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 3 1.1 Competitive advantage 3 1.2 Domestic resource cost and policy analysis matrix 11 1.3 Productivity and efficiency 19

2 Competitiveness of CEE farms in IDARA project 22 2.1 Phase 1 – costs and competitiveness indicators directly linked to structural and financial characteristics of farms 23 2.2 Phase 2 Technical efficiency, total factor productivity and competitiveness 33 2.3 Phase 3 Completing study on overall farm competitiveness 36

3 References 38

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 nation1 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 factor- based 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 Coverage Characteristics Human resources the quantity, skill, cost Physical resources land, water, mineral deposit, the abundance, quality, accessibility timber deposit, climatic conditions Knowledge resources scientific, technical, market the number and quality of knowledge universities, research institutes, business and scientific literature, government statistical agencies Capital resources forms of resources (e.g. risk the amount (saving rates, capital characteristics) and forms of inflow) and cost deployment Infrastructure 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 large- scale 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, etc.). The ways by which competitive advantage in downstream and upstream industries benefit the other industries are pretty similar.

7 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 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).

6 globalisation

8 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 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.

9 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 non- farming 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.

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

10 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 Heckscher- Ohlin 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 Domestic Factor Profits Costs Costs

Financial Prices A B C D

Economic,(social, E F G H opportunity) Prices Net Transfer 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

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

11 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 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.

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 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: Nominal protection coefficient [A/E]-1 EPC: Effective protection coefficient [(A-B)/(E-F)]-1 DRC: Domestic resource cost G/(E-F) SCB: Social cost benefit ratio (F+G)/E PPR: Private profitability ratio (A-B-C)/A PCAC: Private Cost adjustment coefficient A/(B+C)-1 SCAC: Social Cost adjustment coefficient 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 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).

13 The Domestic Resource Cost ratio is usually presented in the form

n D aij P j  jk 1 DRC i k B B Pi aij P j 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;

D B P j social price of non-traded input j, P i border price of output i,

B P j border price of traded input j.

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.

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)

14 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 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

8 Obviously, the social prices of factors might be questioned from the same position.

9 it will be discussed later

15 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 (real10) interest on total fixed assets (of course associated with a particular production) evaluated at the interest rate of government bonds for 1997 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.

10 GDP deflator is always used when costs and prices have to be given in real terms.

16 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.

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.

17 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 D  D Pi aij P j  j1 1 EPCi k B B Pi aij P j 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;

D D P i domestic price of output i, P j domestic price of input j,

B B P i border price of output i, P 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.

18 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

y TE(y,x)  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

 xi, j e j  wi e i  y j  wi  xi, j j i j SCB  e  e P P  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

19 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

Off-farm Inputs Import

Farm Resources Agricultural Production e e b r

e o Labour Technology t h

y w t i e Capital Organisation n s l u e t

r Land Finance d o e p s p

u Skill Marketing O

Income Products

Competitive domestic Non Agricultural market + Processing & Rural economy Distribution (Rivalry)

Urban Economy

Export -International market- Import

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 implications for commodities we have to study farm competitiveness on the commodity

21 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 Parameter Reference Legal form Legal form Business goals, concerns of owners of capital, commitment of labour, internal organisation Business size Annual Total Revenue Economy of scale Labour Share of paid labour on total labour 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 Parameter Reference Operation scale Product revenue Advanced technology, skilled labour, relations to input suppliers, output buyers, economy of scale Specialisation Share of product revenue to total Advanced technology, skilled revenue labour, relations to input suppliers, output buyers, economy of scale Deployed capital stock The share of product specific Advanced technology, economy of assets on the total fixed assets scale Capital/Labour substitution Fixed assets per labour unit 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 driven to financial difficulties from outside due to agricultural market recession and

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 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 Parameter Measures: Liquidity Current ratio Farm business’ ability to pay debts Quick ratio Excludes less liquid inventory from Current ratio. Financial stress Debt servicing ratio The share of the farm business gross cash income needed to service to service debts (Interests+rents) Efficiency Gross ratio 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

24 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 Indebtedness 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. 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 Labour Capital costs Yield costs Variable Energy and Total Capital Investmen costs maintenanc consumpti t (intensif. e on Determinants inputs) Location Soil and climate 1 2 2 2 1

Organisation Legal form 2 2 1 2 1 2

Size 1 2 2 1 1 1 Unpaid/paid 2 2 1 2 2 labour

25 Technology Specialisation/ 1 1 1 1 1 1 Operation scale

Capital stock 1 1 1 1 1 1

Working Liquidity 1 1 2 2 1 capital availability Financial Servicing debts 2 2 2 1 2 stress Borrowed Solvency 2 2 2 1 2 capital Debt burden 2 2 2 2 2

Bank loans 1 0

Other forms of 1 0 borrowed capital (medium and long term)

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:

( 0) 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 Organisation Technology Financial health Corn and beet Individual small Specialised, small scale Sound Cereal Individual large and Specialised, large scale Average limited liability Sub-mountain Coops Non-specialised Vulnerable Mountain Joint stock Stressed

26 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:

( 0) 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 characteristics (variables). This will yield related groups of variables (farm characteristics)

14 this approach was used for example by Short (2000)

15 it may require transformation (e.g. reciprocal) of some ratios

27 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 Non-tradable Tradable capital Non-tradable Labour Other non- intermediate intermediate stock capital stock tradable domestic Seed, fertilisers, Some feeds Machinery, Buildings and Insurance chemicals, (hay, clover equipment other animal feed, fuel etc.), veterinary construction services, works energy, maintenance 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 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)

28 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 ICodeCharact Item Unit Note 1eristics Year [1996][1997][1998][1999] 2 Farm identification Number 3 Legal form Code [Sole proprietorship-full liability][Limited liability company] [Joint stock company][Co-operative] 4 Production region Code climatic and soil quality region 5 Geographical region Code geographical or administrative region 6 Labour input AWU

7 Unpaid labour input FWU

8 Utilised Agicultural Area hectare

9 Rented U.A.A hectare

10 Arable land hectare 11 Forage Crop hectare Fodder crop on the arable land + grassland 12 Total livestock units

13 Total output national currency 14 Output crops and crops national products currency 15 Output livestock and national products currency 16 Other output national currency 17 Intermediate national consumption currency 18 Depreciation national currency 19 Labour costs national currency 20 Rents national currency 21 Interests national at the commercial rate (no interest subsidies incl.) currency 22 Balance current national subsidies & taxes currency 23 Balance subsidies & national taxes on investment currency 24 Total Assets national currency 25 Fixed Assets national currency

29 26 - land, permanent crops national & quotas currency 27 - buildings national currency 28 - machinery national currency 29 - breeding livestock national currency 30 Current assets national currency 31 - livestock national currency 32 - stock agricultural national products currency 33 - other circulation capital national currency 34 Liabilities national currency 35 - long and medium-term national loans currency 36 - of it bank credits national it should correspond to the interests item currency 37 - short-term loans national currency 38 Net Worth national currency

30 ICode Item Unit Content 39 Product [Wheat][Barley/Maise][Sugar beet] [Rape/sunflower seed] 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 obtained revenue from marketed output 46 Seeds national currency/t 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 as good as approximation of total fuel and energy consumed for producing the product 50 Repair and maintenance national currency/t 51 Other variable costs incl. agro- national currency/t technical services 52 Depreciation national currency/t as good as approximation of total capital consumption 53 Labour cost national currency/t as good as approximation of total labour input

ICode Item Unit Content 39 Product [Milk][Beef][Pork] 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 obtained revenue from marketed output 46 Feeds national currency/t own and purchased 47 national currency/t 48 Veterinary treatment national currency/t Medicaments+ veterinary services 49 Fuel and lubricants and other energies national currency/t as good as approximation of total fuel and energy consumed for producing the product 50 Repair and maintenance national currency/t 51 Other variable costs incl. agro- national currency/t technical services 52 Depreciation national currency/t as good as approximation of total capital consumption 53 Labour cost national currency/t as good as approximation of total labour input

31 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 sub- sector (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 Price Labour Actual wage rate increased by social contributions L Fixed capital Paid interests/depreciation K Land Paid rent / farm land 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

16 climatic and soil quality region

17 Annual work units

32 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

( 0)

1 ln(Ci )   0    j ln(w ji )     jk ln(w ji )ln(wki )  (vi  ui ) jL,K ,A 2 jL,K ,A k L,K ,A

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

2 distinguish between random effects (v) like weather with distribution N(0,v ) and cost

2 inefficiencies (u) with half normal distribution |N(0,u )| (Coelli, T.J., 1996). Estimating model ( 0) 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 Price Labour Actual (or opportunity) wage rate increased by social contributions Working capital Interest rate for savings (e.g. government bonds) Fixed capital Interest rate for commercial borrowings Land Actual rent paid by the farms 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)

18 it relates to our assumption about remaining input prices. In some way we may also consider allocative inefficiency.

19 Annual work units

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.

33 1 K base K base ( 0) ln FP  Si  Si ln xi  ln xi  2 i

where xi is a factor input per unit of an output, wi its respective price and

w x S K  i i i ,  w j 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

TFPt yt 1 t 0 t o  ( 0) Tt   exp Si  Si ln xi  ln xi  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 ( 0) now relating to a common base will be added among other variables 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:

A,B 1  A base A base B base B base  ( 0) ln FP  Si  Si ln xi  ln xi  Si  Si ln xi  ln xi  , 2  i i 

21 for generalisation to multi-output technology see Capalbo, Antle (1989, 56)

34 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, co- operative 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.

35 2.3.1 Appendix – Additional information – Questionnaire

No Explanation/comment Question Business characteristics 1 Organisational structure Who takes decision about production Top Representative Assembly of investment manager of owners members employees 2 Human capital Please, tell us qualification structure of you farm labour (employees + family labour) Education university secondary professional basic (and lower) 3 Co-operative behaviour Do you co-operate with other farmers If do not, do you feel a need? 4 If yes in the above questions (3), in which areas input procurement, which inputs marketing products, which products environmental protection

5 Land reform liabilities (e.g. so called Do you have troubles with repaying land transformation debt in the CR, credit for reform liabilities? purchasing land and assets in What is their share on the total liabilities. privatisation) Market imperfections 6 Down stream markets, the best will be to Can you choose buyers? as for each industry separately: Do buyers offer a credit for purchasing inputs? cereals, oilseeds, sugar (beet), milk, do you use this option? meat. The table form might be useful. 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 7 Up stream markets Is input supply satisfactory? similarly, to look at individual industries, Can you choose input supplier? cereals and oilseeds, sugar beet, animal Can you make long term contracts? production – feeds, or Do suppliers offer credits for purchasing seeds, fertilisers and chemicals, feeds? inputs? do you use it? Do suppliers offer enough information and extension?

36 3 References

Bureau, J. Ch., Butault, J. P. (1992) Productivity Gaps, Price Advantages and Competitiveness in E.C. Agriculture. ERAE, 19, pp 24-48

Capalbo, S. M., Antle, J.M. (1988) An Introduction to Recent Development in Production Theory and Productivity Measurement, in Agricultural Productivity, Measurement and Explanation, (Capalbo, S. M., Antle, J.M. ed.) Resources for the Future, Washington, D.C.

Chambers, R.G. (1988) Production Economics, Cambridge University Press

Coelli, T., J. (1996) A Guide to Frontier Version 4.1: A Computer Programme for Stochastic Frontier Production and Cost Function Estimation. CEPA Working Paper, University of New England, Armidale

Curtiss, J. (2000) Technical Efficiency and Competitiveness of the Czech Agriculture in Late Transition – the Case of Crop Production. KATO Symposium, Understanding Transition of CEE Agriculture, Humbolt University Berlin, Novemeber 2-4,

Doucha, T., Juřica, L. (1998)

Franks, J.R. (1998) Predicting financial stress in farm businesses, ERAE 25, pp 30-52

Gorton, M., Davidova, S., Ratinger, T. (2000) The Competitiveness of Agriculture in Bulgaria and the Czech Republic Vis-À-Vis the European Union, Comparative Economic Studies, Vol XLII, 1, Spring, 1-27.

Green, W., H. Frontier Production Function in Handbook of applied Econometrics, Vol. II, (Pesaran, M, Schmidt, P. ed.) Blackwell Publishers Ltd.

Harrison, A., Trantner, R.B. (1989)The Changing Financial Structure of Farming. Centre for Agricultural Strategy, Report 13, University of Reading

Hughes, G. (2000) Agricultural Decollectivisation in Central Europe and the Productivity of Emergent Farm Structures, PhD Thesis, Wye College, University of London.

Jonasson, L (1997) A Policy Oriented Multi-Input and Multi-Output Measure of Overall Efficienecy and its Decomposition, JAE, pp 52-64

37 Matthews et al. (1999) Assessment of competitiveness of Czech agriculture and food industry in the context of EU accession, The final report of the project FAO/TCP/CEH/8821, Volumes 1-8, MZe CR, FAO Rome, also www.vuze.cz

MFDNES (2001) on www.mfdnes.cz, January, 8

Novak a kol. (1999) Analýza nákladovosti českeko zemedělstvi v roce 1998,(Cost Analysis of Czech Agriculture in 1998), Working paper No. 60, VÚZE Praha

PBJ (2001) on www.pbj.cz, January, 8

Porter, M (1990) Competitive Advantage of Nations,

Ratinger, T., Rabinowicz, E. (1997) Changes in Farming Structures in the Czech Republic as a Result of Land Reform and Privatisation, in Agricultural Privatization, Land Reform and Farm Restructuring in Central Europe (ed. Buckwell, Matijs, Swinnen), Avebury, 80-99.

Ratinger, T. (1999) Competitiveness of Czech Agriculture in the Light of EU Integration, in Agriculture and East West Integration, Hartell, J., Swinnen, J. ed. Avebury

Short, D.S. (2000) Structure, Management, and Performance Characteristics of Specialised Dairy Farms Businesses in the United States, ERS, USDA, Agricultural Handbook No.720

Schmitt, G (1991) Why is the agriculture of advanced Western economies still organised by family farms? Will this continue to be so in the future? ERAE 18, pp 443-450

Snedecor, G.W., Cochran, W. G. (1989) Statistical Methods, Iowa State University.

Tsakok, I. (1990) Agricultural price policy. A practitioner’s guide to partial equilibrium analysis. Cornell University Press, Ithaca and London

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