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Measuring market power

Measuring market power. Lecture 32 Economics of Food Markets Alan Matthews. Lecture objectives. What methods can economists use to measure market power in the food industry? What is the evidence on the use/abuse of market power from empirical studies?. Readings. Processor power

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Measuring market power

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  1. Measuring market power Lecture 32 Economics of Food Markets Alan Matthews

  2. Lecture objectives • What methods can economists use to measure market power in the food industry? • What is the evidence on the use/abuse of market power from empirical studies?

  3. Readings • Processor power • US Senate and Tweeten response • Retail buyer power • Dobson, UK Competition Commission • Empirical studies • Bunte, London Economics

  4. A priori stylised facts • Growing concentration upstream and downstream of farmers • Farmers’ share of consumer spending is falling • Farm-retail price spreads are widening, suggesting farmers are being squeezed • When farm prices fall, retail prices rarely follow, suggesting profit-taking by oligopolistic firms

  5. Farmers’ share of consumers’ spending • Can be measured in various ways: • The marketing bill: • the difference between consumer expenditure on food (excluding imports, beverages and seafood) and the farm value. • Reflects changes in price, product quantity, product mix and the quantity of marketing services. • The market basket approach: • measures the changing cost of a fixed basket of groceries • Cost changes solely the result of changes in prices

  6. Farmers’ share of the consumers’ euro • Farm-retail price spread • Used for measuring farm share of individual products • Must be measured in equivalent units • Example • For steers, 2.5 kg of live weight yield 1 kg of retail beef cuts • 2000 retail beef price = €8.40/kg average all cuts • 2000 steer price = €1.20/kg live weight • 2000 farm-retail price spread = €5.40/kg retail cut (= 8.40 – 2.5*1.20) • However measured, evidence that farmers’ share is falling over time

  7. Evolution of Danish farm retail price spreads (Source: Baker 2003)

  8. Interpreting changes in the farmers’ share • Is a large farm-retail price spread necessarily bad? • Shift in consumption patterns towards food with higher value added and more food eaten-away-from-home (marketing bill) • Factor productivity increases more rapidly in agriculture than in manufacturing, let alone services • Could be due to growing market power • Latter suspicion fuelled when reductions in farm prices are not passed through in lower retail prices

  9. Real price of food is falling…. Source: Agri-Aware website

  10. …but Irish food prices remain high compared to other EU countries 2003 comparative price level indices for the main food sub-groups, EU25=100 Source: Eurostat

  11. Buyer power at retail level • Refers to the ability of leading retail firms to obtain from suppliers more favourable terms than those available to other buyers, or which would otherwise be expected under normal competitive conditions. • Extract discounts and obtain low prices • Onerous contractual obligations • Ability to shift financial risk to suppliers

  12. Sources of retail buyer power • Differences in relative economic dependency, determined by relative sizes of contracts and relative switching costs • Multi-faceted roles of retailers as they appear to suppliers (Dobson 2005) • Customers, competitors and suppliers

  13. Examples of retail buyer power • Depends on whether firms operate in a market or bargaining framework • Demand withholding • Adverse investment and innovation effects • The ‘waterbed’ effect • Supply chain practices

  14. Supermarket practices related to relations with suppliers Source: UK Competition Commission (2000)

  15. Measuring welfare loss of market power • Role of demand elasticity • What about the Posner rectangle A?

  16. Approaches to the empirical analysis of farm-retail price spreads • Structure-conduct-performance paradigm • New empirical industrial organisation • Time series price transmission studies

  17. Structure-conduct-performance studies • Examine the cross-industry or geographic (cross section) or time (time series) variation in prices, controlling for local market cost variations • Short review in London Economics Annex 5 • Market concentration measures – Cn measures, HHI index • Indicators of market power – price-cost markup (Lerner index), prices, margins, profitability • Many studies have found significant relationship between measures of market concentration and indicators of market power

  18. Empirical SCP studies • Market power generates consumer welfare losses… • ..but concentration may also have positive effects on firm efficiency • Vulnerable to critique that market concentration is correlated with profits because efficient (i.e. low cost) firms acquire greater market shares over time, not because of pricing power • Rely on reduced form models. Firm behaviour is not explicitly modelled and no statistical tests are performed

  19. New empirical industrial organisation models • Focus of this literature is on the conduct of firms within a particular industry • Based on structural oligopoly models by specifying the first-order conditions for the profit maximising behaviour of a single oligopolist • The key behavioural parameter in this approach is the conjectural variation of the oligopolist (usually designated as θ), which measures the degree to which a firm takes into account its rival’s reactions to its own output choice

  20. Supply of an oligopolistic firm Profits for firm j = total revenue less variable costs Demand function Total supply Conjectural variations elasticity = Percent change in total output for a 1% change in firm output First order condition. When θj = 0, reduces to the competitive outcome Θj/η = Lerner index for oligopoly power, represents the degree to which a firm can set output price above marginal cost Source: Appelbaum, 1982

  21. New empirical industrial organisation models • The expectation of a limited market response to a change in firm output (low θ) suggests market is competitive. • Expectation of an extensive market response suggests presence of market power (high θ) • Estimating the structural model allows the empirical data to provide information on the value of θ • Given the value of θ, the size of the market power mark up can be calculated.

  22. New empirical industrial organisation models • Weaknesses • The estimate of market power relies crucially on accurate estimates of the underlying market and cost conditions • Theoretically highly appealing, but complex to apply empirically and often requires simplifying assumptions

  23. Price transmission studies • Concern is that reductions in farm prices are not passed on to consumers in form of lower retail prices • Three issues • Prices changes are not fully transmitted • There is a time lag between the price adjustments at the respective stages • There is an asymmetry in reaction between positive and negative price shocks. • Imperfections in price transmission may be due to market power but can also be due to adjustment costs (relabelling prices, advertising, goodwill)

  24. Price transmission studies • Traditional regression methods (regressing retail price on farm price) ignore time series properties and give biased results • Co-integration methods are now preferred, which also allow for speed of adjustment and direction of causality to be inferred, as well as testing for asymmetric price responses

  25. London Economics case study • Uses a variety of approaches • Simple correlation analysis between changes in farm-retail price spreads and concentration ratios • Reduced form SCP model linking spreads to concentration, controlling for other factors • Four food products – wheat products, red meat, poultry, fruit and vegetables – drawn from nine countries

  26. Correlation coefficients are generally low, whether spreads are measured in absolute amounts or as a ratio of the two prices (relative spread) Highest correlation coefficient obtained for cereals of about 0.3 Source: London Economics 2004

  27. When changes in concentration are correlated with changes in spreads, in some cases the correlation is negative Correlation coefficients are sensitive to the time period chosen, but even when time period is divided, coefficients remain low Source: London Economics 2004

  28. Example London Economics SCP model • Purpose is to determine the influence of changing concentration ratios on the farm-retail price spread • Model is Spread = f(lagged spread, SCCOSTS, CSHARE, LIP, EXRATE, C5, Trend)

  29. Example London Economics SCP model

  30. Example London Economics SCP model • Concentration in the retail domestic market does not seem to have a significant impact on the evolution of spreads. • Confirms conclusions from correlation analysis

  31. The Marion et al study of monopsony power in US beef packing • Tries to determine influence of packer concentration on cattle prices and packer margins • Uses model P = f (B, S, PG, R, NSD) • Estimates using pooled cross section data from 13 regional markets for time period 1971-1986

  32. The Marion et al study of monopsony power in US beef packing

  33. The Marion et al study of monopsony power in US beef packing • Conclusions • Evidence that higher concentration is significantly related to lower cattle prices paid, other factors controlled for • Relationship is less clear during period 1979-86 when packer concentration was increasing sharply and there was excess capacity and considerable competition for supplies

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