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Erschienen in: Small Business Economics 1/2013

01.06.2013

Supplier development programs and firm performance: evidence from Chile

verfasst von: Irani Arráiz, Francisca Henríquez, Rodolfo Stucchi

Erschienen in: Small Business Economics | Ausgabe 1/2013

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Abstract

This paper evaluates the impact of the Chilean Supplier Development Program, aimed at improving and stabilizing the commercial linkages between small and medium-sized suppliers and their large firm customers, during the period 2003–2008. We use the panel structure of our dataset to control for observables and time-invariant unobservable factors that affect the participation and performance of firms. We find that both small and medium enterprises and large firms benefited from the coordination efforts. The program increased sales, employment, and the sustainability of small and medium-sized suppliers; it also increased the sales of large firms and raised their ability to become exporters. In addition, we find that the timing of the effect is different for suppliers and large firms. While the effect on suppliers appeared 1 year after the firms enrolled in the program, the effect on large firms took 2 years to appear.

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Fußnoten
1
This argument is also raised by Malmberg and Maskell (1997, 2006).
 
2
Using plant-level panel data on Chilean manufacturers, Pavcnik (2002) finds evidence of within-plant productivity improvements in the import-competition sector that can be attributed to liberalized trade. She also finds that, in many cases, aggregate productivity improvements stem from the reshuffling of resources and output from less to more efficient producers.
 
3
Alfaro and Rodriguez-Clare (2004) indicate that many studies fail to find evidence of positive externalities from multinationals to local firms in the same sector (horizontal externalities), but confirm the existence of positive externalities in upstream industries (vertical externalities).
 
4
Girma and Görg (2005) and Görg and Greenaway (2004) show that absorptive capacity matters for productivity spillover benefits.
 
5
Through subsidies, CORFO creates incentives for large firms to provide training, professional advice, technical assistance, and transfer of technology to SME suppliers at a lower cost. This behavior signals to SME suppliers its client’s commitment to developing a long-term relationship with them.
 
6
Most of the related existing literature analyzes either the effect of a particular firm—usually a multinational corporation—on local suppliers in the sector of operation, or the effect of FDI on productivity in related domestic industries at the national level. Although in these cases firms could have consciously developed linkages with their local suppliers, the analysis of the role of government’ programs in the promotion of these linkages is rare (Lauridsen 2004). The World Bank evaluated the impact of SME support programs in Chile—nine CORFO matching grants and credit programs which included the PDP—but the percentage of firms that benefited from the PDP accounted for only 2 % of beneficiary firms in the sample analyzed (López-Acevedo and Tan 2010).
 
7
These costs are associated with training, product development, testing, and factory audit to ensure the capabilities of potential local suppliers and the quality of their products.
 
8
The 2010–2020 Innovation and Competitiveness Agenda created by the National Innovation Council for Competitiveness shows a renewed interest in government policies aimed at concentrating efforts in selected sectors.
 
9
CORFO is the Chilean Economic Development Agency.
 
10
The Unidad de Fomento (UF) is a unit of account widely used in Chile that reflects the real value of the Chilean peso. The UF is adjusted to inflation to keep its real value constant.
 
11
It may be possible to identify these companies by looking at the physical records located in the CORFO’s various regional offices (agentes operadores intermediarios). Because of time constraints and the work load of these regional offices, however, we decided not to pursue this option.
 
12
Since we were not able to identify beneficiaries that completed their projects before 2004, it was not possible to rule out that some of these firms had been included in the control group. This could bias the results downward and result in an underestimation of the impact of the program.
 
13
The Department of Economic and Tax Studies of SII graciously agreed to allow us partial access to their tax records following statistical reserve regulations and under monitored conditions.
 
14
Only 0.03 % of the PDP’s beneficiaries could not be successfully matched to SII’s dataset—3 out of 9,099 firms. One of these firms’ records, although present in SII’s dataset, was empty. We believe that the record of the other two firms in the PDP’s beneficiary dataset had some error in the tax identification number, which was why we could not match them to SII’s dataset.
 
15
See, for example, Wooldridge (2002, chap. 10), Cameron and Trivedi (2005, pp.768–770), or Angrist and Pischke (2009, chap. 5). The estimation of δ using the first-difference transformation of Eq. (1) is equivalent to the DID estimate. Note that the first-difference transformation provides a before–after comparison and the treatment dummy takes the difference between the treated and control groups. The within-group transformation is equivalent to this estimator if the time dimension of the panel is 2. In longer panels with strictly exogenous regressors, both the first-difference and within-group estimators have the same probability limit and differences between the estimators reflect the sampling error. The within-group estimator is more efficient.
 
16
These dummies—commercial legal entities (persona juridica comercial), natural persons, and others—indicate how the firms appear registered at SII. We considered it important to make sure that the control group had the same composition as the treated group. In the case of suppliers, most beneficiaries are registered as natural persons, but there are some beneficiaries registered as commercial legal entities or having other legal statuses. Therefore, we considered these types of firms as possible controls. In the case of sponsor firms (buyers), all beneficiaries were registered as commercial legal entities and, consequently, the control firms were chosen to be all commercial legal entities. Therefore, in the case of sponsor firms, we do not include these dummy variables.
 
17
The pstest Stata command used to carry out these tests estimates probit models instead of the logit models we use in our participation model. The logit models’ pseudo R 2 are reported in Table 3. Logit models are more attractive than probit models, in our case, because they accumulate more probability in the tails of the distribution.
 
18
Firms hire workers until the point at which the marginal product of labor is equal to real wages. Given that the marginal product of labor is decreasing in labor, the increase in real wages and employment has to be the result of a displacement to the right of the marginal product of labor—that is, an increase in productivity.
 
19
We do not observe exit from the market but exit from the administrative records of SII. Therefore, we define sustainability as reporting positive sales for tax purposes (up to 3 years after initiating participation.
 
20
A more appropriate method to measure firms’ sustainability would be to use survival analysis techniques, for which one would need to observe firms for a longer period after participating in the program; there are not enough available data to do this analysis now.
 
21
Data from ProChile, the Export Promotion Bureau.
 
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Metadaten
Titel
Supplier development programs and firm performance: evidence from Chile
verfasst von
Irani Arráiz
Francisca Henríquez
Rodolfo Stucchi
Publikationsdatum
01.06.2013
Verlag
Springer US
Erschienen in
Small Business Economics / Ausgabe 1/2013
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI
https://doi.org/10.1007/s11187-012-9428-x

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