WHAT FACTORS DETERMINE THE OUTSOURCING INTENSITY? A Dynamic Panel Data Approach for manufacturing industries

Keywords: L22 -Firm Organization, Market Structure: Markets vs. Hierarchies; Vertical Integration < L2 -Firm Objectives, Organization, and Behavior < L -Industrial Organization, L60 - Outsourcing, Manufacturing industry, Subcontracting, Unit labor costs JEL classification: L23, L60 Outsourcing, Manufacturing Industries, Explanatory Factors, Unit Labour Costs

I. INTRODUCTION

According to international empirical evidence, a new and complex production organization strategy is currently being developed. This strategy, called fragmentation of production, favours the splitting up of production processes into more specialized and discernible phases in order to obtain the most efficient producer and location for each product or component.

It is devised mainly by developed-countries' enterprises, which face a very competitive market where, on the one hand, products coming from developing countries are highly competitive due to lower labour and production costs and, on the other hand, customers demand highly differentiated products. The main aim of adopting it is to take advantage of specialization and scale economies in components or other production tasks by specialized suppliers as well as to gain flexibility to respond to demand changes quickly i . In this way, firms specialize in those activities or phases where they have a competitive edge seeking to improve production efficiency, and consequently, their competitiveness.

Two dimensions of fragmentation can be distinguished (Curzon [START_REF] Price | Some causes and consequences, in Fragmentation: New production patterns in the world economy[END_REF][START_REF] Kimura | Two-dimensional fragmentation in East Asia: conceptual framework and empirics[END_REF]: an ownership dimension and a geographical dimension (Figure 1). The first one refers to the controllability of a firm over fragmented production and the second one does to the geographical location of that segmented production. One of the most important features of fragmentation of production is that more and more often goes beyond the boundaries of the firm.

When the segmented production is carried out by other independent firms, the term outsourcing ii is used. Outsourcing comprises dimensions 2 and 3 of fragmentation of production in Figure 1. It is important to note that even though there is no direct shareholder control over the segmented phases, it does not mean that there is not any control over them at all. Transactions cannot be considered completely independent market transactions for two reasons: firstly, because the relationship between companies has a long-term nature, and secondly, because of the great quantity of information, such as detailed instructions and specifications, which the external provider receives. As Curzon [START_REF] Price | Some causes and consequences, in Fragmentation: New production patterns in the world economy[END_REF] points out, outsourcing lies somewhere in between F o r P e e r R e v i e w 3 total ownership and complete arm's length transactions. Moreover, the externalized production can be outsourced to suppliers located abroad (international or foreign or cross-border outsourcing) or to domestic providers (national or domestic outsourcing).

Outsourcing of production is thus understood as a process of vertical disintegration of the value chain where some phases or even the whole production process are now contracting out to external enterprises instead of performing inside the firm. This is the aspect of fragmentation we want to study. Our data can not allow to distinguish between national or foreign suppliers, so we focus on total outsourcing which comprises domestic and cross-border outsourcing.

Understanding what factors determine the intensity of total outsourcing production using panel data is the object of the present paper.

In spite of the increasingly use of outsourcing of production activities according to business press iii and academic literature, empirical research about its determinants remains very limited: [START_REF] Kimura | Fragmentation, internalization, and interfirm linkages: Evidence from the micro data of Japanese manufacturing firms[END_REF] and [START_REF] Tomiura | Foreign outsourcing and firm-level characteristics: evidence from Japanese manufacturers[END_REF] for Japanese manufacturing industry, [START_REF] Görg | Does outsourcing increase profitability?[END_REF] for Irish electronics industry, [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF] for some UK manufacturing industries and [START_REF] Holl | Production subcontracting and location: Panel data evidence from Spanish manufacturing firms[END_REF] for Spanish manufacturing industry. Of these, only the last three are panel data instead of cross-section analysis and exclusively [START_REF] Görg | Does outsourcing increase profitability?[END_REF] and [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF] try to infer the factors that may affect the level of outsourcing, whereas [START_REF] Holl | Production subcontracting and location: Panel data evidence from Spanish manufacturing firms[END_REF] focuses on the determinants of the probability that a firm does take the decision of outsourcing using a probit model.

Hence, as far as the author knows, our study is the first on the determinants of outsourcing intensity using panel data for the Spanish manufacturing industry. The estimation includes the GMM approach proposed by [START_REF] Blundell | Initial conditions and moment restrictions in dynamic panel data models[END_REF] especially suitable to deal with models for moderately persistent series from short panels. Furthermore, this paper contributes to the empirical literature by employing a direct and more adequate indicator for outsourcing of internal production. This type of outsourcing is often measured by the ratio of material intermediate inputs to output. But this is a broad measure because it includes raw materials purchases and arms-length purchases of standardized components in the market. A specific characteristic of outsourcing is that the relationship between the firm which contracts out production and external provider is long-term and it usually implies sharing information about the product. That is, purchases of intermediate inputs through a usual marketing channel have not to be regarded as outsourcing. As [START_REF] Grossman | Outsourcing in a global economy[END_REF] notes "outsourcing means more than just the purchases of raw materials and standardized intermediate goods". At the same time, the ratio of material intermediate inputs to output is a narrow indicator because it does not capture the outsourcing of the final production stage, the assembly or specific production tasks.

For these reasons, we use an indicator that fulfils these required conditions. This is Production works done by other firms which refers to tasks which being a part of the own production process are carried out by other firms. It involves contracting out manufacturing of parts and components and also any stage of the production process such as product design or specific tasks (for instance, in the textile industry, tailoring or press ironing) or even the final assembly iv . That is, neither external services such as maintenance of fixed assets, accounting, consulting, cleaning, transportation, etc., nor purchases of raw materials and supplies such as office materials or fuel are included. Subcontracts are included within this concept v .

The paper is structured as follows. In the next section, we briefly review previous literature on the determinants of outsourcing. In section III we describe the data set used for the empirical analysis and then we present some descriptive statistics as well as the econometric model. The results of the empirical estimation are showed in section IV. Lastly, in section V, some conclusions are made.

II. DETERMINANTS OF OURTSOURCING OF INTERNAL PRODUCTION.

Companies will opt for outsourcing when externalisation of certain value chain phases allows them to reduce costs and when de-internalizing has more advantages than in-house production. The technological revolution that has taken place in last decades has allowed for a significant drop in the costs associated with finding information, transport communication and According to transaction cost theory [START_REF] Coase | The Nature of the firm[END_REF][START_REF] Williamson | Figure 2: Outsourcing of Internal Production: Level in 2002 and Change 1993-2002[END_REF], outsourcing would entail a variety of coordination costs associated with various aspects of inter-firm transactions. Search costs to find the right supplier, negotiation costs, costs to design the contract and the incomplete contracts problem, coordination costs, technology transfer risks, etc. have to be considered vi . At the same time, firms which outsource production search to obtain two types of advantages: first, an increase of flexibility for adapting to changes in demand and technological conditions and, second, a reduction in production costs vii .

If firms outsource in order to reduce costs relative to in-house production and, therefore, to increase efficiency, we would expect that those firms and sectors where the labour costs are higher were more active in outsourcing strategy. To test the relevance of the labour cost-saving motive for outsourcing, [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF] include the wage rates for skilled and unskilled workers. However, they do not obtain conclusive results. The sign of the coefficient changes depending on the manufacturing industry and on the estimation technique and frequently the variable is statistically insignificant. [START_REF] Görg | Does outsourcing increase profitability?[END_REF] introduce the average wage per employee when they investigate outsourcing determinants. They also find that the effect of wages is statistically insignificant and not robust to different estimation techniques. [START_REF] Holl | Production subcontracting and location: Panel data evidence from Spanish manufacturing firms[END_REF] does obtain a positive and significant coefficient of the wages on the probability of subcontracting products, parts and components.

In our opinion, a variable more relevant than wage is unit labour cost, that is, the remuneration of labour to produce one unit of output. This indicator of cost pressures in the labour market is computed as the ratio of labour cost to output. It is measured as well as the ratio of labour cost per worker (or per hour worked) divided by labour productivity (output per worker or per hour worked). By this way, changes in unit labour cost are the result of two forces: changes in wage rate and changes in productivity. It has been assumed that high wage firms do more outsourcing because the cost cutting motive will be more important. But those high wages could respond to higher efficiency due to high skills, resulting in lower unit labour costs. That is, it would be the wage, once productivity differences are taken into account, one of the key drivers of outsourcing. Hence, we expect that high unit labour cost manufacturing industries tended to contract out more production works than the rest viii . This result would confirm the initial hypothesis that fragmentation of internal production is an strategy carried out by developedcountry firms in order to improve their efficiency in a context of strong competitiveness coming from cheaper labour regions.

As [START_REF] Abraham | Firm's use of outside contractors: theory and evidence[END_REF] suggest, the cost savings derived from outsourcing can be obtained by two ways: first, exploiting the economies of scale in producing these specialized components or phases which are being contracted out (outsourcing for specialization) and, second, turning fixed costs in variable costs and gaining flexibility if there are frequents fluctuations in the product demand (outsourcing for capacity).

The specialization motive for outsourcing introduces firm size as a determinant of this strategy. There may be economies of scale in the production of specific inputs and, in this sense, size variable have to be considered to control for this scale economies effect. Since small and medium enterprises will have more difficulties to reap the minimum efficient scale, they will opt more intensively for outsourcing.

Nevertheless, we also argue that outsourcing is an strategy for gaining flexibility that allows large firms to reduce their rigidity. In a very strong competence environment, a high grade of product differentiation is increasingly required. Consumers demand more and more specific product characteristics and firms have to achieve flexibility to adapt to changes in consumer wishes. Contracting out the manufacturing of specific components or tasks is one of the alternatives to obtain it. That is, firms would tend to back to the basics focussing on those activities where they are more efficient and outsourcing the rest. In this sense, large firms have more incentives to carried out this process of vertically de-integration of production structures. Another reason to expect a positive relationship between size and outsourcing intensity is proposed by [START_REF] Tomiura | Foreign outsourcing and firm-level characteristics: evidence from Japanese manufacturers[END_REF], who suggests that smaller firms could face to higher search costs, that is, due to stronger market power large firms might find contracting partners more easily.

The sign of firm size is, therefore, ambiguous. Whereas empirical works such as Holl ( 2004) have obtained positive coefficients, the sign is negative in [START_REF] Görg | Does outsourcing increase profitability?[END_REF]. This last study, however, excludes small firms because it uses a Survey that provides information only for firms with thirty or more employees.

The size or thickness of the market is also related with the outsourcing intensity. The larger the market, the more chance of finding a good external supplier and, therefore, more likely to engage in outsourcing. [START_REF] Grossman | Integration versus outsourcing in industry equilibrium[END_REF] and [START_REF] Mclaren | Globalization and Vertical Structure[END_REF] consider the effects of market thickness on the outsourcing of intermediate inputs in their transaction cost models where the trade off between vertical integration and outsourcing is investigated. Since international trade increases the ease for a firm to math with an specialized input provider, one expects that higher international trade lead to a rise in outsourcing through an increase in market thickness. Empirical works such as [START_REF] Görg | Does outsourcing increase profitability?[END_REF] introduce export propensity pointing that export propensity may have a positive effect on outsourcing. It could be argued that the more a company exports, the more the possibilities there are in finding specialized foreign suppliers.

Previous works usually control for ownership nationality. According to [START_REF] Görg | Does outsourcing increase profitability?[END_REF] and [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF], since foreign firms are part of an international network competing in a global market, the potential to contract out to more efficient producers abroad increases. Hence, it could be assumed that they do more outsourcing than domestic firms. However, if foreign affiliates are located in a country just for doing production tasks for the parent company, the possibility from these manufacturing plants for using subcontractors could decrease. The sign of national ownership variable is, as well as firm size, ambiguous and will be [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF] but also negative signs [START_REF] Holl | Production subcontracting and location: Panel data evidence from Spanish manufacturing firms[END_REF][START_REF] Görg | Does outsourcing increase profitability?[END_REF]).

Finally, it seems reasonable that the decision about the outsourcing intensity in period t is related to the level of outsourcing in previous period t-1. The lagged dependent variable is taken into account to consider the persistence in the outsourcing decision [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF].

Moreover, [START_REF] Swenson | Entry costs and outsourcing decisions: evidence from the U.S. overseas assembly provision[END_REF] shows that outsourcing exhibits hysteresis caused by sunk entry costs using data of the U.S. offshore assembly program. The existence of important transaction costs would explain the persistence in the outsourcing intensity. They are a key difficulty in the decision of outsourcing internal production according to the theoretical model by [START_REF] Grossman | Integration versus outsourcing in industry equilibrium[END_REF]. These costs will be higher in the first moments, when the outsourcing strategy is becoming to be used. There would be sunk entry costs associated with outsourcing strategy (such as search costs in finding a suitable provider). In following years, transaction costs probably will be decreasing and they will be compensated by the advantages of farming out parts of the production process. These explanatory variables and the expected signs in previous outsourcing literature are summarized in table 2.

III. DATA AND METHODOLOGY DESCRIPTION.

In order to investigate the determinants of outsourcing of internal production we use industry level data for manufacturing in Spain. The data are derived from the Industrial Companies Survey (Encuesta Industrial de Empresas) published by the Spanish National Statistics Institute. The Survey, which is undertaken annually since 1993, provides information on employed persons, wages, hours worked, sales, intermediate inputs, external services and some more variables for 93 manufacturing industries. The sectors correspond mostly to the 3digit level of NACE Rev.1 (Table 1). The Survey basic unit is industrial company with one or more remunerated employed persons. Approximately 43,000 firms compose the sample in 2002.

The inclusion of the variable Production works done by other firms, as defined in the introduction section, makes the Survey particularly interesting for our analysis of outsourcing of internal production. We measure outsourcing of internal production as the ratio of these production tasks carried out by other firms to gross output. If the ratio goes up, we interpret that manufacturing firms are replacing in-house production for external contract production.

Figure 2 plots the extent of outsourcing for Spanish manufacturing industries in 2002. We observe the heterogeneity in the outsourcing intensity among sectors. Outsourcing level is higher for Textile Industries, Wearing Apparel, Footwear, Publishing and Printing, Fabricated Metal Products and Shipbuilding and Aerospace Industry. All of them show fragmentation levels well above 10% of gross production, and 20% for the last two sectors. According to this indicator, for the average Spanish manufacturing industry around 5% of output are production works contracted out to outside producers. Moreover, our data show that fragmentation of production has increased steadily in many sectors (average rise of 40% from 1993 to 2002) ix . Therefore, we find evidence of the growing disintegration of the production process and rising of outsourcing production activities in Spain.

In order to obtain more information about the characteristics of those sectors where outsourcing is more intensive, we use a classification which cluster industries by their typical input combinations: labour-intensive, technological-driven, capital intensive, marketing-driven and mainstream manufacturing industries [START_REF] Peneder | Intangible investment and human resources. The new taxonomy of manufacturing industry[END_REF]. Outsourcing is common to all groups of industries. Nevertheless, it is more relevant for labour-intensive industries where most of these sectors shows outsourcing levels above average, many of them even above 10% of the gross production (which can be interpreted as a high level of outsourcing). So, we argue that industries producing goods intensive in labour relative to capital and technology seem to give stronger support to fragmentation based on contract out physical production to specialized producers than the rest of industries (Figure 3).

To analyse the determinants of outsourcing of internal production we consider the following regression equation which relates outsourcing intensity to a broad range of industry's characteristics: OUTS it = 0 + 1 OUTS i,t-1 + 2 ULC it + 3 %Small-Firms it + 4 National-own. it + 5 Export-prop. it + 7 DSKILLS it + 8 D t + u it (1)

Where i represent the 92 manufacturing sectors x , t is the time period 1993-2002, OUTS is the outsourcing level measured as production works carried out by other firms per unit of output, UCL are the unit labour costs measured as defined above and %Small-Firms variable is the percentage of small firms (less than 20 employees) in a sector. We include a variable of ownership nationality (National-own.) which reflects the percentage of domestic firms (those with one hundred percent of national capital). Export-prop. is the export propensity ratio measured as exports to output. If firms use outsourcing as a cost-cutting strategy, we would expect that high skill sectors gave stronger support to fragmentation based on contracting out production phases to specialized producers than the rest of the industries, mainly those production tasks more intensive in low skilled labour xi . For this reason, the model also includes a dummy variable to control for high skill requirements (DSKILLS), which takes on value 1 for sectors with high skill requirements and 0 for the rest using the [START_REF] Peneder | Intangible investment and human resources. The new taxonomy of manufacturing industry[END_REF] classification.

This classification is based on the OECD's occupational data, which distinguish between white and blue-collar workers, on the one hand, and between high and low skilled labour on the other.

At last, 10 time dummies are introduced to control for period-specific effects.

The equation (1) represents a standard dynamic model, where lagged dependent variable is included among the regressors. Furthermore, we will treat the unit labour cost variable as endogenous, since it is conceivable that changes in outsourcing level lead to changes in future unit labour cost. For similar reasons, we consider the share of small firms and the export propensity ratio as not strictly exogenous and we also include these variables lagged.

We calculate the outsourcing intensity, the unit labour costs and the percentage of small firms from data of the Industrial Companies Survey. Data for the ownership are drawn from the firm level panel survey, the Survey of Firm Strategies (Encuesta sobre Estrategias All variables are expressed in logarithms. We use a one-way error component model for the disturbance term, u it = i + it , where i denotes the unobservable individual specific effects that are independent and identically distributed (iid) over the sectors with variance 2 and it denotes the remainder disturbance that are iid over the whole sample with variance 2 . The time invariant variables are often difficult to measure or hard to obtain. For example, a sector-specific production technology may allow the dispersion of phases of production process better in that sector than in another sector. This production technology varies across sectors but it is not expected to change very much in a short time period.

Taking into account these three aspects (potential industry unobserved heterogeneity, dynamic nature of the model and endogeneity of some explanatory variables), the appropriate estimator is the Generalized Method of Moments (GMM) developed by [START_REF] Arellano | Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations[END_REF]. They suggest first differencing the model to get rid of the industry specific effects and then using valid instruments (lagged values of the instrumented variables) to deal with the problem that by construction the new error term is correlated with the lagged dependent variable.

The use of instruments is also required to control for the potential endogeneity of other explanatory variables. We use at least three lagged values of unit labour cost as instruments for the equations in first differences to control for the potential influence of current outsourcing level on current unit labour cost. The same lagged values are chosen for the rest of the endogenous variables. Since national ownership is assumed to be strictly exogenous, it is instrumented with itself.

A draw back of the difference GMM estimator of [START_REF] Arellano | Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations[END_REF] is that when first differences are taken, time invariant variables are wiped out. So, the estimator does not use cross sectional information reflected in the differences between industries. Another disadvantage is that lagged levels are often poor instruments for the equation in differences, especially in the the difference GMM estimator, we use a new estimator, the system GMM, developed by [START_REF] Arellano | Another look at the instrument variable estimation of errorcomponents models[END_REF] and [START_REF] Blundell | Initial conditions and moment restrictions in dynamic panel data models[END_REF]. This estimator is based on an augmented system that includes the regression in differences in addition to the regression in levels with lagged differences as instruments. The second part of the system requires the additional assumption of no correlation between the variables in differences and the unobserved industry effects, although there may be correlation between the levels of the explanatory variables and the fixed effects. Some summary statistics for the variables used are provided in Table 3. We observe that, in manufacturing industry labour cost are about 20 percent of the output value and about 30 percent of the output is sold to foreign markets. In addition to, small firms as well as firms without any foreign participation are clearly predominant in Spanish industry (around 80 percent of total industries). Table 4 presents the simple correlations between pairs of variables. Since the correlations between the independent variables are small (except between the shares of small firms and national firms), we interpret there are not multicollinearity problem in the regressions.

In addition, we see that outsourcing is positively correlated with most of the independent variables, mainly with levels of the unit labour costs, the proportion of domestic firms and the high skill requirements. Nevertheless, the outsourcing intensity is determined jointly with these variables and other factors which have to be controlled. For these reasons, an econometric analysis is applied.

IV. ECONOMETRIC RESULTS.

The results of the econometric analysis are reported in Table 5. The first column presents the outcomes from the estimation of equation (1) using GMM system procedure. The positive and significant coefficient of lagged dependent variable indicates a high degree of persistence in outsourcing strategy. Moreover, in line with our prior expectations, higher unit labour costs are 13 related to higher level of outsourcing. We can interpret that sectors tend to use fragmentation of production as a defensive strategy trying to improve their competitiveness. The positive and significant coefficient of unit labour cost is an important result because it provides empirical evidence of the cost-cutting motive for outsourcing. Additionally, according to the positive link between the share of domestic firms and the outsourcing level, as the percentage of national firms increases, so do outsourcing activities. This result would contradict that foreign firms were more prone to contract out internal production. In our opinion, this is because the last have been located in Spain as production affiliates carrying out parts of the production process for the parent firm. Moreover, the dummy variable high skill requirements exhibits a positive and significant sign showing that industries intensive in high skilled-labour tend to farm out internal production more intensively. Lastly, two variables, the percentage of small firms and the export propensity, are statistically insignificant. Most of the time dummy variables are highly significant although, in order to spare space, the coefficients are omitted from the results table.

Consistency of the GMM estimators depends on the validity of the instruments which is examined by four specifications tests. The first is the Sargan test of overidentifying restriction.

The Sargan test does not reject the validity of the instruments employed in the estimation process. Since system GMM used additional moment conditions over the difference GMM, a Sargan Difference test can be employed to examine the validity of these additional instruments obtained from the equation in levels. The Sargan difference test does not rejected the validity of them ( 2 [8]=5.53). The validity of the instruments also requires the lack of second order serial correlation in the dynamic formulation whereas, by construction, first-order correlation is expected even with uncorrelated original error term. Two additional tests are included to examine the absence serial correlation in first differenced residuals. The null hypothesis of no second order correlation cannot be rejected and we can conclude that original error is not serially correlated. We test the robustness of the regressions by removing those variables which do not have a significant impact on the dependent variable. The column 2 of Table 5 presents the results from the estimation of equation ( 1) excluding the share of small firms whereas we have removed the export propensity in the column 3. According to the System GMM estimations, the positive coefficients for previous outsourcing intensity, unit labour cost, national ownership and skill requirements remain robust. Moreover, the negative coefficient of the share of small firms turns out significant when export propensity is not included. According to this result, those sectors where the share of small firms is lower outsource more internal production than the rest, pointing the existence of less difficulties in searching specialized outside producers for large firms.

Taking into account the interaction between the share of small firms and the export propensity variable, we use a variable for international market penetration measured as the percentage of firms in each sector whose main market is foreign xii (column 4 and of table 5). In this case, both variables (size variable and foreign market penetration) are significant. The positive and significant coefficient points out that outsourcing intensity grows when the proportion of firms which produce mostly to foreign markets does. By this way, firms orientated mainly to international markets would use more intensively outsourcing strategy. A greater pressure to improve their efficiency and competitiveness or a greater probability to find specialized suppliers could explain this outcome.

Finally, table 5 contains a last column where the model for a sub-sample of more homogeneous 3-digits sector is estimated xiii . In particular, we have considered exclusively labour intensive sectors according to Peneder taxonomy. Previous outsourcing level and unit labour costs remains positive and highly significant pointing out the robustness of the empirical estimates for these variables. For labour intensive sector, neither firm size nor national ownership seem to have an significant impact on outsourcing intensity. On the contrary, export propensity shows a positive and significant coefficient. In this paper we have investigated the determinants of outsourcing of internal production using industry level data for Spanish economy. Our study covers 93 manufacturing sectors and the period 1993-2002. We observe that manufacturing industries are fragmenting the value chain and they are opting increasingly for contracting out production works to specialized providers.

We test a model where the outsourcing intensity at industry-level depends on lagged level of outsourcing, unit labour cost, share of domestic firms, proportion of small firms, export propensity and skill requirements. We employ the system-GMM estimator proposed by Blundell and Bond (1998) that provides better instruments when right-hand variables are persistent over time.

We find that current level of outsourcing is highly related to previous outsourcing intensity, that is, outsourcing exhibits hysteresis. The market transaction costs associated to contracting out production are probably higher when firms make the decision of outsourcing (some of them are even sunk costs). In due course, some of these costs will be reduced and so the advantages of in-house production will be dropped. Therefore, if firms are achieving their objectives of gaining flexibility and decreasing costs, the outsourcing strategy will be used more and more intensively allowing firms to concentrate on their innermost core competence.

Furthermore, our results show that the unit labour costs affect positively the ratio of production works that are contracted out to external providers related to output. The pressure of low-cost competitors could be more intensive in manufacturing industries with higher unit labour costs and, therefore, they would be mostly encouraged to outsource production works to cheap and specialized contract manufacturers. We find significant evidence for the positive link between the outsourcing intensity and the share of domestic firms, the orientation to foreign markets as well as the high skill requirements. Finally, we observe a negative effect of the share of small firms on outsourcing intensity. Independent Outside Supplier

(1) Intra-firm national fragmentation

(2) Inter-firm national fragmentation (national outsourcing)

(3) Inter-firm international fragmentation (international outsourcing)

(4) Intra-firm international fragmentation (FDI is required).

Source: Own elaboration from [START_REF] Kimura | Two-dimensional fragmentation in East Asia: conceptual framework and empirics[END_REF] and Curzon [START_REF] Price | Some causes and consequences, in Fragmentation: New production patterns in the world economy[END_REF]. i See Piore and Saber (1984). The higher flexibility can be obtained through flexible production which allows firms to adapt standardized inputs to a variety of specifications [START_REF] Eckel | International trade, flexible manufacturing and outsourcing[END_REF]. Through flexible production, firms can alter the final goods they provide according to the specific needs or desires of their customers.

ii Nevertheless, fragmentation of production and outsourcing are often treated as synonymous. The term outsourcing comes from the compound expression "outside resource using". Along this paper, the terms outside and external refer to outside or external to the firm.

iii The Economist has recently published a survey of outsourcing, in which is pointed that "manufacturing has already gone a long way down the road of outsourcing" (The Economist, November 13 th 2004). iv [START_REF] Tomiura | Foreign outsourcing and firm-level characteristics: evidence from Japanese manufacturers[END_REF] employs a similar indicator but, as pointed out above, he uses cross-section data. [START_REF] Holl | Production subcontracting and location: Panel data evidence from Spanish manufacturing firms[END_REF] opt for a narrower indicator, the subcontracting of products, parts and components, to study the probability of outsourcing. At last, [START_REF] Girma | Outsourcing, foreign ownership and productivity: evidence from UK establishment level data[END_REF] use a bit wider measure, the industrial services receive, which comprises activities such as processing of inputs but also certain services as maintenance of production machinery or engineering services. v Various types of outsourcing exist in the manufacturing industries depending on the relationship between the principal and the third-party company. Subcontracting is a particular case where a "dominant/dominated" relationship is created. Specifically, subcontracts correspond to the relationship between two companies (the subcontractor and the main contractor), where the subcontractor company participates in the production process of a particular product, which belongs to the contractor company. The subcontract conditions require the main contractor to provide a diagram and precise technical specifications for the manufacture of the product, as well as the supply of its main raw materials. vi In the context of transaction costs and contractual incompleteness [START_REF] Grossman | Integration versus outsourcing in industry equilibrium[END_REF] examine theoretically the decision between outsourcing or vertical integration of intermediate inputs (make or buy decision) taking into account the costs that arise from search frictions and imperfect contracting and the costs of running a larger and less specialized organization. To consider the international dimension as well as the ownership dimension, [START_REF] Antras | Global outsourcing[END_REF] develop a theoretical framework in which, based on productivity and sectoral characteristics, firms decide whether to integrate into the production of intermediate inputs or outsource them and firms also choose the location of inputs production (at home or abroad). vii A strategic motive can be added to these usual motives for outsourcing when a firm outsourcing decision affects the rivals' outsourcing decisions and the firm takes into account it in the decision process. [START_REF] Shy | Strategic outsourcing[END_REF] and [START_REF] Buehler | Strategic outsourcing revisited[END_REF] study how firms may strategically outsource the productions of inputs analysing the trade-off between the fixed cost of investing into in-house production facilities for an input or the higher marginal cost for sourcing the input over the market (which is caused by changes in input demand and inputs prices). viii This hypothesis is in accordance to [START_REF] Antras | Firms, Contracts and Trade Structure[END_REF] who using a model of outsourcing based on the property rights approach shows that final goods in the capital-intensive sector are produced under vertical integration whereas those in the labour-intensive sector are outsourced. ix This increase is higher than the average scored by German manufacturing enterprises, which has placed in 27% for the period 1992-2000 according to [START_REF] Görzig | Outsourcing and firm-level performance[END_REF]. However, it should be noted that the fragmentation processes in German industry had most probably taken place before the 1990s.

x The sector "Manufacture of office machiney and computers" has been removed from the econometric analysis. The data in 2002 show a sharp decrease of output which is not present in employment or number of enterprises suggesting a measure error for that year. Since the indicador of outsourcing used is calculated related to output, the level of fragmentation will be overestimated. xi Although some American and British firms have already begun to outsource some of their business services abroad (so far mostly to India), the outsourcing of white-collar work is still only emerging (The Economist, November 13 th 2004). xii Following [START_REF] Piga | Sample selection in estimating the determinants of cooperate R&D[END_REF] those firms which face tougher foreign competition may exhibit a stronger tendency to cooperate. For this reason, we also could expect that firms competing in international markets were more prone to engage in outsourcing agreements. xiii The author is grateful to the anonymous referee for this suggestion.

  lowering the transaction costs and augmenting the possibilities for outsourcing.

  . Previous works have obtained positive signs

  ) of the Spanish Ministry of Science and Technology which offers data for 20 manufacturing industries.

  with a small number of time periods with highly persistent data. It can cause large finite-sample biased and poor precision in the estimators. To reduce this problem associated with

Figure 1 :

 1 Figure 1: Dimensions of Fragmentation of Production.

  Figure 3: Outsourcing of production according to industry taxonomy based on factor inputs

Table 1 : Sectoral disaggregation of Industrial Companies Survey 2002 Manufactures of food products, beverages and tobacco Manufacture of fabricated metal products

 1 151 Production, processing, preserving of meat, meat products 2811 Manufacture of metal structures and parts of structures 152 Processing and preserving of fish and fish products 2812 Manufacture of builders' carpentry and joinery of metal 153 Processing and preserving of fruit and vegetables 282 Manufacture of tanks, central heating radiators and boilers 154 Manufacture of vegetable and animal oils and fats Manufacture of leather clothes and other wearing apparel 311 Manufacture of electric motors, generators and transformers 183 Dressing and dyeing of fur; manufacture of articles of fur 312 Manufacture of electricity distribution and control apparatus 191 Tanning and dressing of leather 313 Manufacture of insulated wire and cable 192 Manufacture of luggage, handbags and the like, saddler 315 Manufacture of lighting equipment and electric lamps 193 Manufacture of footwear 314/316 Manufacture of accumulators and electrical equipment n.e.c. Manufactures

	283 Manufacture of steam generators

of paper, paper products, publishing and printing 321

  Manufacture of electronic valves and other electronic components 211 Manufacture of pulp, paper and paperboard 322 Manufacture of television, radio transmitters, apparatus for line telephony 212 Manufacture of articles of paper and paperboard 323 Manufacture of television and radio receivers, sound or video recording 221 Publishing

		Manufacture of transport equipment
	222-3 Printing and service activities related to printing	341 Manufacture of motor vehicles
	Manufacture of chemical	342 Manufacture of bodies for motor vehicles, trailers and semi-trailers
	241 Manufacture of basic chemicals	343 Manufacture of parts, accessories for motor vehicles
	242 Manufacture of pesticides and other agro-chemical products	351 Building and repairing of ships and boats
	243 Manufacture of paints, varnishes and similar coatings	352 Manufacture of railway, tramway locomotives, rolling stock
	244 Manufacture of pharmaceuticals, medicinal and botanical products 353 Manufacture of aircraft and spacecraft
	245 Manufacture of soap, detergents, cleaning, polishing	354-5 Manufacture of motorcycles and other transport equipment n.e.c.
	246 Manufacture of other chemical products

Manufacture of wood, furniture; manufacturing n.e.c.

	F o r
	P
	e
	e r
	R e v
	247 Manufacture of man-made fibres Manufacture of rubber and plastic products 251 Manufacture of rubber products 252 Manufacture of plastic products	201 Sawmilling and planning of wood, impregnation of wood i e 202 Manufacture of veneer sheets and other panels and boards 203 Manufacture of builders' carpentry and joinery 204 Manufacture of wooden containers w
	Manufacture of other non-metallic mineral products	2051 Manufacture of other products of wood
	261 Manufacture of glass and glass products	2052 Manufacture of articles of cork, straw and plaiting materials
	262 Manufacture of ceramic goods	361 Manufacture of furniture
	263-4 Manufacture of construction products	362 Manufacture of jewellery and related articles
	265 Manufacture of cement, lime and plaster	364-5 Manufacture of sports goods and games and toys
	266 Manufacture of articles of concrete, plaster, cement	363/366 Miscellaneous manufacturing n.e.c.
	267 Cutting, shaping and finishing of stone
	268 Manufacture of other non-metallic mineral products
	Manufacture of basic metals
	271 Manufacture of basic iron and steel and of ferro-alloys (ECSC)
	272 Manufacture of tubes
	273 Other first processing of iron and steel
	274 Manufacture of basic precious and non-ferrous metals
	275 Casting of metals

Table 2 : Outsourcing explanatory variables and expected signs in previous literature

 2

	Variable	Expected sign	Previous works
			Abraham and Taylor (1996)
	Labour costs	+	Girma and Görg (2004) Görg and Hanley (2004)
			Holl (2004)
		Q	Abraham and Taylor (1996)
	Firm Size	+	Tomiura (2005) Holl (2004)
	Market Size [Export propensity]	+	McLaren (2000) Grossman and Helpman (2002) [Görg and Hanley (2004)]
	National ownership	Q	Girma and Görg (2004) Görg and Hanley (2004)
		+	Holl (2004)
	Previous outsourcing level	+	Girma and Görg (2004) Swenson (2004)

Table 3 : Summary Statistics

 3

			1993		2002	1993-2002
		Mean Std. Deviation Mean Std. Deviation Mean Std. Deviation
	Outsourcing	3.83	3.59	5.11	4.71	4.49	4.17
	Unit Labour Cost	24.27	7.68	18.26	5.98	19.55	6.78
	% Small Firms	79.21	12.18	74.91	13.21	77.55	13.20
	Export Propensity	28.01	20.07	31.16	19.46	29.76	19.28
	National Ownership	77.53	12.14	77.41	13.10	77.14	12.37
	Foreign market penetration 5.15	3.59	8.02	4.98	6.78	4.64
	Skills (dummy)	0.12	0.33	0.12	0.33	0.09	0.28
	Source: Industrial Companies Survey, Comext, Survey of Firm Strategies and Peneder (1999).
		Note: All the variables are before taking logarithms.

Table 4 : Simple Correlations between variables

 4 Source: Industrial Companies Survey, Comext, Survey of Firm Strategies and[START_REF] Peneder | Intangible investment and human resources. The new taxonomy of manufacturing industry[END_REF].Note: All the variables are before taking logarithms. The number of observations is 870.

		Outsourcing ULC	% Small firms	Export Propensity	National Ownership	Foreign-market penetration	Skills
	Outsourcing	1.000
	Unit Labor Cost	0.440	1.000
	% Small Firms	0.155	0.176 1.000
	Export Prop.	0.184	0.153 -0.320	1.000
	National Own.	0.385	0.159 0.421	-0.183	1.000
	Foreign-market penet.	0.184	0.042 -0.293	0.411	-0.126	1.000
	Skills	0.321	0.281 -0.080	0.249	-0.109	0.298	1.000

Table 5 : Determinants of Outsourcing (GMM Regression Results).

 5 All equations include year dummies. AR(1) and AR(2) are tests of first and second order serial correlation. Sargan is a test of the over-identifiying restrictions (twostep estimations). P-values below 0.05 suggest a rejection of the validity of the instruments at the 5% critical level.

	Parameters	(1)	(2)	(3)	(4)	(5)
	Outsourcing t-1	0.802***	0.789***	0.802***	0.827***	0.922***
		(0.029)	(0.031)	(0.029)	(0.031)	(0.018)
	ULC	0.288***	0.282**	0.255**	0.159**	0.107**
		(0.097)	(0.128)	(0.126)	(0.072)	(0.048)
	%Small-firms	-0.031	-0.277*		-0.233*	-0.055
		(0.101)	(0.151)		(0.132)	(0.047)
	National-ownership	0.342**	0.533***	0.365***	0.443***	0.308
		(0.136)	(0.169)	(0.135)	(0.135)	(0.209)
	Export-propensity	-0.005		-0.015		0.013*
		(0.028)		(0.033)		(0.006)
	Foreign-market penetration				0.010*
					(0.006)
	Standardization	-0.084*	-0.097*	-0.114*	-0.067
		(0.050)	(0.057)	(0.061)	(0.052)
	High Skills	0.033*	0.040	0.040**	0.037*
		(0.017)	(0.026)	(0.018)	(0.018)
	Constant	-0.674**	-0.595*	-0.196	-0.424	-0.062
		(0.268)	(0.317)	(0.359)	(0.257)	(0.145)
	Observations	783	828	783	828	207
	Sectors	87	92	87	92	23
	Test (p-values)
	AR(1)	0.000	0.000	0.000	0.000	0.000
	AR(2)	0.318	0.337	0.329	0.381	0.189
	Sargan test	1.000	0.993	0.994	1.000	1.000
	Notes: Standard errors in parenthesis; statistically significant * at 10%, ** at 5*, *** at 1%.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript