3.2.1 Import Modes

Firms may use two different import modes. Direct imports take place as imports pass customs clearance and enter into free circulation directly upon their arrival in an EU member state. For direct imports, the value of the import transaction is known. Customs warehousing refers to cases where goods are stored in premises authorized by the customs authorities (so-called customs warehouses) upon their arrival in the destination country (EU member state). The products are under customs supervision and will not be subject to import duties or other related charges as long as they remain in the customs warehouse. The import transaction is not registered (and decisions about preference utilizations are not made) until the item is extracted from the customs warehouse.

This means that the customs data related to customs warehousing refer to the warehouse extraction value rather than the underlying import transaction value. The value and size of the underlying import shipment are not known, only the size of the ‘withdrawal transaction’.Footnote ⁶ Customs warehousing is typically used by companies trading in seasonal products or high-value products that are imported infrequently in larger quantities and subsequently sold in smaller lots. There are usually no time limits for storing products in customs warehouses.

Customs warehousing might be used regardless of whether a product is eligible for tariff preferences or not. The customs warehouses for imports to Sweden can be located within the national borders or in any other EU member state.

3.2.2 Import Transactions versus Consignments

In this article, an import transaction is defined as the import of a specific product (at the 10-digit Taric level) from a specific exporter at a given day in time. Firms may, however, import several different products from the same exporters at the same moment in time (here referred to as a ‘consignment’, which is identified by a unique customs ID. A consignment may, accordingly, include various separate import transactions (products).

3.2.3 Firm Size

To categorize firm size, we apply the EU's definition – micro, small, medium, and large – which is based on the number of employees and the turnover or balance sheet total. As firms develop over time, due to changes in number of employees and turnover, they may switch category once or several times over the period of observation. For a detailed review of firm size definitions, see European Commission (2003).Footnote ⁷

3.2.4 Duty Savings Rate versus Preference Utilization Rate

Both the duty savings rate (DSR) and the preference utilization rate (PUR) aim to define the degree to which firms utilize tariff preferences. The PUR is defined as the value of preferential imports (i.e. the import value where tariff preferences are utilized) as a share of the preference eligible import value. However, the DSR is defined as the value of duty savings from utilizing tariff preferences on preferential imports as a share of the potential duty savings (i.e. the possible duty savings on all preference eligible imports).Footnote ⁸ We use the DSR as the main measure of firms’ utilization of tariff preferences in Section 4. In the econometric analysis in Section 5, where the focus is on individual transactions, the key dependent variables are instead the probability that preferences are utilized.Footnote ⁹

4.1.1 Import Values and the Duty Savings Rate

Figure 1 shows the value of Swedish imports from South Korea and the duty savings from three years prior to the entry into force of the free trade agreement (Year –3) until seven years into the agreement (Year 7). As seen in Figure 1, total values seemed to take off about four years after the provisional implementation of the free trade agreement in 2011 (Year 1), suggesting that it may have taken three years or more for importers to start responding strongly to the FTA. For direct imports, there was a relatively sharp increase in imports five years into the free trade agreement, which is likely to be explained by legal changes leading to a shift from customs warehousing to direct imports.Footnote ¹⁰

Figure 1. Import values and duty savings rates. Note: Bars are marked with the duty savings rate

Sources: Swedish Customs Agency, European Commission, and own calculations.

From Figure 1, it can also be seen that the utilization of preferences does not necessarily start from a very low level, since the duty savings rate for total imports was above 60% already from the first year (Year 1). In addition, the share of imports utilizing the tariff preferences increased over time. The DSR for total imports exceeded 80% the third year and levelled out to a rate of slightly above 90% in the sixth and seventh years of the FTA (2017–18). The development for direct imports was similar. This pattern suggests a learning curve where it takes about three to five years for preference utilization to reach a level where it stabilizes.Footnote ¹¹

4.1.2 Number of Importing Firms

A first thing to examine is what happened with the number of importing firms when the FTA came into provisional use in 2011. As seen in Figure 2, the number of firms engaged in total imports from South Korea was about 620 per year during the three years before the FTA entered into force, and about 750 firms per year after seven years. This corresponds to a 20% increase in the number of importing firms. At the same time, the value of imports more than doubled during this period, suggesting that the average value of imports per firm also increased after the establishment of the FTA. A similar pattern can be seen if we look only at firms engaged in direct imports. Comparing the number of direct importers one year before the agreement entered into force (Year –1) with the corresponding number eight years later (Year 7), there was an increase of about 50%.Footnote ¹² The value of direct imports more than doubled over the same period.

Figure 2. Number of firms by mode of import in Swedish imports from South Korea over time

Sources: Swedish Customs Agency, European Commission, and own calculations.

A second notable observation is that the number of firms utilizing tariff preferences for all their imports from South Korea increased over time (grey area of bars in Figure 2). At the same time, the number of non-users decreased (blue area). There were also an increasing number of firms that sometimes utilized, and sometimes did not utilize the tariff preferences (orange area). Combining this observation with the information from Figure 1 on import values reveals that the relatively high number of importers that did not utilize tariff preferences represented only a small share of total imports.

4.1.3 Firms and Trade Flow Survival

There has been a high turnover of firms involved in direct imports from South Korea. Examining the period before the free trade agreement entered into force (Year –3 to Year –1), about 240 firms started importing each year while about 170 firms stopped importing (Figure 3). Three to four years into the free trade agreement, the number of both entries and exits increased notably. The number of entrants rose from about 200 to 400, and the number of exits grew from about 150 to 270 between Year 2 and Year 4.

Figure 3. Number of newcomers and leavers in direct imports

Sources: Swedish Customs Agency, European Commission, and own calculations.

A concept related to the entry and exit of firms is trade flow survival. Before the FTA entered into force, the one-year survival rate of new trade flows was about 60%. During the first years of the free trade agreement, the one-year survival rate of trade flows fell to 56% and reached 43% seven years into the free trade agreement.

These numbers are broadly in line with the findings of Söderlund and Tingvall (Reference Söderlund and Tingvall2013), who showed that about 50% of all new firm–country export flows survived only one year, and that only 15% of the original new trade flows were still active after six years. This micro-level turbulence is often explained by search/matching models where buyers are scanning the market for matching suppliers. That is, firms engage in trade with various suppliers trying to find a trading partner with whom a long-term relationship can be established. A partial explanation for the decrease in trade survival rates over time may therefore be that the establishment of the FTA enticed smaller and less experienced firms to enter into trade searching (and often failing to find) for appropriate suppliers.

As the FTA gradually matures, it is relevant to ask whether the duty savings rates of newcomers change over time. It could be hypothesized that firms learn to utilize tariff preferences as the FTA becomes better known among market participants, suggesting that the DSR among newcomers should increase over time. However, from Figure 4 it is not apparent that firms starting to import at a later date necessarily record higher DSRs than early entrants. This could indicate that own experiential learning may matter more than the experiences of other firms and publicly available information about the FTA. It is also possible that many of the newcomers only planned to make one or a few ad hoc import transactions and did not intend to invest in learning to utilize the tariff preferences due to a limited time perspective.

Figure 4. Duty savings rates by firms importing to Sweden from South Korea during their first year as an importer (over time)

Sources: Swedish Customs Agency, European Commission, and own calculations.

4.1.4 Continuous Importers over Time

In order to analyse the preference utilization for firms that appear continuously in the data set, we have identified so called ‘continuous importers’. Continuous importers are defined as firms that have made at least one import transaction per year during the entire period of observation (including the years before the free trade agreement entered into force). These continuous importers are interesting to study for at least two reasons. First, despite their small number, they represent a relatively large share of direct imports. Secondly, following a homogenous group of firms over time allows us to avoid compositional changes caused by sporadic importers. Learning and behavioural changes in preference utilization are easier to detect in this fixed sub-sample.

The share of continuous importers in the total value of imports from South Korea decreased from about 40% in Year –3 to about 30% in Year 7. Their share in the number of importers fell from about 20% to 10% over the same period. Hence, the continuous importers are relatively few but account for a relatively large share of total import value. Their annual import value has remained stable over time, which means that the overall increase in imports can mainly be attributed to newcomers and irregular importers.

Figure 5 displays the duty saving rates for continuous importers and all importers over the period under study. Two observations seem to distinguish the continuous importers from other firms. First, their DSR had already reached 75% during the first year of the FTA, while the average for all importers was only slightly above 50%. Second, it stabilized at a level well above 90% after only three years, which was significantly above the average DSR for all firms. This pattern applies for continuous importers of all size categories.

Figure 5. Duty savings rates for all importers and continuous importers

Sources: Swedish Customs Agency, European Commission, and own calculations.

These observations suggests that the continuous importers quickly learned to become efficient users of tariff preferences and made almost full use of the tariff preferences after only three to five years into the agreement. Hence, the lower DSR at the aggregate level is to some extent explained by the entry and exit of less experienced firms. This observation also suggests that there is a learning-over-time and/or a learning-by-doing process involved in preference utilization.

4.2.1 Number of Direct Import Transactions and Transaction Values over Time

Figure 6 (left panel) shows that the number of annual import transactions, where positive MFN tariffs were paid (MFN+) or where tariff preferences were utilized (FTA), increased from about 8,200 just before the entry into force of the free trade agreement to over 10,000 in the third year of the FTA, and further to about 12,200 import transactions towards the end of the period under study. During the first years of the FTA, the number of direct import transactions not utilizing the tariff preferences was more than twice as large as the number of import transactions where tariff preferences were utilized. The number of import transactions utilizing the tariff preferences increased during the first years of the FTA to level out after about four years. This is consistent with the findings from Figure 1, where it was noted that it took about three to five years for the DSR to stabilize at a rate of above 90%.

Figure 6. Number of direct import transactions and transaction values by tariff mode in Swedish imports from South Korea over time

Note: Figures are based on direct imports.

Source: Swedish Customs Agency, European Commission, and own calculations.

A second observation from Figure 6 (right panel) is that the number of import transactions per firm undertaken by firms utilizing the tariff preferences was slightly larger than the number of transactions carried out by firms not utilizing the tariff preferences. It can also be noted that the average number of import transactions per firm seemed to decline four years into the free trade agreement. One possible explanation behind the decline in the number of import transactions per firm may be that the new importers that entered into trade with South Korea carried out fewer transactions than experienced firms.

The firms utilizing tariff preferences have also adjusted by pooling imports to fewer but larger transactions. The third panel of Figure 6 shows that the average transaction values were about eight times higher for import transactions utilizing the tariff preferences than for transactions not utilizing these preferences. Moreover, the average value of the transactions not utilizing tariff preferences has diminished over time. This indicates that the threshold value where firms preferred to utilize tariff preferences was falling, which is in line with the hypothesis that learning effects will make preference utilization trickle down to lower value transactions. Part of this learning is likely to take the form of investment in human capital, software, and routines to meet the requirements for preference utilization, which will reduce the marginal cost for using preferences in subsequent transactions. There is also an increasing gap in the size of transactions utilizing and not utilizing tariff preferences, supporting the assertion that transactions not utilizing tariff preferences were, on average, low value transactions.

4.2.2 Import Transaction Frequency and Duty Savings Rates over Time

The analysis of import transaction frequency aims to differentiate between firms making a few import transactions and firms carrying out a large number of transactions during the period under study. This distinction is useful when examining the learning effects of repeated transactions. For this purpose, firms are categorized into four groups according to the total number of direct import transactions during the 7-year period: Low (1–5 transactions); Intermediate (6–25 transactions); High (26–100 transactions); and Very High (+100 transactions). This grouping gives us about 220 direct importers in each category. There is no systematic relationship between transaction frequency and average transaction size. The average import transaction value of firms in the categories Low and High was around EUR 6,000, rising to EUR 10,000 for the Very high category, and EUR 12,000 for the Intermediate group, but with very large variation within the different categories.Footnote ¹³

Figure 7 examines the relation between the DSR, transaction frequency, and firm size. The left panel of the figure shows that the DSR tended to increase over time for all transaction frequency categories, although the rates for firms in the Low (1–5 transactions) and Intermediate (6–25 transactions) categories fluctuated notably between years – this is not surprising considering the relatively high weights of individual transactions in these categories. In addition, there was a pattern where firms making many transactions tended to have a higher DSR than firms making fewer transactions. The exception was a surprisingly large DSR for firms in the Intermediate category in 2016 and 2017. Hence, Figure 7 supports the hypothesis that there is learning over time, as well as the idea that learning is linked to the number of repeated import transactions. These two features will be further scrutinized in the econometric analysis below.

Figure 7. Duty savings rates by transaction frequency over time and by firm size

Notes: The notation low to high denotes the number of transactions undertaken in each category. Micro to large denotes firm size

Sources: Swedish Customs Agency, European Commission, UC, and own calculations.

The right-hand panel of Figure 7 shows how preference utilization varied across firm size and the four transaction frequency categories. The data shown are the average DSRs for the entire seven-year period. It is apparent that the level of duty savings was more closely related to the number of repeated import transactions than to the size of the firm. This result is in line with Kasteng et al. (Reference Kasteng, Kokko and Tingvall2022), who showed that there are only minor differences in the utilization of preferences across micro, small, medium, and large firms.

5.1.1 Firm Characteristics

Firm Size. It is commonly assumed that large firms are better equipped than small firms to handle the costs associated with the utilization of tariff preferences (Albert and Nilsson, Reference Albert and Nilsson2016). One reason is that the fixed costs associated with preference utilization are less of a burden for large firms that can distribute them over a larger volume of sales. However, in line with Kasteng et al. (Reference Kasteng, Kokko and Tingvall2022), the results in Table 1 suggest that firm size seemed to be unrelated to preference utilization (once firms decided to import from South Korea). Figure 8 examines the relevance of firm size by comparing preference utilization across different firm size categories using micro firms as our reference group. The results indicate that there was no significant difference in preference utilization across firm size classes, and that this holds true for both direct imports and customs warehousing.Footnote ¹⁷

Figure 8. Firm size and preference utilization

Note: Based on full model (Table 1, Models 3 and 4). If the estimated 95% confidence band for a given size class crosses the (red) zero-line, preference utilization of that size category is not significantly different (higher or lower) from the reference group (micro firms).

Sources: Swedish Customs Agency, European Commission, UC, and own calculations.

One reason for the insignificance of firm size for preference utilization may be that the selection into trade is the decisive threshold.Footnote ¹⁸ That is, once firms have overcome the costs of engaging in international trade, the cost of utilizing tariff preferences may be relatively small. In that case, no significant differences in preference utilization across size classes should be expected. This relationship may be particularly true for distant markets where the barriers to trade, such as language, transportation time, time zone differences, and institutions are relatively large.

Profitability, Productivity, and Capital Intensity. Non-utilization of tariff preferences is associated with a lost opportunity to reduce costs. Hence, all things being equal, it could be expected that low profitability is associated with a low likelihood that preferences are utilized. It is also reasonable to assume that productive firms are efficient utilizers of tariff preferences. How capital intensity is related to preference utilization is to some extent an empirical question.

Table 1 suggests that the variable profits is mostly insignificant, suggesting that preference utilization has little to do with profits. For direct imports, the results suggest a positive and significant relation between preference utilization and productivity. Specifically, the results in Models 3 and 5 suggest that a 1% increase in productivity raises the odds that preferences will be used with approximately 0.6%.Footnote ¹⁹ We also note that preference utilization seems to increase with capital intensity when engaged in customs warehousing.

Intra-firm Trade. Nearly two-thirds of the import transactions in the data set are undertaken by firms that are part of a company group.Footnote ²⁰ This means that some import transactions stem from firms located in South Korea that are part of the same company group as the importing firm (i.e. intra-firm import transactions). The results in Table 1 suggest that the preference utilization in intra-firm trade differs between customs warehousing and direct import transactions. For customs warehousing, there is a strong positive impact of intra-firm trade on the likelihood that tariff preferences will be utilized. The estimated coefficient for the intra-firm variable in Models 4 and 6 shows values well above unity. The estimated odds ratio suggests that there is a 4.2–5 times higher probability that tariff preferences will be utilized when the import mode is customs warehousing and the import transactions take place between related parties. For direct imports (Models 3 and 5), the results are the opposite. It is significantly less likely that tariff preferences will be utilized when firms carry out direct imports from related firms (intra-firm trade) than from unrelated firms. Hence, for intra-firm transactions, the degree of preference utilization is highly dependent on the mode of import (direct imports or customs warehousing). A closer analysis of why intra-firm decisions differ between direct imports and customs warehousing operations is left for future research.

5.1.2 Import Transaction Characteristics

Using a sample consisting of all Swedish import transactions from South Korea for November 2016, Kasteng et al. (Reference Kasteng, Kokko and Tingvall2022) analysed the impact of the import transaction value, the preference margin, and the potential duty savings on preference utilization. Their data set was a subsample of the data used in this article. The results obtained here, which are summarized in Figure 9, are very similar to those of Kasteng et al. (Reference Kasteng, Kokko and Tingvall2022).

Figure 9. Potential duty savings, import transaction value and the preference margin

Note: Based on Model 3 (for direct import) and Model 4 (for customs warehousing, in Table 1).

Sources: Swedish Customs Agency, European Commission, UC, and own calculations.

Figure 9 shows how preference utilization varies across the full range of duty savings, transaction values, and preference margins. The major takeaways are that preference utilization increases as we move from small to large potential duty savings and from small to large import transactions, while the preference margin is of minor importance for preference utilization. This pattern holds for both direct imports and customs warehousing.

More specifically, Figure 9 shows that the predicted probability of utilizing tariff preferences in direct imports increases from approximately 8% to almost 90% when the potential duty savings go from the lowest to the highest observed value (holding other variables constant). For customs warehousing, the corresponding increase in the probability that tariff preferences are utilized is from approximately 35% to almost 90%. Hence, larger monetary values are positively related to the likelihood that tariff preferences will be utilized.

The observation that there is a significantly higher likelihood that preferences will be used in customs warehousing should also be noted. The average import transaction in customs warehousing is smaller than that in direct imports, and one factor contributing to the higher utilization rate could be that the preference application process is simpler for transactions valued below EUR 6,000. Instead of providing a formal certificate of origin, the South Korean exporter can submit an invoice declaration stating that the goods originate in South Korea. Another possible explanation, proposed by Kasteng et al. (Reference Kasteng, Kokko and Tingvall2022), is that many of the smallest firms importing through customs warehouses may use intermediaries in logistics and customs brokerage, which could reduce the information cost of preference utilization.

5.1.3 Import Diversification

Both the policy debate and the literature on preference utilization suggest that rules of origin are associated with a fixed cost (Keck and Lendle, Reference Keck and Lendle2012; Nilsson and Dotter, Reference Nilsson and Dotter2012; Albert and Nilsson, Reference Albert and Nilsson2016). This means that managing many products with different rules of origin, possibly sourced from several different exporters, may require a greater effort than handling one product from one exporter.

However, once a firm has learned to handle one type of rule of origin, it is plausible to assume that the administrative costs for handling subsequent transactions from the same exporter will be lower. That is, a learning process should take place. It is, however, unclear whether learning is more effective if imports are limited to a small set of products (and a small number of product-specific rules of origin) or many products with a large variety of product-specific rules of origin.

There can also be learning effects associated with having many business relations. Importing goods from several different exporters could allow the importer to gather valuable knowledge from its trade partners. For example, an importer with multiple trade partners is more likely to come into contact with a foreign exporter that will inform it about the possibility to import without tariffs or encourage it to apply for tariff preferences.

To explore these two types of learning, we have included data for the number of business relations with South Korean exporters (#exporters) and the number of product groups imported from South Korea (#product groups) by each firm during the period 2011–2018 into the estimations presented in Table 1. The number of product groups is defined by counting the number of different HS 4-digit codes, since most product-specific rules of origin are defined at that level. The average number of product groups per firm was 2.4 per six-month period, with a maximum of 121 and a standard deviation of 4.53.

The result for the number of product groups appears clear. Table 1 shows that there is no significant impact of #product groups on preference utilization. This suggests that the additional transaction cost faced by firms by importing a larger number of products is not very high. A possible reason is that much of the fixed costs are borne by the exporters, who prepare and supply the documentation that is used by the importer to prove the origin of the products. This result is also consistent with results from surveys on preference utilization (Decoster, Reference Decoster2021; Kasteng and Almufti, Reference Kasteng and Almufti2021) which indicate that the great majority of exporters do not consider rules of origin a major problem.

When it comes to the number of business relations, the results for the variable #exporters show that importing goods from a large set of exporters is positively related with preference utilization among direct importers (Table 1, Columns 3 and 5). The estimated odds ratio of 1.28 suggests that doubling the number of suppliers in the foreign market raises the chance that the tariff preferences will be utilized by 89%.Footnote ²¹ In other words, managing multiple supplier relationships seems to make importers better at utilizing tariff preferences. There is no significant impact of multiple suppliers in customs warehousing.

5.2.1 ‘Learning-over-Time’ versus ‘Learning-by-Doing’

Learning-over-time is related to the length of time during which the firm has been an active importer, while learning-by-doing depends on the accumulated number of import transactions undertaken by the firm. The descriptive analysis in Section 4 found evidence for both learning-over-time and learning-by-doing effects. Apart from the observations that the DSR was generally higher for firms carrying out a larger number of transactions and that it increased over time, the existence of learning effects was supported by the fact that continuous importers reached higher levels of preference utilization than other importers.

Table 2 introduces three new variables to explore the learning process. The variable #periods proxies the length of time (measured as the cumulated number of six-month periods) that the firm has been actively importing from South Korea. The variables #transactions and #ID are firm level variables measuring the cumulated number of import transactions and import consignments (customs IDs) handled by a firm. To analyse potential interdependence between time and the number of import transactions or import consignments, we also add interaction terms between #periods and the cumulated number of import transactions/consignments to the estimation model. These interaction terms allow us to analyse whether the impact of one additional import transaction will successively increase or decrease with time. All other variables from Table 1 are included in the estimations (and all results remain qualitatively unchanged) but are not shown to save space.

Table 2. Learning-by-doing

Logit models, odds ratios.

Notes: *^, **^, and *** indicate significance at the 10, 5, and 1% level respectively. Robust standard errors clustered at the firm level within parenthesis (.). For control variables included, see Table 1 columns 5–6.

Fixed effects at the HS-2 level and each half year included in all regressions.

Sources: Swedish Customs Agency, European Commission, UC, and own calculations.

The top half of Table 2 shows that there is no significant relation between the length of time a firm was engaged in customs warehousing and its preference utilization. For direct imports, shown in the bottom half of the table, there is even a negative relationship between #periods and preference utilization in two out of four estimations. That is, the longer a firm has been active in direct imports, the less likely it is that tariff preferences will be utilized.

The estimated relationship between time and preference utilization is depicted in the first panel in Figures 10a and 10b. Figure 10a shows that preference utilization in customs warehousing is unaffected by the number of periods a firm has been an importer. Figure 10b indicates that preference utilization in direct imports is lower for firms that have been importing for a longer time. Hence, the econometric results give no support for the learning-over-time hypothesis.

Figure 10. (a) Learning and preference utilization. Customs warehousing. (b) Learning and preference utilization. Direct imports.

Note: Based on Table 2.

Sources: Swedish Customs Agency, European Commission, UC, and own calculations.

Turning to the learning-by-doing hypothesis, the results in Table 2 (Models 1 and 3) suggest that preference utilization increases with the number of import transactions and import consignments, both for direct imports and customs warehousing. The middle and right-hand panels of Figures 10a and 10b illustrate these findings. Two observations are particularly notable. First, the estimated levels of significance reveal that there is a closer relationship between learning-by-doing and preference utilization in direct imports than in customs warehousing. The middle panel of Figure 10b shows that the predicted probability that tariff preferences will be utilized in direct imports increases from about 5% to almost 70% as we move from firms undertaking a few too many import transactions (percentile 1 to 99). The corresponding change in preference utilization in customs warehousing is roughly from 5 to 60%.Footnote ²² Secondly, the significance is stronger when we use the number of import transactions as compared to the number of import consignments (customs IDs). This suggests that firms learn not only from the number of consignments handled, but that the number of transactions also adds to the learning process.Footnote ²³

A further detail to note (Models 2 and 4) is the interdependence between time and the number of import transactions [(#periods)·ln(#transactions)]. For customs warehousing withdrawal transactions, this relationship is insignificant, while there is a weak negative relation for direct import transactions. This negative relation suggests that the learning from the nth import transaction is higher if the total amount of import transactions is compressed over a short period of time. A possible explanation could be that corporate routines may change over time, that employee turnover may lead to losses of experience, and that people tend to forget administrative procedures if they are not repeated frequently enough.

It should be noted that our data do not reflect leaning from other FTAs. With more comprehensive data, it would be interesting to examine if there are spillover effects between FTAs. For example, are importers with experience from the EU–South Korea FTA more likely to utilize preferences when they import from Japan, which entered an Economic Partnership Agreement and FTA with the EU in 2019?