2

International Business Review 13 (2004) 383–400 www.elsevier.com/locate/ibusrev

Sources of export success in smalland medium-sized enterprises: the impact of public programs Roberto Alvarez E.
Department of Economics, University of Chile, Santiago, Chile

Abstract This paper analyzes differences in firm exporter performance for small- and medium-sized enterprises (SMEs). Traditionally, it is argued that these firms face several disadvantages for competing in international markets. Few studies, however, exploit the fact that successful exporters exist within this group. Using data for Chilean firms, we study various explanations for differences between sporadic and permanent exporters. Our results suggest that greater effort in international business, process innovation, and the utilization of export promotion programs contribute positively to export performance in SMEs. In addition, we find that some forms of intervention are better than others: trade shows and trade missions do not affect the probability of exporting permanently, but exporter committees show a positive and significant impact. # 2004 Elsevier Ltd. All rights reserved. Keywords: Export performance; Export promotion; Small- and medium-sized enterprises

1. Introduction International evidence suggests that firm size matters for exporter performance. Several reasons have been provided to explain why larger firms perform better in international markets. Advantages associated with scale economies and specialization, better access to financial resources in capital markets, and improved capabilities to take risks are among these reasons (Wagner, 2001). Also, evidence in


Present address: The Anderson School of Management, University of California, Entrepreneurs Hall, Suite C-525, 110 Westwood Plaza, Los Angeles, CA 90095-1481, USA. Tel.: +1-310-825-8207; fax: +1310-825-4011. E-mail address: [email protected] (R. Alvarez). 0969-5931/$ - see front matter # 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.ibusrev.2004.01.002

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Roberts and Tybout (1997) and Bernard and Jensen (1999) regarding the existence of sunk costs to entering international markets implies that small- and mediumsized enterprises (SMEs) face greater limitations than larger firms to be successful exporters. There are, however, firms within the group of SMEs that have been able to compete successfully in international markets. Yet, few empirical studies exploit this fact. This paper contributes to the discussion of firm exporter performance in four ways. First, we compare exporter performance among firms of similar size. Second, focusing only on exporters, we distinguish between sporadic and permanent exporters. Third, we employ a detailed survey of 295 sporadic and permanent exporters. This survey collects information about firm activities not traditionally included in other empirical studies. Fourth, we study evidence in Chile, a country that has experienced a huge increase in export diversification over the last several decades. The Chilean experience is useful for other developing countries trying to improve the international competitiveness of SMEs. There are two empirical facts that motivate this paper. First, the probability of exporting is lower for SMEs than it is for larger firms. This resembles evidence found in other national economies. In the Chilean manufacturing industry, for instance, only 14% of SMEs have exported goods over the period 1990–1996. However, more than 74% of large firms have exported goods over the same period. Second, a reduced number of firms are able to remain as exporters. Among all exporter firms, only about 20% have exported every year of the period. The percentage of successful exporters for SMEs, however, is even lower: only about a 7% can be classified as permanent exporters. Contrast this with large-sized firms, where successful exporters represent more than 40% of the firms in this group (Table 1). The main question we ask here is why some SMEs are more successful exporters than others firms of a similar size. In the next section, we explore various explanations through the use of special survey directed at sporadic and permanent exporter firms. In the third section, a Probit model is estimated to identify empirically the most important determinants of export performance. The fourth section concludes. Table 1 Exporter status by size for the Chilean manufacturing industry 1990–1996 Export status

Small N

Medium %

N

Large %

N

%

Non-exporter Sporadic exporter Permanent exporter

4284 650 47

86.0 13.1 0.9

780 659 185

48.0 40.6 11.4

132 220 164

25.6 42.6 31.8

Total Sporadic/total exporters

4981 –

100.0 93.3

1624 –

100.0 78.1

516 –

100.0 57.3

Source: Own calculation based on Nationwide Survey of Manufacturing Establishments (ENIA). Non-exporters are those firms that did not export during any year of the period 1990–1996, sporadic exporters are those that exported in some year of this period, and permanent exporters are those that exported in every year of this period.

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2. Possible explanations In this section, we explore possible explanations for differences in firm exporter performance. The approach aims to establish if there are significant differences in firm activities that would explain why some SMEs are more successful than others. First, we present the data source. Second, we test for the existence of statistical differences over four aspects: (i) technological innovation, (ii) international business management, (iii) manager’s perceptions about obstacles to exporter performance, and (iv) utilization of public instruments available to SMEs for enhancing productivity and technological capabilities, increasing exports, and improving access to capital markets. 2.1. Data source The information utilized in this paper was provided by a special survey of exporter SMEs carried out between June and August of 2001. The sample of SMEs was chosen from the Annual Nationwide Survey of Manufacturing Establishments (ENIA) undertaken by the Chilean National Institute of Statistics over the period 1990–1996. Out of all manufacturing plants, this survey concerned exporters classified as small-sized firms (10–50 workers) and medium-sized firms (50–200 workers). The sample selection was based on three criteria. First, non-exporter firms were not incorporated because this significantly raised the cost of the survey. Also, it would not contribute to the objective of studying why some firms become permanent exporters and why others fail to remain as exporters. Second, microenterprises (i.e. firms with less than 10 workers) were not included since they have a very low probability of exporting. Third, manufacturing firms were separated into two main sectors according to comparative advantages of the Chilean economy. The exporter sector includes firms from food and beverages (311 and 313),1 wood and furniture (331 and 332), pulp, paper and printing (341 and 342), and chemical products (351 and 352). The other sector includes firms from textiles and apparel (321–322), and metallic products (381), for which Chile does not possess a comparative advantage. Export possibilities for these goods still exist, however, particularly to other developing countries. The universe of firms is provided for by the Annual Nationwide Survey of Manufacturing Establishments (ENIA), which we stratified into six groups corresponding to the sectors defined above. For each group, the number of surveyed firms was chosen from the ENIA universe through a simple random sample with a margin of error of 5%. This guarantees adequate representation of SMEs.2 Under these considerations, the total sample was 295 firms, 138 of which corresponded to 1 The figures in parentheses correspond to three-digit sectors of the International Standard Industrial Classification (ISIC). 2 In statistical terms, 5% means that under the sampling assumptions the sample size was chosen so that deviations in observed values are no larger than 5% from the ‘‘assumed’’ true parameter, where the true parameter is the population proportion with an uninformative expected value of 0.5.

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sporadic exporters and 157 to permanent exporters. This survey collected information on firm characteristics and activities. Firm characteristics were taken for two years, 1996 and 1999.3 To identify the objective group, exporters were chosen using the information provided by ENIA for exports over the period 1990–1996.4 Thus, permanent exporters were defined as those firms that had exported every year in this period. Sporadic exporters were those that had exported for some year during this period. In order to update this information, a filter question was included at the beginning of the questionnaire. This filter question is important because a firm may be classified as permanent exporter in our database 1990–1996, though it may exit from international markets after 1996. Thus, the filter question concerned export performance after this year. If the firm exported in the three following years (i.e. 1996–1999), then it was considered a permanent exporter. Otherwise, the firm was considered a sporadic exporter. Thus, it becomes possible to obtain greater consistency in exporter status. This is defined over the longer period 1990–1999, even though the survey only provides information for 1996 and 1999. 2.2. Preliminary evidence In order to test for the existence of significant differences among types of exporter firms, we estimate the following model: Inti ¼ a þ bExpi þ dExpi  Seci þ ei

ð1Þ

where Int measures the intensity of some action carried out by the firm. This variable corresponds to the answer given by the firm’s owner or manager. The intensity is measured on a scale as follows5: 0: null intensity 1: low intensity 2: slightly low intensity 3: slightly high intensity 4: high intensity. Exp is a categorical variable that defines the exporting status of the firm (1 if the firm is a permanent exporter, 0 otherwise). The interaction between this variable and a categorical variable for sector (Sec ¼ 1 if the firm belongs to an exporting 3

The non-response rate was higher (43%) in sporadic exporters than permanent exporters (26%). This is associated with the fact that sporadic exporters were more likely to exit. Both non-response rates are very similar after correcting for exit. 4 This period is chosen exclusively for data availability. More recent data were not accessible at the time of the survey. Nevertheless, this is not a problem since exports status was checked again at the beginning of the interview. 5 This measurement of activity intensity closely follows the Oslo Manual, a commonly used source in surveys regarding technological innovation by firms. Even this type of measurement is subjective, arising potential methodological problems, Section 3 shows that our results are not sensible to corrections for this problem.

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sector, 0 otherwise) allows us to analyze if differences between both groups of firms depend on sector. Given that the dependent variable is discrete and ordered, the equation is estimated using an ordered Probit model. A categorical variable by sector to the threedigit ISIC is also added to capture potential differences in the level of intensity undertaken by the firms across sectors. 2.2.1. Technological innovation Technological innovation may affect the export status of a firm by increasing productivity (and reducing costs) and/or by developing new goods for international markets. This may be analyzed in the context of firms that compete in differentiated product markets. Firms may sell low-quality goods in domestic markets, but they must upgrade to technologies that produce high-quality goods if they wish to sell abroad then. We test for differences in three types of innovative activities: product innovation, process innovation, and organizational innovation. The results are shown in Table 2, and suggest that there are differences between both groups of exporters. Though permanent exporters engage product innovation in greater intensity than do sporadic exporters, this difference is not significant. However, significant differences exist for process and organizational innovation. The results show that permanent exporters innovate more than sporadic exporters in outsourcing and the computer-based modernization of productive processes. With respect to the Table 2 Technological innovation Type of innovation

Differencea

Difference by sectorb

Product innovation Technological improvements New products Changes in design Changes in packaging

0.11 0.51 0.10 0.43

0.15 0.16 0.10 0.11

Process innovation Purchases of specialized machinery Introduction of quality control Outsourcing Introduction of information technologies

0.17 0.38 0.93
0.77


0.09 0.05 0.22 0.28

Innovation in management Introduction of strategic planning Introduction of re-engineering Introduction of total quality Introduction of specialization and role definition

0.60 0.90
0.69

0.54

0.16 0.38 0.27 0.09

a

Corresponds to parameter b in Eq. (1). Corresponds to parameter d in Eq. (1).
Significant at 5%.

Significant at 10%. b

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introduction of organizational innovation, permanent exporters are more innovative in terms of introducing re-engineering into administrative processes and for total quality development. 2.2.2. Effort in international business Differences in export performance may be explained by different degrees of effort by internationalizing firms. These differences are attributable to firm heterogeneity in access to information and management capability, among other possibilities. Kumcu, Harcar, and Kumcu (1995) show that, for Turkish companies, manager motivation helps to explain awareness of export incentives. Moreover, Spence (2003) shows that the success of UK overseas trade missions is positively affected by manager language proficiency. In the survey, managers were asked about the action intensity of several activities, such as strategic alliances with foreign and domestic firms, training of workers in export operations, and promotion of goods abroad. The results are shown in Table 3. The estimates suggest that permanent exporters are more active than sporadic exporters in only two activities: personnel training in exports operations and obtaining funds for working capital in activity-related exports. 2.2.3. Manager perception regarding obstacles to exporting One possible explanation for differences in exporter performance is that sporadic exporters face greater difficulties in their international operations. Some firms may have good export projects, for instance, but if they face credit access problems in the financial market, then it is more likely that they will leave international markets. In addition, some firms may exit due to protectionist barriers established in foreign markets. These kinds of obstacles have been divided into three types: internal to firms, internal to country, and external. Results are shown in Table 4. Table 3 International business management Activity

Differencea

Difference by sectorb

Strategic alliances with domestic firms Strategic alliances with foreign firms Hiring of staff qualified in international business Training of workers in export operations Promotion of goods abroad Improvement in information systems for external markets Improvements in negotiation abilities for foreign clients Improvements in external distribution networks Obtaining information and new technologies from foreign clients Obtaining loans for financing work capital Obtaining loans for financing investment Obtaining loans for exporting

0.12 0.57 0.49 0.88
0.37 0.04 0.49 0.10 0.20

0.27 0.002 0.12 0.02 0.35 0.45 0.12 0.44 0.21

a b


Corresponds to parameter b in Eq. (1). Corresponds to parameter d in Eq. (1). Significant at 5%.

0.91
0.25 0.30

0.29 0.05 0.22

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Table 4 Obstacles to exporting Obstacle Internal to firm Shortage of funds for financing investment in work capital Shortage of funds for financing physical capital Shortage of funds for financing export operations Low-skilled production workers Low-skilled management workers Scarce information about export markets Scarce information about external demand Low-scale production Shortage of funds for promoting goods abroad Internal to country Low real exchange rate Real exchange rate instability Little availability of export promotion instruments Scarce information regarding export promotion instruments Scarce information regarding productivity enhancing instruments Scarce information regarding new technologies Difficulties with domestic input suppliers Low credit access Low associability with other domestic producers External High tariffs Export quotas Import licenses Environmental barriers Safeguards Unfair competition Subsidies Competitors with preferential access High external transportation costs Changes in legislation in foreign markets Difficulties with external clients Competence in producing high-quality products Low prices in external markets

Differencea

Difference by sectorb

0.16

0.06

0.37 0.29 0.27 0.60 0.08 0.10 0.23 0.31

0.32 0.12 0.31 0.44 0.03 0.03 0.30 0.16

0.87
0.63

0.02 0.03

0.85
0.52

0.04 0.01

0.45

0.27

0.54 0.16 0.70

0.15

0.58
0.23 0.42 0.06

0.45 0.29 0.22 0.71 0.33 0.59 0.54 0.68

0.22 0.09 0.05 0.64 0.26

0.40 0.26 0.27 0.44 0.44 0.67
0.67

0.72
0.41 0.18 0.41 0.72
0.41

a

Corresponds to parameter b in Eq. (1). Corresponds to parameter d in Eq. (1).
Significant at 5%.

Significant at 10%. b

Even the sign of the difference indicates that permanent exporters assign smaller importance to firm-internal obstacles; the difference between both groups of firms is not statistically significant. Significant differences regarding the evolution of the real exchange rate and difficulties in access to financial resources exist, however, for

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the case of country-internal obstacles. This implies that a lower and/or unstable real exchange rate more greatly affects sporadic exporters than permanent exporters. One interesting result is that the interactive variable between status and sector is positive and significant. This reveals that in sectors of the economy without a comparative advantage, real exchange fluctuations tend to be a more important obstacle for sporadic exporters. With regard to credit access, the evidence indicates that liquidity constraints are more relevant for sporadic exporters. This finding in and of itself, however, is not conclusive with respect to a causality relationship. One interpretation is that credit constraints limit the possibility to remain as an exporter. This is plausible for small firms that are traditionally more restricted than larger firms. An alternative interpretation is that capital markets associate greater business risk with sporadic exporters, and lower access to credit may be due to poor export performance in the past. With respect to external obstacles, there are not important differences between permanent and sporadic exporters. Permanent exporters associate lower levels of incidence with almost every obstacle, especially for tariff and no-tariff barriers, but differences with sporadic exporters are not statistically significant. This implies that explanations about why some firms are not able to export permanently are not associated with the existence of trade barriers in foreign markets. 2.2.4. Utilization of public instruments There are several public instruments that Chilean firms can use to enhance their productivity and international competitiveness. It can be argued that differences in export performance are associated with the fact that permanent exporter firms have used these instruments with greater intensity than have sporadic exporters. The Chilean public instruments are classified into three groups. First, there are instruments designed to enhance productivity and technological capability in small firms. Second, there are export promotion instruments whose objective is to increase international competitiveness. Third, there are financial instruments established to improve credit access for small firms. In Fig. 1, we show the results for differences in the utilization of these instruments by firm group. The evidence shows that permanent exporters have used every public instrument more intensively. The most used public instruments have been the export promotion instruments and those specifically administered by the National Export Promotion Agency (ProChile). In the case of export promotion, about 35% of permanent exporters have used this kind of public support. This percentage is only about 19% for sporadic exporters. With regard to ProChile instruments, firm participation has been 26.9% for permanent exporters, and 14.5% for sporadic exporters. 3. Empirical approach The evidence in the previous section suggests that there are significant differences in the firm behavior according to exporter status. In this section, we study whether these factors do in fact explain the differences in exporter status. To do so, we

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391

Fig. 1. Utilization of public instruments.

define a dependent variable that takes the value 1 if the firm has been a permanent exporter over the period 1996–1999, and 0 if the firm has been a sporadic exporter. For the econometric estimation, the following Probit model is used: PrðYi ¼ 1Þ ¼ Uðb0 Xi Þ þ ei

ð2Þ

where U is a normal c.d.f. and X is a vector of covariates. The explanatory variables used in this estimation regard technological innovation, efforts related to international business, and the utilization of public instruments aimed to increase the competitiveness of SMEs. Though using a similar methodology, previous empirical studies only distinguish between exporters and non-exporters. Bernard and Jensen (1999) and Roberts and Tybout (1997), among others, have found that the probability of exporting is positively affected by firm characteristics such as age, productivity, worker skill levels, technological innovation, and foreign capital participation. An important difference between these studies and ours is the way in which we define export success. The empirical approach in this paper explores the differences between those firms that export permanently and those firms that only export sporadically. In addition, we emphasize the role of three potential explanations for differences between exporters: technological innovation, efforts in international business, and the utilization of public instruments. Several papers have addressed the question about how technological innovation can affect export performance. Roper and Love (2002) find that product innovation has a positive effect on the probability and propensity of exporting in British and German manufacturing plants. Basile (2001) obtains similar results for Italian manufacturing firms, concluding that the introduction of product and/or

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process innovation increases the probability of exporting. Bernard and Jensen (1999), Wakelin (1998), Kumar and Siddhartan (1994), and Hirsch and Bijaoui (1985) also find evidence regarding the positive impact of innovation on export performance. Export promotion instruments may also have a positive impact on export performance. Evidence on this positive effects is provided by Wilkinson and Brouthers (2000), Cavusgil and Naor (1987), and Coughlin and Cartwright (1987) for state programs in the US. In terms of specific export promotion instruments, Spence (2003) evaluates the impact of overseas trade missions in the UK showing that this instrument has contributed positively to the generation of incremental sales in foreign markets. The impact of trade shows has been analyzed by Blythe (1996), Pfeiffer, Burgemeister, Hibbert, and Spence (1998), and Shipley, Egan, and Wong (1993). For developing countries, however, there is scarce evidence about the impact of export promotion instruments.6 There are two potential methodological problems associated with this approach. First, in our case, it may be argued that some of the explanatory variables are also affected by the firm’s export status. In fact, firms that export permanently may be not only more likely to carry out technological innovation, but also to put greater effort into international business. Our dataset is not detailed enough to explore this bi-causality phenomenon. Instead, firm panel data would illuminate the impact of export performance on firm behavior. Our approach, however, explores the impact of a firm’s decisions on export performance. This is consistent with related international trade literature that suggests a positive relationship between exports and firm performance is better explained in an empirical sense by a self-selection phenomenon (i.e. better firms are able to export), and not by the effect of learningby-exporting (i.e. the idea that exporters improve their performance by accessing new technologies or taking advantages of scale economies).7 The second, and the most important problem, is the endogenous nature of the utilization of public programs. Following the program evaluation literature, this is the case of non-experimental design where the treatment variable (i.e. participation in a program) is not exogenous. We should expect that some firm characteristics determine a higher or lower probability of participation, and that these variables may also affect export status. Indeed, it may be the case that export promotion agencies select firms based on some implicit or explicit criteria. If better firms selfselect themselves or if they are selected by export programs, then the parameter associated with this variable would capture the impact of unobserved firm characteristics and not a causal effect from promotion to export performance. 6

Exceptions are Alvarez and Crespi (2000), Arslan and van Wijnbergen (1993), and Low (1982). See Clerides, Lach, and Tybout (1998) and Bernard and Jensen (1999) for empirical evidence regarding self-selection. Alvarez and Lo´pez (2003) find similar evidence in Chilean manufacturing plants. They argue, consistent with our approach, that the self-selection phenomenon is endogenous; firms entering international markets have taken previous decisions in order to improve their performance. After exporting, there are no additional gains in performance. 7

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There are two methodologies available to face this problem, depending on the assumption about the selection (or participation) mechanism. One can assume that the participation decision is carried out over either unobservable or observable variables by the econometrician. When a rich dataset is available, the second assumption is more valid. It may be argued that is the case here. In general, certain aspects of firm decisions, such as efforts in international business and barriers faced by exporters, are unobservable in databases available to researchers. In this survey, however, there are a large number of variables that can be used to control for traditionally unobservable effects.8 Assuming selection on observables, the econometric approach consists of two steps. In the first step, we estimate a participation equation that aims to identify which variables influence the utilization of public programs. In the second step, these variables are included as additional regressors in the outcome equation (or export status). The first-step regressions are shown in Table 5. We estimate a Probit model for two programs: (i) promotion instruments managed by the National Agency for Export Promotion (ProChile), and (ii) other export promotion instruments available for firms (FomExp). In the latter category, we have grouped instruments designed to reduce anti-export bias due to tariffs (such as drawbacks) and those destined to minimize costs associated with export activity (such as exports credit insurance).9 To identify which variables to include in this estimation, we ask why firms participate in export promotion programs. First, we hypothesize that initial export performance by firms affects the probability of participating in these programs. It may be argued that firms exporting few products or selling products to a reduced number of markets are more likely to participate in export promotion programs. For these firms, the participation is more useful for opening new markets and for introducing new products that it is for other firms that are exporting many products to many markets. On the other hand, it may be argued that only firms with some degree of experience in international markets are aware of the benefits associated with export promotion programs. In this case, a better previous performance increases the probability of participation. Thus, the relationship between participation and initial export performance is ambiguous. We study the effect of initial export performance, including export value, the number of exported products, and markets at the beginning of the period (1996). We also include other firm characteristics such as size and labor skills. Second, we exploit our dataset by looking for other variables that explain the utilization of export promotion instruments. We hypothesize that greater effort in 8

For a discussion of these issues, see Angrist and Krueger (1998). Two reasons prevent us from studying the impact of each of these instruments. First, the sample size is too small to obtain robust results with the scarce number of firms that use each instrument individually. Second, our objective is more modest. We wish to study whether a system of promotion instruments have a chance of improving export performance in general. Future research may be more directly aimed at evaluating the impact of different instruments. 9

(2) ProChile 0.061 (1.86) 0.021 (0.78) 0.012 (0.41) 0.020 (0.68) 0.106 (3.46)

0.070 (2.04)
0.071 (1.89) 0.035 (0.98) 0.072 (2.34)
0.058 (1.82) 0.041 (1.23) 0.015 (0.34) 0.002 (0.05) 0.050 (1.35) 0.018 (0.77) 0.034 (0.55) 0.005 (1.51) 0.024 (1.90) 0.000 (2.49)
0.030 (0.97) 0.384 (1.49)

296

(1) ProChile

0.075 (2.19)
0.016 (0.55) 0.007 (0.21) 0.028 (0.96) 0.128 (4.06)

0.089 (2.37)
0.071 (1.88) 0.039 (1.05) 0.066 (2.13)
0.057 (1.79) 0.048 (1.47) 0.010 (0.23) 0.003 (0.09) 0.053 (1.46) 0.017 (0.65) 0.049 (0.78)

296

0.241 (3.43)

296

0.061 (1.81) 0.029 (1.04) 0.024 (0.80) 0.017 (0.57) 0.102 (3.40)

0.056 (1.61) 0.067 (1.77) 0.038 (1.06) 0.072 (2.38)
0.061 (1.80) 0.050 (1.52) 0.015 (0.34) 0.002 (0.06) 0.051 (1.40) 0.023 (0.94) 0.002 (0.03) 0.005 (1.33) 0.017 (1.45) 0.000 (2.90)

0.035 (1.10) 0.485 (1.86)

(3) ProChile

296

0.004 (0.14) 0.021 (0.88) 0.035 (1.25) 0.040 (1.57) 0.044 (1.50) 0.068 (1.98)
0.001 (0.02) 0.002 (0.07) 0.015 (0.51) 0.015 (0.53) 0.019 (0.64) 0.025 (0.63) 0.020 (0.60) 0.005 (0.15) 0.015 (0.67) 0.130 (2.33)


(4) FomExp

296

0.004 (0.13) 0.021 (0.97) 0.039 (1.53) 0.027 (1.13) 0.024 (0.85) 0.053 (1.66) 0.004 (0.11) 0.011 (0.36) 0.019 (0.67) 0.010 (0.36) 0.027 (0.93) 0.011 (0.31) 0.021 (0.64) 0.008 (0.25) 0.016 (0.76) 0.110 (1.99)
0.003 (1.73) 0.037 (2.79)

0.000 (0.84) 0.003 (0.12) 0.175 (1.00)

(5) FomExp

296

0.011 (0.38) 0.023 (1.02) 0.042 (1.60) 0.025 (1.00) 0.007 (0.26) 0.039 (1.19) 0.008 (0.24) 0.001 (0.05) 0.006 (0.22) 0.000 (0.00) 0.036 (1.23) 0.007 (0.20) 0.018 (0.57) 0.015 (0.46) 0.020 (0.92) 0.103 (1.86) 0.002 (1.30) 0.034 (2.59)

0.000 (1.32) 0.004 (0.13) 0.253 (1.47) 0.202 (3.20)



(6) FomExp

Notes: Reported estimates represent the change in the probability of an infinitesimal change for each independent continuous variable and, by default, the discrete change in the probability for dummy variables. Absolute value of z statistics in parentheses.
Significant at 5%.

Significant at 1%.

Alliance_dom Alliance_for Qualified_staff Training Promotion_abroad Inf_system Negotiation Ext_distrib Inf_newtech Work-capital Loans_investment Loans_exporting Market_inf Demand_inf Fund_prom Sector Products_1996 Markets_1996 Exports_1996 Size_1996 Labor_skils_1996 ProChile FomExp Observations

Table 5 Probit: participation equation

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international business positively affects the probability of participation; thus, all of the variables regarding international business management, presented in Table 3, are included in the estimation. Third, we test whether firms facing significant obstacles in international markets tend to use these instruments more widely. We look for the kind of obstacles that promotion instruments are designed to deal with to identify the relevant ones. Thus, we include three measures of firm perceptions of obstacles regarding scarce information about export markets (Market_inf), scarce information about external demand (Demand_inf), and the shortage of funds for promoting goods abroad (Fund_prom). A reduction in these difficulties towards better export performance is explicitly present in the objectives of export promotion instruments. Particularly, ProChile’s programs are designed to improve access to information about international markets and to carry out joint actions by firms, thereby reducing the amount of resources that each firm would spend individually to promote its products abroad. The results of this first-step regression, shown in Table 5, suggest that we should control for three variables related to efforts in international business in the second step: (i) promoting goods abroad (Promotion_abroad), (ii) the improvement of information systems for external markets (Inf_System), and (iii) obtaining information and new technologies from external clients (Inf_newtech). The results are mixed with regard to previous export performance. They show that exports are negatively associated with participation in ProChile, but exported products are positively associated with the utilization of other promotion instruments. Fist-step estimation also suggests that, in general, both types of instruments are used in a complementary manner. The probability of using one type of instruments is affected positively by the utilization of the other instrument. We find that other variables, like size and labor skills, do not affect the probability of using exports promotion instruments. In the second-step regression, in addition to control variables identified in the first-step, we have included as regressors those activities that have been found to be significant different between both groups as documented in the previous section.10 With regard to technological innovation, we consider the effect of process innovation through outsourcing (Outsourcing), the introduction of information technologies (Information), and innovation in management through the introduction of total quality (Quality). To analyze the role of effort in international business, we include the training of workers in export operations (Training) and obtaining loans for financing capital work (Work_capital). The sector-specific effects are controlled for by including a dummy variable if the firm produces in a sector of comparative advantage (Sector). The results of using different specifications to estimate the outcome equation (exporter status) are shown in Table 6. In the second column, we add as a control firm size (measured as the log of employment) and labor skills (measured as the proportion of graduate college workers on total employment). The third column 10

I thank both anonymous referees for this recommendation.

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Table 6 Probit: exporter status equation

ProChile FomExp Outsourcing Information Re-engineering Quality Training Work-capital Promotion_ abroad Inf_system Inf_newtech Sector Exports_1996 Markets_1996 Size_1996 Labor_skils_1996 Innovation mean Effort mean Observations

(1)

(2)

(3)

(4)

0.055 (0.72) 0.270 (3.29)

0.082 (2.92)

0.052 (1.72) 0.020 (0.58) 0.012 (0.43) 0.097 (2.93)

0.031 (0.96) 0.067 (1.95)

0.052 (0.69) 0.267 (3.22)

0.082 (2.91)

0.059 (1.89) 0.005 (0.14) 0.011 (0.38) 0.085 (2.57)
0.030 (0.93) 0.067 (1.93)

0.056 (0.74) 0.282 (3.38)

0.105 (3.43)

0.030 (0.87) 0.027 (0.68) 0.012 (0.37) 0.091 (2.42)
0.040 (1.03) 0.078 (2.02)


0.295 (3.54)

0.105 (3.42)

0.030 (0.86) 0.025 (0.63) 0.013 (0.40) 0.094 (2.51)
0.042 (1.08) 0.082 (2.13)


0.100 (3.30)

0.047 (1.39) 0.011 (0.28) 0.018 (0.55) 0.086 (2.24)
0.033 (0.81) 0.067 (1.78)

0.082 (2.06)
0.028 (0.98) 0.139 (1.91) 0.000 (2.46)
0.061 (3.27)



0.078 (1.93) 0.019 (0.63) 0.136 (1.83) 0.000 (2.15)
0.064 (3.28)

0.065 (1.53) 0.173 (0.68)

0.065 (1.47) 0.002 (0.05) 0.131 (1.75) 0.000 (2.14)
0.065 (3.36)

0.074 (1.73) 0.199 (0.76)

0.063 (1.44) 0.002 (0.05) 0.132 (1.77) 0.000 (2.13)
0.066 (3.39)

0.074 (1.76) 0.215 (0.84)

0.047 (1.06) 0.003 (0.08) 0.147 (1.98)
0.000 (1.88) 0.070 (3.49)

0.078 (1.88) 0.095 (0.37)

0.130 (1.62)

0.127 (1.61)

0.100 (1.34)

0.047 (0.37) 296

0.055 (0.44) 296

0.020 (0.16) 296

296

296

(5) 0.116 (1.52)

Notes: Reported estimates represent the change in the probability of an infinitesimal change for each independent continuous variable and, by default, the discrete change in the probability for dummy variables. Absolute value of z statistics in parentheses.
Significant at 5%.

Significant at 1%.

adds mean firm intensity for two of the activities considered in the estimation: technological innovation and effort in international business.11 When doing so, we control for potential measurement error in the ranking of individual activity intensities. As this ranking is subjective, some firms may overestimate or underestimate their efforts. The mean by firm plays a similar role to that of a fixed effect in longitudinal or panel data.12 Finally, given that both instruments may be strongly correlated both are included individually in the fourth and fifth equations. 11 For each firm, we calculate the average intensity of 12 innovation indicators (Innovation_mean) and 12 international business indicators (Effort_mean). 12 I thank one anonymous referee for calling attention to this problem. Levin (1988) and Cohen and Levinthal (1989), for example, have found that including industry means for the qualitative variables reduces the problem of using subjective measures. This is valid, however, under the assumption that the bias in the answers has an industry component. If the component is firm-specific, we think that our procedure is more accurate.

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The results suggest that two activities explain differences in export performance: processes innovation, through outsourcing, and the training of workers in export operations. Both positively and significantly affect the probability of exporting permanently in each specification. The other forms of innovation, such as the introduction of information technologies, re-engineering, and total quality, do not impact on exporter success.13 How do we explain this result, which differs so greatly from previous studies? First, it may be argued that small firms, especially in developing countries, are specialized in market niches that do not require large innovative effort. Second, though previous studies have found a positive impact on the probability of exporting, they do not explore the effects on being a permanent exporter. Consistent with previous literature, our findings imply that technological innovation may be useful to enter international markets. Yet, posterior performance requires higher innovative action in processes, such as those related to outsourcing. Other significant variables are firm size and initial export performance. Both positively and significantly affect the probability of exporting permanently. Within the SMEs, larger firms have an advantage entering and staying in international markets, which is consistent with previous empirical evidence (see Wagner, 2001). Interestingly, initial export performance is correlated with posterior exporter success. As suggested by our results, firms that initially export more and to more markets have a higher probability of being a permanent exporter. This may reflect the fact that their exports are more diversified. Thus, they would be less likely to exit from foreign markets if negative shocks affect their exports to some market in particular. In terms of ProChile’s instruments, our results differ slightly from previous studies of Chilean firms. Alvarez and Crespi (2000) have found a positive impact for such instruments on exports and exported products. In this case, however, the evidence suggests that ProChile instruments do not enable firms to achieve permanent exporter status. In contrast, these results show that the utilization of other export promotion instruments help to generate success in international markets. These two results are robust to different specifications, particularly when both are included separately in the estimation. With regard to this finding, we explore the impact of specific instruments managed by ProChile. In fact, as suggested by Wilkinson and Brouthers (2000) for statesponsored US programs, the impact of each instrument on export performance may differ. In this case, we identify the impact of three different instruments: (i) trade shows that take place at fixed overseas locations and are designed to establish contact between exporters and potential foreign clients (Trade_shows), (ii) trade missions, aimed to improve firm learning about the exporting process (Trade_missions), and (iii) exporter committees, composed of a group of firms with common objectives in international business. The main activities for export 13 To check the robustness of our results in the presence of possible high correlation among innovation activities, we estimate the specification in column 3 including each type of innovation separately. The results remained unchanged. To save space, here we report the individual coefficients and t-test (in parentheses) for each variable; outsourcing: 0.128 (3.59), information: 0.059 (1.52), re-engineering: 0.028 (0.69), and quality: 0.029 (0.86).

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Table 7 Probit: exporter status equation (1) Trade shows Committee Trade mission FomExp Outsourcing Information Re-engineering Quality Training Work-capital Promotion_abroad Inf_system Inf_newtech Sector Exports_1996 Markets_1996 Size_1996 Labor_skills_1996 Innovation_mean Effort_mean Observations

(2)

(3)

0.151 (1.82) 0.143 (2.01)
0.289 (3.46)

0.114 (3.69)

0.029 (0.82) 0.023 (0.60) 0.014 (0.41) 0.096 (2.57)
0.040 (1.02) 0.075 (1.98)
0.067 (1.52) 0.005 (0.15) 0.134 (1.78) 0.000 (2.12)
0.064 (3.35)

0.072 (1.72) 0.225 (0.87) 0.140 (1.75) 0.054 (0.43) 296

0.052 (0.65) 0.293 (3.51)

0.108 (3.51)

0.033 (0.94) 0.026 (0.65) 0.015 (0.47) 0.091 (2.40)
0.041 (1.04) 0.078 (2.04)
0.066 (1.49) 0.002 (0.05) 0.131 (1.76) 0.000 (2.11)
0.065 (3.34)

0.075 (1.78) 0.202 (0.80) 0.131 (1.64) 0.042 (0.34) 296

0.280 (3.31)

0.108 (3.44)

0.037 (1.04) 0.030 (0.77) 0.016 (0.48) 0.092 (2.45)
0.040 (1.03) 0.069 (1.80) 0.069 (1.58) 0.001 (0.03) 0.133 (1.75) 0.000 (2.13)
0.067 (3.42)

0.078 (1.81) 0.161 (0.60) 0.144 (1.78) 0.046 (0.37) 296

Notes: Reported estimates represent the change in the probability of an infinitesimal change for each independent continuous variable and, by default, the discrete change in the probability for dummy variables. Absolute value of z statistics in parentheses.
Significant at 5%.

Significant at 1%.

committees are trade missions, international marketing research, external promotion, participation in international fairs and events, market studies, and invitations to clients, authorities, and experts (Committees). ProChile’s activities aimed to improve the international competitiveness of Chilean exporters are carried out largely through these exporter committees. The results in Table 7 show that differentiation by type of instrument matters to a proper assessment of the impact of ProChile’s instruments. As suggested by these results, trade missions and trade shows do not increase the probability of being a successful exporter. Participation in exporter committees, however, has an important quantitative impact: firms that use this instrument have a 14% higher probability of being a permanent exporter. 4. Conclusion In this paper, we have analyzed why some SMEs are more successful than others in international markets. Starting from international evidence about the

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disadvantages associated with size to export performance, we focus on the fact that some Chilean firms within the SME segment show a superior performance in international markets. In the first part, various hypotheses were analyzed in order to estimate an empirical model that accounts for differences in export performance. The main difference with previous studies concerns the definition of successful exporters. In this paper, we are concerned with exporters only, and distinguishing between them as permanent and sporadic exporters. In the second part, the econometric results indicate that certain hypotheses are more plausible as explanation of firm export success. Our estimates show that effort in international business, particularly with regard to the training of workers, process innovation such as outsourcing, and the utilization of export promotion instruments are important sources of success. The results are significant in terms of public policies formulated to increase international competitiveness among SMEs. First, it is worth emphasizing that internal efforts aimed to improve export performance are required to be a successful exporter. There is a self-selection phenomenon that public agencies should keep in mind when designing optimal programs. Second, some types of programs work better than others. In this paper, we find that trade shows and trade missions do not affect the probability of exporting permanently, but exporter committees show a positive and significant impact.

Acknowledgements The author thanks Gustavo Crespi, Jose´ Miguel Banavente, Julio Ca´ceres, Mark Dincecco, Bernardita Escobar, Ronald Fischer, Pablo Gonzalez, Dominique Hachette, Gonzalo Islas, Ricardo Lopez, Victor Macias, Patricia Noda, Alejandra Sanhueza, two anonymous referees, and attendees of seminars at the Department of Economics, University of Chile, for their valuable comments and suggestions. This research was funded by the Fondo para el Estudio de las Politicas Publicas and the National Agency for Export Promotion (ProChile). Erwin Hansen provided able research assistance. The usual disclaimers apply.

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