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The World Economy (2008)doi: 10.1111/j.1467-9701.2007.01087.x

2008 The Authors

Journal compilation 2008 Blackwell Publishing Ltd, 9600 Garsington Road,

212 Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA

Blackwell Publishing LtdOxford, UKTWECWorld Economy0378-5920 2008 The Author Journal compilation Blackwell Publishers Ltd.2008XXXOriginal ArticlesCONTRIBUTION OF EXPORTINGRICHARD HARRIS AND QIAN CHER LI

Evaluating the Contribution

of Exporting to UK

Productivity Growth: Some

Microeconomic Evidence

Richard Harris and Qian Cher Li

University of Glasgow

1. INTRODUCTION

E

MERGING evidence on industrial restructuring using micro-based data from

the Annual Respondents Database (ARD) has shown that UK productivity

growth is increasingly the result of a market selection process, in which moreproductive entrants replace less productive establishments whilst high pro-

ductivity incumbents gain market share (Oulton, 2000; Disney et al., 2003a).

In particular, the study by Disney et al. suggests that between 1980 and 1992,

50 per cent of labour productivity growth and 8090 per cent total factor produc-

tivity (TFP) growth could be explained by what they term external restructuring

effects (i.e. the impact of market entry and exit as well as inter-firm reallocations

in market share).

1

Using comparable data and a similar approach, Harris (2004)

reports that over the 199098 period, the growth in manufacturing TFP did not

substantially benefit from incumbents improving or a reallocation of market

share from worse to better plants; rather TFP benefited mostly from the

The authors wish to thank UKTI for sponsoring this project and two anonymous referees for theirhelpful comments. However, all views expressed are solely the responsibility of the authors. Thiswork contains statistical data from ONS which is Crown copyright and reproduced with the per-mission of the controller of HMSO and Queens Printer for Scotland. The use of the ONS statisticaldata in this work does not imply the endorsement of the ONS in relation to the interpretation oranalysis of the statistical data. This work uses research datasets which may not exactly reproduceNational Statistics aggregates.

1

Note, and anticipating the results we present below, Disney et al. (2003a) use a different decom-

position approach to the one used here. They also cover a different (non-overlapping) time period,and their data source is the ARD (rather than FAME).

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CONTRIBUTION OF EXPORTING 213

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Journal compilation Blackwell Publishing Ltd. 2008

churning of plants whereby plants with higher TFP entered and those with

below-average TFP were more likely to exit.

None of these previous studies have considered the role of exporting firms in

contributing to productivity growth. Exporters are usually larger firms, withhigher productivity, higher capital intensity, faster growth and a more skilled

workforce (see Baldwin and Gu, 2004; Girma et al., 2004; and Greenaway and

Kneller, 2004, for recent evidence). Nevertheless, microeconomic evidence on

the exportingproductivity relationship still remains inconclusive, particularly on

the existence of productivity gains post-export market entry. As noted in a recent

survey:

the micro and macro evidence on exporting and growth would appear to be inconsistent: thereis weak evidence of a causal relationship between exports and productivity growth at the firm

level but a strong correlation at the aggregate level (Greenaway and Kneller, 2005).

However, this evidence is very likely to be reconciled when considering inter-

firm reallocations of resources towards more productive firms, which inter alia

we consider here.

Until now it has not been possible to assess the contribution of exporters to

UK aggregate productivity levels and growth, particularly in terms of restructur-

ing effects, due to data limitations.

2

Consequently, and as noted in DTI (2006),

there has to date been little evidence, particularly for the UK, that substantiates

the overall benefits from international trade, and therefore providing a rationale

for government intervention to help firms develop their exporting activities.However, in this study we are able to use a (weighted) FAME database to

consider, for the first time, the contribution of exporters to aggregate productivity

growth. We have constructed a dataset that distinguishes firms that enter and

exit the database (separately from those that are taken over by others as part of

mergers and acquisitions), and employed the approach taken by Haltiwanger

(1997) to decompose measures of productivity into various components that

represent the impact of resource allocations across surviving exporters and

non-exporters as well as the impact on productivity of the entry and exit of firms.

We consider both labour and total factor productivity, with the TFP measure

being preferred since it takes into account all factor inputs other than labour in

the production process. Labour productivity may increase because of greater

outsourcing or capital deepening, as firms substitute intermediate inputs and cap-

ital for labour, while the efficiency with which all inputs are used may not

necessarily increase (and possibly may even decline).

In summary, we show that in aggregate (and covering all sectors) exporting

firms contributed more to overall UK productivity growth than non-exporting

2

Note the Annual Respondents Database (ARD), the primary source of UK micro-data, does notcontain information on exporting activities.

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214 RICHARD HARRIS AND QIAN CHER LI

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firms (i.e. 2.32 per cent compared with 1.55 per cent per annum in terms of

labour productivity, and 1.27 per cent relative to 0.81 per cent per annum in

terms of TFP). This is made up of both intra-firm productivity improvements and

inter-firm reallocations of resources towards more productive exporting firms(which includes the impact of firm entry and exit). Such external restructuring is

especially important in the non-manufacturing sector, suggesting overall that

government policy aimed at boosting exporting needs to take account of the

different channels through which productivity growth occurs across different

sectors.

A major contribution of this paper lies in the dataset used: to obtain data that

are representative of the population of firms operating in the UK (for all market-

based sectors), our analysis is based on a weighted FAME dataset using weights

compiled from the ARD (at the three-digit industry SIC by five size-band levels),

as the unweighted FAME database is unrepresentative of small- to medium-sized

enterprises and therefore cannot produce results that can be generalised to the

UK level.

The rest of the paper is structured as follows. In Section 2, we briefly review

the literature related to export-market dynamics and the linkage between

exporting and aggregate productivity growth. In Section 3 we describe the

weighted FAME dataset used for this study and highlight some data issues. This

is followed by a discussion of methodological issues associated with productivity

decomposition, together with our results (Section 4). The last section concludes.

2. EXPORTING, MARKET DYNAMICS AND AGGREGATE PRODUCTIVITY:

EVIDENCE FROM THE LITERATURE

From a policy perspective, it would seem that there is substantial international

evidence of the benefits from international trade which, at least in part, should

provide a rationale for government intervention to help firms develop their

exporting activities (for the UK see especially Chapter 3 in DTI, 2006).

3

These

benefits are largely linked to the higher productivity of exporters, which leads tohigher overall UK productivity growth through some or all of the following:

(i) exporters achieving relatively higher productivity before they begin selling

overseas which results in them having higher productivity growth post-entry (the

so-called self-selection effect see below); (ii) exporting firms becoming more

productive over time through a learning-by-exporting effect; (iii) intra-industry

(i.e. inter-firm) resource reallocations for firms that remain in operation in a

3

The further issue of whether there are grounds for policy intervention only in the case of market

failures or whether intervention is justified in more general terms is also relevant but discussedelsewhere (see Harris and Li, 2005).

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certain period away from non-exporters to higher productivity exporters; (iv) the

entry of higher productivity exporters, i.e. new firm start-ups that immediately

or very soon sell to international markets (what have been called born global

companies in the literature see Oviatt and McDougall, 1995, and the review ofthis literature in Harris and Li, 2005); and (v) the shutdown of lower productivity

firms (which may be exporters but are more likely to be non-exporters who

have the lowest levels of productivity of all, causing them to exit first). The

contribution of (i) + (ii) is the within (or intra-) firm effect of higher produc-

tivity exporters contributing to higher overall UK productivity growth because

they internally improve their levels of efficiency and/or innovativeness; whereas

(iii)(v) are concerned with external restructuring due to the reallocation of

resources between firms that remain in operation throughout and/or through

creative destruction (cf. Schumpeter, 1950).

The earliest studies concerned with the relationship between exports and

productivity growth (and thus the debate on export promotion policies) used a

macroeconomics approach, from the conventional HeckscherOhlin model to

new trade models.

4

However, these macroeconomics-oriented models, arguably,

only provide a limited understanding of firms exporting behaviour and thus have

a limited role in informing policy, which is to a considerable extent targeted at

individual firms. In contrast, the last decade has seen a surge of interest in

studying the microeconomic evidence, taking into account the importance of

heterogeneity amongst firms. This emphasis on the firm-level evidence has

been partly triggered by the availability of data at firm and/or plant level, as wellas recent developments in the use of theoretical modelling and econometric

techniques to exploit these usually more intricate micro-data.

a. An Intra-Firm Perspective: Exporting and Firm Performance

Research on the exportingproductivity relationship was initially empirically

driven, and it is universally found that exporting is positively associated with

firm performance (for recent surveys of the literature, see Greenaway and Kneller,

2005, 2007; Lpez, 2005; Wagner, 2007). Nevertheless, despite this positivelinkage, there is still much controversy about the causal direction of this link,

which is often examined empirically by testing two competing but not mutually

exclusive hypotheses, viz. self-selection and learning-by-exporting.

5

Underlying the self-selection hypothesis are the notions of sunk cost and

firm-level heterogeneity. Since international exposure is associated with more

4

For a review of macroeconomic evidence on trade and growth, see Lpez (2005).

5

In particular, Greenaway and Kneller (2005, Table 1) and Wagner (2007, Table A1) provide

summaries of empirical findings on the exportproductivity nexus and the causality issue usingfirm-level data.

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intensive competition, firms that internationalise are forced to become more

efficient so as to enhance their survival characteristics. Additionally, the existence

of sunk entry costs means exporters have to be more productive to overcome

such barriers to entry before they can realise expected profits, and these fixedcosts have been incorporated into recent theoretical modelling, such as those

undertaken by Clerides et al. (1998), Bernard et al. (2003) and Melitz (2003),

who maintain that exporting firms need to be more productive before entering

the export market in order to overcome the sunk costs of entering overseas

markets. Notably, and perhaps more importantly from a policy perspective, it has

been argued that firms do not naturally consider exporting just because they

have reached a certain necessary productivity threshold; in fact, such self-

selection could be a conscious decision, involving a purposeful improvement of

productivity as a planned strategy to enter export markets (Lpez, 2004, 2005).

For instance, Lpez (2004) develops a simple model in which forward-looking

firms need to invest in new technology in order to become exporters, and the

adoption and assimilation of this technology require them to be more productive

to begin with. Ample empirical evidence has confirmed that this is indeed the

case: in more than 30 studies reviewed in Greenaway and Kneller (2005),

covering a wide range of countries, self-selection is universally found to be

important.

The other direction of this causality concerns the learning effect associated

with exporting: the exposure to more competitive international markets

intensifies firm performance, and therefore gives productivity a further boost, dueto knowledge accumulation, technology transfer, competition effects and the like.

If this fails to hold, there are important policy implications if better firms do

self-select into export markets, and exporting does not further boost productivity,

then export promotion policies could simply be a waste of resources (involving

large-scale dead-weight and possibly even displacement effects given that firms

that export usually also sell to domestic markets).

6

The learning-by-exporting

proposition has, in general, received less support in the literature, with only

significant learning effects found in particular groups, such as younger exporters

(Baldwin and Gu, 2003, 2004, for Canadian manufacturing; Greenaway and Yu,2004, for the UK chemical industry), exporters in small, open and highly export-

oriented economies (Hansson and Lundin, 2004, for the Swedish manufacturing

sector), or firms serving advanced, high-wage export markets (Damijan et al.,

2005).

It is worth noting that the paucity of evidence on this learning effect could

in large part be due to methodological issues involved when testing for the

6

Robust empirical evidence shows that exporters tend to sell very small fractions of their outputabroad (Roberts et al., 1995; Aw et al., 1997).

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productivity effect of exporting, such as sample selectivity.

7

The latter suggests

that participants in export markets may possess certain characteristics (e.g.

superior human capital, greater absorptive capacity) such that they would achieve

higher productivity compared with non-participants even if they did not enterexport markets, and thus productivity growth is correlated with the decision to

participate in global markets (but is not caused

by selling in international

markets). Nevertheless, significant post-entry productivity gains in exporting

firms have been reported in recent studies that overcome problems of selectivity

bias, such as Girma et al. (2004) who employ matching techniques and UK

manufacturing data, and Harris and Li (2007a) who use three distinct approaches

(instrumental variable, control function and data-matching techniques) applied to all

market-based sectors in the UK.

b. An Inter-Firm Perspective: Export Market Dynamics and

Aggregate Productivity

Self-selection and the learning-by-exporting hypotheses reviewed above

have attempted to assess only the linkages between exporting and within-firm

productivity growth. Since entry (and exit) in export markets inherently involves

changes in market shares, and thus industrial restructuring, in order to evaluate

or justify trade-promotion policies it is equally important to look at the impact

of firm-level exporting on intra- or inter-industry reallocations of resources and

therefore aggregate productivity growth. This approach provides a holistic viewof the interaction of firms, industries and the aggregate economy.

In the context of exports, the process of entry and exit in export markets

differs from market entry and exit in the conventional sense, since firms can

continue to produce for the domestic market.

8

Moreover, as discussed above,

entrants to export markets invariably have to achieve superior performance

before they enter and could be rewarded with even better performance after they

penetrate foreign markets.

Export market dynamics have been modelled in recent studies by incorporat-

ing intra-industry heterogeneity. General empirical findings in the trade literature

7

See Harris and Li (2007a) for a discussion of the sample selectivity issue in the context ofevaluating the exportproductivity relationship; and more generally, Blundell and Costa Dias(2000) and Heckman and Navarro-Lozano (2004) for reviews of this issue and various solutions.

8

Meanwhile, a persistent transition in and out of exporting has been observed by Bernard andJensen (2004a) a high degree of re-entry by former exporters and a high propensity to stopexporting in former non-exporters. There are at least two competing views to explain this persist-ence the sunk costs argument (i.e. exporting begets exporting) and heterogeneous attributes(certain firms are more export-oriented). Bernard and Jensen attempt to identify the roles of bothsunk costs and plant heterogeneity and confirm the significant presence of both. Nevertheless,

it remains unanswered as to how firms acquire these characteristics that facilitate their entry intoforeign markets.

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tend to suggest that the determinants of a firms entry decision include trade

liberalisation (Baldwin and Gu, 2004), sunk entry costs (Das et al., 2001; Bernard

and Jensen, 2004a; Girma et al., 2004); some firm-level characteristics such as

size (Aw and Hwang, 1995; Roberts and Tybout, 1997; Bleaney and Wakelin,2002; Gourlay and Seaton, 2004); the firms experience, including ex-ante

success (Bernard and Jensen, 1999; Greenaway and Kneller, 2004; Kneller and

Pisu, 2007); export spillovers (Aitken et al., 1997; Greenaway et al., 2004); and

foreign networks (Sjoholm, 2003). In addition, the exit decision depends mainly

on industrial characteristics such as the level of sunk costs, and the minimum

productivity or efficiency needed to secure non-negative profits (Das et al., 2001;

Bernard and Jensen, 2004a).

The impact of export market dynamics on productivity has been studied in an

emerging strand of recent theoretical literature, seeking to explain empirical

findings and then generating testable predictions. Bernard et al. (2003) show that

trade liberalisation expands the market shares of the most productive firms by

providing them with large export markets, while at the same time such liberal-

isation forces firms at the lower end of the productive efficiency distribution to

quit as international competition intensifies. Similarly, in a seminal paper, Melitz

(2003) develops a forward-looking model of steady-state trade with heterogen-

eous firms and imperfect competition to show that trade liberalisation increases

a countrys imports and erodes domestic sales and profits. Firms at the higher

end of the productivity distribution expand their export sales more than they

contract their domestic sales; whereas those non-exporters at the lowest end ofthe productivity distribution have to contract or quit. Consequently, this model

generates a prediction that exporting provides an additional channel for produc-

tivity gains whereby export market dynamics act to increase aggregate produc-

tivity, as better firms expand their market share and the worst firms contract

or exit.

9

A more recent development in the theoretical modelling in this regard is

provided in Bernard et al. (2007). Their approach differs from Melitzs model

in that they focus on comparative advantage. It is found that intra- and

inter-industry reallocations of resources brought about by trade liberalisationimprove average industry productivity and sectoral firm output, but relatively

more so in industries with a comparative advantage than those with comparative

disadvantages.

10

9

In addition, Helpman et al. (2004) provide an extension of Melitzs model to include foreigndirect investment (FDI) as another strategy of firms international expansion. Their model assumesthe (fixed) costs differ amongst domestic firms, exporters and multinationals, in conjunction withfirm-level heterogeneity in productivity.

10

Additionally, their model also has implications for job creation and welfare gains associated withthe creative destruction of heterogeneous firms leading to reallocations of resources.

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Empirically, the effect of transitions into and out of export markets on

business performance is often captured by the notion of an export premium,

which measures how much a firms performance changes when it exports (e.g.

Bernard and Jensen, 1999, for the US; Aw et al., 2000, for Korea and Taiwan;Silvente, 2005, for the UK). More specifically, the studies for the US, Korea and

Taiwan conclude that when firms switch from being non-exporters to becoming

exporters, their performance improves, while switching from being exporters to

being domestically-oriented firms retards their performance. Likewise, Silvente

looks at a sample of UK small firms over a seven-year period, showing that there

are symmetric effects on the export premium between entrants and those exiting

new exporters enjoy considerable gains while those exiting from overseas

markets suffer significant losses in terms of employment, wages, sales and pro-

ductivity growth rates.

11

Another strand of the empirical literature compares productivity amongst

distinct sub-groups of exporting firms as well as domestic non-exporters. As

Bernard and Jensen (2004b) report, in US manufacturing new entrants into export

markets are rewarded with a surge in TFP, especially during the first year post-

entry, and thereafter their productivity path becomes flatter, following that of

continuous exporters (although with significantly lower productivity levels).

In contrast, those that exit from exporting are characterised by a substantial

deterioration in productivity to eventually resemble the flat growth trajectory of

continuous non-exporters. In particular, they find increased export opportunities

are associated with both intra- and inter-industry reallocations in the US,accounting for 40 per cent of TFP growth in the manufacturing sector, half of

which can be explained by an intra-industry reallocation of economic activities.

Thus, the higher productivity levels as well as the faster growth rates found in

exporters (in terms of employment and output) offer an additional reallocative

channel for explaining aggregate productivity growth.

12

For Canada, Baldwin and Gu (2003) point to a negative impact for those that

exit, arguing that the ebb and flow induced by international competition culls

some participants from export markets. The least successful entrants have to

withdraw to domestic markets and then lag further behind those that continueserving foreign markets. That is, productivity growth is lower for quitters than

continuers, and substantially lower when compared to new entrants to export

markets.

13

Thus, changing export status is indeed associated with considerable

11

The results from these studies control for the impact of covariates, such as size and industryeffects.

12

Nevertheless, this study does not consider market entry and exit all plants in the dataset existthroughout the period of study. Thus, there is no comparison of the relative importance of creativedestruction, and most importantly how internationalisation interacts with market entry and exit.

13

In addition, the negative impact of exit on the firms efficiency is also captured in Bernard andWagner (1997) and Clerides et al. (1998).

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fluctuations in productivity. Overall, they find exporters accounted for almost

75 per cent of productivity growth in Canadian manufacturing during the 1990s,

28 per cent of which was accounted for by export market entry (both existing

and new entrants).In contrast with the well-documented evidence available for the US and

Canada, there seems to be a paucity of evidence worldwide on aggregate produc-

tivity growth in the context of international trade. Only a limited amount of

evidence of trade-induced productivity growth is available for other countries.

For example, Hansson and Lundin (2004) decompose overall manufacturing

productivity growth in Sweden into within-firm and reallocation effects. They

discover that reallocations due to increased exporting positively impact on aggre-

gate productivity growth, which is then counteracted by reallocations attributed

to changes in domestic shipments. Falvey et al. (2004), again using Swedish

manufacturing data, find that exporting has a sizeable effect on industry pro-

ductivity growth, in terms of increasing market share for higher productivity

exporters.

None of the above studies, however, use nationally representative data that

covers all market-based sectors, to look at the contribution of exporting via

intra-firm, inter-firm and market churning effects. We do this using UK data for

19962004, as set out in the following sections.

3. DATA ISSUES

The FAME dataset used for this study includes all firms operating in the UK

that are required to make a return to Companies House, covering every sector

of the market-based economy. It contains basic information on firm-specific

characteristics, such as turnover, intermediate expenditure on bought-in goods,

services, materials, employment, assets and, most importantly, overseas sales.

We started with over 7,000,000 records covering the period 19962004,

14

and

then omitted all those that lacked the required data (especially on exporting

activities). The result was an unbalanced panel covering 81,819 firms with326,906 observations for 19962004. In this panel, nearly 23 per cent of the

firms are observed throughout the nine-year period.

The resulting FAME dataset (containing the financial information required)

is severely biased towards large enterprises, and is thus unrepresentative of UK

firms. To obtain a representative distribution, we treat the firms in the FAME

14

We therefore have reason to believe that we observe almost all relevant firms who have to makea Companies House return during this period.

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dataset as a sample of the ARD population,

15

and consequently weight the FAME

data to produce a database that is representative (by industry and firm size) of the

population of firms operating in Great Britain.

16

Specifically, we use aggregated

turnover data from the ARD subdivided into five size-bands (based on turnoverquintiles

17

) and three-digit industry SICs (resulting in 757 sub-groups).

18

We then

aggregate the FAME data into the same sub-groups, so that we can calculate weights

using ARD total turnover data divided by the comparable data from FAME.

19

Table 1 presents the results from weighting the FAME data, using the weights

derived from the (three-digit by five size-bands) turnover data from the ARD. The

unweighted data from FAME are dominated by the largest firms (defined as firms

with turnover of 7.2 million or above); this sub-group accounts for over 97 per cent

of total turnover. Weighting the FAME data produces a distribution across size-

bands that is comparable to that obtained when using the ARD. This is confirmed

in the final column in Table 1 the ratio of FAME to ARD turnover by size-band is

within a margin of 10 per cent. There is a suggestion that even weighted, the FAME

data slightly underestimate the contribution of the smallest firms (and corre-

spondingly overestimate the importance of the largest firms), but these differences

are not likely to unduly impact on our decomposition of productivity growth using

these weighted data. Further information on the construction of our weighted

FAME dataset and the export market dynamics is provided in Harris and Li (2007b).

Next, the FAME data for 1996 and 2004

20

are subdivided into (i) those firms

that existed throughout 19962004; and (ii) those that first appeared after 1996

15

For a detailed description of the ARD (available at the ONS), see Oulton (1997), Griffith (1999)and Harris (2002, 2005). Analysis using this database for the UK covers a range of areas but notexporting, due to its lack of information on exports. The counterpart to the ARD in the US is theLongitudinal Research Database (LRD) for US manufacturing provided through the US Bureau ofCensus. This US database has been merged with information on exports at the enterprise level toallow studies to be undertaken on the impact of exporting on aggregate productivity growth(see, for example, Bernard and Jensen, 2004a). Other countries have also compiled similar mergeddatabases (e.g. Baldwin and Gu, 2003, for Canada).

16

Efforts have also been made to actually merge FAME into the ARD, but this has been largelyunsuccessful. (See Harris and Li, 2007b, Ch. 2, for details.)

17

Note these are based on dividing the FAME data into five equally sized groups based onconstant-price turnover data, in order to obtain the cut-off points for each size-band.

18

Where there are fewer than 10 enterprises in any sub-group, these data are not used, in order toensure that the ONS data do not potentially disclose confidential information. This results in theloss of some 4 per cent of the total turnover available in the ARD. Note the ARD data have beenweighted to produce population totals for turnover for each size-band by industry (see Harris, 2005,for a discussion of weighting the ARD data).

19

Note we do not weight the FAME data for 34 industries (by three-digit SIC2003), thus allowingeach observation to represent itself; because the FAME data have better coverage in terms of totalturnover than the ARD (because certain industries such as some of financial services are notincluded in the ARD), or (very occasionally) the data do not match the ARD data by size-bandwithin the industry. These 34 industries (out of a total of 215 industries covered) account for just

2.9 per cent of total FAME turnover.

20

Only these two years are needed to decompose productivity growth for 19962004.

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or could not be located in 2004.

21

The second group comprises all the firms that

had experienced some form of changes during the period considered. We then

disaggregate this change group into various sub-groups using information on

when the firm was first and last observed in the database during 19962004, andthe year the firm was incorporated. Details of constructing each sub-group are

provided in Table 2.

21

As previously stated, we started with more than 7,000,000 records from FAME; and we calculatewhich firms belong to the various sub-groups in Table 2 using this full dataset (i.e. we attempt to

avoid interpreting births and deaths of firms based on entries and exits to and from a dataset thatdoes not cover the population of relevant firms).

TABLE 1GBa Turnover (m) in 2003 Based on FAME and ARD by Size-Bands

Size-Bandb FAME ARD % FAME

Unweighted % Weighted % ARD

(1) (2) (3) (2) (3)227 to 1,184 3,578.5 0.2 60,892.8 5.3 63,751.8 5.9 95.5>1,184 to 7,244 49,683.9 2.4 198,417.1 17.4 200,988.3 18.5 98.7>7,244 1,988,609.3 97.4 874,543.9 76.5 812,157.0 74.8 107.5

All 2,042,279.4 100.0 1,142,283.4 100.0 1,085,916.2 100.0 105.0

Notes:a Unweighted FAME data cover the UK.b Size-bands are in 000.

Source: ARD and FAME databases.

TABLE 2Construction of Sub-Groups in FAME

Criteria Sub-Group N a

Observed in both 1996 and 2004 Continuing firm 12,897 (18.7)

Observed in 2004 but not 1996+ Year of incorporation > 1996

Opened post-1996 17,038 (24.7)

Observed in 2004 but not 1996

+ Year of incorporation < 1997

Merger/acquisition 11,322 (16.4)

Observed in 1996 but not in 2004+ Year of incorporation < 1997

Closed before 2004 27,638 (40.1)

Note:a Number of firms observed in FAME database (weighted using ARD weights); figures in parentheses arecolumn percentages.

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The main issue in dividing the change group into the various sub-groups is

that firms observed in 2004 but not in 1996 could be either start-ups or subsumed

into other firms through acquisition or merger. We differentiate between these

two sub-groups based on the year of incorporation reported for the firm: thosethat were started in 1996 or earlier are not taken to be new start-ups but rather

first observed post-1996 as part of a newly merged venture.

4. METHODOLOGY AND RESULTS

In order to calculate the total factor productivity, we firstly estimate an aug-

mented production function as follows:

y

it

=

0

+

E

e

it

+

M

m

it

+

K

k

it

+

T

t

+

X

it

+

t

, (1)

where y

, e

, m

and k

refer to the logarithms of real gross output, employment,

intermediate inputs and capital stock in firm i in time t.22 Notably, we have also

included a vector of variables, X, that determine TFP.23 Hence, TFP in growth

terms is defined as (dropping subscripts):

ln TFP=%T+6 %E%M%K . (2)

As shown in equation (2), our preferred approach to estimating TFP is todirectly include the factors determining output (and thus TFP) into the production

function, since this avoids any problems of inefficiency and omitted variable

bias associated with estimating a two-stage model based on typically a growth

accounting approach.24 In short, since TFP is defined as any change in output not

due to changes in factor inputs, these determinants should be included directly

into the model (equation (1)) that determines TFP.

Equation (1) has been estimated for 16 separate industry groups using panel

data for 19962004 and the generalised methods of moments (GMM) systems

approach available in STATA 9.2 (Arellano and Bond, 1998), taking account of

22 With reference to variable definitions in the FAME dataset, output is defined as turnover, inter-mediate inputs as cost of sales less remuneration, and capital stock as tangible assets, all in 000(2000 prices).23 Full details and results are provided in Harris and Li (2007b, Ch. 3). Given data availability, Xcomprised the exporting status of the firm, and which industry and region it belonged to.24 See Harris (2005) for a detailed discussion of the measurement issues surrounding TFP, such asinefficient estimates (Newey and McFadden, 1999, Sec. 6), the omitted variable problem (Wang

and Schmidt, 2002) in a two-stage model, and the endogeneity of inputs and outputs in a productionmodel.

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both self-selection and endogeneity issues.25 Having obtained estimates of TFP

at firm level, the index of aggregate productivity in year tas well as its growth

between tand t kis defined as a geometrically weighted average of individual

firm-level productivity in the economy:

(3)

where it is the share of gross output for firm i in period tfor the economy (in 2000

prices), and P measures productivity (labour productivity26 or TFP). Following

Haltiwanger (1997) and Foster et al. (2001), the decomposition of productivity

growth recognises that there are firms continuing in operation between t and

t k, new firms entering for period t and firms exiting that contributed to

productivity in t k. Thus productivity growth between t and t k (lnPt

) is

defined as:

(4)

Here the first term shows the productivity impact of resource shifts within

firms that are open in both tand t k, depending on how important such firms

are in the base year (in terms of their shares of output in the economy). Term

(ii) also concerns continuing firms, but measures the impact of changing output

shares across firms weighted by the firms ranking in the economy in the base

year. There might be a presumption that the highest ranked firms in the base

year would increase their market shares, denoting a positive redistribution ofresources. However, term (ii) is complemented with term (iii) the covariance

effect that considers whether increases in productivity correspond with increasing

25 Full details and results are provided in Harris and Li (2007b). Note, to account for endogeneitywe instrument the model using lagged values of all the endogenous variables plus two additionalinstruments: the age of the firm and whether it possessed any non-zero intangible assets (accumu-lated through R&D, advertising, etc.). These additional instruments are also included to identifythe model and thus overcome the self-selection problem surrounding which factors determine whoexports (where age and non-tangible assets are highly significant) separately from what factors

determine TFP (where age and non-tangible assets are not significant).26 Here labour productivity is defined as a firms gross output per employee in 2000 prices.

ln ln ln ln ln ,P P P P Pt it it i

t t t k = =

( )

ln (ln ln ) ln

(ln ln ) (ln ln )

i (ii) (iii)

Continuers: Continuers: Continuers:

within-firm between-firm cross-firm

(iv) (v)

Entering firms Exiting firms

it k it it k t k it it it

it it t k it k it k t k

P P P P

P P P P

+ + +

..

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market shares. Lastly, terms (iv) and (v) denote the contributions of entering27

and exiting firms, both measured with respect to the economy average in the base

year. Note, term (v) is expected to be negative (if exiting firms have lower

productivity), and thus this term is preceded by a negative sign to allow for apositive impact on aggregate productivity.

Equation (4) has been applied at the total economy level, allowing resources

to be reallocated across industries as well as firms, but separately for exporters

and non-exporters.28 We have also undertaken analyses separately for the manu-

facturing and non-manufacturing sectors, given that exporting is usually more

prevalent in manufacturing (and thus it is of interest to see how the two sectors

differ in terms of their contributions, via exporting, to productivity growth).

Table 3 reports the output shares (the i) for the various sub-groups in 1996 (t k)

27 As explained earlier (Table 2), entrants in the FAME database are separated into firms thatopened post-1996 and firms that were merged/acquired.28 Given that equation (4) is used separately for each sub-group, with respect to within-firm effectsand entering/exiting firms, this is the correct approach since it involves internally consistentdisaggregations of the data. However, our approach implies that the between-firm effects areseparate for each sub-group, and there is no allocation of resources between them. This is unlikelyto be strictly true (although barriers to exporting do exist and seem to be substantial). Allowing for

interactions will involve more covariance terms and the decompositions become significantly morecomplicated. This is something for future consideration.

TABLE 3Output Shares, All Market-Based Sectors, 19962004

ContinuingFirms (t k)

ContinuingFirms (t)

Takeovers/Mergers (t)

EnteringFirms (t)

ExitingFirms (t k)

(a) ManufacturingNon-exporters 8.3 11.3 5.8 5.5 6.7Exporters 47.5 52.6 14.8 10.0 37.5All 55.8 63.9 20.6 15.5 44.2

(b) Non-manufacturingNon-exporters 23.6 19.9 21.0 15.5 33.2Exporters 20.3 21.1 10.3 12.2 22.9All 43.9 41.0 31.3 27.7 56.1

(c) All sectors

Non-exporters 19.6 17.9 17.4 13.1 26.3Exporters 27.4 28.6 11.4 11.7 26.7All 47.0 46.5 28.8 24.8 53.0

Note:Manufacturings share of real gross output in 1996 and 2004 was 26.0 per cent and 23.8 per cent, respectively.

Source: Tabulations from weighted FAME.

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and 2004 (t).29 Notably, the shares of entering (including mergers or acquisitions)

and exiting firms over the period are large (whichever sub-sector of the economy

is considered), which in part is due to opening and closures being cumulative and

the longer the span between t kand t, the greater the effect of churning.30

It is also shown in Table 3(c), covering all sectors, that exporting firms

contributed a significant amount of total output in terms of continuing firms, but

much smaller amounts in terms of mergers or takeovers. However, these figures

for all market-based industries hide differences that exist between the manu-

facturing and non-manufacturing sectors; for continuing firms, output shares are

much higher for exporters (denoting there are both relatively more exporters, and

they tend to be larger firms). In addition, the smaller shares of output for mergers

and takeovers was particularly prevalent for manufacturing non-exporters, and

this sub-group also accounted for relatively much smaller output shares of new

entrants and firms that ceased production.

Table 4 produces initial relative productivity indices for the sub-groups,

confirming that exiting firms tended to have the lowest productivity levels for both

exporters and non-exporters (although this is less pronounced for exporters in

manufacturing), and new firms exhibited relatively high productivity, particularly

for exporters (although again manufacturing exporters are an exception).31

Firms taken-over/merged in both manufacturing and non-manufacturing also had

relatively high productivity (especially if they were also exporting), while non-

manufacturing firms in this sub-group also had high capital intensities (given the

much higher labour productivity indices relative to those for TFP). Exportingfirms that were in operation throughout 19962004 not only had relatively high

productivity in 1996, but experienced a large growth in productivity much

higher than the average for all continuing firms. Overall, Table 4 confirms that

exporting firms are more likely to have higher productivity than non-exporters,

whichever sub-category we consider.

Table 5 and Figure 1 demonstrate that the TFP distribution of exporters

dominates that of non-exporters for each sub-group of firms. 32 Using the

KolmogorovSmirnov test available in STATA (version 9), we are able to reject

29 Note, estimates of productivity growth are known to vary over the business cycle as utilisationof factor inputs vary; however, 1996 and 2004 were neither peaks nor troughs during what wasa relatively stable period of growth in the UK (average GDP growth was 2.7 per cent and 3.2per cent per annum, in 1996 and 2004, respectively).30 Although dealing with the 198092 period, Disney et al. (2003b, Table 6) also report large sharesfor entrants and exiting firms.31 Care needs to be taken when interpreting these relative indices, since they are simple arithmeticmeans that take no account of the relative size of each firm contributing to the overall mean valuereported.32

Separate results for manufacturing and non-manufacturing, while not presented, produced a verysimilar outcome to these results covering all market-based sectors.

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TABLE 4Relative Productivity, All Market-Based Sectors, 19962004

Exiting

Firms (t k)

Entering

Firms (t)

Takeovers/

Mergers (t)

Continuing

Firms (t k)

Continuing

Firms (t)

(a) ManufacturingLabour productivityNon-exporters 0.55 1.39 0.96 1.16 1.85Exporters 0.92 0.95 1.24 1.13 1.66All 0.76 1.13 1.22 1.14 1.71

Total factor productivityNon-exporters 0.71 0.89 0.79 0.93 1.01Exporters 1.04 1.03 1.19 1.03 1.28All 0.89 0.97 1.00 1.00 1.21

(b) Non-manufacturing

Labour productivityNon-exporters 0.71 0.90 1.12 0.96 1.02Exporters 1.34 1.78 4.00 1.31 1.38All 0.86 1.09 1.75 1.08 1.14

Total factor productivityNon-exporters 0.83 0.99 1.01 0.99 1.09Exporters 1.14 1.52 1.49 1.18 1.46All 0.90 1.11 1.12 1.06 1.22

(c) All sectorsLabour productivityNon-exporters 0.71 0.96 1.13 1.00 1.12Exporters 1.16 1.58 2.77 1.20 1.47

All 0.86 1.12 1.59 1.09 1.29Total factor productivityNon-exporters 0.79 0.95 0.96 0.96 1.06Exporters 1.12 1.39 1.40 1.15 1.42All 0.90 1.07 1.09 1.05 1.23

Note:Productivity indices are relative to calculated index in 1996 for all firms, based on equation (3) (for eachsub-sector considered).

Source: Tabulations based on weighted FAME data.

TABLE 5

Two-Sample KolmogorovSmirnov Tests on the Distribution of TFP by Sub-Groups, 1996 and 2004

Sub-Group Difference Favourable To:

Exporter Non-Exporter

Continuing firms (t) 0.020 0.247**Mergers/takeovers (t) 0.021 0.269**Entering firms (t) 0.022 0.276**Exiting firms (t k) 0.024* 0.243**

Note:

** Denotes null rejected at 1% level; * null rejected at 5% level. t= 2004; t k= 1996.Source: Calculations based on weighted FAME data.

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the null hypothesis that the distribution is favourable to non-exporters, confirmingthat exporters have a productivity distribution to the right of non-exporters.

Only for firms that exited before 2004 is there some evidence of some significant

cross-over for the two sub-groups (at high values of the empirical cumulative

distributions).

Based on the decomposition of productivity growth set out in equation (4),

Table 6(c) shows firstly that in aggregate, and covering all sectors, exporting

firms contributed more to overall UK productivity growth than non-exporting

firms (i.e. 2.32 per cent compared with 1.55 per cent per annum in terms of

labour productivity, and 1.27 per cent relative to 0.81 per cent per annum interms of TFP33), even though Table 3 shows that in 2004 exporters produced

51.7 per cent of all market-based output. This faster growth was due to relatively

better performance in nearly every category in Table 6(c), except that exporting

firms that exited had relatively high productivity, resulting in a negative impact

on aggregate productivity levels.

With respect to the TFP results in Table 6(c), aggregate productivity for

exporters benefits from a large contribution from continuing firms improving

33

In percentage terms, this amounts to 60.8 per cent of aggregate TFP growth is due to exporters;the latter account for 59.9 per cent of labour productivity growth.

FIGURE 1Productivity-Level Differences between Exporters and Non-Exporters in

Various Sub-Groups, 1996 and 2004

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their productivity, while there is little redistribution of resources across exportersthat remain open throughout. The covariance term also indicates that large

continuing exporters in 1996 experienced increases in productivity andincreas-

ing market shares. Exporters that had either entered or been taken-over/merged

also contributed about 38 per cent each of the overall (1.27 per cent per annum)

increase in aggregate productivity. In contrast, most of the TFP improvement

for non-exporters (around 91 per cent of the total) was attributable to lower

productivity firms exiting, rather than from internal improvements or the positive

impact of new firms (or takeovers/mergers).

The labour productivity results in Table 6(c) are broadly similar for exporters,although the contribution to aggregate growth was dominated by the contribution

TABLE 6Decomposition of Productivity Growth, All Market-Based Sectors, 19962004 (cf. equation (4))

Total Within Between Covariance Mergers/

Takeovers

Entering Exit

(a) ManufacturingLabour productivityNon-exporters 1.02 0.15 0.03 0.14 0.03 0.23 0.50Exporters 3.51 1.70 0.36 0.75 0.40 0.06 0.37All 4.53 1.85 0.39 0.89 0.37 0.17 0.87

Total factor productivityNon-exporters 0.07 0.03 0.03 0.03 0.17 0.08 0.29Exporters 1.61 0.83 0.01 0.62 0.32 0.04 0.18All 1.67 0.86 0.04 0.64 0.15 0.05 0.11

(b) Non-manufacturingLabour productivity

Non-exporters 1.76 0.31 0.33 0.24 0.30 0.20 1.41Exporters 1.85 0.34 0.08 0.45 1.79 0.88 0.84All 3.62 0.65 0.25 0.69 2.08 0.68 0.57

Total factor productivity


(c) All sectorsLabour productivity

Non-exporters 1.55 0.19 0.25 0.20 0.26 0.07 1.10

Exporters 2.32 0.19 0.03 0.47 1.45 0.66 0.49All 3.87 0.00 0.27 0.68 1.71 0.59 0.62

Total factor productivity


Note:Figures show the percentage increase per annum.

Source: Tabulations based on weighted FAME data.

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of firms that had merged/been taken over (accounting for over 62 per cent of the

per annum improvement). For non-exporters, there was a relatively large negative

within-firm effect, implying that continuing firms that were relatively large in

1996 had experienced declines in labour productivity between 1996 and 2004.In other respects, the results are similar to those for TFP.

Table 6 also produces results when decomposition of productivity growth is

undertaken separately for manufacturing and non-manufacturing firms.34 Con-

centrating on the TFP results, it can be seen that overall growth per annum was

significantly lower in manufacturing (1.67 per cent compared to 2.28 per cent

per annum in non-manufacturing), due to the poor performance of manufacturing

firms that did not export. The latter mostly reflects the lower TFP contribution

of firms that merged or were taken over, while new firms also contributed

negatively to overall growth. In contrast, manufacturing exporters experienced

significant intra-firm productivity gains (0.83 per cent per annum), with addi-

tional gains for large exporting firms that were also increasing their market shares

(i.e. a covariance effect of 0.62 per cent per annum); while both intra-firm and

covariance effects were much smaller for non-manufacturing exporters. Other

significant differences between exporting firms in manufacturing and non-manu-

facturing were the overall negative impact of churning in manufacturing (with

a net contribution of 0.14 per cent per annum), while new exporters in non-

manufacturing contributed significantly to overall growth in this sub-group.

Finally, Table 7 compares our TFP results with those obtained in other studies

(as discussed in Section 2). Because of the different methods used, the figuresfor various countries and time periods are not strictly comparable; for example,

Bernard and Jensen (2004b) and Hansson and Lundin (2004) used balanced panel

data that do not allow for entry and exit effects. Nevertheless, the table does

show that overall exporters do account for a larger proportion of productivity

growth than do non-exporters in both manufacturing (cf. the US, Canadian and

Swedish figures) and in all market-based sectors (in the UK). However, lack of

comparable information means it is not possible to provide any evidence on

whether productivity growth was mostly due to intra-firm improvements or

external restructuring. The only study (not included in Table 7) that started witha similar approach to ours was Falvey et al. (2004), for Swedish manufacturing

(198094). They used the Haltiwanger-type approach to decompose TFP growth

by industries but did not separate out exporters. Rather, they regressed the net

entry and between-firm contributions (by industry) on export growth (across

industries) and interpreted the results as showing the relationship between

34 These figures cannot be added together to get overall growth across the UK. However, Table 3shows that manufacturings share of real gross output throughout the period was around one-

quarter of total market-based output, which is approximately the weight needed to combine thefigures for manufacturing and non-manufacturing to achieve the overall UK totals.

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Journalcompilation

B

lackwellPublishingLtd.2008

TABLE 7Decomposition of Productivity Growth, Various Studies

Bernard and Jensen(2004b), Table 8

Hansson and Lundin(2004), Table 10

Baldwin and Gu(2003), Table 13

HarTab

Data and period US LRD, 1983 92 Sweden, 1990 99 Canadian ASM, 1974 96 UKSector Manufacturing Manufacturing Manufacturing All

Decompositionmethodology

Within and betweeneffects only

Within and betweeneffects only

Within + between andentry only

W(me

Methodologicalfeatures

Uses balanced panel soexcludes entry and exit

Uses balanced panel soexcludes entry and exit

Assumes exits replace entrants(thus no separate role for exits)

Userepr

Productivity measures TFP TFP Labour productivity TFPMain results: (% p.a.) (% p.a.) (% of total) (%

Within Between Total Within Between Total Within+Between Entry Total WNon-exporters 0.76 0.48 0.28 1.5 4.2 2.7 3.6 0.9 2.7 0.04Exporters 0.07 1.07 1.14 4.0 2.1 6.1 79.3 18.0 97.3 0.42

Total 0.83 0.59 1.82 5.5 2.1 3.4 82.9 17.1 100 0.46

Note:a The covariance term is added to between, and mergers/takeovers is added to entry from Table 6 to obtain the result

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exporting and productivity growth. However, they ignore intra-firm effects and the

covariance term (in the Haltiwanger decomposition), and mostly their regression

results are statistically insignificant; but they do find evidence to suggest that

export growth raises overall productivity growth through its positive effect on theentry of new firms.

5. CONCLUSIONS

Knowing the contribution of exporting to productivity growth is important;

for example, evidence of the benefits from international trade can support the

UK government when designing policies to help firms develop their exporting

activities (DTI, 2006). We have shown that exporting leads to productivity gains

within firms (confirming the self-selection and/or learning-by-exporting

hypotheses in the exportingproductivity literature), while additionally showing

the importance for UK aggregate productivity growth of inter-firm reallocations

of resources towards more productive exporting firms. Such external restructuring

was especially important in the non-manufacturing sector, suggesting that govern-

ment policy aimed at boosting exporting needs to take account of the different

channels through which productivity growth occurs across different sectors.

Despite some limited micro evidence of trade-induced aggregate productivity

growth for countries like the US, Canada and Sweden, to the best of our knowl-

edge this paper presents the first set of results that assesses the contribution ofexporters to UK aggregate productivity growth between 1996 and 2004, taking

into account restructuring effects. Firstly, and concentrating here on the results

across all market-based sectors, we are able to show that exporting firms con-

tribute a significant amount to the total output of the UK economy, partly due to

their relative size and particularly their better productivity. We have confirmed

that exiting firms tend to have the lowest productivity levels for both exporters

and non-exporters, and new entrants exhibit relatively high productivity (par-

ticularly for exporters). Firms that have been taken over/merged also have

relatively high productivity (especially in conjunction with exporting), and highcapital intensities. Exporting firms in operation throughout 19962004 not only

had relatively high productivity in 1996, but experienced a large growth in

productivity, much higher than the average for all continuing firms. Overall,

these results confirm that exporting firms are more likely to have higher pro-

ductivity than non-exporters, whichever sub-category of firms we consider.

Based on a decomposition of productivity growth we are able to show that,

in aggregate, exporting firms experience faster productivity growth than non-

exporting firms and therefore contribute more to overall productivity growth.

That is, there is a large contribution from continuing firms that exported; and

within productivity gains for exporters were relatively large between 1996 and

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2004, with little redistribution of resources across exporters that remained open

throughout. Our results also show that continuing exporters that were initially

large and experienced increases in productivity also experienced increasing

market shares. Exporters that entered global markets after 1996 through beingeither taken over or merged, or as new start-ups, also contributed about 38 per cent

each of the overall growth in aggregate productivity. In contrast, most of the

productivity (labour or TFP) improvement for non-exporters is attributable to

the contribution of lower productivity firms exiting, rather than internal

improvements or new firms entering with high levels of productivity.

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