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The Effects of Competition, Liquidity and Exports on Markups: Evidence from the UK Food and Beverages Sector

Abstract

This study investigates the pricing decisions of the UK food and beverages sector over 2007–2016. The markup model formulated by Hall (1988) and Roeger (1995) is employed where market power is expressed in terms of pricing decisions reflected by the difference between the price level and the marginal cost of production. The analysis is conducted under three steps: the first step estimates the markup ratio of the UK food and beverages sector over 2007–2016; the second step provides the price-cost margin of the 32 4 digit level NACE Rev.2 constituent industries over 2007–2016; and the last step tests the relationship between the cross-sectional estimates of market power and the structural effects of concentration, liquidity and exports over 2009, 2011, 2015 and 2016. The results suggest the presence of imperfect competitive conduct in the sector, while the three structural effects appear to have a significant influence on the pricing decisions of the UK food and beverages industries.

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Fig. 1

Notes

  1. 1.

    This period is very crucial to the UK economy as three major effects occurred: the global financial crisis in 2008, the implementation of austerity policies initiated in 2010 and the EU referendum that took place in 2016.

  2. 2.

    As intermediate inputs we refer to the goods and services used in the intermediate process to produce the final product. Raw materials, semi-finished goods and energy can be considered as some of those inputs.

  3. 3.

    Recent studies, such as Bellone et al. (2016) and De Loecker et al. (2016) also employ a similar methodology where the markup estimation depends on the elasticity of output with respect to inputs and the share of input expenditures on total value added.

  4. 4.

    An additional markup formulation employed by Braun and Raddatz (2016) calculates the price-cost margin as the rate of change between labour cost and total value added. Even if the value of intermediate inputs is included, this indicator lacks the growth dynamics of the Hall-Roeger approach and the inclusion of the user cost of capital.

  5. 5.

    Levinsohn (1993) and Harrison (1994) applied micro-level production data to the Hall model.

  6. 6.

    As Görg and Warzynski (2003, 2006) employed the Hall-Roeger approach, it would be useful to adopt the same methodology and compare the markup estimates in the UK food and beverages sector.

  7. 7.

    See Konings et al. (2005) and Feenstra and Weinstein (2010) for more information on the index formulation.

  8. 8.

    This indicator has been formulated according to the indications of Makaew and Maksimovic (2013).

  9. 9.

    However, the number of establishments may not reflect this particular outcome because concentrated sectors with a limited number of firms may own a significantly high number of establishments. For this reason, the establishments ratio is used as a measure of market concentration rather than a proxy of the number of firms (see Rezitis and Kalantzi 2011).

  10. 10.

    Net current assets are defined as the sum of trade debtors, bank and deposits, group loans (asset), directors’ loans, other debtors, prepayments, deferred taxation and investments. Current liabilities is the sum of trade creditors, short term loans, corporation tax, dividends, accruals and def. Inc., social securities and VAT, and other current liabilities.

  11. 11.

    Also see Braun and Raddatz (2016) on how liquidity constraints influence the price-cost margin.

  12. 12.

    It is expected that firms with higher liquidity ratio will tend to charge a higher price-cost margin as they can offset any loss in consumer demand with liquid assets (Lane 2012). However, if economic uncertainty prevails, the primary aim of firms could be their long-run sustainability and survival. For this reason, even firms with relatively high net current assets may tend to charge a lower price-cost margin in order to prevent any loss in consumer demand and thus, any loss in revenue.

  13. 13.

    The dataset includes firm-level balance sheets, profit and loss accounts and financial ratios of the constituent UK food and beverages firms.

  14. 14.

    The FAME database contains information of companies registered at Companies House in the UK and it covers company financials, corporate structures, information on shareholders and subsidiaries with up to 10 years of history. It includes 7 million companies across the UK, where 200,000 companies are in a summary format. However, given that only large companies are obliged to report to Companies House, information about turnover, assets and employment of medium and small firms may not be available.

  15. 15.

    In particular, the cost of sales includes the cost of materials and services employed in the production process, excluding any indirect expenses such as distribution costs.

  16. 16.

    An alternative specification of δ could refer to the firm-specific depreciation ratios calculated by the depreciation costs available in the FAME database (see Molnar and Bottini 2010).

  17. 17.

    See Tables 6 and 7 in appendix for the cross-sectional dependence, panel unit root and cointegration tests.

  18. 18.

    See Table 8 in appendix.

  19. 19.

    This outcome is consistent with several studies for various economies. Imperfect competitive conduct has been identified by Boyle (2004) in the Irish manufacturing industry; Dobbelaere (2004) in the Belgian manufacturing industry; Dobrinsky et al. (2004) in the Hungarian and Bulgarian manufacturing industries; and Wilhelmsson (2006) in the Swedish food and beverages sector.

  20. 20.

    Bellone et al. (2016) estimate a markup equivalent to 1.09 for the agro-food sector. This shows that even if the Hall-Roeger methodology disregards productivity shocks, competitive conduct in this sector is very intense.

  21. 21.

    De Loecker et al. (2016) provide evidence in favour of a more downward rigid behaviour reflected by the price level compared to marginal cost, thus increasing the price-cost margin.

  22. 22.

    Although the authors did not include the HHI in the final results, their findings point to the same outcome.

  23. 23.

    It is also worth mentioning that similar studies such as Pontuch (2011) and Braun and Raddatz (2016) find that industries with limited competition tend to charge a higher markup. However, limited competition is calculated as the average of the price-cost margin of an industry in a country, thus neglecting the role of concentration. For this reason, the HHI has been chosen over alternative indicators.

  24. 24.

    This indicator has been formulated according to Makaew and Maksimovic (2013).

  25. 25.

    This is similar to the leadership effect discussed by Olive (2008) under which profitable firms have the ability to pass cost increases on the selling price due to sufficient profit cushions.

  26. 26.

    A complementary behaviour to this process may refer to the acquisition of market share through lower price-cost margins. If a lower price level results in increased revenue due to additional demand, then firms might force their competitors to exit the market resulting in additional power and liquidity. Thereby, they will be able to hold more money as precaution to unforeseen circumstances (Rotemberg and Saloner 1986).

  27. 27.

    See Melitz and Ottaviano (2008) for an extended theoretical analysis capturing the relationship between exports and markup ratios.

  28. 28.

    Bernard et al. (2003) argued that more efficient producers face lower costs than their competitors allowing them to set higher markup ratios.

  29. 29.

    Also see Taymaz and Yılmaz (2015) for a similar analysis in the Turkish manufacturing industry using export intensity as well as import penetration ratios to capture their effect on the markups charged by the constituent sectors.

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Correspondence to Chrysovalantis Amountzias.

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This paper benefited from the comments of two anonymous reviewers. I am thankful to them and the responsibility for any errors lies with the author.

Appendix

Appendix

Table 5 Classification of industries according to NACE Rev.2 classification
Table 6 Pesaran’s cross-section dependence and panel unit root tests
Table 7 Westerlund’s (2008) cointegration test for the Hall-Roeger models
Table 8 Markup estimations under the GMM estimation technique.

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Amountzias, C. The Effects of Competition, Liquidity and Exports on Markups: Evidence from the UK Food and Beverages Sector. J Ind Compet Trade 18, 187–208 (2018). https://doi.org/10.1007/s10842-017-0260-5

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Keywords

  • Markup ratio
  • UK
  • Food and beverages sector
  • Concentration
  • Liquidity
  • Hall-Roeger approach

JEL Classifications

  • L16
  • L13
  • L66
  • D43
  • E31