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Globalization drives strategic product switching

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Abstract

Using firm-level panel data for Estonia, we analyse the impact of international competition on firm dynamics, considering both firm closedown and product switches. We contribute to the literature in two important ways: first, this is the first paper to study the determinants of exit and product switching in an emerging market; and second, we consider explicitly the role of export opportunities. Our results indicate that globalization does not affect firm exit significantly but it is an important factor explaining why firms choose a different core product. Previous studies on industrial countries have shown that product switching has been a defensive strategy against low-cost imports. In contrast, our results suggest that Estonian firms change their core products as an offensive strategy to take advantage of the export opportunities created by a globalized economy.

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Notes

  1. The Association Agreement with the EU was signed in 1995 and entered into force in 1998. The agreement replaced previous treaties with the EU (an Agreement on Trade and Commercial Cooperation, signed in 1992, which was converted into a Free Trade Agreement in 1994). For a more detailed description, see Weber and Taube (1999). Partly as a result, there has been a reorientation of trade away from Russia.

  2. We only have information on a firm’s main product line (which is defined by the Registrar’s Office based on the activity from which the firm gets the largest share of its sales) but not on its entire product mix or whether a firm is single- or multi-product. This could lead to spurious correlation in the data, resulting from marginal switches (for example, a firm producing two products with market shares of 51 and 49% respectively, changes their relative importance to 49 and 51%). However, as noted by Bernard et al. (2006), such marginal changes should bias our results against finding a significant impact of globalization on changes in a firm’s core product.

  3. Henceforth, product switches are defined as changes in industry at the four-digit NACE level (General Industrial Classification of Economic Activities within the European Community). Although four-digit codes—broken down in 640 classes—are not true products in the strictest sense of the word, this is the most detailed classification we have in our data. This notation has also been used in Bernard et al. (2006) and Greenaway et al. (2008).

  4. For an overview of the empirical literature, see Tybout (2003) and Bernard et al. (2007a).

  5. Goldberg et al. (2010) analyse the response of Indian firms to trade liberalization but they focus on product churning rather than looking into the firm dynamics per se.

  6. For a detailed description of the data, see “Appendix”. Detailed statistics on product switching in Estonia are provided in the IMF Working Paper version of this paper (Moreno Badia et al. 2008).

  7. The OECD database is the only one, to our knowledge, with information on services trade by partners. However, the coverage is incomplete and at relatively aggregated level and, thus, it cannot be used to estimate our model.

  8. We classify the manufacturing sectors according to technology intensity and services according to knowledge intensity using the Eurostat classification (Eurostat 2010).

  9. For a theoretical background of trade and quality, see, among others, Falvey and Kierzkowski (1987), Flam and Helpman (1987), and Murphy and Shleifer (1997). Empirical papers on this topic include Schott (2004), Hummels and Klenow (2005), and Hallak and Schott (2008).

  10. Melitz (2003) shows that developments in the export markets of firms have repercussions on the domestic market. Although we cannot control for the export status of the firm in our data set, our findings are consistent with this argument.

  11. Results are not reported here for brevity, but can be obtained from the authors upon request.

  12. If we exclude the wholesale and retail sectors from the analysis, no significant results are obtained for the export variables.

  13. This measure is known as the minimum efficiency scale (MES). We prefer the MES based on sales to a MES based on median employment since the latter does not capture the fixed costs of capital-intensive industries adequately. Alternatively, we could have used the minimum of industry entry and exit rates as in Greenaway et al. (2008). However, in practical terms this would have been equivalent to using exit rates, creating endogeneity problems.

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Acknowledgments

We would like to thank Larissa Merkulova and Kadri Rohulaid of the Centre of Registers and Infosystems for the data and valuable clarifications on the Registrar’s Office database. We also thank participants at the LICOS seminar and ETSG 2008, Jonathan Eaton, Hylke Vandenbussche, Beata Smarzynska Javorcik, Lenno Uusküla and an anonymous referee for helpful comments and suggestions. All errors are our own. The views expressed herein are those of the authors and should not be held to represent those of the institutions of affiliation.

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Correspondence to Ilke Van Beveren.

Appendix: definitions of variables

Appendix: definitions of variables

The firm-level data used in this paper are provided by the Estonian Business Registry and cover the period 1997–2005. The trade data are from the UN Comtrade (commodity trade statistics) database and consist of the trade values and quantities of import flows at the six-digit product level, according to the Harmonized System (HS) classification 1988/92. See Moreno Badia et al. (2008) for details about the data cleaning process.

1.1 Firm-level variables

All monetary variables are expressed in real terms. Output and intermediate input deflators, as well as the gross capital formation price index, were obtained from the Statistical Office of Estonia. Deflators are available for 16 sectors corresponding to the International Standards Industrial Classification (ISIC Rev.3.1) at the one-digit level.

Exit it+1 :

Dummy variable, equal to 1 in period t if the firm exits in period t+1. Firm exit is defined based on the official date of liquidation from the Commercial Register. If a firm disappears from the data set and has an official liquidation date, it is considered to exit in the last year of observation. Liquidation due to a merger, acquisition or re-registration in the registry is not considered an exit.

Switch 2d,it+1 :

Dummy variable, equal to 1 in period t if the firm switches two-digit NACE industries in period t+1. An industry switch is defined as a change in the firm’s primary sector of activity. Firms in Estonia are asked only about their primary sector of activity. This implies that, if a firm reports a particular industry/product code in 1 year and a different code in the next, it has changed its main sector of activity.

Switch 4d,it+1 :

Dummy variable, equal to 1 in period t if the firm changes four-digit NACE products in period t+1. A product switch is defined as a change in the firm’s main product line.

Age it :

Age of the firm in period t, defined as the number of years the firm has been in the registry (using the registry entry date).

Size it :

Firm size, measured by the number of employees in period t.

Wage it :

Average real labour costs, defined as total firm-level labour costs divided by the number of employees.

Capital it :

Capital intensity, measured as real capital per employee. Capital is defined as the sum of tangible and intangible assets, net of goodwill at the firm level.

TFP it :

Total factor productivity at the firm level, estimated at the two-digit industry level using the methodology of Levinsohn and Petrin (2003) while taking into account industry switches over time. For a detailed description of the methodology employed to estimate TFP using the current data set, we refer to Moreno Badia and Slootmaekers (2009).

Foreign it :

Foreign ownership dummy, equal to 1 if at least 50% of the firm’s shares are foreign owned.

1.2 Product-level variables

All product-level variables are defined at the four-digit NACE level.

Sunk jt :

Sunk costs variable, defined as the natural logarithm of the median of real sales in each particular four-digit industry j at time t.Footnote 13

Herf jt :

Herfindahl–Hirschman index for the domestic market, defined as the sum of squared market shares. Market shares are defined as firm-level real sales over product-level total real sales. It ranges from 0 to 1 as it moves from a very large amount of very small firms to a single monopolistic producer.

Imports jt :

Total imports of product j at time t, measured in Estonian krooni (EEK).

IIT jt :

Intra-industry trade variable, defined as the Grubel–Lloyd index, that is, \( \left\lfloor {1 - \left( {{{\left| {X_{jt} - M_{jt} } \right|} \mathord{\left/ {\vphantom {{\left| {X_{jt} - M_{jt} } \right|} {\left( {X_{jt} + M_{jt} } \right)}}} \right. \kern-\nulldelimiterspace} {\left( {X_{jt} + M_{jt} } \right)}}} \right)} \right\rfloor \), where X jt and M jt are respectively exports and imports of product j at time t.

CA jt :

Revealed comparative advantage dummy, equal to 1 if X jt  > M jt , i.e. if exports are larger than imports for product j at time t.

Exports jt :

Total exports of product j at time t, measured in Estonian krooni (EEK).

Herfex jt :

The Herfindahl–Hirschman index for the export market is calculated at the Harmonized System (HS) six-digit level. Conversion to NACE Rev. 1.1. at the four-digit level is achieved using a concordance table provided by Eurostat. We define a market as a pair consisting of a geographic destination and a product. We calculate the index of concentration in market m as.

$$ H_{m,t}^{j} = \sum\limits_{\forall Exporter} {s_{n,t}^{2} }, $$

where \( \mathop s\nolimits_{n,t}, \) is the market share of exporter n in market m at period t. Aggregating across all export markets for product j we obtain the overall index of market concentration for exports of product j:

$$ Herfex_{jt} = \sum\limits_{\forall m} {H_{m,t}^{j} *\beta_{m,t}^{j} } $$

where \( \mathop \beta \nolimits_{m,t}^{j} \) is the share of market m in total exports of product j in period t.

UVR jt :

Average relative unit values index for Estonian export products, taking into account Estonia’s main competitors. In particular, we compute the unit value for product j in market p by dividing the export value of each exporter by the export quantity. Relative unit values for product j in market p are then calculated dividing the unit value of Estonia by the weighted average of the unit values of its competitors in that market. The overall relative unit value for product j is the weighted sum of the relative unit values across all markets, with weights equal to export shares.

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Miranda, V., Moreno Badia, M. & Van Beveren, I. Globalization drives strategic product switching. Rev World Econ 148, 45–72 (2012). https://doi.org/10.1007/s10290-011-0114-x

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