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

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

FOODIMA 5rd meeting

November 25th, 2008

Prague

2Warwick Business School

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 1983-2007Country contribution to domestic/inwards/outwards mergers in the EU food industry during 1983-2007Merger Types along the food industry in the EUData on merger activity at sector level


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-sectorsMerger activity in food wholesaling is dispersed more widely and equally among the sub-sectors


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.


D2.2 An empirical evaluation of M&A waves observed throughout EUFindings

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


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

D2.5 An Empirical Assessment of the Driving Forces of M&A Activity in the Food Supply

Chain : the Case of the UK and Greece

Some Preliminary Results


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 timeMacroeconomic 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


Valuation dispersion of firms and merger activity

The relation between relative valuation of firms and mergers is open to two interpretations:

1) 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


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.

of M/B associated of M/B associated

with growth opportunitieswith misvaluation

( )

partpart

m fm b f b


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

ita

firm specific sector specific long run value to bookvalue component value component component

/ / / /it it jt it jt it j it j itit itb m f f f f bm

/it jtf

/it jf


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

1

value value term value of firm i at time t of firm i at time tattributed to all book equity

firms on averagein sectorj at time t

it ojt jt it it

market book errormarket increamental

m a b

1ˆ ˆ/ lnit jt ojt jt it

f a B

1/ lnit j oj j itf a a a B


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


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

, expi o th t X h t X


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 valuation dispersion (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


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 exchangeacquisition of an independent firm50% or higher change of ownership

Data are sourced by Thompson ONE Banker and Datastream

UK sample size Greek sample size495 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 merged40% of food firms are being merged)


Results (1): the case of the UK Dependent Variable Weibull model Log-Logistic model

Hazard rate

Coefficient Independent Variables

βο constant -5.10 (9.82***) 3.09 (12.33***)

a shape parameter 1.59 0.59

λ1 Growth VD 0.59 (1.15) 0.65 (1.12)

λ2 Firm Specific VD 0.21 (4.28***) 0.22 (5.13***)

λ3 Sector Specific VD 0.52 (1.94**) 0.59 (1.99**)

λ4 GDP 0.01 (3.23***) 0.01 (2.26***)

λ5 Sector Concentration 0.03 (1.66**) 0.02 (1.71**)

Pseudo-R-squared 0.28 0.29

Log - Likelihood -364.11 -365.86

Number of observations 8910 8910


Results (2): the case of Greece Dependent Variable Weibull model Log-Logistic model

Hazard rate

Coefficient Independent Variables

βο constant -3.10 (9.82***) 2.09 (12.33***)

a shape parameter 1.29 0.55

λ1 Growth VD 0.03 (1.09) 0.04 (1.12)

λ2 Firm Specific VD 0.97 (2.56***) 0.92 (2.60***)

λ3 Sector Specific VD 0.42 (1.28*) 0.40 (1.28*)

λ4 GDP 0.01 (1.16) 0.01 (1.19)

λ5 Sector Concentration 0.32 (1.28*) 0.34 (1.38*)

Pseudo-R-squared 0.25 0.26

Log - Likelihood -214.11 -215.86

Number of observations 2277 2277


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 industryMisvaluation 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 ratesGrowth opportunities of firms seem not to play a significant role on merger rates within the food industry in both countriesMacro determinants have a small effect on merger rates as regards the UK while no such effect is found in the case of GreeceSector 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


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

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

Documents

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