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Brief Reference and Elaboration of D2.1 and D2.2

Brief Reference and Elaboration of D2.1 and D2.2. FOODIMA 5 rd meeting November 25th, 2008 Prague. D2.1 Report and database on the M&A activity during the last decades in the food supply chain. Results Literature review of theoretical approaches in analysing M&A activity

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Brief Reference and Elaboration of D2.1 and D2.2

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  1. Brief Reference and Elaboration of D2.1 and D2.2 FOODIMA 5rd meeting November 25th, 2008 Prague

  2. D2.1 Report and database on the M&A activity during the last decades in the food supply chain Results Literature review of theoretical approaches in analysing M&A activity Detailed database on the M&A activity: • Merger activity in the EU food industry during 1983-2007 • Country contribution to domestic/inwards/outwards mergers in the EU food industry during 1983-2007 • Merger Types along the food industry in the EU • Data on merger activity at sector level

  3. D2.1 Report and database on the M&A activity during the last decades in the food supply chain • Mergers in the food industry account for almost 20% of aggregate EU mergers • Eight countries (UK, Germany, France, Spain, Italy, Netherlands, Finland, and Denmark) account for 90% of domestic/cross border mergers in the EU food industry • Horizontal mergers correspond to 76% of all mergers of which 33% have occurred within the food manufacturing sector, 25% within the retailing sector, and 18% within the wholesaling sector. Conglomerate mergers account for 16% and vertical for 8% of total merger activity in the EU food industry At lower levels of aggregation: • Mergers of grocery stores account for 74% of total merger activity in retailing • In food manufacturing, 53% of total sector merger activity is concentrated in 8 sub-sectors • Merger activity in food wholesaling is dispersed more widely and equally among the sub-sectors

  4. D2.2 An empirical evaluation of M&A waves observed throughout EU • Formal investigation of EU food industry M&A waves; power, periodicity. Specifically, investigated countries are: Denmark, Finland, France, Germany, Italy, Netherlands, Spain, UK However, data on merger activity in Greece do not allow for formal investigation of merger waves • The synchronization over merger waves of the above different countries • The relation of each country merger waves with business or capital market cycles.

  5. D2.2 An empirical evaluation of M&A waves observed throughout EU Findings • All EU examined countries (except Netherlands) exhibit a regular merger cycle in the food industry • It is found that the duration of merger cycle in the food industry is 17 quarters (except that in the UK which has 7 quarters duration) • EU countries such as Germany and France, Finland and Denmark, and Italy and Spain exhibit similar cyclical pattern in merger activity in the food industry. • Merger activity in the UK, Denmark, and Germany is a leading indicator of mergers in the EU food industry • EU mergers in the food industry are partly determined by the business or capital market cycles

  6. D2.2 An empirical evaluation of M&A waves observed throughout EU Further elaboration • Historical analysis of M&A activity observed in the UK and Greece and in dairy, meat slaughtering and retailing sectors (descriptive statistics indicating the major effects on market structure and performance) • We further examined merger cycles at sector level and found that food manufacturing and retailing sectors exhibit cyclical fluctuations of short length which is different from country to country • We empirically investigated the dynamic relation of merging behaviour between food manufacturing and retailing sectors and found that merger activity in manufacturing can determine similar activity in retailing

  7. D2.5 An Empirical Assessment of the Driving Forces of M&A Activity in the Food Supply Chain : the Case of the UK and GreeceSome Preliminary Results

  8. Determinants of M&A activity in the food supply chain: the empirical model The constructed model incorporates three main factors affecting merger activity providing explanation of its time pattern • The structure of food industry through time • Macroeconomic factors (eg. business cycles) • Valuation dispersion of firms The model is estimated by using data from the UK and Greece However, before doing so the associated relation between valuation dispersion and merger activity is further investigated in order to identify the sources of this dispersion

  9. Valuation dispersion of firms and merger activity The relation between relative valuation of firms and mergers is open to two interpretations: • Under the neoclassical view, this fact is evidence that assets are being redeployed towards more productive uses. 2) Under a behavioural view, if financial markets value firm incorrectly (in the short run) or managers have information not held by the market this may result in increased merger activity due to overvaluation. We, thus, model the source of valuation in order to distinguish among these two different driving forces of merger activity

  10. Stage 1: The decomposition of market-to-book (M/B) value To explore valuation empirically, we decompose M/B into two parts (eg. Rhodes-Kropf et al. 2005) (1) Where m is market value, b is book value, and f is some measure of fundamental or true value If markets perfectly anticipate future growth opportunities and cash flows, the term m-f would always be equal to zero and the term f-b would be trivially equal to M/B at all times Furthermore, it is suggested that misvaluation of a firm could be firm specific or being shared by all firms in a given sector.

  11. Stage 1: The decomposition of market-to-book (M/B) value Estimating f involves expressing f as a linear function of firm-specific accounting information at a point in time, , and a vector of conditional accounting multiples, (2) Where represents firms specific accounting information at time t conditional on sector j and time t represents firms specific accounting information at time t conditional on sector j

  12. Stage 1: Estimating the pieces of the decomposition To generate estimates of f (.) we use fitted values from a simple accounting model linking market equity to book equity (3) Model 3 is estimated in ln for each sector –year which allows average market value of each sector and incremental book value to vary over time and across sectors Thus, using model 3 we have: And average over time for each set of parameters and calculate

  13. Stage 1: Results of stage 1 From stage 1 we get annual data on: • Firm specific valuation • Sector specific valuation • Growth specific (long run) valuation We further use this data to estimate the main model of interest

  14. Stage 2: estimation of the empirical model The hazard rate of mergers is given by Where, Xt is a vector of time dependent covariates ho(t) gives the relationship between the hazard rate for a firm with characteristics X(t) and the hazard rate for the case when X(t)=0, i.e. the ‘baseline’ hazard, and depends only on time

  15. Definition and measurement of explanatory variables Hypotheses Description / Measurement 1.Valuation dispersion due to growth Standard deviation of growth opportunities (λ1) specific valuation (obtained in stage 1) 2. Firm specific valuation dispersion (λ2) Standard deviation of firm specific valuation (obtained in stage 1) 3.Sector specific valuationdispersion (λ3) Standard deviation of firm specific valuation (obtained in stage 1) 4. Macro economic determinants (λ4) Real GDP as a proxy of the business cycle 5. Sectors’ structure (λ5) Market capitalization of the four largest firms in the sector as a proxy of sector concentration

  16. Sampling and data sources The sample is constructed as one in which the proportion of firms operating within the food supply chain is similar to the population proportion and also the proportion of food firms acquired is the same as the population proportion of food firms acquired in the UK and Greece over the period 1990-2007. In order to be considered, a merger has to meet the following criteria: • a UK (Greek) domestic merger (acquirer and acquired companies operate mainly in the UK (Greece)) • listing of both firms on the UK (Greek) stock exchange • acquisition of an independent firm • 50% or higher change of ownership Data are sourced by Thompson ONE Banker and Datastream UK sample sizeGreek sample size 495 firms 127 firms (of which 30% operate within (of which 26% operate within food supply food supply chain. Also, chain. Also, 40% of food firms are being merged 40% of food firms are being merged)

  17. Results (1): the case of the UK

  18. Results (2): the case of Greece

  19. Summary Findings of the empirical analysis suggest: • Firm specific and sector specific valuation dispersion have a positive and statistical significant effect on merger rates both in the UK and Greece which in turn implies that short run misvaluation (either in firm or sector level) is the driving force of mergers in the food industry • Misvaluation at the sector level seems to be more important in the UK while in Greece misvaluation at the firm level exhibits the highest influence on merger rates • Growth opportunities of firms seem not to play a significant role on merger rates within the food industry in both countries • Macro determinants have a small effect on merger rates as regards the UK while no such effect is found in the case of Greece • Sector concentration is found to have a significant effect on merger rates in both countries which in turn implies the existence of market power motives in the food industry mergers. Market power motives are more pronounced in Greece than in the UK However, conclusions on the relative magnitude of explanatory variables between Greece and the UK is only indicative. Further statistical analysis is being conducted to obtain robust comparative results

  20. Ongoing Research We further investigate the empirical models by incorporating • Firm specific performance indicators (productivity, innovative ability) • Level of overall stock prices (it is likely that valuation dispersion is higher during times of high overall stock prices than during times of low prices which in turn means that increases in overall prices may cause increases in merger activity) • Other measures of macro determinants (eg. interest rates) At the firm level, we are empirically model the probability of a firm in the food industry to be an acquirers or target in terms of the three components of valuation (implication of theoretical model) Finally, we will attempt to increase the sample size in the case of Greece by searching at alternative (accounting) data sources

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