Patrik Karpaty
email: patrik.karpaty@oru.se

Richard Kneller

Demonstration or Congestion? Export Spillovers in Sweden 1

Keywords: FDI, export spillovers, intensive export margin, extensive export margin. JEL classification: F13; F23

A key feature of the Swedish economy over the last two decades has been the rapid internationalisation of its economy, both through FDI and exports. In this paper we consider their inter-relationship, examining whether there have been spillovers from foreign firms to the export performance of domestic firms. We also contribute to the empirical modelling of export spillovers. We do this by exploiting information on whether foreign MNE sales are intra-firm or inter-firm, and by allowing for heterogeneity in the characteristics of the sender and receiver of spillovers. Our results indicate that foreign MNEs had positive effects on Swedish exports.

Section 1: Introduction

A key feature of the Swedish economy over the last two decades has been the rapid expansion of the stock of foreign-owned capital. Over the second half of the 1990's Sweden was the seventh largest recipient of foreign direct investment (FDI) globally and saw the percentage ratio of foreign to domestically owned firms rise by 10 percentage points to 27 per cent between 1990 and 2000 [START_REF] Blomström | The Economics of Foreign Direct Investment Incentives[END_REF]. Within the data we use in this study we calculate that the number of foreign-owned firms increased by 60 per cent between 1990 and 2001 (to 597 firms by 2001).

Alongside this increase in inward FDI, there has also been a rapid rise in Swedish exports. Our data reveal that the volume of export trade has risen by 150 per cent (to 691 million Swedish krona) over the sample period, while [START_REF] Greenaway | Exporting may not always boost firm level productivity[END_REF] and [START_REF] Hansson | Swedish business sector in a globalized world -Impact of internationalization on productivity and employment[END_REF] have previously reported that the number of firms exporting from Sweden rose from 75 per cent to over 86 per cent over the same time frame. Moreover this increase in exports has been faster amongst domestically owned firms: the share of total exports accounted for by domestically owned firms rose from 21 to 32 per cent between 1990 and 2001. 2An interesting question considered in other contexts has been to what extent there are export spillovers from foreign to domestic firms. 3 The aim of this paper is to test whether rising foreign presence in the Swedish economy has helped domestic firms to expand their export sales.

For this purpose we use data on Swedish manufacturing firms for the period 1990 to 2001.

Export spillovers are believed to be important for a number of reasons. To the extent that it encourages the growth of firms in industries in which the country has a comparative advantage then the country will benefit from classic gains from trade. As part of these gains, the recent heterogeneous firm literature has emphasised the effect that greater exports by firms has on aggregate productivity. Some studies have additionally suggested there is a causal effect from the decision to export on firm productivity. 4 Finally, there could also be dynamic gains from large scale production. If a firm can lower its average costs by entering new markets the extra resources that this releases could be used for investment in R&D ensuring that the firm brings its product or services into line with consumer needs. 5While the above discussion suggests that export spillovers are of economic relevance and that Sweden is an interesting country to search for them, the main contributions that we make come from the empirical modelling of spillovers. Building on the work of [START_REF] Greenaway | Do domestic firms learn to export from multinationals?[END_REF] we are able to separate the sales of foreign firms into those aimed at the domestic market and exports. This difference should allow us to determine whether any spillover effects we observe are general, in that they do not depend on the destination of final sales, or specific to export markets. As in the paper by [START_REF] Greenaway | Do domestic firms learn to export from multinationals?[END_REF] we are also careful to allow for separate effects of foreign multinational enterprises (MNEs) on the extensive (number of firms who export) and the intensive margins (the intensity with which those firms export) of exporting, accounting for the interdependence of these decisions through a Heckman selection model.

In addition to information on whether sales are to the domestic or export markets, we also have information on the buyer of those goods: whether sales are between other affiliates within the same group or not. This allows us to explore the possibility that sales between affiliates within the same firm reveal different information compared to sales to unrelated firms. In turn we also use this information to compare spillovers according to the type of FDI that has taken place. The presence of intra-firm domestic sales indicates that the foreign-owned firm has multiple plants located in Sweden. We investigate whether this deeper integration (either geographic or industrial) means that export spillovers are stronger than for single-plant foreign-owned firms.

We also explore possible heterogeneity in the effects of spillovers across other dimensions. Firstly, we test whether the characteristics of the foreign multinational (which we label sender-capacity) are important. 6 Specifically we examine the question of whether one can find stronger evidence of spillover effects from foreign-owned firms that are more productive compared to measures of foreign presence based on the size of firms. Secondly, we explore whether the effects of export spillovers differ according to the characteristics of the domestic firm. Are some firms better placed to capture the spillover benefits of foreign-owned firms? Absorptive capacity effects have previously been explored in the productivity spillovers literature by [START_REF] Cohen | Innovation and Learning: the Two Faces of R&D[END_REF]; [START_REF] Grünfeld | Meet Me Halfway but don't Rush -Absorptive capacity and strategic R&D investment revisited[END_REF]; [START_REF] Girma | Are there regional spillovers from FDI in the UK? In D[END_REF]; [START_REF] Haskel | Does Inward Foreign Direct Investment Boost the Productivity of Domestic Firms?[END_REF]; [START_REF] Kokko | Local Technological Capability and Productivity Spillovers from FDI in the Uruguayan Manufacturing Sector[END_REF]. However, to the best of our knowledge there is no previous study on the effects of sender capacity.

To preview some of the main findings of the paper, we find that in general increased FDI has had a positive effect on Swedish exports, where this effect has been primarily on the export intensity of existing exporters. We also find support for the extensions that we make to the spillovers literature. FDI spillovers are stronger for intra-firm sales (domestic and export) compared to inter-firm sales. This suggests that foreign multinationals that are more deeply embedded in the local economy impart stronger spillover effects. We also find that controlling for such heterogeneity in the foreign firms sending spillovers and the domestic firms receiving them is important. Stronger evidence of export spillovers can be found when greater weight is given to more productive foreign firms and when domestic firms are more R&D intensive.

The rest of the paper is organised as follows. Section 2 presents the empirical methodology used in the estimation and Section 3 the data sources and the construction of the main variables of the paper. Section 4 presents the empirical results. These include the main results as well as tests of heterogeneity. Section 5 concludes the paper.

6 Nothing in the above argument about demonstration or congestion is specific to the presence of foreign multinational firms. Larger numbers of domestic or foreign-owned firms that export will likely crowd out scarce resources in a similar manner, or equally offer opportunities for imitation. In such a case we might then expect no difference in the effect of foreign compared to domestic multinational firms, i.e. from large firms. We explored this by replacing foreign with domestic (Swedish) multinational firms in the regression. Unfortunately, this extension of the analysis leads us no further since none of the MNE presence coefficients were significant. Those estimates are not reported but can be ordered from the authors upon request.

Section 2: Empirical Methodology

In this paper we are interested in modelling the export decision of domestically owned firms. In the presence of firm heterogeneity and sunk costs of export market entry this can be thought as a twostage decision process whereby firms firstly decide whether to export or not, and secondly how much to export. Our econometric analysis accounts for both decisions and the fact that they are interdependent, thus avoiding any bias involved were they to be considered separately. Two equations are estimated using firm level data,

y* ijt = x ijt β + u ijt (export share regression) (1) d* ijt = z ijt γ + v ijt (export decision) (2) with y ijt = y* ijt if d ijt = 1; y ijt = 0 if d ijt = 0 and d ijt = 1 if d* ijt > 0; d ijt = 0 if d* ijt ≤ 0
The second equation describes the export participation decision for firm i in industry j in period t and is estimated as a probit regression. The first equation describes the intensity with which the domestic firm i in industry j in period t exports. The observed export share (y ijt ) is zero when the firm decides not to export (d ijt = 0) and assumes a positive value when the firm decides to export (d ijt = 1). The distribution of the error terms (u ijt ,v ijt ) is assumed to be bivariate normal with correlation ρ. The two equations (i.e. decisions) are related if ρ ≠ 0. In this case estimating only the export share regression would induce sample selection bias in the estimate of β since the error term u ijt , and the regressor x would be correlated. To avoid this problem both equations must be estimated. [START_REF] Heckman | Sample Selection Bias as a Specification Error[END_REF] proposed two alternative estimation methods; the maximum likelihood method and the two-step method. Of these we employ the former. 7 A drawback with the Heckman selection model is that it does not account for unobserved firm level characteristics. We assume that the observed firm level covariates such as productivity, absorptive capacity and size, are strongly correlated with any unobserved firm characteristics such as the quality of the capital, management philosophy and the value of intangible assets.

Within the vectors of covariates x ijt and z ijt we include measures of firm and industry characteristics, including our measures of the domestic and export activities of foreign MNEs. We describe in the next section the construction of these measures and their data sources. Identification of the sample selection model requires that the set of regressors in x ijt and z ijt cannot be the same and here we follow [START_REF] Helpman | Estimating Trade Flows: Trading Partners and Trading Volumes[END_REF] in using the heterogeneous-firms model of international trade [START_REF] Melitz | The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity[END_REF] to motivate the inclusion of a measure of the sunk-costs of exporting in the selection equation as the exclusion restriction. To capture the 'sunk-costs' of export market entry we follow [START_REF] Roberts | The Decision to Export in Colombia: An Empirical Model of Entry with Sunk Costs[END_REF] and [START_REF] Bernard | Why some firms export[END_REF] and include the lagged export status of the firm in equation (2).

Section 3: Data Sources and Construction of Variables

The data used in the paper are supplied by Statistics Sweden (SCB) and include all manufacturing firms in Sweden with at least 50 employees for the years 1990-2001. We rely principally on two data sets from SCB: the Financial Statistics Database (FS) and the Regional Labour Market Statistics Database (Rams). Combining these data provides us with information on the profit and loss accounts of firms and associated variables such as gross production, value added, employment, capital stock, purchases of other inputs, R&D expenditure, as well as detailed information on the level of human capital (e.g., the share of employees with post secondary college education).

While rich in the set of variables that might be used to describe the export behaviour of firms, the employment cut-off at above 50 in these data is worthy of comment and helps explain the relatively high proportion of export firms that we reported in the introduction. We consider the possible consequences of this sampling restriction for the conclusions that we draw from the paper by examining whether our results for export spillovers in Section 4 differ for firms of different sizes. We find some evidence that this is the case and are therefore careful not to generalise the conclusions that we reach as representing effects present for Swedish firms with employment below 50.8

To construct the measures of foreign presence needed in our empirical analysis requires us to be able to identify the nationality of the owner of the firm. We identify ownership using data collated by the Swedish Agency for Growth Policy Analysis (former ITPS). In these data a firm is defined as Swedish-owned if the Swedish owners control at least 50 per cent of the votes in the firm. If the firm belongs to a group of firms, ownership is defined as Swedish if the ultimate owner of the group controls at least 50 percent of the votes. A Swedish firm that has an overseas affiliate with at least one employee is classified as a domestic MNE. If the top level firm in the group hierarchy has at least one employee abroad, then all the firms within this group in Sweden are classified as Swedish MNEs. When more than half of the voting rights in the firm, or the firm at the top level, are controlled by a foreign owner the firm is classified as foreign-owned (foreign MNE).9

We make one further restriction to the sample of domestically owned firms that we use in our estimations, choosing to use only those firms that remain domestically owned firms throughout the sample period. In Sweden, as in most developed countries, the overwhelming majority of inward FDI occurs as a merger or acquisition. If the acquired firm was previously domestically owned, then without this restriction this firm will disappear from the sample following its acquisition and appear instead as increased foreign presence (i.e. as part of the calculation of one of the dependent variables). To avoid any problems that might occur from this movement across the regression we only include those domestic firms that were not acquired during the sample window.

This restriction reduces the number of firms included in the regressions by 13 per cent (2,078 observations). 10

Foreign presence and the destination of sales

The empirical evidence for other countries would suggest that the presence of foreign multinational firms in the domestic economy can have both positive and negative effects on the export decisions of domestic firms. The positive impacts come from demonstration or competition effects. These positive benefits might come in a number of different forms [START_REF] Aitken | Spillovers, Foreign Investment, and Export Behavior[END_REF]. For example, foreign multinationals may improve the information that domestic firms have about the preferences of foreign consumers, or the costs of serving those markets. They may alternatively encourage improvements in the domestic public infrastructure necessary to provide access to overseas markets, or themselves provide access to the distribution networks they have established.

This may lead additional domestic firms to start to export and the expansion of sales of existing exporters, extending both the extensive and intensive margins of domestic exports. Strong positive effects of this kind have been previously found for Mexico [START_REF] Aitken | Spillovers, Foreign Investment, and Export Behavior[END_REF]), for Uruguay [START_REF] Kokko | Trade regimes and spillover effects of FDI: Evidence from Uruguay[END_REF]) and the United Kingdom (Greenaway et al. 2004; Kneller and Pisu 2007). 11 Positive spillovers from FDI have not been found in all contexts, however. [START_REF] Ruane | Foreign Direct Investment and Export Spillovers: How Do Export Platforms Fare? IIIS Discussion Paper[END_REF] for Ireland, and [START_REF] Swenson | Multinationals and the Creation of Chinese Trade Linkages[END_REF] for China have found that the presence of foreign firms has a negative effect on the export possibilities of domestic firms, while [START_REF] Barrios | Explaining Firms' Export Behaviour: R&D, Spillovers and the Destination Market[END_REF] for Spain, and [START_REF] Sjöholm | Which Indonesian firms export? The importance of foreign networks[END_REF] for Indonesia find no effect. Explanations of the negative export effect that foreign firms have in Ireland and China differ somewhat. [START_REF] Ruane | Foreign Direct Investment and Export Spillovers: How Do Export Platforms Fare? IIIS Discussion Paper[END_REF] suggest that they are explained by the use of Ireland as an export platform to the rest of the European Union, such that there is little interaction between domestic and foreign firms. In her 10 The eliminated firms are distributed unevenly between the 22 industries at the two digit level: Machinery, equipment (17%), Fabricated metal (11%), Food & beverages (9%), Wood (8%), Motor vehicles (8%), Paper & pulp (7%), Medical instruments (6%), Chemicals (6%), Non-metallic mineral (5%), Rubber & plastic (4%), Publishing, printing (4%), Basic metals (3%), Other manufacturing (3%), Electrical machinery (3%), Other transport eq. ( 2%), Radio TV (2%), Textiles (1%), Electrical & optical (1%).

11 For a more detailed comparison of studies within this literature see [START_REF] Greenaway | Firm heterogeneity, exports and FDI[END_REF].

explanation for China, [START_REF] Swenson | Multinationals and the Creation of Chinese Trade Linkages[END_REF] draws on the evidence for negative productivity spillovers found by [START_REF] Aitken | Do Domestic Firms Benefit from Direct Foreign Investment? Evidence from Venezuela[END_REF]. A firm's entry into export markets is known to be sensitive to its level of productivity [START_REF] Bernard | Exceptional exporters performance: cause, effect or both?[END_REF][START_REF] Aw | Export Market Participation, Investments in R&D and Worker Training, and the Evolution of Firm Productivity[END_REF]). If the presence of foreign firms drives up the costs of labour or other factor inputs, then in a heterogeneous firm framework [START_REF] Melitz | The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity[END_REF], this would make it less likely that the marginal domestic firm will start to export and lower the extent to which established exporters sell their goods abroad. In a similar manner foreign firms may also contribute to the congestion of local infrastructure or services necessary for access into, or delivery to, export markets, again raising the costs of exporting.

The exports spillovers literature has thus far allowed for possible differences in the effect of foreign presence according to whether sales are in the domestic or export markets, with the expectation that the potential for knowledge diffusion or congestion is greater from export rather than domestic sales. The data for Sweden have additional information on the buyer of those goods, whether they are to other firms under the same management or to independent firms. SCB collect these data using questionnaires sent to every firm in the manufacturing sector. 12 Strong arguments can be made why this separation into inter-firm and intra-firm sales might matter for export spillovers to domestic firms. Intra-firm exports might not contain the same information about the characteristics of foreign markets compared to inter-firm exports for example.

Given that spillover effects are in general expected to be weaker for domestic sales this might be used to argue in favour of combining the data on intra-firm and inter-firm domestic sales. We

choose not to because it may alternatively reveal information about the type of FDI being conducted by the foreign firm. By definition intra-firm sales can only occur when the foreign firm has multiple production units within Sweden. The scope for spillovers may therefore be greater if multiple production units within Sweden reflect greater integration of the foreign multinational into the 12 The response rate in the manufacturing sector was very high. For firms with more than 50 employees the response rate is over 95 per cent. After 2001 the survey was less ambitious in scope and therefore marks the end of the data period we use in the study. Comparing these data with a different series on firm exports (which does not separate between intra-firm and inter-firm exports) also collected by Statistics Sweden, we find a correlation (for the years 1997-2005) of export values of over 93 per cent. The correlation in terms of number of exporters is a few percentage points lower since the data where intra-firm and inter-firm exports are collected at a higher level in the enterprise.

domestic economy. Spillovers to domestic firms might be expected to be greater because production is spread across different regions, and spillovers have been shown to decline with distance [START_REF] Greenaway | Exporting, Productivity and Agglomeration[END_REF], or because multiple aspects of the production process are located within Sweden increasing the potential for spillovers along the production chain. [START_REF] Javorcik | Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers Through Backward Linkages[END_REF] has previously shown that vertical productivity spillovers are stronger than horizontal spillovers.

This variable may therefore capture effects on domestic firms that go beyond those of just information about foreign markets and may suggest differences in export spillovers according to the type of FDI that takes place. As this fits into the broader issue of differences in the potential for spillovers across foreign firms that we investigate in the paper we leave this as an open question and allow the data to determine its importance. To reflect this discussion we interpret the results for this variable as being somewhat broader than those for the other foreign presence measures.

The measure of the presence of foreign-owned firms, P, in industry j at time t used in the paper is constructed as the ratio of sales by foreign-owned firms (FOF) in total sales, where the category of sales varies across domestic and export sales and intra-firm and inter-firm sales. More specifically it is measured as

N i ijt F f fjt jt Y Y P 1 1 (3)
where P jt is the presence of foreign-owned firms in industry j at time t defined as the ratio between Y fjt , i.e. the sales in the fth foreign firm in the jth industry at time t by foreign-owned firms and Y ijt which is the total industry sales in industry j at time t. 13 We calculate four variants of the index above; domestic sales to firms within the same group of companies (horizontal domestic intra) and 13 Given the use of both industry and firm level variables in the regression we estimate all specifications using the Moulton--White standard errors adjusted to account for possible correlation within a cluster [START_REF] Moulton | An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit[END_REF].

to other firms (horizontal domestic inter), exports to firms within the same group of companies (horizontal export intra) and to other firms (horizontal export inter). 14Table 1 provides the values of the four foreign presence variables for 22 industries at the 2-digit level in 1990 and 2001. The distribution of sales by foreign MNEs is characterized by large variation across industries, although -consistent with the rising presence of foreign firms in the Swedish economy over time -the observed trend is upward for each of these different measures.

Of the different combinations of intra/inter domestic/export sales for the 22 industries listed in Table 1, foreign presence fell between 1990 and 2001 in only 8 out of 84 industries. These falls are confined largely to domestic (intra-firm or inter-firm) sales. According to the evidence presented in the table they increased by the largest amount for intra-firm export sales. For example in the chemical sector the intra-firm export increased from 4.8 to 44.17 per cent between 1990 and 2001.

One explanation for this has been the acquisition of large Swedish MNEs during the 1990's, such as Astra, Pharmacia, Volvo Car, Saab Automobile, by foreign firms. These firms have large intra-firm exports to their overseas affiliates. Support for this view can be found from the noticeably large changes of foreign presence in the chemical and the motor vehicle industries. Foreign multinationals also seem to have increased their host-market sales in the food industry and in other manufacturing.

Absorptive Capacity and Sender Capacity

In the paper we also consider whether the flow of export spillovers from foreign firms depends on sender and receiver (absorptive) capacity of foreign and domestic firms. In the construction of foreign presence in equation (3), foreign firms are given greater weight depending on the level of sales of the firm. We might anticipate however, that the larger the technology gap between domestic and foreign firms the greater the scope for catching up or learning effects [START_REF] Findlay | Relative Backwardness, Direct Foreign Investment and the Transfer of Technology: A Simple Dynamic Model[END_REF]. To explore such effects we construct a new weighted measure of foreign presence, allowing the weight of foreign firms to differ according to their productivity. We assume that the functional form is nonlinear such that the marginal sender capacity is increasing in the foreign firms' productivity, but at a decreasing rate. We compute this new weighted index of foreign presence ( fjt W is the ratio between productivity in foreign-owned firm f in industry j relative to (one plus) its productivity. Spillover effects have also been shown to depend on the absorptive capacity of the domestic firm [START_REF] Cohen | Innovation and Learning: the Two Faces of R&D[END_REF]). Here we follow [START_REF] Grünfeld | Meet Me Halfway but don't Rush -Absorptive capacity and strategic R&D investment revisited[END_REF] and include in the regression interaction terms between domestic firm characteristics and foreign presence. The interaction variables intended to capture absorptive capacity are calculated as the product of the presence variables and the R&D intensity (labelled absorptive capacity) of the domestic firm. The data used to measure R&D is taken from the FS database and cover all firms with at least one employee active in R&D activities (at a minimum of 50 per cent of full time). These data are retrieved annually and it is compulsory for firms to reply. The respondents are asked to give an exact figure for R&D expenditure or answer in an interval scale (1-249 000, 250 000-999 000, 1-4.9 million, 5-9.9 million or 10 million SEK or more). If the yearly R&D expenditures exceed 10 million SEK, firms specify the exact amount of expenditure. 15

Additional control variables

In this paper we are interested in the potential demonstration or congestion effects that arise from the presence of foreign MNEs on the export decision of Swedish firms. We are therefore careful to control for other factors that may affect the correlation of these measures with the export behaviour of Swedish firms. 16 To capture differences in export behaviour across firms we follow [START_REF] Greenaway | Firm heterogeneity, exports and FDI[END_REF] and include in the regressions measures of firm size (the log of employment), total factor productivity (TFP) 17 , R&D intensity and previous export market experience. 18 Also included in our estimated equations are a full set of time fixed effects, industry fixed effects (there are 200 4-digit industries) and region fixed effects (24 counties). We use the industry and region effects to control for a wide range of time-invariant omitted industry and regional factors, such as infrastructure and local labour markets, that might explain possible correlations of firm export decisions with our foreign presence variables. 19 The time effects are used to control for shocks common to all firms, such as exchange rate movements at the accession 15 As around two thirds of firms report no R&D, we follow [START_REF] Grünfeld | Meet Me Halfway but don't Rush -Absorptive capacity and strategic R&D investment revisited[END_REF] and set these values to zero. 16 We also follow standard practice in using lagged foreign presence measures. 17 TFP is measured using the Törnqvist Index approach. 18 By including both firm level R&D and skill intensity we would introduce a double counting problem, since a substantial part of the R&D expenditures are wages to high-skilled employees. The other obvious option would be to adjust firm level R&D intensity to consider this double counting problem. Not reported, but with qualitatively similar results are specifications using skill intensity instead of R&D intensities. 19 As an alternative to 4-digit industry effects we also attempted to control for differences in the propensity to export across industries and for changes in difficult-to-measure factors that have changed across time, such as trade costs, by including a measure of the industry export share. This variable is constructed at the 2-digit level. Our estimates are robust to the inclusion of this variable and can be ordered from the authors upon request.

of Sweden into the European Union. Finally, to capture changes to the competitiveness across time of each industry we include an industry specific producer price index. 20

Section 4: Empirical results

The Heckman selection model is used in Tables 23456to empirically test whether the export intensity in a domestically owned firm is higher or lower due to the presence of foreignowned firms. The Heckman method uses an ordinary probit model (column 1 in the tables) in the first step to obtain consistent estimates of the parameters of the selection equation. In the second step, the export share (column 2 in the tables) is evaluated and equation ( 1) is estimated by OLS for the observations with positive exports only. If the estimated term is significantly different from zero we may reject the hypothesis of no correlation between the two error terms from the export decision and the export share equations respectively. Significance of this term indicates that the Of the control variables reported in column 1 most have the expected relationship with the probability of exporting. Amongst the firm level variables the lagged export status of the firm would appear to be a very important predictor of exporting. The effect of the lagged export dummy is positive and highly significant. This is typically interpreted as evidence of sunk costs to export market entry [START_REF] Bernard | Why some firms export[END_REF]. A number of the other firm level controls, while less important, also play a role. The probability that a domestically owned Swedish firm exports is increasing in its size, as well as its TFP and R&D intensity (absorptive capacity), although only the effect of size is significantly different from zero. A greater number of the firm level variables are 20 The producer price index shows the average change in prices at producer and import stages for different industries and product groups, i.e. in the first distribution stage when goods are delivered from Swedish producers or come into Sweden.

significant determinants of how much they export in the second step regression. The export intensity of the firm is rising in R&D intensity, size and productivity. 21 All effects are strongly significant. Finally we note that the industry producer price index has no significant effect in the export intensity regression, but it is found to lower the probability of starting to export. Given the inclusion of common time effects this would suggest that in industries where competitiveness has worsened, domestic firms find it harder to export.

The presence of foreign multinationals within the Swedish economy has an interesting relationship with the export decision of domestically owned firms. Firstly, as can be seen in Table 2 column 1, it has no statistically significant effect on the decision to participate in export markets.

The rise in inward FDI over the sample period does not seem to have affected the extensive margin of exporting. Some aspects of foreign FDI have affected the intensive margin of firm exports however. Both intra-firm domestic and export sales are positively correlated with the export intensity (column 2). In both cases these effects are positive, suggesting demonstration rather than congestion effects. The results, therefore, display greater similarity with those for the United Kingdom [START_REF] Greenaway | Do domestic firms learn to export from multinationals?[END_REF][START_REF] Kneller | Industrial Linkages and Export Spillovers from FDI[END_REF] and Spain [START_REF] Barrios | Explaining Firms' Export Behaviour: R&D, Spillovers and the Destination Market[END_REF]) compared to those for Ireland [START_REF] Ruane | Foreign Direct Investment and Export Spillovers: How Do Export Platforms Fare? IIIS Discussion Paper[END_REF], where the co-presence of foreign multinationals was found to negatively affect firm exports.

That the effects of knowledge diffusion from FDI are greater for intra-firm sales, both domestic sales and exports, contrasts with our prior expectations. It was expected that inter-firm exports would reveal more about the required distribution networks and tastes of foreign consumers than intra-firm exports. In our sample it would appear that the opposite is true. For domestic intrafirm sales we believe that the significance of this variable may reflect a difference in the type of FDI. Those foreign firms with intra-firm domestic sales have multiple plants and so are more deeply 21 In the present specification competition effects of foreign presence cannot be captured as all parameters are identified conditional on firm productivity. One way to deal with this issue would be to re-estimate the model without continuous TFP and size, but with pre-sample TFP and employment as control variables instead. To investigate whether this had any effect on our results we tried an additional specification using initial TFP and initial size instead of TFP and size as a continuous variables. The results are robust to this approach as the significance and magnitude of the relevant parameter estimates remained almost unchanged.

integrated into the Swedish economy. As a consequence they have a stronger effect on the behaviour of domestic firms. We take this to suggest that not all FDI is the same. This raises the possibility that similar effects are present for intra-firm exports.

To further investigate this point we construct a new measure of foreign presence that separates between multi-plant and single-plant foreign firms. Table 7 in the Appendix provides summary statistics of the four presence measures further separated in this way. According to Table 7 there were 3.3 times more multi-plant foreign firms than single-plant firms in the data in 1990. By 2001 the number of both types had risen, but single-plant firms grew proportionally more quickly such that the ratio of multi-plant to single-plant firms fell to 2.3. Table 7 also reveals differences in the size of average sales (domestic and export, intra-firm and inter-firm) across these different firm types. The regression results which are shown in Table 3 reveal however, no differences in the effect of multi-plant and single-plant foreign firms on the export performance of domestic firms beyond that already uncovered in Table 2. In addition, compared to these earlier results, the significance of the variable measuring foreign intra-firm export sales is lost. The export spillover effects of foreign firms remain confined to those from intra-firm domestic sales. Based on these results we choose not to carry the distinction between multi-and single-plant foreign firms forward in the paper, although given the continued significance of intra-firm domestic sales we believe the results are worthy of future exploration within the spillovers literature.

Extensions and Robustness Testing

From the above regressions we find some evidence of demonstration effects in Sweden towards established exporters, in particular the greater are intra-firm exports and domestic sales of foreign MNEs. In this section we search for further detail on the nature of the demonstration effects uncovered thus far, by allowing for differences amongst domestically owned firms receiving the spillovers and amongst the foreign-owned firms transmitting them. Our results from this section suggest that controlling for such heterogeneity is important when modelling export spillovers from FDI.

In Table 4 we consider the possibility that the spillover effects from foreign multinationals may depend not on the sales but on the productivity of the foreign firm, and that, other things being equal, the behaviour of more productive foreign-owned firms may have greater influence on the export behaviour of domestically owned firms. We label this as sender capacity in Table 4. We find support for this new measure. 22 Comparing the results to those in Table 2 we find that the magnitude of the positive demonstration effects is stronger in Table 4 for the variables measuring intra-firm exports and domestic sales. Interestingly we also find using this new weighting of foreign firms a (weak) significant effect from inter-firm exports in the export participation regression. The changes relative to those reported in Table 2 would appear to occur from an increase in the size of the coefficients on the spillover variables, although we find no noticeable change in the log-likelihood between the two tables. Taken together the results for intrafirm domestic sales and those for sender capacity more generally suggest that Swedish firms benefit from the presence of the best foreign multinational firms, rather than just large foreign firms. Given this we retain the use of the sender capacity variable to calculate foreign presence in the remainder of the paper.

Table 5 reports an extension to consider differences in the effect of foreign presence across domestic firms. Just as foreign multinationals may exert different external spillovers according to their sender-capacity, domestic firms may not be equal in their ability to receive the benefits of spillovers. We capture these differences in the ability of domestic firms to absorb the knowledge contained within the foreign firm using a measure of the level of R&D intensity of the receiver (domestic) firm interacted with the foreign presence variables. 23The results in Table 5 support the hypothesis that the absorptive capacity of the domestic firms is important for export demonstration effects, where the effects are felt in both the export participation and the export share regressions. For a number of the measures of foreign presence the most R&D intensive domestic firms appear most likely to benefit from observing the methods that foreign multinationals use to successfully export to foreign markets. In the export participation regression positive spillover effects are found from the extent of intra-firm exports by foreign-owned MNEs but only for the most R&D intensive firms. For those without R&D we find some evidence of congestion effects. We find similar negative direct effects from inter-firm exports for the export intensity of the firm, although again the interaction with R&D is significant and positive. The results suggest that for firms with no R&D, export intensity is reduced by 0.16 percentage points. In contrast for a firm with the mean level of R&D intensity (1.3 per cent of sales) the export intensity of the firm is increased by 0.05 percentage points, while for a firm with an R&D intensity one standard above the mean the effect on export intensity is estimated to be 0.30 percentage points higher.

In the export intensity regression we also uncover a strongly significant interaction term between the variables measuring the inter-firm exports of foreign MNEs and the R&D intensity of domestic firms. Here the direct effect is also positive, however. The export intensity of a firm with no R&D is raised by 0.065 percentage points, while for a firm one standard deviation above the mean it is raised by 0.21 percentage points. Finally, as before, we find demonstration effects from intra-firm and inter-firm domestic sales. Unlike for the exports of foreign firms we find no evidence that these effects differ according to the R&D intensity of the firm.

As described in section 3 the data sample is restricted to firms that have more than 50 employees. From a statistical view one can establish the importance of this restriction by testing whether the effect of foreign presence differs across firms of different sizes. If the results appear to be common, and the interaction terms are statistically insignificant, then we might reasonably generalise the conclusions to all Swedish firms. If they are significant we should reflect this outcome in the conclusions that we reach.

According to the results presented in Table 6 there is evidence of heterogeneity in the effect of the presence of foreign MNEs on the export behaviour of Swedish firms for firms of different sizes, and these results are distinct from those found for R&D intensity in Table 5. The interaction terms found for R&D and foreign presence in Table 5 are robust to the inclusion of the interactions with firm size. Absorptive capacity and firm size measure different aspects of firm heterogeneity in the current context.

That the results for foreign presence interacted with employment are positive in some cases and negative in others shows that the effect of the size-cut of the sample on the results is not in one particular direction. Most noticeably, the effects of intra-firm and inter-firm domestic sales by foreign firms on export intensity vary with the size of firm. There is no evidence of demonstration effects from intra-firm domestic sales for the largest domestic firms, but congestion effects from inter-firm domestic sales. Given the interpretation of the intra-firm domestic sales variable as capturing the type of FDI, this result again points to a motivation for a closer analysis in future work.

Section 5: Conclusion

In the last few decades Sweden has been successful in increasing the extent of its international exposure, both in terms of increased inward (and outward) FDI flows and export sales.

In this paper we consider the extent to which these increased inward FDI flows affected export flows through export spillovers. We allowed these effects to be positive, which we called demonstration effects, and negative, which we called congestion effects. We also allowed for differential impacts on the intensive and extensive margins of exporting and according to the destination of sales (domestic and foreign) and whether they were intra-firm or inter-firm. This rich disaggregation of the measures of foreign presence generated results that allow us to point at the specific nature of export spillovers in the Swedish context.

It would appear from our results that to the extent that foreign MNEs had an effect on Swedish firms with employment greater than 50 it was broadly positive. These effects are primarily concentrated on the export intensity of Swedish firms. There is also some suggestion that the benefits from FDI are not general, they depend on the characteristics of the foreign firm sending them and the domestic firm receiving them. Export spillover effects are strongest when greatest weight is given to the most productive foreign firms within the sample and the most R&D intensive domestic firms. We also uncover some initial evidence that suggests that the type of FDI matters.

To the extent that we can find congestion effects these appear confined to large firms the greater are inter-firm domestic sales of foreign firms and for domestic firms with no R&D.

Overall it would appear that the increased globalisation of Sweden over the 1990's has contributed positively to the growth of Swedish export sales, and that positive spillover effects are possible even when the extent of global engagement is already high. (1.91) * Note: MLE estimates. Cluster (industry) adjusted std errors standard errors in parentheses. *** significant at the one per cent level, ** significant at the five per cent level, * significant at the ten per cent level. The model includes the same conditioning variables included in the estimation of Table 2. F-tests; Ho: b_FOR×abs + b_FOR ==0 where b_FOR×abs and b_FOR are the estimated coefficients of the foreign presence with interactions and foreign presence without interactions, respectively; z-values are given in parenthesis. Note: Foreign firms with a single-plant in Sweden have no intra-firm domestic sales since the firm and plant by definition is the same. The number of plants in Sweden for the multi-plant foreign-owned firms varies between 2 and 140 with an average of 5.84 plants per firm.

The multi-plants constitutes 75% of all foreign-owned firms in Sweden during the period 1990-2001. Source Statistics Sweden and authors own calculations.

  each foreign firm's output by its productivity and then summing across foreign firms. This measure gives greater weight to those foreign MNEs in the top percentiles of the distribution, but on the margin the weight is decreasing in productivity. Formally we can write this as follows: foreign firm's sale (intra/inter) or export (intra/inter).

  domestic firm's R&D intensity, measured as R&D expenditures divided by sales. The marginal return to absorptive capacity is decreasing in a firm's R&D intensity. For firms with low initial R&D intensity an increase in R&D intensity will have a large positive effect on the absorptive capacity, whereas for high initial values the marginal increase in the absorptive capacity is smaller.

Table 1

 1 Percentage share of sales by foreign MNEs in total industry sales by destination (domestic/exports) and buyer (intra/inter-firm) for 2-dgit industries in 1990 and 2001 The sample is truncated at 50 employees. The foreign presence indices have been recalculated at the two digit level and are expressed as percentage share of export and domestic sales to total domestic sales. Source: Statistics Sweden.

	1990	2001

Table 2 :

 2 Heckman selection model of export spillovers on Swedish manufacturing firms that remain domestic the whole period. MLE estimates. Cluster (industry) adjusted std errors standard errors in parentheses. *** significant at the one per cent level, ** significant at the five per cent level, * significant at the ten per cent level.

	Variables	Export Dummy	Export share
		(1)	(2)
	Firm Variables
	lagged export dummy	1.998
		(0.054) ***
	log of employment	0.180	0.032
		(0.039) ***	(0.010) ***
	TFP	0.843	0.824
		(0.878)	(0.253) ***
	Absorptive capacity (R&D)	6.145	1.311
		(3.594)	(0.368) ***
	Foreign Presence
	lagged intra-firm exports sales	-0.773	0.125
		(0.477)	(0.066) *
	lagged inter-firm exports sales	0.543	-0.056
		(0.346)	(0.043)
	lagged intra-firm domestic sales	-0.369	0.159
		(0.939)	(0.062) **
	lagged inter-firm domestic sales	-0.047	0.067
		(0.393)	(0.042)
	Other Control Variables
	producer price index	-0.004	0.000
		(0.002) *	(0.000)
	4-digit industry effects	X	X

Table 3 :

 3 Heckman selection model of export spillovers on Swedish manufacturing firms that remain domestic the whole period, divided into single-and multi-plant foreign firm presence. MLE estimates. Cluster (industry) adjusted std errors standard errors in parentheses. *** significant at the one per cent level, ** significant at the five per cent level, * significant at the ten per cent level.

	Variables	Export Dummy	Export share
		(1)	(2)
	Firm Variables
	lagged export dummy	1.998
		(0.054) ***
	log of employment	0.180	0.032
		(0.039) ***	(0.010) ***
	TFP	0.796	0.824
		(0.879)	(0.253) ***
	Absorptive capacity (R&D)	6.192	1.311
		(3.614) *	(0.368) ***
	Foreign Presence
	Single-plant foreign firms
	lagged intra-firm exports sales	-2.448	-0.144
		(1.654)	(0.139)
	lagged inter-firm exports sales	0.552	-0.057
		(0.853	(0.097
	lagged intra-firm domestic sales	0.074	0.057
		(0.716)	(0.076)
	Multi-plant foreign firms
	lagged intra-firm exports sales	-0.222	0.108
		(0.486)	(0.072)
	lagged inter-firm exports sales	0.165	-0.048
		(0.316)	(0.050)
	lagged intra-firm domestic sales	0.008	0.016
		(0.393)	(0.047)
	lagged inter-firm domestic sales	-0.434	0.147
		(0.966)	(0.062) **
	Other Control Variables
	producer price index	-0.004	0.000
		(0.002) *	(0.000)
	4-digit industry effects	X	X
	Region effects	X	X
	Year effects	X	X
		-0.275
		(0.063) ***
		-0.061
		(0.015) ***
	Log pseudo likelihood	-1,200
	No. of obs	10,702
	Censored obs	1,973
	Uncensored obs	8,729
	Note:

Table 4 :

 4 Heckman selection model of export spillovers on Swedish manufacturing firms that remain domestic the whole period, controlling for sender capacity. MLE estimates. Cluster (industry) adjusted std errors standard errors in parentheses. *** significant at the one per cent level, ** significant at the five per cent level, * significant at the ten per cent level. The model includes the same conditioning variables included in the estimation of Table2.

	Variables	Export Dummy	Export share
		(1)	(2)
	Firm Variables
	lagged export dummy	1.995
		(0.049) ***
	log of employment	0.184	0.034
		(0.036) ***	(0.010) ***
	TFP	1.525	0.788
		(0.840) *	(0.212) ***
	Absorptive capacity (R&D)	6.729	1.311
		(3.426) *	(0.357) ***
	Foreign Presence (Sender Capacity)
	lagged intra-firm exports sales	-0.862	0.165
		(0.667)	(0.093) *
	lagged inter-firm exports sales	0.776	-0.068
		(0.470) *	(0.057)
	lagged intra-firm domestic sales	-0.513	0.251
		(1.252)	(0.083) ***
	lagged inter-firm domestic sales	-0.206	0.089
		(0.558)	(0.058)
	Other Control Variables
	producer price index	-0.002	0.000
		(0.002)	(0.000)
	4-digit industry effects	X	X
	Region effects	X	X
	Year effects	X	X
		-0.274
		(0.064) ***
		-0.061
		(0.015) ***
	Log pseudo likelihood	-1,197
	No. of obs	10,702
	Censored obs	1,973
	Uncensored obs	8,729
	Note:

Table 5 :

 5 Heckman selection model of export spillovers on Swedish manufacturing firms that remain domestic the whole period, controlling for sender and receiver capacity.

	Variables	Export Dummy	Export share
		(1)	(2)
	Firm Variables
	lagged export dummy	1.995
		(0.055) ***
	log of employment	0.176	0.032
		(0.039) ***	(0.010) ***
	TFP	0.805	0.838
		(0.871)	(0.254) ***
	Absorptive capacity (R&D)	2.694	0.800
		(3.274)	(0.509)
	Foreign Presence (Sender Capacity)
	lagged intra-firm exports sales	-1.301	0.065
		(0.779) *	(0.114)
	lagged inter-firm exports sales	0.844	-0.160
		(0.517)	(0.073) **
	lagged intra-firm domestic sales	-0.574	0.216
		(1.296)	(0.105) **
	lagged inter-firm domestic sales	-0.339	0.108
		(0.570)	(0.064) *
	Foreign Presence×Absorptive Capacity
	lagged export intra×absorp. capacity	80.306	2.976
		(30.039) ***	(1.583) *
	lagged export inter×absorp. capacity	-7.744	6.394
		(21.442)	(2.336) ***
	lagged domestic intra×absorp. capacity	-12.197	1.927
		(15.715)	(3.168)
	lagged domestic inter×absorp. capacity	39.784	-0.758
		(38.007)	(3.095)
	Other Control Variables
	producer price index	-0.004	0.000
		(0.002)	(0.000)
	4-digit industry effects	X	X
	Region effects	X	X
	Year effects	X	X
		-0.274
		(0.063) ***
		-0.061
		(0.015) ***
	Log pseudo likelihood	-1,197
	No. of obs	10,702
	Censored obs	1,973
	Uncensored obs	8,729
	F-tests
	lagged export intra×abs + lagged export intra = 0	79.004	3.041
		(2.65) ***	(1.97) **
	lagged export inter×abs + lagged export inter = 0	-6.900	6.233
		(0.32)	(2.31) ***
	Total effect from interaction variables	98.778	10.768
		(1.92) *

Table 6 :

 6 Heckman selection model of export spillovers on Swedish manufacturing firms that remain domestic the whole period, controlling for sender capacity and size. MLE estimates. Cluster (industry) adjusted std errors standard errors in parentheses. *** significant at the one per cent level, ** significant at the five per cent level, * significant at the ten per cent level. The model includes the same conditioning variables included in the estimation of Table2

	Variables	Export Dummy	Export share
		(1)	(2)
	Firm Variables
	lagged export dummy	1.994
		(0.055) ***
	log of employment	0.173	0.036
		(0.046) ***	(0.014) ***
	TFP	0.781	0.834
		(0.862)	(0.254) ***
	Absorptive capacity (R&D)	2.640	0.775
		(3.285)	(0.502)
	Foreign Presence (Sender Capacity)
	lagged intra-firm exports sales	4.860	0.292
		(3.049)	(0.440)
	lagged inter-firm exports sales	4.148	-0.703
		(2.399) *	(0.414) *
	lagged intra-firm domestic sales	-23.739	-0.997
		(7.403) ***	(0.720)
	lagged inter-firm domestic sales	-0.727	0.881
		(1.711)	(0.368) **
	Foreign Presence×Absorptive Capacity
	lagged export intra×absorp.capacity	90.710	3.064
		(30.641) ***	(1.533) **
	lagged export inter×absorp.capacity	-7.572	5.913
		(22.998)	(2.255) ***
	lagged domestic intra×absorp.capacity	-18.197	1.316
		(15.892)	(3.997)
	lagged domestic inter×absorp.capacity	39.769	-0.059
		(38.163)	(3.059)
	Foreign Presence×employment
	lagged export intra×employment	-1.376	-0.049
		(0.580) **	(0.081)
	lagged export inter×employment	-0.736	0.114
		(0.570)	(0.085)
	lagged domestic intra×employment	5.286	0.249
		(1.620) ***	(0.146) *
	lagged domestic inter×employment	0.071	-0.162
		(0.363)	(0.076) **
	Other Control Variables
	producer price index	-0.002	0.000
		(0.002)	(0.000)
	4-digit industry effects	X	X
	Region effects	X	X
	Year effects	X	X
		-0.286
		(0.060) ***
		-0.063
		(0.014) ***
	Log pseudo likelihood	-1,147
	No. of obs	10,702
	Censored obs	1,973
	Uncensored obs	8,729
	Note:

Table 7

 7 Average size, TFP, domestic sales (intra-and inter-firm), exports (intra-and inter-firm) for foreignowned firms with single or multiple plants inSweden 1990Sweden -2001. .

		Number of	Average	Total Factor	Inter-firm	Intra-firm	Inter-firm	Intra-firm
		firms	employment	Productivity	domestic sales	domestic sales	exports sales	exports sales
	Year	single	multi	single	multi	single	multi	single	multi	single	multi	single	multi	single	multi
	1990	81	263	173	374	2.25	2.27	82,726	216,177	0	45,240	102,016	93,341	37,121	79,742
	1991	84	281	173	370	2.22	2.29	78,359	199,664	0	45,004	90,194	107,443	40,098	75,443
	1992	73	288	157	349	2.30	2.37	71,977	180,442	0	37,389	57,792	100,860	44,687	81,262
	1993	69	249	147	338	2.36	2.36	79,067	189,342	0	44,626	70,234	125,654	44,883	96,581
	1994	72	262	165	331	2.27	2.26	94,640	218,115	0	49,721	76,766	154,537	61,381	116,787
	1995	95	306	168	352	2.20	2.16	108,637	220,856	0	61,143	92,884	171,444	43,170	170,957
	1996	102	308	184	354	2.21	2.17	127,214	251,888	0	56,224	90,703	123,336	80,536	160,788
	1997	115	325	163	360	2.96	2.95	117,031	245,015	0	52,623	94,515	154,892	72,804	178,558
	1998	138	340	152	378	3.18	3.30	116,240	239,074	0	74,444	110,700	167,864	63,907	199,548
	1999	133	352	162	432	3.24	3.73	133,910	271,542	0	104,237	128,464	195,095	41,847	411,855
	2000	150	367	155	480	3.20	3.34	155,526	316,653	0	94,855	141,832	320,760	38,818	444,486
	2001	178	419	146	470	3.21	3.29	117,623	343,505	0	104,049	141,056	260,213	45,338	423,438

Acknowledgements: Richard Kneller gratefully acknowledges financial support from the Leverhulme Trust (Grant No. F114/BF) and Patrik Karpaty acknowledges financial support from the Jan Wallander and Tom Hedelius Foundation.

The previous studies on Sweden use the same data as in the present paper.

See for example the review in[START_REF] Görg | Much ado about nothing? Do domestic firms really benefit from foreign direct investment?[END_REF],[START_REF] Girma | Does exporting lead to better performance? A microeconometric analysis of matched firms[END_REF] or[START_REF] Greenaway | Firm heterogeneity, exports and FDI[END_REF].

See for example[START_REF] Greenaway | Firm heterogeneity, exports and FDI[END_REF] and[START_REF] Wagner | Productivity and Size of the Export Market: Evidence for West and East German Plants[END_REF] for a review of this literature.

See Swedish Government Official Report (2008: 90) for a further discussion of this point.

The two-step methodology involves estimating first the probit of the export decision (i.e. selection equation), computing the inverse of the Mills ratio and inserting it as regressor in the export share regression.

[START_REF] Hansson | Swedish business sector in a globalized world -Impact of internationalization on productivity and employment[END_REF] report summary statistics that show how the share of exporters in Swedish manufacturing is distributed over different size classes.

We use votes rather than shares, since Swedish firms may, and do, issue shares with widely different voting power. Obviously the issue of foreign control is not so simple that it can be completely described by a binary variable switching from 0 to 1 at a certain level of voting power, here 50 per cent, since -depending on the ownership structurea share of the votes much lower than that may be sufficient to give a high degree of control.

The term horizontal spillovers refers to within industry spillovers. Spillovers may also follow input-output flows, upstreamfrom a foreign-owned customer to a domestic seller -and downstream (backward and forward linkages). See, e.g.,[START_REF] Griliches | The Search for R&D Spillovers[END_REF][START_REF] Griliches | R&D and Productivity: Econometric Results and Measurement Issues[END_REF] on the issue of input-output flows and knowledge spillovers. These between industry spillovers may be tracked by using input-output tables. This is, however, beyond the scope of this paper.

In relation to the discussion of the type of FDI, the evidence in Table7suggests that these new measures of foreign presence give more weight to single-plant rather than multi-plant firms. Table7suggests that multi-plant firms are much larger than single-plant firms, whereas the TFP gap, while still positive, is proportionately smaller on average.

As an alternative measure of absorptive capacity we used the skill intensity. The interaction of skill intensity, measured by the proportion of the labour force with post secondary education, gives similar results.


Davide Orsi

Luigi Cristofolini
email: luigi.cristofolini@fis.unipr.it

Marco P Fontana

Emanuele Pontecorvo

Chiara Caronna

Andrei Fluerasu

Federico Zontone

Anders Madsen

Microscopic dynamics in nanocomposite photosensitive films studied by X-ray photon correlation spectroscopy

Keywords: photoinduced effects, nanocomposites, polymers user supplied): XPCS, slow dynamics

Introduction

In recent years there has been an increasing scientific and technological interest in nanocomposite systems which combines hard and soft materials with a resulting improvement in functionalities, physical properties, and overall stability [1].

Embedding nanoparticles in a soft matrix is a common solution through which new functionalities can be achieved. Depending on concentration, dimension and composition of the nanoparticles, they can either intensively modify the dynamical properties of the system in which they are included, or just follow passively the dynamics of the surrounding material. Recently it was shown that adding Ag nanoparticles at low concentration -up to a few % in weight -in azopolymer films improves the stability of the system [2], with possible novel applications in optical recording for high-density data storage. In this case, a possible interpretation consists in a modification of the long-time dynamics of the sample induced by the presence of the nanoparticles.

On the other hand, stabilized nanoparticles at low volume fraction may be considered as passive tracers of the superdiffusive microscopic bulk dynamics observed in low-molecular-weight polymer melts [3] and in supercooled liquids near the glass transition [4].

In this work, we investigate the influence of the presence of gold nanoparticles -at concentrations below 0.1% in weight -over the internal microscopic dynamics of photosensitive polymeric Langmuir-Schaeffer films deposited on silicon. In particular, the system we investigated consists of a side-chain liquid crystalline polymer with an azobenzene moiety attached to the main chain via a flexible molecular spacer [5][6][7]. We employed X-ray Photon Correlation Spectroscopy (XPCS) as a tool to directly measure the microscopic relaxation times of the system in the exchanged momentum range provided by synchrotron light [START_REF] Gruebel | Soft-Matter Characterization[END_REF], corresponding to spatial scales of the order of 10-100 nm.

The long time dynamics of a similar sample was previously investigated in a XPCS experiment [START_REF] Orsi | [END_REF], observing a superdiffusive dynamics typical of colloidal gels, clays, and glasses [START_REF] Fluerasu | [END_REF][11][12]. The effects of photoperturbation with UV light were intensively studied, both in-equilibrium and out-ofequilibrium [13]. These studies showed a reduction of the relaxation times upon UV exposure, which is in qualitative agreement with a reduction of the viscosity of the polymer. However, the superdiffusive character of the dynamics did not change. With the present work we aim at extending our previous investigations by exploiting the larger contrast provided by the addition of the gold nanoparticles, with higher electron density, and hence a higher signal-to-noise ratio with lower incident radiation dose. It is reasonable to assume that the polymer dynamics will not be significantly affected by the addition of nanoparticles as they are stabilized to prevent aggregation, and are present at very low concentrations. Therefore, we expect to minimize problems related to radiation induced damage which was encountered in our previous experiments, especially when the sample was illuminated by UV light, while still being able to track the dynamics of the unperturbed system.

Sample

The photosensitive polymer employed in this study is poly[[4-pentiloxy-3'-methyl-4'-(6acryloxyexyloxy)] azobenzene] (denoted PA4 in the following) which has a glass phase with T g = 20°C and a nematic phase with clearing point T NI =92°C [14]. Multilayers of PA4 were prepared by the Langmuir Schaeffer (LS) technique. Gold nanoparticles (GNP) of 5 nm nominal diameter that were stabilized by a layer of lipoic acid to avoid cluster formation following the work of Chen and Kimura [15] were embedded in the PA4 films. Single layers were prepared from a solution of PA4 and GNP in chloroform. The solution was spread on a pure water surface in a Langmuir trough and a film at surface pressure Π=10mN/m was formed by barrier compression. Subsequently, several layers of the obtained film were deposited on Si substrates using the LS technique. The multilayer samples were checked using Scanning Electron Microscopy (SEM) to verify for their uniformity and the absence of GNP clusters. A typical SEM image of a sample with 1% weight percentage of GNP is displayed in the left panel of figure 1. Cluster of nanoparticles were not present and the particle diameter estimated from this image is in agreement with the nominal value of 5 nm, which however is very close to the resolution limit of the SEM instrument (a few nm) in this configuration. Since an accurate estimate of the GNP size is crucial for the subsequent analysis of the XPCS data, we resorted to small angle X-ray scattering (SAXS) measurements to have a more quantitative information. The right panel of figure 1 shows the SAXS pattern from the very same system as measured by SEM. We employed a Bruker D8 Discover diffractometer in a total reflection geometry, which is explained in more details in the following section, operating in the range of 1 -5 nm -1 in momentum transfer. For comparison we also measured the SAXS signal of a pure polymeric film (i.e. without GNPs), which is found to be much weaker. The fact that most of the SAXS signal arises from the GNPs is expected, despite their very low concentration, because of the large difference between gold and polymeric electron densities. The scattering contribution coming from the azopolymer was then subtracted and the remaining scattered intensity profile was fitted with the form factor of polydisperse hard spheres [16] to yield a mean radius R=2. 26(3) nm of the particles along with the width σ=0.48(2) nm of the radii distribution and a normalized χ 2 =1.2. of gold nanoparticles in PA4 is 1%. right SAXS measurement on the same system: the intensity I(q) is fitted with the form factor for polydisperse hard spheres yielding a best fit with mean radius R=2.26nm and polydispersity σ=0.48nm.

Since PA4 contains the azobenzene moiety, it may experience several internal modifications as a consequence of photoperturbation. In particular its trans isomer presents an absorption peak in the UV region of the spectra. When trans-PA4 is exposed to light of wavelength around 390 nm it switches to cis-PA4, with a subsequent reduction of the dynamic shear modulus [17] and a decrease of its microscopic relaxation times [START_REF] Orsi | [END_REF]. Measurements in bulk are made difficult by the short penetration depth of UV light in PA4 which prevent uniform photoperturbation of the sample, showing the necessity of performing this type of measurements on a multilayer.

The samples for XPCS consisted of 75 molecular layer thick Langmuir-Schaeffer multilayers on a silicon substrate. This thickness was chosen to minimize surface effects, such as the presence of a dead layer which affects the first nanometres of thickness, and at the same time to ensure homogeneous exposure to the UV radiation. Samples were characterized by null-ellipsometry, SEM and AFM microscopy, evidencing a typical total thickness of 150nm and a mean roughness of about 1 nm, values consistent with previous measurements on similar samples [18,19].

XPCS measurements were performed at 40 °C and 52 °C with 0.10% weight concentration of GNP and at 60 °C and 72 °C with 0.05% GNP. Even if we used two different concentrations, both of them are sufficiently low to not alter the mechanical properties of the GNP/polymer composite which are the same as in the pure polymer at these low concentrations [20][21][22], thus leaving only temperature and illumination as parameters governing mechanical properties. On the contrary, for higher GNP concentrations, in the regime of a few percent and above, mechanical properties of GNP/polymer composites are known to be altered in a progressive way as the concentration is increased [20][21][22]. This is known in general for many GNP/polymer combinations, furthermore we characterized the interfacial shear modulus G* for our particular case of GNP/PA4 for different concentrations up to 5%, finding that G* is not affected by the presence of GNP for concentrations below 0.5% in weight [23].

Experimental setup

Experiments were conducted at the ID10A beamline of the European Synchrotron Radiation Facility, employing partially coherent X-rays at 8.06 keV with a relative bandwidth ∆λ/λ ≈ 10 -4 . Higher energy X-rays were suppressed by a Si mirror placed after the monochromator, while slits blades with highly polished cylindrical edges defined a transversely coherent beam of size 10 x 10 µm 2 . Diffraction fringes coming from the beam-defining slits were blocked by a system of guard slits placed between the sample and the beam defining aperture. The sample was placed in a vacuum chamber equipped with thermal control and a high power UV LED array (395nm) for sample illumination.

The experimental geometry (figure 2) was chosen to improve the photoperturbation efficiency while minimize beam damage effects on the sample. Similar strategies have already been adopted in previous experiments [START_REF] Orsi | [END_REF]24]. The sample, mounted vertically in the vacuum chamber, was aligned forming an angle of 0.15° with respect to the incident beam, well below the critical angle for total external reflection from the silicon-air interface at 8.06 keV (α c =0.22°). This condition minimizes radiation damage to the sample caused by photoelectrons coming from the Si substrate, allowing at the same time measurements of small angle scattering around the strong specular reflection, which is blocked by a beam stop. The diffuse scattering from the sample was collected by a 2D detector (MAXIPIX) --placed 2.2 m downstream from the sample --consisting of an array of 256x256 pixels, each of size 55 x 55 µm 2 . The minimum exposure time is 1 msec, however we typically used an integration time of 100 msec in order to increase the detector signal. To follow slow dynamics, on the scale of several hours while minimizing radiation damage effects, a waiting time of 1-4 seconds was introduced between successive frames. During these intervals, a fast shutter placed upstream of the sample was protecting it against beam damage effects. All the measurements reported here are performed in equilibrium conditions, i.e. allowing a suitable waiting time after the application of photoperturbation or of any temperature variation. The onset of a stationary equilibrium regime was checked by a careful analysis of two times correlation function, as described in [START_REF] Orsi | [END_REF]25].

For the data analysis we proceeded as follows: first, individual pixels of the detector were grouped in several "coarse-grained" iso-q rings (typically 20). Subsequently, we considered the temporal evolution of the intensity detected by each pixel i, computing both mean values I i and standard deviation δ i . Finally, we excluded from every ring those pixels with I i or δ i significantly different from the average values <I i > and <δ i > calculated on the total number of pixels in the considered ring. On the remaining pixels the intensity auto-correlation functions g (2) (q, t) are then calculated as I(q,t 0 ) is the intensity measured at time t 0 and wave vector q; the average <...> is performed over all the pixels in the q-bin and over all times t 0 , since we are interested in equilibrium dynamics.

2 0 0 2 q, I * q, t q, I(q) t) + t ( ) t I( = ) ( g ) ( ( 1

Results

Thermal equilibrium

The diffuse scattering around the specular reflection was measured with the sample at several temperatures, in dark and under UV illumination. As discussed in section 2, most of the scattered signal originates from the gold nanoparticles, because of their higher electron density.

The correlation functions, exemplified in the left panel of figure 3, were fitted by a Kohlrausch-Williams-Watts (KWW) modified exponential form:

( ) γ τ t ) ( β + Α = ) ( g / 2 - 2 e t q, * (2)
where A is the baseline, typically equal to unity, and is the contrast of the correlation function which in this geometry is around 0.3.

Τhe characteristic relaxation time τ usually follows a power law as a function of q with exponent n,

n q τ - ∝
while the parameter γ is the KWW exponent. In the case of Brownian diffusion, i.e. for low concentration colloidal particles moving in a simple viscous fluid, n=2 and γ=1 are observed. In the right panel of figure 3 we report the relaxation time τ measured as a function of momentum transfer q at several temperatures, with concentrations of gold nanoparticles in PA4 lower than 0.1 % in weight. An increase in temperature reduces the relaxation times while the slope of the curves remains unchanged. Figure 4 shows the results of fitting the correlation function with the KWW exponential form. While the dynamics of the nanoparticles becomes faster as the temperature increases, the q-dependence of the relaxation times remains q -1 (Fig. 4 hand, the KWW exponent γ is q-independent and close to 1.5 (right panel). These results are very similar to what we recently measured in a XPCS experiment on multilayers of pure PA4 [START_REF] Orsi | [END_REF], suggesting that the dynamics of nanoparticles can be used to investigate the internal dynamics of the polymer, in analogy with previous measurements on glassy polymer melts [3]. This is particularly true given that the GNP concentration is low enough to leave the mechanical properties of the polymer unaffected [20][21][22].

, left panel). On the other

A similar superdiffusive behaviour of nanoparticles in a two-dimensional polymeric environment was found in Ref. [26] where gold particles moving in a polystyrene film were investigated by XPCS. In figure 5, the relaxation times measured at q=0.09 nm -1 as a function of temperature are shown in an Arrhenius plot and compared to analogous data for pure PA4. The motion of gold nanoparticles in the azopolymer is sensibly faster, with a reduction of relaxation times of about one order of magnitude respect to that measured for the pure azopolymer.

Data were compared with the well-known Vogel-Fulcher-Tammann law:

        - ∞ 0 exp T T T τ = τ A (3)
The curve for the nanocomposite system (continuous line) is characterized by a less steep temperature dependence represented by a lower activation temperature (T A =800 °C) with respect to the curve previously measured in bulk and in molecular layers for pure PA4 (dashed line, T 0 =-33°C and T A =997°C).

Photoperturbation with UV light

Subsequently, we investigated the effect on the dynamics of the nanoparticles caused by photoperturbation with UV light at λ=395 nm. The power density of UV light on the sample was 1 mW/cm 2 while the temperature was set to 40°C with 0.1°C accuracy. In order to allow the system to reach equilibrium conditions with UV exposure, the correlation function measurements were started a few minutes after switching the light on. An analysis of two-time correlations for representative values of q confirms that the system has reached indeed a stationary state. In figure 6 we report the characteristic relaxation time τ as a function of the momentum transfer q measured both in dark and under UV illumination. The dynamics is accelerated by a factor of 30, in qualitative agreement with the fluidification effect of UV light on a PA4 layer observed by Interfacial Shear Rheology and XPCS [START_REF] Orsi | [END_REF]17].

The q-dependence of the relaxation times is linear even under UV light (open circles and continuous line in Fig. 6), in quantitative accord with previous XPCS results for pure PA4 [START_REF] Orsi | [END_REF]. This underlines our previous statement that the motion of the nanoparticles reflects the internal dynamics of the azopolymer, even when the system is suddenly illuminated by UV light. By fitting the KWW expression to the correlation functions we found that the parameters γ and n are not significantly affected by the photoperturbation. However, at constant temperature, the dynamics of the polymer/GNP system is sensibly faster than that of the pure polymer, and this holds both in dark and under UV illumination. This indicates that, while photoperturbation induces the well known fluidification with the resulting reduction of relaxation times, on the other hand this process does not alter the superdiffusive behavior-which is speculated to originate from dynamical heterogeneities.

Conclusions

We have characterized microscopic dynamics in gold-nanoparticle and photosensitive azopolymer mixtures by X-ray Photon Correlation Spectroscopy measurements. Correlation functions were measured as a function of exchanged momentum and illumination conditions (dark and UV light) and fitted with the Kohlrausch-Williams-Watts (KWW) exponential form. We found non-Brownian superdiffusive behavior with relaxation times τ ≈ q -1 , in analogy to what was observed in the pure azopolymer [START_REF] Orsi | [END_REF]. Such behavior has been related to intermittent rearrangements [27] or random dipolar interactions within an elastic medium [28]. Photoperturbation with UV light makes the dynamics faster, in agreement with a reduction of the polymer viscosity that has previously been measured by shear rheology [17]. Interestingly, the parameters of the KWW law of the correlation functions are not significantly affected by the photoperturbation, in agreement with the results on polystyrene/GNP mixtures reported in the literature [3], and suggesting that GNPs can be used to trace the temperature-and in our case also illumination-dependence of dynamics in polymeric Deleted: . However, at constant temperature, the dynamics of the polymer/GNP system is sensibly faster than that of the pure polymer, and this holds both in dark and under UV illumination. This is

Figure 1 :

 1 Figure 1: left SEM image of gold nanoparticles (dark dots) embedded in PA: the sample consists of 36 Langmuir-Schaeffer layers deposited on Si substrate. The particle diameter is smaller than 10 nm. The nominal weight percentage

Figure 2 :

 2 Figure 2: experimental setup. The incoming and reflected x-ray beams are indicated by dotted lines. Two guard slits (GS) block the interference fringes from the beam defining aperture (not shown). The sample (S) is aligned at an angle of α = 0.15 ° with respect to the incident beam. The beam stop (BS) blocks the specular reflection while the detector (D) collects diffusely scattered radiation.

)

Figure 3 ,

 3 Figure 3, left: normalized correlation functions measured in GNP/PA4 in dark, at T=72°C. Data are shifted for clarity.Right: relaxation times τ as a function of the exchanged momentum q, at several temperatures in absence of illumination. Data are fitted with a power law dependence

Figure 4 :

 4 Figure 4: left Temperature evolution of the exponent n at different illumination conditions; right γ averaged over the investigated q range; the dashed line is guide to the eye.

Figure 5 :

 5 Figure 5: Arrhenius plot of the relaxation times of the nanocomposite system in absence of illumination, compared to the relaxation times of pure PA4. Data are measured at q=0.09nm -1 and lines represent the VFT law.

Figure 6 :

 6 Figure 6: relaxation times of the nanocomposite system in dark (black squares) and under UV illumination (open circles, at T=40°C. Data are compared with inverse ( q -1 )dependencies (solid lines). The acceleration of the dynamics of the gold nanoparticles is a consequence of the photoinduced fluidification of PA4.

  the advantage of increased scattered intensity, even if the absolute values of the relaxation times are affected by the presence of the GNPs.

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Acknowledgements

We acknowledge dr Francesca Pincella and dr Yuri Gerelli (University of Parma) for help with the SAXS measurements in total reflection geometry.