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Exporters’ agglomeration and the survival of export flows: empirical evidence from Colombia

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Abstract

The survival of new exports is key for underpinning the dynamics of exports growth. In this paper, we explore whether agglomeration of exporters enhance duration of export flows at the firm-product-destination level using transaction level data for the universe of exports in Colombia between 2005 and 2011. We find that both the presence and size of agglomerations increase the survival rate of trade flows, defined by the triple firm-product-destination. This agglomeration effects seems to be related with flow specific spillovers and are highly concentrated across space. The effects tend to be stronger as firms perform similar product-destination export activities. Also the effects are larger for differentiated products where uncertainty about demand is more prevalent.

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Fig. 1

Source Authors’ calculation on DIAN data

Fig. 2

Source Authors’ calculation on DIAN data

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Notes

  1. Even though the classification of products corresponds to the national nomenclature level (10 digits), this aggregation was chosen in order to avoid high mass probability at zero, in both survival time and agglomeration size, that could significantly affect the econometric results.

  2. Measuring duration requires knowledge of the year in which the export activity initiated. Therefore, export activities already present in 2004 are neglected. Besides censoring, these triples are also subject to right truncation. To account for this, there is need to impose strong assumptions on the underlying duration distribution function.

  3. Although our data set contains monthly exports, we aggregate them annually to avoid noise coming from infrequent or irregular trade patterns, and also because we include all exported products and the agricultural ones tend to have seasonal behaviors. Therefore, we consider as operative export activities that register at least one flow in a particular year, independently from their monthly behavior.

  4. See Besedes and Prusa (2007), Besedes and Blyde (2010), Nitsh (2009), Fugazza and Molina (2016), Tovar and Martínez (2011), Volpe Martincus and Carballo (2009), among others.

  5. With the exception of the SEZs and routes length, these variables were taken from the National Planning Department (DNP 2012), elaborated from the 2005 National Population Census. Data on the SEZs were sourced from the legislation that created each of the SEZs, while routes length was sourced from the corresponding national agency (INVIAS 2009).

  6. For constructing this variable we use data covering the period 1996–2011. We are precluded from employing this dataset for estimation since data on municipalities are available only from 2004 on.

  7. We formally test the difference between survival distribution using log-rank, Wilcoxon and Tarone-Ware test, which confirms that the survival functions are statistically different.

  8. Complete tables with estimated coefficients are available upon request.

  9. The groups are defined using the agglomeration’s distribution. Nonetheless, estimations using other groupings show similar results.

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Author information

Authors and Affiliations

  1. Universidad de Ibagué, Ibagué, Colombia

    Ricardo Arguello

  2. Universidad EIA, Envigado, Colombia

    Andres Garcia-Suaza

  3. Georgetown University, Washington D.C., USA

    Daniel Valderrama

Authors
  1. Ricardo Arguello
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  2. Andres Garcia-Suaza
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  3. Daniel Valderrama
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Correspondence to Andres Garcia-Suaza.

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Appendix

Appendix

1.1 Variable definitions

Firm level These variables were obtained from the national export registry.

  • Reappearing Dichotomous variable taking value 1 if the firm has previous exporting experience during the observation period, and cero otherwise.

  • Number of products Number of HS-four-digit products exported by the firm at time t.

  • Number of destination markets Number of countries to which the firm exports at time t.

  • Initial export value (in logs) The log of initial export value in FOB USD.

Municipality level These variables come from different sources.

  • Routes length Primary and secondary routes area in squared kilometers, calculated Arcgis using INVIAS (2009) maps.

  • Special Economic Zones Number of active SEZs in municipality i at time t. Source: legislation on SEZs (2011).

  • GDP per-capita Estimation based on bank deposits at the municipality level during 2005–2011. Source: Colombian Financial Superintendence.

  • Urbanization rate Share of urban population on total municipal population based on 2005 Population Census data. Source: DNP (2010).

  • Political institutions A combination of an index that measures public municipal investment per capita (DDTS 2005–20010) and an index of institutional capability at the municipality level (DDTS 2005–2010). Source: DNP (2010, on DDTS).

  • Poverty index Index of basic unsatisfied needs. Source: DANE (2005).

Product level Variables calculated at the HS-four-digit level.

  • Product share in total exports Share of product exports to total exports at time t.

  • Types of goods Homogenous goods, referenced price good, and differentiated good. Based on Rauch’s (1999) classification.

Market level Calculated at the destination market level.

  • Free Trade Agreements (FTAs) Dichotomous variable with value 1 if there is an FTA in place at time t with the destination country and cero otherwise.

  • Preferential Agreements (PAs) Dichotomous variable with value 1 if there is an PA in place at time t with the destination country and cero otherwise.

  • Destination markets share Share of the destination export to total exports at time t.

  • World trade growth Growth rate of world imports, excluding Colombian trade, at product-market combinations.

  • International crisis Dichotomous variable with value 1 for the crisis years (2009–2010).

See Fig. 3 and Tables 6, 7, 8, 9, 10, 11 and 12.

Fig. 3
figure 3

Source authors’ calculation on DIAN data. “Same product-destination” refers to the agglomeration defined by the number of firms in the same municipality that export the same product to the same destination. Similarly, “Same product” and “Same destination” refer to the measure based on the number of firms, located in the same municipality, that export either the same product or to the same destination. “Total” measures the networks as the total number of firms that export and are located in the same municipality

Agglomeration size at different dimensions by product-destination.

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Table 6 Percentage of transactions at the firm-product-destination level by destination and type of good.
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Table 7 Distribution of the number of products and destinations at the firm level, 2005 and 2011.
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Table 8 Marginal effect covariates of hazard rate estimation.
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Table 9 Effect of agglomeration specificity on the hazard rate estimation.
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Table 10 Concurrent effects of agglomeration specificity on the hazard rate estimation for firm-product-destination export flows.
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Table 11 Effect of agglomeration measure on the hazard rate estimation for firm-product-destination export flows.
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Table 12 Marginal effect by type of product according to Rauch’s (1999) for firm-product-destination export flows.
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Arguello, R., Garcia-Suaza, A. & Valderrama, D. Exporters’ agglomeration and the survival of export flows: empirical evidence from Colombia. Rev World Econ 156, 703–729 (2020). https://doi.org/10.1007/s10290-020-00378-y

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