both because increased exports are a policygoal, and because of the empirical link between export participation and higher firmproductivity (Bernard & Jensen, 1999; Wagner, 2007). This motivates our analysis.At the theoretical level, there are two channels through which foreign ownership

might promote exports. First, foreign-owned firms might directly contribute toexports where FDI is export-platform in nature (Ekholm, Florsid, & Markusen,2003; Grossman, Helpman, & Szeidl, 2003; Motta & Norman, 1996). That is, FDI in

Agribusiness, Vol. 26 (3) 329–347 (2010) rr 2010 Wiley Periodicals, Inc.

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/agr.20254

329

a particular host economy serves as a production base for exports, which can haveeither a home or third-country orientation.In contrast, the argument that foreign-owned firms or multinational enterprises

are less likely to be exporters is based on the proposition that the primary motive offoreign investors is to capture rents from concentrated domestic markets (Pritchard,2005). Second, foreign-owned firms might indirectly contribute to exports throughspillovers (Aitken, Hanson, & Harrison, 1997; Greenaway, Sousa, & Wakelin, 2003).The perception is that if multinational enterprises (MNEs) possess firm-specificassets and have established links and experience in operating in internationalmarkets, then the local concentration of MNE export activity makes domestic firmsmore likely to export. These spillovers can be informational, reducing thedistribution costs associated with exporting. They may also be spillovers that reduceproduction costs, if the presence of MNEs enhances local competition or MNEinnovation activity has imitation effects on domestic firms.In this article, we examine whether foreign-ownership affects the probability of

export participation in the Australian food and beverage manufacturing sector.Adopting the framework of Aitken et al. (1997), we employ a business registerdatabase of firms in food and beverage manufacturing for 2005 to examine exportparticipation, using data on firm characteristics, including foreign ownership status,and measures that capture the effects of export spillovers. Specifically, we test thehypotheses that foreign-ownership increases the probability of export participationand that the concentration of export activity of foreign-owned firms generatesspillover effects. We find for Australian food manufacturing that export participa-tion is unrelated to foreign ownership, and that there is no evidence in support ofspillovers from foreign-owned firms. We present evidence consistent with spilloversfrom general export activity, and exporting is positively related to firm size, age,diversification, and involvement in importing. Disaggregating across Australian foodmanufacturing industries, the foreign ownership results are mostly robust, but thesignificance of firm characteristics is found to vary.This article is organized as follows: background information on the sector is

provided in section 2. A brief review of the relevant literature and the analyticalframework are presented in sections 3 and 4, respectively. Section 5 presents thedata, empirical model and results. Section 6 concludes.

2. BACKGROUND

The food and beverage manufacturing sector constitutes the largest subsector ofAustralian manufacturing, contributing about 20% to total manufacturing and2.5% to gross domestic product. It currently employs about 200,000 people, and hasemerged as the fastest growing manufacturing employer in regional areas (Vaile,2006). It is also a net exporter, contributing approximately 15% to merchandiseexports in 2005–2006 (DAFF, 2008). The sector’s growth, which is largely exportdriven, has averaged 2% over the past decade (Australian Bureau of Agriculturaland Resource Economics [ABARE], 2006). Exports from the sector are oftencategorized by level of transformation which reflects the degree of processing andinputs involved (ABARE, 2006). Exports are dominated by minimally andsubstantially transformed foods (for example, meat cuts and preserved or frozen

330 PHILLIPS AND AHMADI-ESFAHANI

Agribusiness DOI 10.1002/agr

foods), with only a small proportion of elaborately transformed products, such aspastries or confectionary, exported.Two areas of policy that affect the sector can be identified. The first may be

broadly defined as microeconomic reform. As a result of deregulatory policies, anumber of industries in the sector have undergone major restructuring over the pasttwo decades. Typical examples are the Australian dairy and beef processingindustries, where domestic deregulation, along with global trade liberalization, hascreated investment opportunities, some of which were taken up by foreign investors.Australia has historically experienced an imbalance in favor of inbound FDI in thefood sector (BIS Shrapnel Pty. Ltd., 2003; Wondu Pty. Ltd., 2000), and in 2001–2002the level of foreign investment in this sector was A$17.6bn (BIS Shrapnel, 2003). Thesector was dominated by large firms, and about 75% of industry revenue wasgenerated by the 50 largest firms, more than half of which were foreign-owned orpublically listed. Foreign involvement tends to be prominent in more transformedproducts, but also happens to be strong in industries such as meat processing. Thegrowth in foreign presence has been facilitated by a liberal set of foreign investmentpolicies in Australia.Second, there have been a number of policy initiatives aimed at boosting exports

from this sector, such as the ‘‘Supermarket to Asia’’ and its successor, the NationalFood Industry Strategy (Beeson & Cloney, 1997; Pritchard, 2005). These joint publicand private initiatives involved a range of measures, such as R&D concessions,industry development grants, and other such policies. Although the term of theNational Food Industry Strategy is over, growth is still seen to be ‘‘inextricablylinked’’ to increased exports because domestic markets are considered to be mature(DAFF, 2008). Despite these initiatives, there is a perception that Australia has acomparatively poor performance in exports relative to other sectors (Bureau ofIndustry Economics (BIE), 1996; Howe, 1994), and to food sectors from othercountries (Drysdale & Lu, 1996; Instate Pty. Ltd., 2000).Some believe that the sluggish performance in exports may be attributable to the

level of foreign involvement in the sector (Beeson & Cloney, 1997; Instate Pty. Ltd.,2000; Pritchard, 2005). Instate Pty. Ltd. (2000) argues that the foreign-owned firmsare less committed to exporting than their domestic counterparts either because ofthe lack of profitable opportunities, or because their strategy is to serve the domesticmarket alone. Pritchard ([1995, 2005) and Beeson and Cloney (1997) suggest thelatter. Others (for example, BIE, 1994) have postulated that foreign-owned firmshave invested in part due to Australia’s proximity to East Asia, treating Australia asan export base.

3. PREVIOUS STUDIES

Theory identifies both a direct and an indirect channel through which foreign-ownedfirms might contribute to host country exports. A direct channel for the contributionto exports can arise from the strategic motives of firms, where FDI serves as anexport platform. That is, FDI in a particular host economy serves as a productionbase for export to other countries (either to a third or home country). Motta andNorman (1996) and Ekholm et al. (2003) present export-platform FDI models theresults of which are driven by trade cost differences generated by regional tradingzones such as the European Union (EU) or the North American Free Trade

331EXPORT MARKET PARTICIPATION, SPILLOVERS, AND FOREIGN DIRECT INVESTMENT


Agreement (NAFTA). Motta and Norman (1996) model horizontal FDI andexamine the effect of economic integration. Foreign firms invest within a regionalbloc to reduce product prices of exports to other countries within the bloc.Complex international production strategies, where firms can be involved in both

horizontal and vertical FDI, are modeled in Ekholm et al. (2003), Yeaple (2003), andGrossman et al. (2003). Ekholm et al. (2003) present a three-country model withmultiple stages of production to provide a motive for vertical FDI, and a free tradearea to motivate export-platform FDI. They list results from empirical work forseveral EU countries that operate as export platforms to third countries. In a furtheranalysis, Ekholm, Florsid, and Markusen (2007) present results for U.S. affiliates.Models of complex FDI such as Yeaple (2003) and Grossman et al. (2003)incorporate firm characteristics into the analysis, with heterogeneous productivityand size playing a role in the integration strategy of firms. In Grossman et al. (2003)complex strategies that involve both FDI and exports can be adopted by moreproductive firms. Yeaple (2003) and Grossman et al. (2003) consider the existence ofhost country demand on FDI. Building on this work, Liang (2007) explores the effectof host country size, and provides empirical evidence that size has a positive effect onexport-platform FDI. Support for this finding is also reported in Kravis and Lipsey(1982), but in contrast Hanson, Mataloni, and Slaughter (2001) find export-platformFDI to be attracted to small, open, and low tax economies.More recently, a body of empirical work that explores a range of firm-level

characteristics as determinants of export participation has also emerged. Evidence ofa positive relationship between foreign ownership and exports in low-incomeeconomies is presented in Duenas-Caparas (2006), Keng and Jiuan (2001),Wignaraja (2002), and Yoshino (2007). Foreign ownership was found to beinsignificant in Lall (2000). It may be more likely that foreign-owned firms areexporters in low-income countries, where such ownership brings skills andtechnology that are unavailable domestically, or FDI is attracted by relative laborcosts. However, evidence of a positive effect of foreign ownership on exporting isprovided, among others, in Bernard and Jensen (2004), Sterlacchini (2001), Philp(1998), Philp and Wickramasekera (1995), Blake and Pain (1994), Kneller and Pisu(2004), Barry and Bradley (1997), O’Sullivan (1993), Pain and Wakelin (1997),Ekholm et al. (2003) and Jussaume and Kennedy (1993). Conversely, foreign-ownedfirms in Canada tend to export less than domestic food firms (for example, Vaughn,1995; West & Vaughn, 1995).The contribution of foreign-owned firms to exports may also be indirect, as a

result of spillovers from foreign-owned to domestic firms (Aitken et al., 1997;Greenaway et al., 2004; Kneller & Pisu, 2007). The proposition is that domestic firmsbecome more export-oriented, where there are MNEs present in the domesticmarket, because MNEs cannot protect their firm specific assets completely. Aitkenet al. (1997) propose a model in which domestic firms learn from MNEs thoughinformation externalities. Because MNEs are part of an international network, theyhave superior knowledge and experience, and can benefit from international networkeconomies in international marketing and servicing. The transferal of this knowledgeis treated as a spillover, and lowers the foreign distribution costs for domesticexporters. Greenaway et al. (2004) extend the model to include spillovers to bothproduction and distribution costs. The presence of MNEs promotes domesticexports via information, competition, and imitation spillovers.



Empirical evidence in support of indirect effects is provided in Aitken et al. (1997)for Mexico, Kokko, Zejan, and Tansini (2001) for Uruguay, and Greenaway et al.(2004) for UK manufacturing. Kneller and Pisu (2007) find export spillover effectsfor the UK and distinguish between intra- and interindustry effects. Intraindustryeffects are found to depend on the export orientation of MNEs. Studies in which theeffect was found to be negative or insignificant are Ruane and Sutherland (2005) forIrish manufacturing industries, Bernard and Jensen (2004) for U.S. manufacturing,and Barrios, Gorg, and Strobl (2003) for the Spanish case. Ruane and Sutherland(2005) find that both the export decision and export intensity of domestic firms isaffected negatively by the export intensity of foreign-owned firms. They argue thatwhere FDI is export-platform by nature, MNEs operate in isolation from domesticfirms, and hence there is less chance for spillover effects to occur. A negative effectmay imply that foreign-owned firms tend to establish by acquisition in industrieswhose structures are oligopolistic, and there is no increased competition that mayfacilitate entry into export markets.In summary, previous literature provides support for foreign-ownership status as a

determinant of export involvement for firms. There is, however, mixed evidence forindirect effects from foreign presence to the export behavior of domestic firms.

4. ANALYTICAL FRAMEWORK

We adopt firm-level determinants of export behavior as presented in Aitken et al.(1997) and Greenaway et al. (2004). In this model, firms are assumed to maximizeprofits and can produce for either or both of the foreign and domestic markets. Totalcosts are given by:

hðqd1qf Þ1mdðqdÞ1mf ðqf Þ

where q represents quantity, and subscripts d and f denote domestic and foreignmarkets, respectively. Costs consist of two components: production (h) anddistribution for both domestic and foreign markets, (md and mf). The focus of ouranalysis is on the effect of the concentration of export activity on foreign distributioncosts, implying that spillovers from the concentration of export activity may reduceforeign distribution costs. Defining the local concentration of export activity as GEX,and the export activity of MNEs to be GMNE, positive export spillovers exists if:

@mf ðqf Þ

@GEX

� 0 and@mf ðqf Þ

@GMNE

� 0:

The cost functions are assumed to take the form:

hðqd1qf Þ ¼a

2ðqd1qf Þ

21gðqd1qf Þ

and

mi ¼bi

2q2

i 1ciqi for i ¼ d or f

where a, g, bi, and ci are scalar parameters. As in Aitken et al. (1997), g and ci arefunctions of the cost variables that firms take as given in their output decision:g5 g(X), cd 5 cd(X,Zd), and cf 5 cf(X,Zf,GEX,GMNE), with X representing costs



common to both markets and Z representing costs specific to markets.A representative firm’s production decision is given by the solution to:

maxqd ;qf

pdqd1pf qf � hðqd1qf Þ �md ðqd Þ �mf ðqf Þ

s:t:qd ; qf � 0

where p represents price. Theoretically, output could be zero in either market.However, in our database all firms produce for the domestic market, but not all areinvolved in export activity. Accordingly, as in Aitken et al. (1997), only thepossibility of a corner solution for qf is considered by defining a continuous latentvariable for the decision to produce exports, q�f : q�f ¼ qf if qfj40 and q�f ¼ 0otherwise.The solution to the firm’s maximization problem is a simultaneous system of

export and domestic output equations with a censored variable. The system ofequations derived from the first-order conditions is:

qd ¼1

a1bd

ðPd � aq�f � gðX Þ � cdðX ;ZdÞÞ ð1Þ

q�f ¼1

a1bf

ðPf � aqd � gðX Þ � cf ðX ;Zf ;GEX ;GMNEÞÞ ð2Þ

Greenaway et al. (2004) extend the model to include competition spillovers, whichoperate via the relative importance of foreign firms in the market (O), anddemonstration spillovers from the innovative activities of foreign firms (C), such thatg5 g(X,O,C). Increased foreign presence generates competitive pressure that causesfirms to reduce production costs. Demonstration (or imitation) spillovers may arisefrom innovation activity by foreign-owned firms if domestic firms imitate the moretechnologically intensive MNE activity. This may increase efficiency and reduceproduction costs of domestic firms. The empirical approach of Greenaway et al.(2004) is based on a two-step Heckman selection model to determine the exportdecision and the export intensity of domestic firms as a function of firmcharacteristics, and variables that represent the presence of MNEs. We have nodata on export intensity, but instead model the export decision alone as in Aitkenet al. (1997).For empirical estimation Equations 1 and 2 can be written:

qdj ¼ a1pd1a2q�fj1a03Zdj1a04Xj1udj ð3Þ

q�fj ¼ b1pf 1b2qdj1b03Zfj1b04Xj1b5GEXj1b6GMNEj1ufj : ð4Þ

In Equations 3 and 4 the subscript j refers to the firm, Zij is a 1�K vector of marketspecific cost variables, Xj is a 1� J vector of cost variables common to domestic andforeign markets, a3 and b3 are 1�K vectors of coefficients, a4 and b4 are 1� Jvectors of coefficients. Our focus is on the export decision Equation 4. Byconstructing a dummy variable, yj such that yj 5 1 if qfj40 and yj 5 0 otherwise, theexport function (2) can be transformed into a reduced form probit model:

Prðyj ¼ 1Þ ¼Pr½b1pf 1b2ða1pf 1a03ZdjÞ1b03Zfj

1ðb4a041b04ÞXj1b5GEXj1b6GMNEj1vj40� ð5Þ



where vj 5 b2udj1ufj. The model allows the probability that a firm is an exporter to beestimated as a function of variables that represent export spillovers from foreign-owned firms, and variables representing costs, prices and trade. We also include firmcharacteristics (of which foreign-ownership status is a focus). The addition of firmcharacteristics variables is based on the empirical literature that suggests that factorsinternal to firms need to be included to account for export behavior (for example,Chetty & Hamilton, 1993).

5. DATA, EMPIRICAL MODEL, AND RESULTS

5.1. Data

We use the business register compiled and maintained by Dun and Bradstreet (DB), as itallows export and foreign ownership status to be linked at the firm level. The DB registeris a cross-section data set for the year 2005 of information on firms in the food andbeverage manufacturing sector. The register consists of information on 2,349 firms andincludes business name, four-digit Australian Standard Industrial Classification Codes(ANZSIC) subdivision 21 (food, beverage and tobacco manufacturing), number ofemployees, age of the business, parent details, and importer and/or exporter status. Ofthe 2,349 firms, 192 are foreign-owned. One possible drawback is that the classification ofFDI in the DB database is not exact, and may be understated. The FDI definition allowsfor a 10% threshold for foreign ownership of ordinary shares of a firm. In the DB dataset, firms indicate whether they have a parent firm, and if so, its nationality. The 10%threshold allows for controlling interest, but in food manufacturing most firms aremajority-owned, so this problem may not be of much magnitude in this data set.Accordingly, the database entries were checked and firms reclassified as foreign-owned, ifit could be established that there was at least 10% foreign ownership. It is possible thatother types of ownership structure, such as cooperatives, might limit export participation,but there is no information in the DB database on them.We define an MNE to be a firm with at least 10% foreign equity ownership. The

dominant source countries of FDI in the data base are USA (30%), UK (15%), NewZealand (16%), and Japan (10%). These reflect, among other things, both historicalties and geographic proximity.We present descriptive statistics from the data in Table 1. The industry groups

with the highest proportion of exporting firms are seafood products, plant andanimal oil products, and sugar refining. Alcoholic beverages, soft drinks, dairy, meatand cereal products, are the next largest groups. Industries with the smaller numbersof exporters include bakery products, snack foods, animal feed and foodpreparations. An obvious point of interest is any variation of FDI across industriesin this sector which, in the DB data base, can be measured by the percentage of firmsthat have foreign ownership by ASIC groupings. There is foreign ownership in mostgroups, and the sector average is 11%, but the percentage of foreign-owned firmsvaries somewhat across groupings. It is largest in cereal products, soft drinks, dairyproducts, and processed fruit. In terms of the distribution of FDI, this is a somewhatsimilar picture to that of Canada (Vaughn, 1995), the UK (Giulietti, McCorriston, &Osborne, 2004) and Greece (Anastassopoulos & Trail, 1998). In terms of total FDIwithin the sector, the highest concentration of foreign-ownership is in alcohol, meat,and dairy. As FDI is not evenly distributed across industries, it is likely that



spillovers from FDI may not be expressed among leading export industries. Indeed,there is no foreign presence in sugar refining, an industry in which almost half thefirms export, although there is a reasonable foreign presence in dairy, processed fruit.and cereal products. These are among the leading export industries as measured byexport participation in the DB database.

5.2. Empirical Model

The probit model (Equation 5) is used to estimate the probability that a firmparticipates in exporting as a function of spillover variables, and variablesrepresenting costs, prices, and trade. The regression was estimated for the sector(2,349 observations), and because variation in export participation across industriesis an important consideration, separate regressions were estimated for industries forwhich there were sufficient numbers of observations. In the probit model, foreign-ownership status is represented by a binary variable (fown). To test for spillovereffects four variables measured at the ANZSIC 4-digit level are constructed by state.There are 50 separate industries at the ANZSIC 4 digit level. Australia has six statesand two territories. There are no food manufacturers in the DB data base in theNorthern Territory, and only 10 firms in the Australian Capital Territory, so thesewere included as part of the state of New South Wales. As a result, there are sixstates in the analysis. First, following Aitken et al. (1997), we include three spillovervariables. Their basic geographic concentration measure is

ðState� Industry Share ofNational Industry FirmsÞ

ðState Share ofNational Sector FirmsÞ

This measure controls for variation in the size of industries nationally, and for caseswhere the state-industry is large because the state is large. The three variables are

TABLE 1. Descriptive Statistics on Exports and Foreign Ownership by Industry

Industry descriptionNumber of

firms % exporting% foreign-owned

Foreign-owned firmsas a proportion oftotal foreign firms

Meat products 305 0.32 0.07 0.11Dairy products 152 0.34 0.14 0.11Alcoholic beverages 412 0.37 0.09 0.19

Processed fruit 198 0.38 0.12 0.09Cereal products 52 0.42 0.19 0.05Animal feeds 148 0.21 0.09 0.07

Bakery products 247 0.12 0.06 0.08Sugar products 17 0.47 0.00 0.00Confectionary 132 0.27 0.08 0.06

Plant and animal oils 53 0.49 0.04 0.10Soft drinks 94 0.38 0.16 0.08Seafood products 63 0.56 0.03 0.01Snack foods 61 0.15 0.05 0.02

Food preparations NEC 415 0.19 0.06 0.13Total 2349 1.00

Note. NEC5 not elsewhere classified (includes items such as prepared meals).



MNEXact, EXact, and OAact. First, MNEXact measures the local concentration ofMNE export activity, and is constructed as the state-industry share of MNEexporters in national industry exporters, relative to the state share of national sectorexporters. Second, EXact, which provides a measure of the concentration of totalexport activity, is calculated as the state-industry share of national industry exportersrelative to the state share of national sector exporters. This variable controls forcases where a state industry may have many exporting firms just because the statehas many exporters. Finally, OAact is a measure of the overall concentration ofeconomic activity, and is used to control for other spillovers and ‘‘site specific factorsof production’’ that may confound the effect of export spillover variables. It ismeasured as the state-industry share of national industry firms relative to the stateshare of national sector firms. To allow for the possibility that there may be nationalcompetition spillovers as in Greenaway et al. (2003), we construct an industry levelvariable, forpres. This variable reflects industry presence of foreign-owned firms, andis constructed as the proportion of foreign-owned firms in each industry. Thisvariable may pick up competitive forces that place downward pressure onproduction costs.We include firm characteristic variables in the probit model from the DB data-

base. They include size, importer status, age, vertical integration, industryconcentration, and diversification. Import activity and diversification should bepositively related to exporting. Importing can give firms knowledge and experiencein international activity. Diversification of a firm can be positively related toexport participation, both as a result of strategic behavior, and economies ofknowledge and experience across industries (Lefebvre & Lefebvre, 2001). Size andage are theoretically interlinked in firm life cycle arguments. Firms tend to seekgrowth initially in domestic markets, and after attaining some size, pursue exportsales growth (Bonaccorsi, 1992). It is suggested that larger and older (moreexperienced) firms are better positioned to export because of the required resources.Also, smaller firms are often considered to lack the ability to absorb risk associatedwith exporting.A set of industry and state dummies are also included in the model. Because there

are 50 categories by ANZSIC classification at the 4-digit level, 14 industry dummieshave been created by aggregating to the 3-digit level (for example, the dairy dummyaggregates observations for fluid milk, creamery butter, dried milk products, and icecream). Exceptions are the ANZSIC 203, where animal feed is separated fromcereals, ANZSIC 208 where soft drinks were separated from alcoholic beverages,and ANZSIC 209, where seafood, snacks and food preparations were separated.These separations were determined where adequate observations to estimate industryregressions existed.Equation 5 also includes variables on costs and prices. Unfortunately, these are

unavailable at the firm level in the DB data base. Instead, the DB database issupplemented by industry data from the Australian Bureau of Statistics (ABS) onwages, capital expenditure, and trade. The domestic price and export price indicesand cost variables are deflated by a producer price index. Trade factors that affectthe overall export profile of the industries are accounted for by inclusion of ameasure of trade orientation, as suggested in Howe (1994) that should reflect to somedegree price competitiveness of individual industries. The variable names anddefinitions are presented in Table 2, along with summary statistics in Table 3.



Finally, in estimating spillover effects, Aitken et al. (1997) use a two-stagemaximum likelihood estimator to address potential endogeneity of the spillovervariables, whereas other studies have not accounted for such a potential in this way.Aitken et al. (1997) use instruments that represent factor intensity and relative laborcosts as determinants of foreign investment, and find their spillover variables to be

TABLE 2. Variables Names and Definitions

Variable Definition Source

fown Binary variable that takes the value one if a firm isforeign owned

DB

MNEXact (State-industry MNE exporters/national industryexporters)/state share of national sector exporters

DB

EXact (State-industry share of national industry exporters)/

state share of national sector exporters

DB

OAact (State-industry share of national industry firms)/stateshare of national sector firms

DB

forpres Proportion of foreign-owned firms by industry DBexporter Binary variable that takes the value one if a firm exports DBsize Number of employees per firm /100 DB

size2 Squared term for size /1000 DBimporter Binary variable that takes the value one if a firm imports DBage Number of years a firm has been in operation DBdiv Binary variable that takes the value one if a firm is

involved in two or more 4-digit categories

DB

vert Binary variable that takes the value one if a firm hasbackwards linkages into agriculture or forward

linkages into retail as defined by 4-digit code

DB

trade Export to imports ratio of each industry scaled by thesame ratio for the total manufacturing sector

ABS

Cat.No.5368rw Wage per employee ($’000) deflated by the producer price

indexABS

Cat.No.8221rk Net capital expenditure ($m) deflated by the producer

price indexABS

Cat.No.8221

dprice Domestic price index for food groups ABSCat.No.6401

fprice Export price index for food groups ABS

Cat.No.6457conc Binary variable that takes the value one if a firm is from a

concentrated industryDB

industry andstatedummies

14 industry dummies were created from the ANZSIC 4-digit industry classifications by aggregating similargroups to the 3-digit level, e.g., meat packing plants,prepared meats, and poultry processing were

aggregated to form a dummy for meat processing

DB



endogenous. Although the U.S. data used for instruments in Aitken et al. (1997) areavailable by industry for the food manufacturing sector, to our knowledge no suchdata exist for the other major investors who comprise about half of the foreign-owned firms in the Australian food manufacturing sector. Nor are there data oncapital stock by industry. Preliminary first-stage estimation using U.S. laborvariables indicated that these were weak instruments for our data set. Econometricproblems can obviously arise if a two-stage procedure is used when instruments areweak. In this case the instrumental variables estimators can be badly biased, andeven for large samples estimation is not reliable (Hill, Griffiths, & Lim, 2008). Due toa lack of availability of appropriate instruments, we cannot address this issue in ourstudy. This is in keeping with Greenaway et al. (2004), who argue that the literatureon firm-level determinants of exporting suggest that endogeneity is unlikely to be aserious problem. However, this issue does represent a caveat for the current analysis.

5.3. Results

The regression estimates at the sector level for all firms and for domestic firms onlyare presented in Table 4. Wald tests for the industry and state dummies indicate thatregional effects, but not industry effects, could be excluded from the model. Resultsfor separate industries are displayed in Table 5. Industry level variables are excludedfrom these regressions.Turning first to foreign ownership effects, the estimates in the first column of

Table 4 indicate that the coefficient on fown is insignificant, implying that foreignownership does not help to predict whether or not a firm will be involved inexporting. Foreign ownership neither increases nor decreases the probabilityof export participation. This result holds across the industry regressions in Table 5,except for the meat regression and the bakery regression. In the meat regression, thecoefficient on fown is positive, but only significant at the 10% level, and for thebakery regression the coefficient is negative and significant. The insignificance offown in most of the regressions appears inconsistent with the evidence provided inPhilp and Wickramasekera (1995) and Wondu (2000) for Australia, of an associationof export behavior with foreign-owned food manufacturing firms. The statisticalinsignificance of the coefficient on fown may, however, be consistent with that

TABLE 3. Summary Statistics

Variable M SD Max Min

size 99.23 422.71 8700 6age 23.41 22.61 168 1

trade 53.89 135.08 435.25 0.32MNEXact 0.0003 0.0004 0.006 0.00EXact 0.99 0.69 4.45 0.00

OAact 1.26 0.81 8.20 0.09forpres 0.083 0.06 0.46 0.00rw 39.97 6.54 69.48 23.24

rk 247.83 175.05 551.28 11.11dprice 151.42 26.47 399.00 100.00fprice 121.95 19.59 137.80 57.10



presented in Pritchard (1995, 2005), where the corporate strategy of foreign affiliatesis to seek rents from highly concentrated and stable domestic markets, with at most aminimum of involvement in exports. Foreign investors are motivated to earn profitsfrom domestic markets that can be transferred internationally for investment and taxstrategies, and this is where the competitive advantage of firms that operateinternationally lies. Accordingly, any distinction in terms of performance gapsbetween foreign- and domestically owned firms appears of less consequence, if thedomestically owned firm also has foreign operations. To further explore thisobservation, the fown variable was replaced with an MNE variable that includesboth foreign- and domestically owned MNEs. However, because there are only a fewAustralian food sector MNEs, the results (available on request) appeared robust tothis change in definition of the ownership variable.Focusing next on the spillover variables, the coefficient on MNEXact is

insignificant at the sector level, and for the industry regressions. Local concentrationof MNE export activity is unimportant in predicting the probability that a firm is anexporter. In contrast, the concentration of total export activity, EXact, has a positiveand significant coefficient at the sectoral level, and this effect also appears robustacross most industry regressions. The variable forpres, that likely captures nationallevel competition spillovers, has a negative and insignificant coefficient, implyingthat the export decision of domestic firms is unaffected by the presence of foreignfirms in the sector. This is in contrast with research for the UK by Greenaway et al.

TABLE 4. Probit Sector Regression Results (Dependent Variable exporter)

Variable All firms Robust z-stat Domestic firms only Robust z-stat

fown 0.093 (0.756)EXact 0.307 (5.149)�� 0.302 (4.719)��

MNEXact 68.166 (0.674) 3.271 (0.025)OAact �0.054 (�0.894) �0.048 (�0.704)forpres �0.208 (�0.267) �1.078 (�1.276)

div 0.447 (4.681)�� 0.494 (4.841)��

vert �0.089 (�0.825) �0.108 (�0.926)size 0.095 (3.896)�� 0.192 (4.448)��

size2 �1.613 (�2.912)�� 4.172 (�3.407)��

importer 1.163 (12.134)�� 1.142 (10.797)��

age 0.008 (5.322)�� 0.007 (4.230)��

trade 0.0007 (1.229) 0.0006 (1.175)conc �0.229 (�1.807)� �0.235 (�2.067)��

priced 0.001 (0.559) 0.003 (0.838)pricef 0.002 (0.394) 0.001 (0.281)

rk �0.0007 (�1.394) �0.0006 (�1.560)rw �0.014 (�1.616)� �0.0038 (�0.405)constant �0.907 (�1.245) �1.439 (�1.848)��

McFadden R2 0.22 0.21N. obs 2349 2157Industry effects w2ð14Þ 56.87�� 69.57��

State effects w2ð6Þ 2.309 6.104

��Significant at the 1% level. ��Significant at the 5% level. �Significant at the 10% level.



TABLE

5.

ProbitIndustry

RegressionResults(D

ependentVariable

exporter)

Variable

Meat

allfirm

sMeat

dom.firm

sDairy

allfirm

sDairy

dom.firm

sAlcohol

allfirm

sAlcohol

dom.firm

sProcessed

fruitallfirm

sProcessed

fruitdom.firm

s

fown

0.599

�0.202

�0.119

0.093

(1.674)�

(�0.495)

(�0.417)

�0.126

EXact

�0.08

�0.204

0.888

0.566

1.24

1.012

5.311

�1.571

(�0.263)

(�0.722)

(3.036)��

(2.004)��

(3.541)��

(2.969)��

(2.480)��

(�0.546)

MNEXact

�48.66

25.311

3.526

31.56

�12.9

74.58

�12.45

16.906

(�0.835)

�0.514

�0.061

�0.565

(�0.561)

�0.896

(�1.130)

(1.690)�

OAact

�0.26

�0.402

�0.965

�0.764

�1.376

�0.826

�8.19

8.594

(�0.426)

(�0.768)

(�2.423)��

(�1.915)��

(�3.222)��

(�1.821)

(�1.713)�)

�1.245

div

0.325

0.221

0.677

0.798

�0.659

�0.117

1.108

0.973

�1.451

�0.932

(2.545)��

(2.724)��

(�1.591)

(�0.304)

(3.771)��

(3.209)��

vert

�0.396

�0.363

0.702

0.597

0.617

0.666

�0.602

�0.559

(�1.233)

(�1.138)

�1.468

�1.219

(3.011)��

(2.952)��

(�1.018)

(�0.860)

size

0.202

0.218

0.238

0.198

0.488

0.725

0.766

2.87

(3.087)��

(2.991)��

(2.377)��

�1.275

(3.709)��

(3.145)��

(1.765)�

(4.176)��

size

2�3.531

�3.961

�9.39

�7.102

�5.341

�5.794

�6.858

(�2.387)��

(�2.443)��

(�1.976)��

(�0.937)

(�3.500)��

(2.813)��

(�1.586)

importer

1.061

0.9815

0.593

0.638

0.864

0.824

1.213

0.912

(3.586)��

(3.182)��

�1.491

(1.618)�

(2.924)��

(2.624)��

(3.900)��

(2.676)��

age

0.005

0.005

0.004

0.007

0.0125

0.115

�0.005

�0.002

�1.194

�1.051

�1.024

�1.213

(3.209)��

(2.770)��

(�0.723)

(�0.344)

trade

0.0018

0.0012

�0.019

0.0255

0.054

0.127

�0.022

0.005

(2.508)��

(1.752)�

(�1.698)�

�1.49

�1.132

�0.94

(�0.448)��

�0.453

constant

�1.926

�1.287

�0.256

�0.478

�0.53

�0.773

0.992

�7.118

(�2.228)

(�1.225)

(�0.306)

(�0.585)

(�1.171)

(�1.673)

�0.428

(�2.076)��

McF

adden

R2

0.21

0.15

0.25

0.23

0.22

0.2

0.34

0.38

N.obs

305

283

151

131

412

376

148

131

state

effectsw2 ð

6Þ

7.38

10.01

5.25

6.01

4.29

6.73

5.56

7.34



TABLE

5.

Continued

Variable

Confectionary

allfirm

sConfectionary

dom.firm

sBakery

allfirm

sBakerydom.

firm

sAnim

alfeed

allfirm

sAnim

alfeed

dom.firm

sFoodprepNEC

allfirm

sFoodprepNEC

dom.firm

s

fown

�0.234

�1.497

0.67

0.135

(�0.357)

(�2.256)��

�1.365

�0.367

EXact

�0.044

0.127

0.254

0.376

�0.634

1.012

0.591

0.567

(�0.222)

�0.658

�0.427

�1.22

(�1.121)

(2.969)��

(2.866)��

(2.628)��

MNEXact

�91.648

�72.915

�78.81

�15.75

96..66

74.58

325.91

470.13

(�0.137)

(�1.277)

(�0.397)

(�0.081)

�0.152

�0.896

�0.419

�0.578

OAact

0.114

0.086

1.824

1.69

1.837

�0.826

0.097

0.112

�0.341

�0.265

�1.549

�1.435

�1.25

(�1.821)

�1.376

�1.544

div

0.544

0.491

0.519

0.362

�0.183

�0.117

0.546

0.563

�1.408

�1.212

�1.545

�1.138

(�0.464)

(�0.304)

(2.262)��

(2.063)��

vert

�0.928

�0.863

�1.708

0.597

�0.734

0.666

�0.0222

�0.559

(�1.425)

(�1.109)

(�3.831)��

�1.219

(�1.702)�

(2.952)��

(�0.092)

(�0.860)

size

1.207

1.239

0.146

0.545

0.298

0.725

�0.021

0.895

(2.707)��

(2.189)��

(2.173)��

(3.104)��

�1.567

(3.145)��

(�0.264)

(2.497)��

size

2�14.95

�17.999

�1.688

�13.48

�8.346

�5.794

�0.177

�17.87

(�2.529)��

(�21.399)

(�1.681)�

(�2.493)��

(�0.867)

(2.813)��

(�0.073)

(�2.192)��

importer

1.566

1.317

2.195

1..968

1.778

0.824

1..364

1.502

(3.960)��

(3.248)��

(3.936)��

(3.588)��

(4.682)��

(2.624)��

(6.428)��

(6.387)��

age

0.009

0.009

0.011

0�0.004

0.115

0.0089

0.011

�1.355

�1.2

�1.583

�0.0004

(�0.638)

(2.770)��

�1.447

�1.52

constant

�2.986

�1.553

�4.872

�3.551

�13..92

�0.773

�2.193

�2.44

(�2.884)

(�3.246)��

(�4.075)��

(�4.025)��

(�1.336)

(�1.673)

(�7.425)��

(�7.75)��

McF

adden

R2

0.29

0.29

0.25

0.29

0.33

0.2

0.24

0.26

N.obs

132

122

247

232

148

135

415

390

state

effectsw2 ð

6Þ

4.59

6.02

5.81

7.23

7.93

9.05

6.76

7.56

Note.z-Statisticsare

given

inbracketsusingrobust

standard

errors.NEC

5�� S

ignificantatthe1%

level.��

Significantatthe5%

level.� S

ignificantatthe10%

level.



(2003), but in keeping with results in Ruane and Sutherland (2005) for Ireland, andBarrios et al. (2003) for Spain.The absence of spillover effects may mean that foreign firms operate to some

extent in isolation from domestic firms, albeit seemingly unlikely for the Australianfood manufacturing case, where production tends to be clustered in regional areas.Ruane and Sutherland (2005) argue that, where foreign-owned firms are entirelyexport-oriented, there will be no spillover effects from competition in the domesticmarket. However, our findings failed to support this FDI motive.Of the significant firm characteristic variables, all except conc, have positive effects

on the probability of export participation in both sector regressions. Firms frommore concentrated industries are less likely to participate in exporting. If a firm hasdiversified production, it is more likely to be an exporter. This is consistent with theproposition that firms that develop a strategy of product diversification might have acompetitive advantage in exporting that is generated from economies of scope(Malmberg, Malmberg, & Lundequist, 2000). Size also seems to promote exportinvolvement, and the coefficients of size and size2 indicate that the marginal effect ofsize on exporting decreases beyond a certain size level. Exporting may simply not beattractive for large firms oriented to concentrated domestic markets (Bleaney &Wakelin, 1999; Pritchard, 1999). Involvement in importing increases the odds infavor of export participation for all regressions. This variable captures the mostconsistent effect across all industries. There is, however, no information on thesource or nature of the imports in the DB database. In the Australian case, this maypartly reflect the fact that much of plant and machinery is imported.Of the industry variables, industry real wages have a small negative effect on the

probability of exporting, and firms are less likely to be exporters, if they come formconcentrated industries. The variable reflecting the trade orientation industries,trade, is insignificant. This is consistent with Bleaney and Wakelin (1999), who alsoconclude that firm characteristics are a major determinant, but find only weaksupport for trade theoretic effects for UK manufacturing firms.The regression probability analysis for all firms, and across industries presented,

indicates that foreign ownership neither detracts from, nor helps predict exportparticipation. Positive spillovers are found from total local export activity, but notlocal concentration of MNE export activity. At the national level, there is noevidence of competition spillovers. Important firm characteristic factors arediversification, size, and whether a firm is involved in importing or not. Theindustry analysis indicates that, with the exception of import and size, the statisticaland economic importance of other factors varies across industries.

6. CONCLUSION

The degree to which foreign-owned firms contribute to Australian trade is animportant issue. In this article, we have examined whether the probability that a firmparticipates in exporting in the Australian food and beverage manufacturing sector isaffected by ownership structure. In addition, we have identified various firmcharacteristics that are common to export participation. Results indicate that foreignownership neither increases nor decreases the probability that a firm will be involvedin exporting. This finding is broadly consistent across industry subgroupsinvestigated here, with the exception of meat and bakery products.



We find no evidence of competition or export spillovers from MNEs. Informationabout exporting does not seem to flow through to domestic firms from MNEs. Thismay simply imply that there are no spillovers because MNEs can operate to a degreein isolation, and protect their firm specific assets. The finding may also imply thatsunk costs of exporting that spillovers are supposed to reduce may not be thatimportant. Indeed, in a recent Australian Bureau of Statistics (ABS) survey ofAustralian exporters, about two-thirds were irregular exporters, suggesting that sunkcosts of entry and exit may not be that great (ABS, 2000). Informational barriers toentry in export activity may play a minor role, with entry into foreign markets moreresponsive to macroeconomic or other conditions. Consistent with this observation,Bonacorsi (1992) finds that entry and exit into exporting activity is quite widespread,implying that it is less costly than is generally proposed in the literature.The findings on export participation and the existence of spillovers from MNEs

might also reflect trade policy in combination with economic factors that affect foodmanufacturing trade (such as comparative advantage and the distribution of FDI).The degree of tariff protection typically increases with the level of transformation offood products, and MNEs are more heavily involved in production of these types ofgoods, with the exception of meat processing. Furthermore, Australia shares nocommon border with other countries, a factor that often encourages trade in suchproducts. Comparative advantage also plays a role. Australia is relatively wellendowed with agricultural inputs for food manufacturing, and has the establishedinfrastructure to make it an attractive location for export-platform FDI. However,these factors need not automatically translate into comparative advantage in theproduction of processed foods, as relative prices of other inputs such as labor,marketing, packaging, and transport services are also involved. The food-processingsector is generally regarded to have a high revealed comparative advantage, but thatthe situation differs across industries. The Australian Bureau of Agricultural andResource Economics (ABARE, 2006) provides revealed comparative advantageanalysis, indicating that Australia has advantage in meat processing, dairy, but adisadvantage in categories such as fruit and vegetable processing and cerealproducts. Export outcomes might have more to do with the comparative advantageof the various industries, or factors other than its foreign-ownership structure. Thus,tariff escalation, Australia’s geographic position, comparative advantage, and thedistribution of FDI within food manufacturing may inhibit spillover effects.We emphasize that our findings are for the Australian case, and believe that

spillovers are more likely to be found for country cases, where domestic firms haveless connections or experience in foreign markets. In such cases, MNEs may in factact as export catalysts.This study suffers a number of limitations, which are largely data driven. The

approach would benefit greatly from firm-specific measures of costs and prices,ownership advantages such as R&D expenditure, productivity measures, morespecific trade information, and information on the export history of individual firms.The latter would most likely embody managerial attributes, such as the preparednessto adapt products to foreign demand and legal requirements.The field is obviously wide open for further work despite these limitations. Our

finding indicates that foreign ownership is not important in predicting export statusof a firm, but additional data are required to shed light on this observation.Information on the proportion of exports to total firm sales as opposed to



information on export participation may be more useful. It might still be the casethat domestically owned and foreign-owned firms exhibit differing ratios of exportsto total sales. The consistency of the effects of size and importer status at theaggregate and industry level, and to a lesser degree diversification, also deservesfurther research attention. These are particularly interesting areas for research, albeitchallenging in terms of data requirements, as primary data will need to be compiledby the managers of firms, seemingly not a feasible undertaking.

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Shauna Phillips is an associate lecturer in Agricultural and Resource Economics, currentlypursuing a Ph.D. in Agricultural Economics, University of Sydney, Australia. She holds a

BAgrEc (Hons) (University of Sydney) and an MA (Hons) in Economics (University of NewSouth Wales). Her primary research interests are in the fields of macroeconomic linkages toagriculture, international trade, and foreign direct investment.

Fredoun Z. Ahmadi-Esfahani is an honorary associate professor in Agricultural and ResourceEconomics, University of Sydney, Australia. He holds a BS in Mathematics (University of

Oregon), an MA in Economics (San Francisco State University), and a Ph.D. in AgriculturalEconomics (University of Manitoba). His primary research interests are in the fields ofmarketing, international trade, development economics, and industrial organization.



Documents

Export market participation, spillovers, and foreign direct investment in Australian food manufacturing