Methodology
for assessing determinants of competitiveness of Czech,
Hungarian and Polish farms
(A version for the workshop on methodology and data collection,
Wye 22-27 January 2001)
Tomas Ratinger
Wye, 16 January, 2001
Table of contents
1
General context
1.1
Competitive advantage
1.2
Domestic resource cost and policy analysis matrix
11
1.3
Productivity and efficiency
19
2
3
Competitiveness of CEE farms in IDARA project
2.1
3
3
21
Phase 1 – costs and competitiveness indicators directly linked to structural and financial
characteristics of farms
22
2.2
Phase 2 Technical efficiency, total factor productivity and competitiveness
32
2.3
Phase 3 Completing study on overall farm competitiveness
35
References
37
2
1
General context
Competitiveness with respect to EU becomes one of the main concerns of CEECs.
Governments of these countries are aware that they need to identify areas where their
competitiveness rests, monitor the evolution of their competitiveness and draw policies
likely to strengthen competitiveness already before the accession.
1.1
Competitive advantage
There is a long history of efforts of economists to explain international success of nations
in particular industries. Adam Smith is credited with the notion of absolute advantage, in
which a nation exports goods in which is the world’s low cost leader. David Ricardo
introduced a refinement of this notion to that of comparative advantage. The nation 1 will
allocate resources to relatively more productive industries. In his theory, trade was based
on labour productivity differences between nations. These differences were attributed to
“environment” or “climate” of nations favoured some industries. Heckscher and Ohlin
shifted the focus from environment that favoured the productivity to factors (labour,
capital and natural resources) availability. Their theory supposes that all nations have
equivalent technology but differ in their endowments of factors. Nations gain factorbased comparative advantage in industries that make intensive use of abundant factors.
Heckscher-Ohlin theory not only contributed to explaining trade pattern but also provided
rationale for governmental policies to strengthen competitiveness. Governments have
wrongly or rightly implemented various policies like reduction of interest rates, efforts to
hold down wage costs, devaluation of currencies etc. in attempts to alter factor
advantages.
However, there has been growing awareness that the factor endowment approach does
not give sufficient explanation to actual trade patterns. The (H-O) theory cannot help to
explain why much of world trade takes place between advanced industrial nations with
the similar factor endowments or why there is a growing volume of trade in products with
1
more precisely, market forces
3
similar factor proportion. Trade between national subsidiaries of multinational firms left
out of the theory. Also some of the underlying assumptions can be questioned in some
industries: Porter (1990) questioned the absence of economies of scale, identical
technologies, undifferentiated products and fixed pool of national factors. However, these
are often considered as typical characteristics of agricultural production2.
Porter in his book Competitive advantage of nations (1990) claims a change of paradigm;
he argues that recent decades have been characterised not only by rapidly changing
technologies, but by their varieties and degrees of employment in firms and industries;
advanced nations tend to broadly similar endowment of factors and competition has
internationalised: “Firms compete with truly global strategies involving selling
worldwide, sourcing components and materials worldwide, and locating activities in
many nations to take advantage of low cost factors.” (Porter, 1990, pp.14) Globalisation
has caused both – decoupling firms from the factor endowment of a single nation and
making factor endowment unfixed3.
Porter considers (national) productivity4 to be the only meaningful concept of
competitiveness (at national level). He argues that once Ricardo was on the right track as
well as later technology gap theories, but they have left unanswered the question why
does productivity differences or technology gap emerge? Porter observed (what he calls a
paradox) that despite globalisation leaders in particular industries tended to be
concentrated in a few nations and sustained competitive advantage for a long time. He
accounted it to national conditions – firms’ home base. According to Porter (1990)
international success in a particular industry lies in four broad attributes of the industry
and its environment (home base):
1. the nation position in factors of productions;
2
economy of scale is offset by high transaction costs to control labour; agricultural products are often
undifferentiated – cereals, live animals, milk; agricultural technologies (genetic material, fertilisers and
chemicals, machinery and equipment) in developed or semi-developed (middle income) countries are
available at pretty similar cost
3
e.g. capital mobility
4
Productivity is the value of output produced by a unit of labour or capital (Porter, 1990, pp. 6)
4
2. the nature of home demand for the industry’s product
3. the competitiveness of related and supporting industries
4. the conditions governing how the industry is organised and nature of domestic
rivalry.
“The determinants, individually and as a system, create the context in which a nation’s
firms are born and compete: the availability of resources and skills necessary for
competitive advantage in an industry, the information that shapes what opportunities are
perceived and the directions in which resources and skills are deployed; the goals of
owners, managers and employees that are involved in or carry out the competition; and
most importantly the pressures on firms to invest and innovate.” (Porter, 1990)
Figure 1 National diamond
Firm strategy, structure
and rivalry
Factor
Demand
conditions
conditions
Related and supporting
industries
Source: Porter (1990), pp 72.
In Porter’s view, the basic element in competitiveness assessment is a firm which gains,
sustains or looses competitive advantage. The national competitive advantage is a set of
conditions (the environment) favouring firms’ innovative behaviour and their seeking for
new market segments, and encouraging new entrants in the industry.
5
1.1.1
Factor conditions
Factors of production are inputs necessary to produce and compete in any industry like
labour, capital, land, natural resources etc. The standard theory of trade rests on factors of
production. According to the theory nations are endowed with different stocks of factors.
However, Porter argues that the understanding of factors should be broaden. The factors
important to competitive advantage are not only inherited, but are created within the
nation. Inherited (basic) factors include physical resources, unskilled and semiskilled
labour and debt capital. Created (advanced) factors include modern communication
infrastructure, highly educated labour, knowledge resources etc. The stock is generally
less important than the rate at which the factors are created.
Table 1 Factors of production
Factor group
Human resources
Physical resources
Knowledge resources
Capital resources
Infrastructure
Coverage
land, water, mineral deposit,
timber deposit, climatic conditions
scientific, technical, market
knowledge
Characteristics
the quantity, skill, cost
the abundance, quality, accessibility
the number and quality of
universities, research institutes,
business and scientific literature,
government statistical agencies
the amount (saving rates, capital
inflow) and cost
forms of resources (e.g. risk
characteristics) and forms of
deployment
the transportation system,
the type, quality and user costs
communication systems,
payments or funds transfer, health
care etc.
Source: Porter, 1990, pp.74-75
Competitive advantage of firms results from efficient and effective deployment of the
factors. How and where factors are translated to international success depends on the
other determinants in the diamond.
1.1.2
Demand conditions
The characteristics of domestic demand shape firms’ perception and respond to buyers
needs. One might think that domestic demand will lose importance when competition is
internationalised5. However, there are arguments why this is not true. First, attention to
5
meant as globalisation
6
nearby needs is the most sensitive and understanding them is least costly. Second, firms
tend to feel more confident in domestic markets.
Box 1 An example – Organic production
Health safety and environmentally appropriate way of production has become important concern
of western food consumers. Existing demand for organic products gives advantage to EU farmers
comparing to their CEE neighbours where the demand for organic products is negligible. Czech,
Hungarian or Polish farmers, who want to enter the organic product business because they
learned about changing trends (and hence, future markets) in the EU, can hardly anticipate in
which directions or segments the concern of consumers has been moving. Obviously, the time
lag of getting this information from the EU consumers let them behind the EU farmers.
Also size and growth of domestic demand play an important role. Large home market can
lead to competitive advantage in industries where there are economies of scale or
learning. Large markets or rapidly growing markets encourage firms to invest in largescale facilities, technology development and productivity improvements, mainly, because
it reduces risk.
Large home demand will not favour the competitive position of firms if it is for segments
too nationally specific. It can be a case of many food products which are designed for
nation specific tastes or rites.
Box 2 An example – Czech beer
Czech beer consumption per capita is one of the largest in the world. Even the nation is relatively
small the beer market is large. Also Czech beer is appreciated by tourists who increase the
market significantly. High inflow of FDI illustrates how attractive the industry was considered
during the transition. However, Czech beer brewers have experienced difficulties to expand their
markets abroad. The explanation rests in a specific taste which goes well with the Czech cuisine,
but becomes almost disadvantage elsewhere.
1.1.3
Related and supporting industries
The presence of internationally competitive supplier and related industries favour
competitiveness of the industry in question (e.g. agriculture, branches of food industry,
7
etc.). The ways by which competitive advantage in downstream and upstream industries
benefit the other industries are pretty similar.
The first is efficient, early, rapid and perhaps preferential access to the most cost effective
inputs. However, the access is not necessary the most significant benefit. More
significant is the advantage that home based suppliers provide in terms of co-ordination.
Probably, even more vital benefit is in the process of innovation. Suppliers help firms
perceive new methods and opportunities to apply new technologies.
Box 3 Agricultural input markets in the Czech Republic
Matthews et al.(1999) reported in their final document to the FAO/TCP project on competitiveness
that supply of agricultural inputs and machinery is sufficient and the input markets are
competitive. Consequently, they concluded that there are not serious impediments to
competitiveness on the side of agricultural inputs. In the context what we introduced above,
however, the fact that the most chemicals and powerful and sophisticated machinery has no
domestic origin may question their conclusions. Even more, it helps to explain why Czech farmers
have been catching up slower than it was expected shortly after political changes..
Related industries are not only downstream industries, but also those which involve
products that are complementary. The benefit from the presence of an internationally
successful related industry is obvious. It provides opportunities for information flow and
technical interchange and stimulate innovation.
1.1.4
Firm strategy, structure, and rivalry
The way firms are organised is influenced by national circumstances. There is no
uniformity across all firms, however, there are often obvious national features. Some
nations succeeded to compete in internationalised environment6 with very individualised
small and medium scale firms other nations are leaders in industries dominated by large
companies with technocratic top management and hierarchical organisation. Important
areas of managerial practices are training, background and orientation of leaders, group
versus hierarchical style, individual initiative, way of decision making, the nature of
relationship with customers, attitude toward international activities, and relationship
6
globalisation
8
between labour and management. The differences of managerial approaches and
organisational skill create advantages in competing in different types of industries and
across nations (Porter, 1990, pp109).
The institutional environment and competencies which are deeply embedded in education
systems, social and religious history, family structures and many other unique national
conditions favour some organisation structures and management approaches.
Company goals are very much determined by ownership structure and motivation of
owners and debt holders as well as by the nature of company governance. The goals of
publicly held corporations (relevant to food processors) reflect the characteristics of the
nations public capital market.
Box 4 Who does determine goals of public corporations in CEECs
Do senior managers pay more attention to the board of directors or to share prices? Capital
markets are much less developed in CEE and share prices of many companies have been falling
since privatisation. The management of such companies has not felt under pressure, since the
take over is unlikely to happen, because of weakness of domestic investors. But the
responsiveness to the board of directors is not better. Neither domestic investment funds nor
domestic banks have always succeeded to form effective counterparts to top managers of
corporations. Unless foreign investors were involved in privatisation the company goals have
been dominated by personal goals of managers who have often plundered companies and lead
them to bankruptcy ( …).
In agriculture and food industry private companies play very important role. They have
usually long time horizon and are intensively committed to the industry. Often pride and
desire to provide continuity (e.g. family farms) are important factors.
Box 5 Goals in restitution of a farm
In the survey conducted by Jurica and Doucha (1998) family farmers often reported that the
desire to renew the parent farm was an important factor for deciding to withdraw land and
agricultural assets from cooperatives and state farms and to start their own farming business.
Particular in transitional countries the nature of involvement of debt holders in formatting
firm or farm goals is essential. During restitution, privatisation and restructuring firms
collected large amount of debts. Generally, the involvement of debt holders in decision
9
making by acquiring also a significant equity stake should turn the attention of creditors
to long term company health instead of short term cash flow. However, in many case it
has led to disaster hitting the financial sector seriously.
Box 6 Involvement of debt holders
Either directly or though their sister investment funds Czech banks has been involved in
governing quite a lot corporations since privatisation. Recently, there was criticism to this
because instead of improving the governance of companies it resulted in blindness of banks to
their mismanagement. In the effect, Czech banks carry high proportion of bad loans. The audit of
the failed bank IPB (in June 2000) shown that three quarters of the bank loan portfolio was not
performing (MF, 2001, PBJ, 2001)
While the above is relatively common in food industry, it is impossible or unlikely that
banks or other creditors will hold a proportion of the (even corporate) farm equity. Rather
the opposite can happen that debt holders are discouraged or restricted to exercise their
rights. Then it is possible that deeply indebted farms have stayed in the business for a
decade. Such phenomena disfavours sector competitiveness.
Box 7 Structure of debts of Czech farms
Czech Individual farms exhibit relatively low share of loan capital on the net worth 20% in 1998;
the figures for co-operatives and farming companies are dramatically higher 150% and 77%
respectively. The liabilities of individual farms consist of 66 percent of bank credits and 34%
mainly current liabilities. The first structural difference in indebtedness of individual and corporate
(coops and companies) farms rest in 55 percent share of current liabilities on total liabilities.
Second, the share of bank credits on total liabilities is low just 21%. But there is about 23% of
other deferred liabilities, namely outstanding privatisation debts – either compensations to nonfarming owners of land and assets or repayments of privatised assets to the state. The
compensations to non-farming owners was delayed for seven years to 2000 and since that the
government has sought the way how to help farms carrying these debts to avoid paying them
back. Similarly, the government treated quite softly those who failed to repay the acquired state
assets.
Finally, Porter emphasises the role of domestic rivalry as again stimulating innovation
and efficiency. Again, the argumentation stresses the threat of domestic competitors is
perceived by firms as more serious and valid.
10
1.2
Domestic resource cost and policy analysis matrix
Domestic resource cost coefficient (DRC) enjoyed great popularity in assessing
competitiveness of agricultural sectors in CEE countries. DRC is a ratio of social costs of
factors and the net foreign exchange earned or saved by producing the good domestically
(Tsakok, 1990, pp. 119). In other words, it is a ratio of opportunity earnings to “true”
sector earnings. For this property DRC is considered as an indicator of comparative
advantage. With its concentration on factor (resource) costs DRC refers to HeckscherOhlin notion of competitiveness. If we assume the identical technology also out of the
country and undistorted world markets than DRC values domestic factors (resources)
against factor costs in competing nations.
However, it was not competitiveness but protection which originally concerned trade
economists. Technically, DRC and effective protection coefficient (EPC) are both ratios
of domestic value added to value added available at border prices; the domestic value
added in EPC is expressed at market prices. DRC and EPC both can be incorporated in a
consistent accounting framework – the policy analysis matrix.
Table 2. Policy analysis matrix
Revenue
Tradable Input
Costs
Domestic Factor
Costs
Profits
Financial Prices
A
B
C
D
Economic,(social,
opportunity)
Prices
Net Transfer
E
F
G
H
I=A-E
J=F-B
K=G-C
L
Source: Matthews et al., 1999, Vol. 4
The policy analysis matrix (Monke and Pearson, 1989) is based on two simple accounting
identities, namely:
1. Profit = Revenue – Costs
11
2. Transfers=Financial values – Economic values
In order to construct the PAM, costs are further broken down into tradable inputs and
non-tradable inputs called domestic resources or factors. Profits, revenue and the two
types of costs are then calculated using both actual prices (referred to in the PAM as
financial or private (market) prices since they are the prices actually faced by private
agents) and economic or social prices (designed to measure the opportunity cost to the
economy of using a resource or the scarcity value to the economy of producing the
commodity). The differences between the private and social sets of prices are referred to
as transfers.7 The size of these transfers reflects the extent to which actual prices diverge
from social prices. The general structure of the PAM is shown in Table 2.
1.2.1
Interpreting the PAM
The PAM matrix gives three absolute measures:
Financial profit (D = A - B - C) represents the net income of the farmer when revenue
and inputs are evaluated at actual market prices. Coupled direct payments, if relevant, are
added to revenue and subsidies and direct taxes are included in input costs. The fact that
the PAM budgets include returns to domestic factors of production (land, labour and
capital) is relevant to the interpretation of financial profitability. Zero private profits
means zero ‘excess‘ profit. At this breakeven point capital, land and labour will still be
receiving normal returns. A non-negative value of financial profit indicates that the
producer is competitive at the market conditions he faces.
Economic profit (or Net Economic Benefit NEB, H = E - F – G) illustrates the benefit to
the economy from producing the given commodity. The revenue and costs are evaluated
at social (economic) costs. The calculation of economic profitability can be broken down
into two steps: first, getting the value added in border prices, which indicates the net
7
In calculating government interventions, it is assumed that divergences between market and social prices
in the PAM are due solely to government policies. In principle, divergences could also arise because of
market imperfections due to, for example, the exercise of market power in product or factor markets. An
important issue in the Czech Republic is the treatment of processing margins which is discussed in more
detail below.
12
earnings (or net savings) of foreign exchange given foreign trade opportunities; second,
reducing the value added by the cost of the non-tradable factors in terms of alternatives
forgone. Zero economic profit suggests that the activity is only just efficient in terms of
its foreign exchange earning capacity.
Net transfer (L = I + J + K) is an overall measure of the difference between financial
(private) and economic (social) valuations of revenues and costs. The actual content and
interpretation of this measure depend on for what economic prices correct. If economic
prices corrected only for the effects of distorting policies then this measure would be a
net transfer of policies. However, economic prices usually correct for both policies and
market imperfections (particularly, border prices of tradable inputs or products). Hence,
net transfer measure implicitly includes effects of market failures and effects of efficient
policies. For this case Monke and Pearson (1989) suggest adding three rows for
separating effects of market failures, distorting policies and efficient policies.
Alternatively, a number of useful competitiveness and policy indicators can be derived
from the PAM. Incentives are measured relative to foreign markets by protection
coefficients, while efficiency is illustrated either by the relative private profit evaluated at
actual (financial) prices (PPR) or by the domestic resource cost coefficient evaluated at
social opportunity prices (DRC) and by the social cost benefit ratio (SCB).
Table 3. Economic indicators derived from the PAM
NPC:
EPC:
DRC:
SCB:
PPR:
PCAC:
SCAC:
Nominal protection coefficient
Effective protection coefficient
Domestic resource cost
Social cost benefit ratio
Private profitability ratio
Private Cost adjustment coefficient
Social Cost adjustment coefficient
[A/E]-1
[(A-B)/(E-F)]-1
G/(E-F)
(F+G)/E
(A-B-C)/A
A/(B+C)-1
E/(F+G)-1
Competitiveness Indicators
Non-negative values of the private profitability ratio (PPR) indicate that there is a market
incentive for producers to expand production at current market prices for output and
inputs. Negative values of the PPR indicate that producers have an incentive to reduce
production at these market prices. A negative PPR does not imply that a farm must go
bankrupt immediately as it can continue in business if it is able to pay some production
13
factors (particularly family-owned labour, land or capital) less than the market price.
However, in the long run, unless a farm type can adequately compete for these factors
with other economic activities, then it will not survive. Thus private profitability ratio is
regarded as an important indicator of domestic competitiveness if linked to producers
(groups of producers).
The Domestic Resource Cost ratio is usually presented in the form
n
DRC 
i
a P
ij
j  k 1
D
j
k
P  a P
B
i
j 1
ij
B
j
with
aij
quantity of the j-th traded (if jk) or non-traded (if j>k) input (j = 1, 2, ..., n) used to produce one
unit of output i;
D
P
B
j
social price of non-traded input j,
j
border price of traded input j.
P
i
border price of output i,
B
P
The DRC is a proxy for social profitability; i.e. it reflects the ratio by which the economic
value of non-tradable inputs used in production of the good considered exceeds (if >1) or
is below (if <1) international value added. The latter is that amount of foreign exchange
which would have to be paid if the good were purchased from abroad.
The Social Cost Benefit ratio (SCB) is the ratio of domestic factor costs evaluated at
economic (border) prices to total revenue also evaluated at economic (border) prices. The
SCB and DRC are strongly related. This is seen if the following definitions using the
NEB (a measure of social profitability, see above) are compared:
SCB = 1 – ( NEB / E )
DRC = 1 – ( NEB / (E – F) )
The SCB offers a correct ranking of alternatives of production with regard to increasing
social benefit; the higher the ranking the stronger the impact on social profitability. The
DRC does not have the same consistency in ranking.
14
1.2.2
Economic (social) prices
There are two critical inputs for being able to construct the PAM; economic (social)
prices and technical coefficients. In the both cases, there is not only a technical problem
to obtain them but conceptual problems as well.
The opportunity cost of a tradable commodity is its border price – the price of an export
or import converted into domestic currency at a given exchange rate. Tsakok, (1990)
argues that the relevance of border prices as efficiency benchmark is not dependent on
the competitiveness of international markets. In spite of being a result of dumping or
some other form of market power, they represent what the country would have to pay or
would receive if trading internationally. The important consideration is whether border
prices are likely to prevail during the period of interest to policy makers. However, this
position is fully relevant only when measuring protection. If border (world market) prices
are largely distorted the essence that DRC measures advantage of nation factor costs
relatively to factor costs in competing nations vanishes8. Alternatively, Tsakok proposes
to use foreign market prices in the DRC calculations. A difficulty might arise to obtain all
respective input prices.
Box 8 DRC calculations relatively to EU markets
Ratinger (1999) used EU prices when calculating DRC for Czech wheat, barley, milk, beef and
pork. The EU policy prices were applied to outputs and feed costs were adjusted to the higher
cereal price level in the EU accordingly. The other tradable costs were considered unaffected by
the access to the EU markets9.
Similarly, EU prices were used for assessing competitive position of Hungarian agriculture.
(Moelman et al, 2000)
Often there are off farm costs included in benchmark prices (border or foreign market
prices) associated with transport, processing and marketing of products. These costs must
be either added to farm costs or the benchmark prices have to be reduced. Referring to
8
Obviously, the social prices of factors might be questioned from the same position.
9
it will be discussed later
15
what we stressed in 1.1. efficiency of up and down stream industries (i.e. processing
margins, transport and marketing costs) can be critical for assessing competitiveness of
primary producers.
Valuing factors at their social costs refers to what the economy forgoes because they are
used in the production of a given commodity. In turn, it means that the social (economic)
cost of a non-tradable primary factor is given by its marginal product in its next best
alternative use. As far as it is a straightforward definition its realisation can be quite
puzzling as illustrated in
Box 9 Economic values of primary factors - CR
Labour: Despite some regulations, the Czech labour market is assumed to be competitive. The
average wage rate of non-agricultural labour could be taken as a relevant economic cost of
agricultural labour. However, there may be quite a high transaction cost for a farmer to get
(accept) an alternative job which, in fact, offsets its advantage.
Land: Although around 80 percent of the total agricultural land is leased (rented), the land leasing
market is underdeveloped. Most of the contracts are based on the low administrative price of land
and originate in the sector privatisation in early 1990s. High transaction costs associated with
surveying and negotiating access to plots hamper enforcement of property rights and market
transactions. Therefore, one can argue that the rental rate should be considered under-valued.
However, a more important factor in determining the rental rate is the abundance of land for
leasing (at least three quarters of private owners have no interest in farming and around 700
thousand hectares of state land have been offered for leasing, Ratinger, 1997). The reduction in
agricultural production also demands less inputs including land. In the end, the applied rent might
be assumed not to diverge from its social value.
Fixed capital: The tradable element (machinery) of depreciation is adjusted to zero tariffs, while
the value of the non-tradable component (buildings) is assumed not to be biased from its social
value since there have been no specific policies for agricultural investment goods since 1990.
The opportunity cost of agricultural capital is calculated a long-term basis. The value foregone by
using capital in agricultural production is represented by the (real 10) interest on total fixed assets
(of course associated with a particular production) evaluated at the interest rate of government
bonds for 1997
10
GDP deflator is always used when costs and prices have to be given in real terms.
16
Matthews et al. (1999) Vol. 4
From the opportunity cost concept, the equilibrium exchange rate would be a correct
coefficient for converting border (foreign market) prices to national currencies in PAM
calculations (Tsakok, 1992). If the current exchange rate is distorted (being far from its
equilibrium), it is necessary to adjust it for under-valuation or over-valuation. However,
having no solid base for considering Czech, Hungarian and Polish exchange rates
distorted we are going to use current exchange rates.
1.2.3
Technical coefficients
Rather then technical coefficients researchers used respective cost items from farm book
keeping for the assessment of agricultural competitiveness in CEE countries. This was
first of all dictated by the availability of data. Bojnec (1998) used the estimates of
technical coefficients from the Slovene Advisory Service, but in many other CEE
countries either such a source did not exist or there were doubts how well they represent
actually applied technology.
Box 10 Technical coefficients for fertilisers – Czech republic
Czech Research Institute for Crop Production would provide technical coefficients for fertilisers
twice higher than they were actually applied over the recent 5 years. (Matthews at al. 1999, Vol.
4)
The problem with cost data from farm book keeping is that many of items are usually not
allocated to individual products. This is less dramatic if farms are specialised but on
typical Czech or Hungarian mixed production farms it requires a caution handling.
Box 11 Common costs
Overheads are typically a common cost and to individual products are usually allocated according
to gross margin. However, a lot of labour and capital costs might be hidden in overheads. First,
these costs have to be separated from overheads and add to already assigned labour and capital
costs to products. Then pure overheads can be allocated.
17
Technical coefficients are supposed to be independent on prices. This might be
particularly unrealistic assumption if financial (private) and economic (opportunity)
prices diverge substantially.
In many studies technical coefficients or costs refer to an “average” domestic technology,
which is also assumed to be the prevailing technology. However, it can be shown that the
costs vary substantially (e.g. in Matthews et al., 1999, Vol.2.). It is likely that there are
some competitive farms (even a large proportion) when DRC calculated on “average”
costs (technical coefficients) is larger than 1 and opposite.
Box 12 Cost variability - CR
Recognizing cost variability particularly due to different deployment of labour and capital by
different farm types Matthews et al. (1999, Vol. 4) calculated 4 policy analysis matrices (for small
and large individual farms and for cooperatives and farming companies). However, the
differences in results were less pronounced than it was expected while costs varied still
substantially within the farm type groups. It suggests that cost differences have to be assessed
against also other farm characteristics.
1.2.4
Appendix
The Private Profitability Adjustment Coefficient is defined as the ratio of revenue to costs at
market prices minus 1. The coefficient gives the degree of adjustment required, or the degree of
flexibility allowed, at prevailing prices and costs respectively.
The Social Cost Adjustment Coefficient is defined as the ratio of revenue to costs at social prices
minus 1. The coefficient gives the degree of adjustment required, or the degree of flexibility
allowed, at prevailing prices and costs respectively.
The Effective Protection Coefficient is defined as follows:
k
P  a P
D
EPC

i
i
j 1
k
D
ij
Pi  aij P j
B
j
1
B
j 1
with
aij
quantity of the j-th traded (if jk) or non-traded (if j>k) input (j = 1, 2, ..., n) used to
produce one unit of output i;
18
D
P
D
i
domestic price of output i,
i
border price of output i, P
B
P
P
j
domestic price of input j,
B
j
border price of input j.
The EPC can be interpreted as the rate by which value added evaluated at financial prices
(domestic value added) exceeds (if >0) or is below (if<0) value added evaluated at economic
prices (international value added). Notice that non-tradable inputs include besides primary
factors also non-traded intermediate inputs like, e.g., domestically grown seeds. In addition, many
of the ‘tradable’ inputs contain some components of non-tradable ones.
1.3
Productivity and efficiency
As we emphasised in 1.1.1 competitive advantage of firms or farms results from efficient
deployment of factors. Usually, three concepts of efficiency are used: technical
efficiency, allocative efficiency and social efficiency. Technical efficiency refers to
technical relationships between inputs and output; allocative efficiency refers to
positioning of inputs and outputs (according to input and output price relationships; social
efficiency refers to Pareto optimal state.
By adopting opportunity cost concept for calculating DRC and SCB we consider them as
indicators of social efficiency. DRC or SCB below 1 indicate that it is beneficial for the
nation to move resources to the industry, because rearranging outputs will generate
additional welfare.
In the paragraph 1.2.3 we mentioned that unit costs vary among CEE farms significantly.
At least part of this variation can be accounted to technical inefficiencies. The output
based Debreu-Farrell measure of technical efficiency is defined as a ratio between actual
and frontier output
TE ( y, x) 
y
f ( x)
where y denotes output and x a vector of inputs. Obviously, 0  TE ( y, x)  1 . If we
implement technical inefficiency in the SCB formula we get
19
w
e
i
i
SCB 
x
i, j
j
y
j
Pe
w x
e
i
j

i
i, j
j
P e  f (x j )TE ( y j , x j )
j
where index j refers to farms, index i to inputs and superscript e to economic (social,
opportunity) prices. Evidently, technical inefficiencies make denominator smaller, and
hence, SCB larger.
If financial (private) prices diverge from economic (opportunity) prices then inefficient
allocation of inputs (and outputs in multi-output technologies) in respect to economic
prices is supposed. Since technical coefficients are not allowed to change, allocative
efficiency is implicitly present in SCB and DRC. From this point of view, SCB and DRC
coefficients overvalue non-competitiveness.
Profitability of particular production in a particular firm or farm indicates domestic
competitiveness of that producer. Technical and allocative inefficiencies reduce private
profitability, and hence, competitiveness. If they both can be separated and assessed then
they give important insight in origins of farm competitive advantages and disadvantages.
Technical efficiency refers to farm internal problems, organisation and management, skill
in deployment of technologies etc. Inappropriate positioning inputs and outputs
respectively to the relative price structure suggests that market imperfection.
20
2
Competitiveness of CEE farms in IDARA project
Figure 2 Competitiveness of farms as an issue in rural economy
Following Porter’s approach the analysis of competitiveness should focus farms, their
internal organisation and the environment in which they produce, adopt new
technologies, develop strategies, co-operate and compete. Farms in aggregation
determine competitiveness of commodity sub-sectors. To be able to assess the
21
implications for commodities we have to study farm competitiveness on the commodity
base. We concentrate on 8 main agricultural commodities and we look how they
constitute farm output, revenue, cost and profit.
Productivity of factors is central in competitiveness assessment. Productivity is
determined by technology and efficiency with which is technology deployed.
Productivity and factor costs determine unit costs of products. Costs are easily observable
and relatively well surveyed. Therefore, costs are starting point of our analysis.
Total costs of individual commodities are broken down to cost groups. In these groups
we do not only survey the actual size of costs but also applied policies (tariffs, taxes and
subsidies) and input market imperfections. The later will enable us to evaluate costs at
economic (opportunity) prices.
2.1
Phase 1 – costs and competitiveness indicators directly linked to
structural and financial characteristics of farms
2.1.1
Step 1
Our first objective is to understand variations of unit costs across farm. Initially, we are
adopting the assumption that farms face the same input and output prices in a given year.
Non-price determinants of cost variation are our primary concern. There are numbers of
potential causes of cost variations starting with natural conditions, continuing with
business set up, utilisation of economy of scale, financial health and ending with
structures of human and physical capital.
Structural characteristics
Following results of Hughes, (2000)11 we expect that farm legal form and farm size will
play role. They both represent internal organisation of farm business, formation of
business goals and labour commitment to the business and benefits from economies of
11
Hughes (1999) shown that legal form and farm business size matter, however, differently in different
countries. While there were significant evidence of economies of size agriculture and no significant
evidence of the importance of business form in Czech agriculture, individual private farmers exhibited
higher productivity than corporate farms, but economy of scale did not appeared to matter in Hungary.
22
size12. The effects of scale economies might be offset by increasing transaction costs
associated with the principal agent problem of managing hired labour (Schmitt, 1991).
We consider that simple ratio of paid (hired) labour to total labour should effectively
capture this phenomenon.
Table 4 Organisation
Determinant
Legal form
Parameter
Legal form
Business size
Labour
Annual Total Revenue
Share of paid labour on total labour
Reference
Business goals, concerns of
owners of capital, commitment of
labour, internal organisation
Economy of scale
Higher transaction costs due to
principal agent problem.
Specialisation and large operation scale allows farms to invest in specific machinery and
equipment and keep specialised skilled labour. Such farms have also collected experience
and likely have developed close relationships to input suppliers and output buyers. Farm
concentration on a particular production should push unit costs down13.
Table 5 Technology related determinants
Determinant
Operation scale
Parameter
Product revenue
Specialisation
Share of product revenue to total
revenue
Deployed capital stock
The share of product specific
assets on the total fixed assets
Fixed assets per labour unit
Capital/Labour substitution
Reference
Advanced technology, skilled
labour, relations to input suppliers,
output buyers, economy of scale
Advanced technology, skilled
labour, relations to input suppliers,
output buyers, economy of scale
Advanced technology, economy of
scale
Labour or capital intensive
technology
Financial health
It is often spelled that problems with keeping sufficient cash-flow are a reason for
worsened farm performance (Novak, 2000). Farms lacking working capital cannot afford
buying inputs, and hence, their yields are declining. On one hand, CEE farms have been
12
Better use of farm resources, better up-downstream relations, better risk management (see Hughes, 2000,
pp. 130)
13
It may also aim at product quality with the ultimate goal to earn price premium.
23
driven to financial difficulties from outside due to agricultural market recession and
institutional changes, on the other hand, farms have adopted financial management
strategies which not always are appropriate to cope with transitional difficulties.
Box 13 Financial strategies - UK
The choice of appropriate financial strategies is not a problem of transitional economies. Harrison
and Tranter (1989) surveyed 1276 UK farms to assess the financial strategies used to counteract
the effects of the agricultural recession in the 1980. While 45.1 percent of farmers had increased
the output from existing enterprises and 32.1 percent had reduced the amount of inputs used,
only 16.8 percent had taken advise on financial maters, while only 5.6 percent had opted to retire
debts/ reduce overdraft by selling land.
Source: Franks, 1998
Property rights and market reforms, and consequent adjustment processes have generated
costs largely carried by agricultural entrepreneurs. (Ratinger, Rabinowicz, 1997).
Restitution and privatisation induced formal and physical shifts of assets from old
farming structures and recognised owners to newly emerging farming organisations,
particularly in the Czech republic and Hungary. The process included almost costless
acquirement through restitution, but in the large extent purchases of assets (privatisation)
of assets, investments for completion of acquired assets. Alternatively assets were
temporarily given (leased) for using with the ultimate aim to be purchased in the end. It
has resulted in collecting bank credits but even more medium and long term liabilities to
the state and private (non-farming) owners. Large indebtedness, consequently, the
necessity to serve these debts and low solvency have slowed down investment activities
and made agricultural enterprises vulnerable
Table 6 Indicators of Financial Health
Object
Liquidity
Parameter
Current ratio
Quick ratio
Financial stress
Debt servicing ratio
Efficiency
Gross ratio
24
Measures:
Farm business’ ability to pay debts
Excludes less liquid inventory from
Current ratio.
The share of the farm business
gross cash income needed to
service to service debts
(Interests+rents)
Proportion of gross cash farm
income absorbed by cash
operating expenses
Fixed ratio
Proportion of gross cash farm
income absorbed by fixed
expenses
Labour cost ratio
Proportion of gross cash farm
income absorbed by labour
Interest to gross cash income ratio Proportion of gross cash farm
income absorbed by interest
payments
Asset turnover
The gross farm income generated
per dollar of farm business assets
Debt to assets ratio
Indication of overall financial risk.
(Solvency)
Debt burden ratio
The burden placed on net farm
income to retire outstanding debt.
Leverage
The proportion to which debt is
used, as related to equity capital,
to finance the total farm business.
Indebtedness
Source: Short (1999)
Structure and means of the analysis
The analysis is based on the notion that costs are determined by the choice of technology
and by its efficient implementation. Since relative price structure is supposed to be
identical for each farm, the choice of technology and its efficient implementation depend
only (mainly) on factors discussed above. Location and specialisation/operation scale
should affect the choice of technology, while the rest should be accounted to efficiency.
The analysis is structured along the cost break down (column headers in Table 7).
Common costs like interest payments and overheads are not included in commodity
costs. Non-price determinants are supposed to have primary or secondary effects on
production cost formation.
Table 7 Primary (1) and secondary (2) effects of non-price determinants of cost
variation.
Intermediate costs
Location
Determinants
Soil and climate
Organisation Legal form
Size
Labour
costs
Energy and Total
maintenanc
e
Variable
costs
(intensif.
inputs)
1
2
2
2
1
2
25
Capital costs
Yield
Capital
Investmen
consumpti t
on
2
2
1
1
2
1
2
2
1
1
1
Technology
Working
capital
availability
Financial
stress
Borrowed
capital
Unpaid/paid
labour
Specialisation/
Operation scale
2
2
1
2
2
1
1
1
1
1
1
Capital stock
1
1
1
1
1
1
Liquidity
1
1
2
2
1
Servicing debts
2
2
2
1
2
Solvency
Debt burden
2
2
2
2
2
2
1
2
2
2
Bank loans
1
0
Other forms of
borrowed capital
(medium and
long term)
1
0
Technical apparatus for assessing statistical evidence
We will follow two approaches for confirming or rejecting our notion about determinants
of differences in costs among farms: analysis of variance and regression analysis.
Analysis of variance
Farms are classified (grouped) according their location, organisation, technology and
financial health. The following model is supposed:
( 1)
Cl ,o,t , f    l   o   t   f   l ,o,t , f
where  denotes the mean (cost clean of all non-price effects),  , , ,  are effects of
location, organisation, technology and financial health,  refers to residuals with a
normal distribution N(0,  2 ) and the indexes l, o, t, f relate to classes of factors
(Snedecor and Cochran, 1989). The significance of effects of factors is tested.
Table 8 Example of a classification (of independent variables)
Location
Corn and beet
Cereal
Organisation
Individual small
Individual large and
limited liability
Technology
Specialised, small scale
Specialised, large scale
26
Financial health
Sound
Average
Sub-mountain
Mountain
Coops
Joint stock
Non-specialised
Vulnerable
Stressed
Alternatively the model can be extended to include interactions between factors
(independent variables) or to include a variable linearly related to the dependent variable
(i.e. analysis of covariance) (Snedecor and Cochran, 1989).
Regression analysis
Since the size, financial indicators, employed labour and assets are continuos variables
we can consider a regression model for assessing the determinants of cost variation:
( 2)
Ci    X i   i
where Xi is a vector of independent variables (determinants),  a vector of parameters
and the subscript i refers to individual farms14. Some determinants (particularly, financial
characteristics) which are represented by ratios have to be treated carefully to be included
in the model in the right way15. Alternatively, quadratic regression might be considered.
Cluster analysis.
A problem might arise how to group farms for example according to their financial
status. We identified a number of financial indicators however it is not obvious how to
combine them to create proper groups of farms. An option is to use cluster analysis. The
distances (or similarities) between farms are calculated from the set of financial
characteristics. The hierarchical agglomerating clustering will put together the nearest
farms. Since for the cluster analysis the variables have to go the same directions some of
financial indicators have to be reformulated.
Another way how to employ cluster analysis is to group farms according to their
cost/productivity/competitiveness performance and look structural and financial
14
this approach was used for example by Short (2000)
15
it may require transformation (e.g. reciprocal) of some ratios
27
characteristics (variables). This will yield related groups of variables (farm
characteristics)
2.1.2
The second step
One we yield non-price determinants of costs we may think if they are not better linked to
profit than just to costs. Profit will vary if we can consider different output prices. From
the Czech data it is evident that prices are not identical. We should also test if prices vary
significantly along farm groups, i.e. if some farm groups get better prices than the other
groups. One explanation to price variation is that price reflects quality of the product.
FADN data do not include information on quality of product even for such obviously
differentiated products like food and feed cereals.
The FADN samples contain information on unit cost of hired labour. Using this
information we can separate labour price and physical labour input and improve our
analysis from the first step.
2.1.3
The third step
We break down cost to tradable and non-tradable components. First we assess differences
in the employment of tradable and non-tradable inputs and factors among farms. We will
utilise the results of the step one. We do not expect that tradability plays the role, but we
would like to understand if production of some farms relies more on domestic resources.
Table 9 Tradable/non tradable break down of costs
Tradable
intermediate
Non-tradable
intermediate
Seed, fertilisers, Some feeds
chemicals,
(hay, clover
animal feed, fuel etc.), veterinary
services,
energy,
maintenance
Tradable capital
stock
Non-tradable
capital stock
Machinery,
equipment
Buildings and
other
construction
works
Labour
Other nontradable
domestic
Insurance
Using conversion coefficients (to economic prices) for inputs and opportunity prices for
output we calculate SCB ratios. The economic prices (or conversion coefficients) of will
come in two alternatives – the border prices and social costs of factors and the EU market
prices (e.g. Ratinger, Slaisova) and social costs with affected by the access to the EU
28
factor markets. For the purpose of comparability we will express profitability as a ratio
similar to SCB (we will call it “private cost benefit ratio” – PCB). Thus, we yield an
indication of competitiveness of each farm at three levels: i) domestic market, ii)
international and economy wide, and iii) in the EU environment. If we classify farms as
“Competitive” when cost benefit ratio is significantly below 1, “at BreakEven” if it is
close to1 and “Non-competitive” if it is sharply over 1. We yield 27 classes for three
price schemes, but most of them are unlikely to appear. Then we investigate the linkage
to structural and financial characteristic of farms.
2.1.4
Appendix Structure of FADN and cost survey data required for analysis
Farm Characteristics
ICode
1
2
3
Item
Year
Farm identification
Legal form
Unit
4
5
6
Production region
Geographical region
Labour input
Code
Code
7
Unpaid labour input
8
Utilised Agicultural Area
hectare
9
Rented U.A.A
hectare
10
11
12
Arable land
Forage Crop
Total livestock units
hectare
hectare
13
Total output
14
Output crops and crops
products
Output livestock and
products
Other output
national
currency
national
currency
national
currency
national
currency
national
currency
national
currency
national
currency
national
currency
national
currency
national
currency
15
16
17
18
Intermediate
consumption
Depreciation
19
Labour costs
20
Rents
21
Interests
22
Balance current
subsidies & taxes
Number
Code
Note
[1996][1997][1998][1999]
[Sole proprietorship-full liability][Limited liability
company][Joint stock company][Co-operative]
climatic and soil quality region
geographical or administrative region
AWU
FWU
Fodder crop on the arable land + grassland
at the commercial rate (no interest subsidies incl.)
29
23
Balance subsidies &
taxes on investment
national
currency
24
Total Assets
25
Fixed Assets
26
- land, permanent crops
& quotas
national
currency
national
currency
national
currency
27
- buildings
28
29
30
31
32
33
34
35
36
37
38
national
currency
- machinery
national
currency
- breeding livestock
national
currency
Current assets
national
currency
- livestock
national
currency
- stock agricultural
national
products
currency
- other circulation capital national
currency
Liabilities
national
currency
- long and medium-term national
loans
currency
- of it bank credits
national
currency
- short-term loans
national
currency
Net Worth
national
currency
it should correspond to the interests item
30
ICode
Item
39
Product
40
Year
number
[1996][1997][1998][1999]
41
Farm identification
number
referring to farm characteristics
42
Area
hectares
harvested area
43
Output
t
44
Marketed output
t
output actually sold out of the farm
45
Revenue
national currency
46
Seeds
national currency/t
obtained revenue from marketed
output
own and purchased
47
Fertilisers
national currency/t
incl. manure
48
Chemicals
national currency/t
49
Fuel and lubricants and other energies national currency/t
50
Repair and maintenance
national currency/t
51
Other variable costs incl. agrotechnical services
national currency/t
52
Depreciation
national currency/t
53
Labour cost
national currency/t
ICode
Item
Unit
39
Product
40
Year
number
[1996][1997][1998][1999]
41
Farm identification
number
referring to farm characteristics
42
Stock
heads
43
Output
t
44
Marketed output
t
output actually sold out of the farm
45
Revenue
national currency
46
Feeds
national currency/t
obtained revenue from marketed
output
own and purchased
47
Unit
Content
[Wheat][Barley/Maise][Sugar
beet][Rape/sunflower seed]
as good as approximation of total fuel
and energy consumed for producing
the product
as good as approximation of total
capital consumption
as good as approximation of total
labour input
Content
[Milk][Beef][Pork]
national currency/t
48
Veterinary treatment
49
Fuel and lubricants and other energies national currency/t
national currency/t
50
Repair and maintenance
national currency/t
51
Other variable costs incl. agrotechnical services
national currency/t
52
Depreciation
national currency/t
53
Labour cost
national currency/t
31
Medicaments+ veterinary services
as good as approximation of total
fuel and energy consumed for
producing the product
as good as approximation of total
capital consumption
as good as approximation of total
labour input
2.2
Phase
2
Technical
efficiency,
total
factor
productivity
and
competitiveness
Curtis (2000) investigated in which extent technical efficiency contributes to
competitiveness of farms or in turn, how much revenue could be gained if farms got the
maximum from inputs they are using. The link between technical efficiency and was
explained in 1.3. Curtis used the stochastic frontier approach to assess technical
efficiency for three crop products – wheat, rapeseed and sugar beet for a specific
production16 region in the Czech republic. She noted significant improvement of cost
benefit ratios when she applied frontier yields instead the actual ones. Even sugar beet
producer might reach the break even of international competitiveness if they improved
technical efficiency. The results of Curtis also suggest that farm type, size and
specialisation are important determinants of farm technical efficiency, and hence, of farm
competitiveness.
We might follow this approach for selected products (or only for the case study subsector (milk)) and structural and financial farm characteristics, which will have appeared
significant in the phase 1.
Alternatively, we may look at efficiency using cost function. We will concentrate on
labour, capital and land (if relevant). Labour input is measured in AWU17and includes
hired and family labour, fixed capital input is represented by depreciation and is
measured in monetary units, land input is given in hectares. Our assumption is that price
of factors vary across farms, while prices of other inputs are the same. Their respective
prices are given.
Table 10 Prices of factors
Inputs
Labour
Fixed capital
Land
Price
Actual wage rate increased by social contributions
Paid interests/depreciation
Paid rent / farm land
16
climatic and soil quality region
17
Annual work units
32
L
K
A
Our hypothesis is that different proportion of own and hired labour, inherited and
invested assets and own and rented land matter in shaping costs. If the prices of
remaining inputs do not differ across farms, their optimal use is incorporated in the
constant and departures in the residual term. Adopting translog functional form we yield
( 3)
ln( Ci )   0 

j  L,K , A
j
ln( w ji ) 
1
2
 
j  L,K , A k  L,K , A
jk
ln( w ji ) ln( wki )  (vi  u i )
where C denotes farm product cost, w factor prices,  are parameters, i identifies farm,
and j, k relate to factors. (vi+ui) is an error term. Adopting stochastic frontier approach we
distinguish between random effects (v) like weather with distribution N(0,v2) and cost
inefficiencies (u) with half normal distribution |N(0,u2)| (Coelli, T.J., 1996). Estimating
model ( 3) we obtain information how much cost variation can be accounted to
differences in factor prices and how much to technical18 inefficiency.
Now we turn our attention to productivity of factors: labour, working capital, fixed
capital and land. Labour input is measured in AWU19and includes hired and family
labour, fixed capital input is represented by depreciation and is measured in monetary
units, land input (if relevant) is given in hectares, working capital includes all remaining
production costs (which have to be paid). For their respective prices we adopt the
opportunity price concept.
Table 11 Factor prices – an alternative definition.
Inputs
Labour
Working capital
Fixed capital
Land
18
Price
Actual (or opportunity) wage rate increased by social contributions
Interest rate for savings (e.g. government bonds)
Interest rate for commercial borrowings
Actual rent paid by the farms
it relates to our assumption about remaining input prices. In some way we may also consider allocative
inefficiency.
19
Annual work units
33
Following Bureau and Butault (1992) we define the farm factor productivity position
index (FP) for a given commodity as a Tornquist input index20 relating to a base (a fictive
farm)
( 4)
ln FP 


1
S iK  S ibase ln xiK  ln xibase

2 i

where xi is a factor input per unit of an output, wi its respective price and
S iK 
wi xi
,
 wj x j
j
is the input share in total costs. Superscription K relates to farms in the sample and
superscription base indicate a base to which all indexes relate. This index will be
included among variables for clustering farms.
Multi-output version of Tornquist index (Hughes, 2000, 142) will be used when we
concentrate on the performance of whole farms.
We will use Tornquist index in to other (more standard) ways too. It will be used to
measure technical change on average in each country over the last four-five years. The
index for single21 output production have a form of
( 5)
Tt 
1

TFPt
y
 t exp   S it  S i0 ln xit  ln xio 
TFP0 y0
2 i




where y denotes output and t time. The data will probably allow us to look at the
technical change at very aggregate level. Working capital and fixed capital both have to
be deflated to get it in comparable volumes
We will also use the approach suggested by Bureau and Butault (1992) for comparing
productivity of Czech, Hungarian and Polish and possibly some EU farmers. Either the
index defined in ( 4) now relating to a common base will be added among other variables
20
Tornquist index is called a superlative of technical change or difference because it is an exact relative
measure of the distance for functional form that is flexible.
34
for clustering Cz-Hu-PL farms or will be used directly for comparing Cz-Hu-PL farm
groups, however, in the form ensuring transitivity i.e. with using a common base:
( 6)
ln FP A, B 

1
A
base
ln xiA  ln xibase   S iB  S ibase ln xiB  ln xibase  ,
 S i  S i
2 i
i







where A, B  {Cz, Hu, Pl,[EU]}. Again adjustment of capital volumes to a common
level is necessary.
2.3
Phase 3 Completing study on overall farm competitiveness
We will broaden the scope of investigation of competitiveness favouring condition in
directions of Porter’s diamond in the third phase .
We will gather two sets of additional information:
i)
on farm business such a decision making, employed human capital, cooperative behaviour and character of transitional debts (see 2.3.1)
ii)
on market relationships such as access to suppliers and buyers,
contracting etc.
The both set are supposed to improve explaining of cost and profit variation, the first set
relates to farm internal advantages, the second set should give inside if actual market
environment (and in a certain extent farm marketing strategies) favour farm
competitiveness. The information on i) and ii) will be obtained by surveying a subset of
farms from FADN which are included in the farm diversification survey. The questions
(Appendix 2.3.1) have already been included in the respective questionnaires.
This step should complete the analysis of step 1 and 2 of the Phase 1. Therefore,
clustering and analysis of variance will remain the main analytical instrument for
assessing the influence of additional organisational and market factors.
21
for generalisation to multi-output technology see Capalbo, Antle (1989, 56)
35
2.3.1
No
Appendix – Additional information – Questionnaire
2
Explanation/comment
Business characteristics
Organisational structure
production
investment
employees
Human capital
3
Co-operative behaviour
1
Question
Who takes decision about
Top
Representative
manager
of owners
Please, tell us qualification structure of you
farm labour (employees + family labour)
Education
university
secondary
professional
basic (and lower)
Do you co-operate with other farmers
If do not, do you feel a need?
If yes in the above questions (3), in which
areas
input procurement, which inputs
marketing products, which products
environmental protection
4
5
6
7
Assembly of
members
Land reform liabilities (e.g. so called
transformation debt in the CR, credit for
purchasing land and assets in
privatisation)
Market imperfections
Down stream markets, the best will be to
as for each industry separately:
cereals, oilseeds, sugar (beet), milk,
meat. The table form might be useful.
Up stream markets
similarly, to look at individual industries,
cereals and oilseeds, sugar beet, animal
production – feeds, or
seeds, fertilisers and chemicals, feeds?
36
Do you have troubles with repaying land
reform liabilities?
What is their share on the total liabilities.
Can you choose buyers?
Do buyers offer a credit for purchasing inputs?
do you use this option?
How many buyers do you have?
Do you have problems with buyers payments
(do they pay in time?)
If you have, what does you prevent to change
buyer?
wrongly agreed contract
transport distance/costs
higher quality requirements of the other
buyers
Tell us please the average contract length
Is input supply satisfactory?
Can you choose input supplier?
Can you make long term contracts?
Do suppliers offer credits for purchasing
inputs?
do you use it?
Do suppliers offer enough information and
extension?
3
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