Journal of the Scientific Agricultural Society of Finland Voi. 47: 283-383, 1975 Maataloustieteellinen Aikakauskirja ECONOMICS OF FOREST LAND CLEARING FOR AGRICULTURE Selostus: Metsämailla suoritettujen uudisraivausten taloudellisuudesta K. U. PIHKALA SUOMEN MAATALOUSTIETEELLINEN SEURA HELSINKI https://www.c-info.fi/en/info/?token=WzHfQ5qhcOUrfFf6.735VYqbEU0AEokXfvN-c-Q.cRWNBOlhglP96yW3rvcPF2vuoVpWMtP9SBTTDwT_H5Ebm-zLLFKaERKmGUZNdusM33tglNBHjYNdVJwEntQ-n8KrQHqMf9bKFKMSsMdIjshMRw2M39rKehQEPkkLmD4pgx-41wuB4Zb9PGV1hnPylXC6WtyW9fzMGc-r 285 Preface This volume contains in an abbreviated form the main report of a Finnish Study Group formed in 1959 to investigate the economics of alternative use of land for agriculture or forestry. The study group worked within the frame- work of the Institute of Agricultural Policy, Faculty of Agriculture and Forestry, University of Helsinki. Expert forestry knowledge was represented by the group members, Professor Viljo Holopainen, at present General Director of the Forest Research Institute, and Dr. Matti Keltikangas, today Professor of Forestry Economics. The other members of the group, Dr. Tapani Lasola, of the Institute of Agricultural Policy, Mr. Paavo Väisänen, M. Agr. Sc., Councillor in the Ministry of Agriculture and Forestry, and the writer, Professor Kaarlo Uolevi Pihkala, now retired Head of the Institute of Agricultural Policy, are agricultural economists. The members of the group have contributed to the planning of this study, in the organizing and supervising of the field work and by some printed publications and unpublished manuscripts. They have further helped by offering comments and by reading through the manuscript. The forest observa- tions in the field work were by Dr. Keltikangas. Dr. Lasola has also helped in the numerical work. Especially Dr. Arvi Valmari and Mr. Kalervo Hyppölä have given valuable help to the study group in the form of advices and criticisms. We are grateful to them as well to all coworkers on the field, including these hundreds of small farmers who contributed with information. This research has been mainly financed through a grant made by the U. S Department of Agriculture under P. L. 480 and, at its initial stage, by grants of the Yrjö Jansson Foundation, the State Research Council of Natural Sciences and the Foundation of Natural Resources. The main report was distributed in the from of mimeographed sheets in 1969. The final revision has been greatly delayed by the author’s increased teaching duties and pressure of administrative work in the University. K. U. Pihkala CONTENTS I INTRODUCTION 289 II COMPARATIVE STUDIES ON LAND USE FOR AGRICULTURE AND FORESTRY 291 v. ThxJnen 291 Recent studies in English speaking countries 293 A German study 299 Studies in the Northern countries 299 111 AIM AND SCOPE OF THIS STUDY 306 IV A FIELD STUDY ON A NUMBER OF PIONEER FARMS IN FOUR REGIONS IN FINLAND 309 Method used in the field study 309 The data on agricultural production 311 Some figures characterizing the land use and economic size of study farms . 311 The main crops and the use of fertilizers and lime 312 The marketable crop and its value 314 The data on milk production 315 Draft animals 316 Estimate of beef production 318 The non-marketable crop and its utilization 318 Value of agricultural production 319 Method of cost estimations 320 Cost of tractive power and field machinery 321 Some cost items of livestock production 322 Cost of investment in buildings 322 Cost of labour 323 Balance of return and costs 325 The data on forestry 327 Projections relating to the volume and value of potential cuttings 332 Comparisons with other relevant data 336 The farm income from forestry 338 Land rent of forestry compared with that obtained in agriculture 338 V MARGINAL CALCULATIONS ON THE EXTENSION OF AGRICULTURAL PRODUCTION BY LAND CLEARING 340 VI LAND CLEARING IN THE DIFFERENT SITE AND AGE CLASSES OF TIMBER STAND 346 The influence of price rise 349 VII THE LINEAR PROGRAMMING APPROACH 354 VIII ADVANTAGE OR DISADVANTAGE IN SOCIO-ECONOMIC CALCULATIONS 356 SUMMARY 361 REFERENCES 364 SELOSTUS 368 APPENDICES I-VII 370 NOTES AND ABREVIATIONS 383 289 JOURNAL OF THE SCIENTIFIC AGRICULTURAL SOCIETY OF FINLAND Maataloustieteellinen Aikakauskirja Voi. 47: 283—383, 1975 Pihkala, K. U. 1975. Economics of forest land clearing for agriculture. J. Scient. Agric. Soc. Finl. 47; 283—383. Abstract. In the literature review an account is given of the methodological problems of the economic comparison of land use for agriculture or forestry. In the empirical study, the comparison is focused on situations where a decision on the possible transfer from forest to agricultural use may have current interest. On the basis of data, mostly collected from pioneer farms established after the war on forest or peat land within four main study areas in Finland, estimates of gross margin, social output, labour income and land rent are made, using the price structure of 1959 63. The comparisons indicate among other things that although agricultural land rent in the existing structure of farm size is often negative, the land rent in marginal calcula- tion may be positive. The land rent is neither the sole criterion of land use to the farmer, nor to the national economy, as the labour income plays an important role. The farmer's problem is to find the optimum combination of agricultural and forest activities. In the national economy, not only labour in primary production but also in secondary and tertiary industries has to be considered. The economic losses caused by badly timed forest land clearing are illustrated by calculations. I. Introduction State support for pioneer farming and forest land clearing for agriculture has old traditions in Finland, it was in fact established already during the last decades of the Swedish era. After the hunger period of the first year of Independence, 1917 18, certain measures to promote land clearing were introduced. In the year 1928, special legislation providing financial support to smallholders willing to enlarge their fields by forest or waste land clearing was enacted. The policy of subsidizing resulted in an enormous increase in the cultivated area. Until the outbreak of the Second World War, approximately 200 000 hectares of land had been cleared under subsidy schemes. Subsidies were, again, to a large extent used to promote land clearing needed for the post-war resettlement of the displaced population from the Karelian territory ceded to the U.S.S.R. This practice continued also after the completion of the resettlement programme. During the period 1945—6O approximately 300 000 ha were cleared for cultivation or pasture, an area that exceeded the cultivated area left behind the new borderline. The total increase 290 of arable land far exceeds corresponding increases in any other European country. Subsidized land clearing has been criticized, in the first place, as promoting surplus production in agriculture (see footnote p. 299). The outbreak of the war put this problem in a new perspective; and the necessity of new land clearing was now commonly accepted. After the recovery of agricultural production in the first half of the 1950’5, the appropriateness of subsidizing land clearing was again questioned, and the Committee on Agriculture, in its report (Kom. miet. 1962,p. 122) recommended the termination of subsidy allocations. Allocations for this purpose were, however, included in the State Budget without substantial reductions until 1968. While more emphasis has been laid on the necessity to increase forestry production, the subsidizing of land clearing has in recent years had to give way to promotion of afforestation and other measures promoting forestry. Irrespective of the aims of Government policies, there is a need for objective information on the productivity of land in both alternative uses. Such informa- tion is equally useful for decisions an afforestation and on land clearing. Interest in studies concerning the comparative advantage of land use alternatively for agriculture or forestry was, during the fifties, rather lively among others in the Northern countries. As will be seen, several studies have since been made on this theme. It may be mentioned that a working group was set up in Norway for these studies, and the Nordisk Jordbruksforskares Förening organized a seminar in December 1958 in Prestebakken, Norway, to discuss problems conenctid with this topic. The plan of the present study developed gradually from some simple calculations made by the author during the first postwar years. Various aspects of the research problems, some of which had been discussed also during the above mentioned seminar, have been discussed in a preliminary publication (Pihkala, 1964). The study includes also empirical data concerning the price trends and calculations presented to the Committee on Agriculture (1961). 291 11. Comparative studies of land use for agriculture and forestry Although the comparative study of the economics of land use has a long tradition starting with von Thunen’s classical work, the number of recent studies where economic comparisons between alternative uses of land for agriculture or forestry are made, seems to be rather small. No such study can give a general answer valid in any other natural and economic conditions than those prevailing in the sphere of the respective study. The empirical results of such studies are thus of no special interest to us. The method used in various studies, is however, interesting from the point of view of this study. A brief account of the studies available to us is therefore given. v. Thunen The method used in v. Thiinen’s famous book »Der isolierte Staat», the first edition of which was published in 1826, is of sufficient interest to be first reviewed here (v. Thunen 1875). The purpose of v. Thiinen’s study was to demonstrate why the geographic location of various lines and intensity levels of agricultural production shows certain regularities. The model used was an imaginary State, isolated from the rest of the world, with a homogeneous soil and climate, and only one market centre, the Town, in the centre. The empirical data were based on detailed book-keeping records of the estate Tellow, at a distance of 37.5 km from the market place of Rostock, Mecklenburg. The soil there was first class »barley» soil, and the rotation »KoppelwirtschafU (fallow, 3 grain crops, 3 leys). The calculations concerning other intensity levels (among others Dreifelderwirtschaft, Fruchtwechselwirtschaft) were deduced mostly from the data of Tellow, assuming certain hypotheses on the equilibrium of plant nutrients in different rotations, and utilizing work time records of various field operations. Some data concerning intensive agriculture were, however, cited from a study on Belgian agriculture, where the actual data of Edegem farm, south of Antwerp, were used as representative data. All costs were expressed partly in Scheffels (= 0.544 hi) of rye which were valued on the basis of the market price in the Town from which transport costs were subtracted, partly in money (Thalers). The former costs decreased with the growing distance from the Town, the latter, supposed to be determined in the Town itself with its higher costs of 292 living (eg. the products of industry, the salaries of officials educated in the Town), were independent of the distance to the Town. The larger the share of mining, industry and trade in the rural area, the smaller the part of the costs expressed in money and independent of the distance from the town. v. Thunen used the ratio %:% between the former and the latter part of costs. The labour time requirements were assumed partly as fixed per areal unit, partly varying in the same proportion as the crops. The calculations relating to forestry are in the edition from the year 1826 based on an approximate estimation of the growth of a 100 years’ beech stand; it was admitted that the estimate was not founded on reality, v. Thunen assumed a sustained yield from plots of equal size representing all age classes. The yield in the form of thinnings and final cuttings was estimated at 1000 cords (a 5.51 cu.m) from a total area of 100 000 square rods (217 ha), for the paying of five per cent interest to the capital in standing timber (which was estimated as 15-fold the value of yearly cuttings) 750 cords would be marketed, while the remaining 250 should cover the other costs of production as well as land rent as an opportunity cost. Land rent was calculated for rye giving 8 bushels per square rod, i.e. 20.08 hi per hectare and priced 1.5 Th. per bu in the Town, as a function of the distance to the market place, being e.g. equal to 1066 Th. when the distance is 7.5 km, 893 Th. 37.5 km, 685 Th. 75 km. To find the largest possible error, alternative calculations presuming a very large (eight-fold) variance either in the costs or in the yield were presented for comparisons. If the price of fuel wood per cord was assumed to be 21 Th. in the Town, and the assumptions of yield and costs were tenable, forestry was best competitive within distance, of 30 to 52.5 kms from the Town. In this connection v. Thunen already noted the value growth occasioned by a lengthening of the rotation period, but also the drawbacks caused by a retarded volume increase. Higher priced sawlogs were more advantageously produced at a longer distance than fuel wood; the leavings after timber cutting could be marketed as charcoal. It was difficult to unite a rational sustained yield forestry with an interest rate higher than the natural value growth; the purely economic reasons favoured the realisation of the timber stand. In the third volume of v. Thunen(s work, posthumously published in 1863, more detailed calculations on forestry were presented. They refer to Tellow pine stands, which with proper thinning could have a total growth of 76.8 cu. ft. per square rod (= 8.71 cu.m/ha) in from 5 to 30 years; this growth should, according to the author continue in equal volumes yearly except in the old age classes. The stumpage price of the yield, consisting of two-fifths of fuel wood, three-fifths of wood for fencing posts and roof poles, was on an average 0.9 shillings per cu.ft (= 0.76 Th/Cu.m). The yield of a 100-year stand was assumed to consist of two-thirds of building timber, priced at 4 sh. per cu. ft. (= 1.62 Th/cu.m), the remainder being used as fuel. v. Thunen here assumed a linear rise in the stumpage price of stands between 30 and 100 years of age and, the value formula (third grade function) of the stands in varying age classes was thus derived. v. Thunen subsequently devotes himself to extensive speculations on the effects of thinnings on the growth and the economic results of forestry. 293 He introduces the concept of forest rent, which includes the interest to the standing timber capital, and notes that while the forest rent increases with the lengthening of the rotation period, the land rent reaches its maximum at a point which is dependent on the intensity of thinning. Having studied the theory of a contemporary forester who recommended thinnings to such an extent that only half of the yearly growth remains in the stand, v. Thunen develops his own ideas, to some extent based on observations, on the optimum distance of trees in relation to the diameter. He comes to the conclusion that the highest land rent is obtained by thinnings which are heavy in the beginning (two-thirds of the growth), but gradually decrease with the age of the stand (being e.g. 1/3 in stands of 45, 1/5 in stands of 85 years). The optimum period of rotation was estimated at 90 years; the rate of interest was assumed to be 4 per cent. As the result of elaborate calculations v. Thunen presented his comparison of the relative advantages of agriculture and forestry, which refers to five site quality classes of land and the market conditions of Tellow. It was assumed that the volume of cuttings was directly proportional to the rye crops typical for the respective site classes. The land rent in agriculture (the existing Koppelwirtschaft in Tellow), in forestry (pine stands in Tellow), the ratios of these, and the forest rent are reproduced, converted in to metric measures, in the following tables. Site quality, measured by Land rent ' Land rent' „ M ~ Forest rent, the crop of agriculture forestry Katio a/t Th/per ha ~,, , . Th/pcr ha Th/per harye (hi/per ha) 25.1 6.28 10.00 0.628 21.16 22.6 4.86 8.92 0.560 18.96 20.1 3.59 7.85 0.474 16.78 17.6 2.44 6.77 0.361 14.59 15.1 1.17 5.70 0.206 12.40 The figures indicate a distinct comparative advantage of forestry, a result which v. Thunen himself found startling and highly noteworthy. The advan- tage of forestry was largest in high site qualities which, according to v. Thunen, contradicted the prevailing opinion. He maintained, however, that in reality, the land rent of forestry in lower site classes may still have been overestimated, as the lower yield consisted of a smaller proportion of building logs than of larger size timber. Recent studies in English speaking countries In Great Britain, after the Second World War, land reclamation as well as afforestation measures have been discussed. During the War, land reclamation was used as an effective means of raising agricultural production (e.g. Trist 1948). Later the rival efforts to achieve food and timber self-sufficiency and thereby to improve the national balance of payments caused differences of opinion between the Ministry of Agriculture and the Forestry Commission, 294 especially with regard to the future use of hill land. Without an economic criterion for a comparison of land use in agriculture or forestry, the planning of land use proved to be difficult. Notable attempts to solve this problem have been made by Walker (1958) and the Land Use Study Group set up by the Committee on Agiculture of the Natural Resources (Technical) Committee (1966). The contribution of Mac Gregor (1959) should also be mentioned. Walker’s study (1958) concerns the major hill land areas of Great Britain (Scotland and Wales), and is based on data of costs and returns for 1953. The agricultural data were obtained from reports published by the Colleges of Agriculture in Scotland and from primary records of the Ministry of Agriculture’s Farm Management Survey. A great deal of the information on forestry was obtained by the Forestry Commission or by eminent scientists. According to the author »a forest cycle of 50 years is assumed; so that the comparison is between the net value added per 100 acres under 50 years with the aggregate of the annual land products per 100 acres under agriculture, each year’s product accruing at interest from the year of origin to the fiftieth year. The net value added by land is obtained by exhausting the gross product (net of direct subsidies) of all non-factor and factor payments except payments to land itself, The residual is then a measure of the value added by land alone, or the price which might be paid for the use of land.» The net product of land in forestry was obtained from estimated gross receipts, accruing at compound interest from the year of origin to the fiftieth year, subtracting costs, similarly prolonged at compound interest. Five alternative rates of interest, viz. 3,4, 5,6, 7 per cent were used, in addition four alternatives of future development in wages and prices were assumed. The results of this study an extract of which is included in Table 1 below point to a distinctive comparative advantage of forestry, when the interest- rate is 3, often even when it is 4; if there is a yearly rise of 1.5 per cent in relative timber prices, even when it is 6 (in two regions even 7). The author believes that the results for forestry can be still better, as a 10—15 per cent fall in costs could be attained by economics of scale, and by eliminating the burden of compound interest, after establishing forests on a basis of sustained yield. The Land Use Study Group (1966), discussing methodology, first defines the choice of indicator, profitability, stating that »if there is no limit on the availability of capital or labour at their market price, then the activity which should be favoured is that which makes the biggest profit per unit area after all costs, including interest, have been taken into account.» Where the capital available over a certain period is insufficient to cover all demands placed on it »the activity yielding the highest profit per unit capital should be preferred.» For the purpose of the study both situations were considered. In the calculations of the Study Group, the different time spans of the two activities are overcome by discounting future expenditures and revenues to the initial year of the project. Three alternative rates, 3,5 and 7, are used. It has been emphasized that the rates adopted are real rates and do not contain any element to cover possible future inflation. The difference between the discounted revenue (D.R.) and discounted expenditure is called net discounted 295 revenue (NDR). It represents the discounted profit from the undertaking over the whole appropriate rotation. This profit is, according to the purpose in question, related to acreage (NDR per acre) or to capital investment (NDR per £ 100 capital). Capital has been defined as »the outlay required to embark on a particular enterprise, and the further expenses incurred up to the point at which it becomes self-financing.» ln addition, a third indicator, the well- known internal rate of return, is used. The Study Group has been interested not only in the profits to private economy, but also in the returns accruing to the Nation from both alternative uses. In principle, the revenue derived from subsidies should have been elimina- ted in calculations concerning the latter. This has been done in the case of production grants and subsidies. A simple deduction of market price subsidies was, however, in the opinion of the Study Group unlikely to result in prices which would correspond to factual prices in a hypothetical situation brought about by the removal of subsidies. Market price subsidies have therefore been included in most calculations on the return to the Nation. Twelve areas were selected for the study. In tire first place on the basis of reliability of data, further, looking for a variety in soil types and in the aspect of scale as it affects current management. Nine areas consisted of marginal, partly unreclaimed land where investments were needed, while in three areas land was currently being farmed at a high level of production. There were cases where the calculations were made for the whole farm (involving full budgeting) , and others, where a given additional area was assumed to be taken into use e.g. by reclamation, which involved partial budgeting. There exists a certain comparability with Walker’s study areas. The prices used in calculations were those prevailing in 1962 64. A forecast of a 1.5 per cent rise in the overall prices of industrial wood, in real terms, is however presented in the Report. As a general conclusion, the Study Group states that »on the extensively farmed marginal areas, agriculture earns a higher return to the Nation and the private owner than does forestry unless the discount rate is a low as 3—4 per cent; and, in areas of better quality farm land, the profitability of agriculture is higher than forestry even at a discount rate as low as 3 per cent.» (p. 64.) Under the hypothesis that market subsidies are removed and the prices remain correspondingly low the majority of the land in the selected areas is unsuitablefor profitable agriculture or forestry at discount rates at or above 5 per cent (p. 79.) A direct comparison of the results of Walker and the Study Group is difficult because the latter is using discounted values, while the former uses values covering the entire rotation period for forestry, but, as it seems to us, simple interest rate accrued values with a yearly increasing trend for ag- riculture. Regarding forestry, the net discounted revenue (NDR) per acre can be made comparable to the land rent when it is divided by the interest rate used in discounting. An interesting feature mentioned in the Report of the Study Group is that forestry in an upland area employs more men per unit area than agriculture. 296 Employment per 100 acres has been on plantations of forest 0.67, in agriculture, on all holdings 0.24 and on full-time farms 0.16 man years. Mac Gregor (1959), in a paper prepared for a course on Land Use for Forestry and Agriculture, discusses several points of view while aiming at comparable calculations of the alternative land uses. He stresses the importance of the rate of interest in forestry calculations, where interest on capital assumes large proportions in the structure of costs, which is applicable irrespective of »whether the forest authority borrows capital from a governement Treasury or not and whether it pays interest or not for although capital may be free to authority it is not free to the economy.» The opportunity cost is here the most relevant one. Finding the physical factors fairly obvious, Mac Gregor thinks it reasonable to expect that the productivity influences in forestry are similar to those in agriculture, while according to him submarginal land for agriculture may often be supra-marginal for forestry and vice versa. A different approach to the problem was adopted in a much earlier study in the U.S.A., performed under the guidance of John D. Black by Messrs. Barraclough and Gould (1954). In this study the optimum combination of agricultural and forest production has been investigated. On the basis of an analysis of a number of farms in New England, production plans were made for nine farms of varying conditions. Three intensity levels of forestry, two assumptions of sawlog prices, and three investment plans for livestock produc- tion with wholesale milk production as the main line, were taken as alter- natives. The calculations on forestry have been made for nine future decades, but the discounting has been left to the owner himself. The preferences of owners for immediate returns over future returns are. according to the study, correlated to the extent at which the existing net farm income maintains their present standard of living, in other words, they seem consistently to discount future returns at a high rate until current income increases to a certain minimum level, thereafter their rate of discounting future income drops sharply. The authors present a number of input-output data and stress the importance of more work for developing better data. The linear programming approach has been applied in more recent studies on land use planning in the Tennessee Valley watershed area. Court» and Ellertsen (1960) have tried by this method to find the most profitable enterprise combinations on individual farms, when forestry activities are considered along with a different line of agricultural production. They took into account different alternatives in forestry management, intensity of stand development, and extent of processing. Different alternatives in factor and product prices and rates of interest (3, 5, 10 per cent) were also assumed. For all enterprises budget estimates of the amount of resources required to yield a specified (100 $) net income were made. The discounted forestry income was converted to an annual basis by using the annuity concept (cf. below, p. 346). Family labour was not assumed to be used in forestry operations as the estimates were based on stumpage values. The method was applied on two case farms, of which one was a small farm, the other a large one. The optimum use of resources provided no forestry activities on the small farm (8 hectares), except in 297 highly favourable timber price conditions (threefold future increase of prices). For the large farm (100 hectares), the use of two-thirds of the land area for forestry, including nearly one third for afforestation by planting was optimal, if a discount rate of 3 per cent, investment of 9 500 $ and good forest management were assumed. Later, further studies were published by Ellertsen and Le Roy Rogers (1965 a, 1965 b) who used the data on six farms in Henderson County, Tennessee. The farms included a selection of sizes ranging from 28 to 116 hectares, of typical soils and different timber growing sites and forest stand conditions. Timber and other farm resources were inventoried, basic input-output data needed for complete farm planning analyses were assembled, and operating plans for each farm were prepared employing linear programming procedures. Several alternatives were presented on similar lines as in the former study. Thus, e.g. three price level alternatives were used for timber: current prices, an average annual increase of 2.5 per cent for the following 25 years, and a respective 5.0 per cent increase. Four discount rates, 4,6, 10 and 15 per cent, were applied (p. 12). A rotation period of 70 years was selected for calculating the present average annual income. The total amount of available labour was determined by the number of men and boys in the farm operator’s family and full-time tenants on the farm. Seasonal restrictions were imposed taking into account the additional limitations caused by the weather. The computat- ions indicated generally a good competitiveness of forestry; even based on current stumpage values and a discount rate of t 6 per cent, the land optimally allocated to forestry ranged from 18 to 77 per cent of the whole farm area (p. 15). Conversion of natural (hardwood) stands to pine plantations was profitable only at low discount rates. Stumpage prices were for pulpwood 4 and 2 $ per cord, for average sawtimber 30 or 20 $ per 1 000 board feet (resp. for pine or hardwood). 1) In the Southern Hemisphere, two contributions, those of Thomson and Grainger (1961) and Treloar and Morison (1962) have been recorded. The former presents some bases for comparing the relative economics of farming and forestry in New Zealand. The authors who are forest economists do not claim full validity for their results which they regard as preliminary for suggested continued research; and refer to many difficulties, e.g. unequal attainments in farming and forestry techniques. They set as their goal compa- isons made on a national, regional, or an individual property basis. The national calculations should be based on prices of the products at the end of the first cycle of production, e.g. factory ex-dairy, ex-woollen mill, ex-sawmill, ex-pulp or paper mill. The above set of comparisons applies only after the forest is a going concern while it ignores the lengthy unremunerative development stage. Taking a local example for a large forest complex in central North Island (Murupara and Waipa Working Circles, Kaingaroa and Whaka forests, 279 000 acres), the ex-mill value of products was in 1960 £ 34.10 s, but which was estimated to increase to £63 per acre. The figures on farming are from farms !) MBF = 1 000 board feet = 219 cu.ft. (2.3(3 cu.m.) Tapion Taskukirja, 15, p. 425. 298 of an average efficiency on better sites of the same type of soils. The sheep farming gives £ 24, while only 10 per cent of the area would be suitable for dairying, with a gross return of £46 per acre. If export values only are taken into account, all North Island contributions to export are £ 20 per acre in farming and £ 40 per acre in forestry, or, if the import requirements for production are deducted, respectively £ 18.10 s. and £ 34.0 s. per acre. If the forestry products are processed and sold as newsprint, it can theoretically be as much as £ 124 per acre (assuming an annual growth of 240 cu.ft. obtained from radiata pine on an average site). The employment in forestry up to the end of the primary stage of production, according to statistics relating to the whole of New Zealand in 1956, indicates twice as many men per acre as in agriculture, viz. 1 man per 96 acres in forestry, 1 man per 197 acres in farming. Treloar and Morison (1962) have made economic comparisons of forestry and agriculture in three areas (Chapman Forest, Blackwood Valley and Natura- liste Leeuwin Horst) in Western Australia. These areas are mostly State or Corporate owned forest land, but regarded as potential areas suitable for clearing for farming. The first study investigates the economics of retaining a tract of forest for the production of hardwood and associated timber products or clearing it for farming; the second and third relate to the comparative economics of pine plantations and farming of various types. A choice of aims that are set in a wider framework than that of the individual farm or locality. The effects of the eventual decisions must, according to the authors, be traced throughout the systems of industries that supply the factors of production, and process the products of each alternative local activity. There are, however, according to the writers, limitations set by difficulties of getting data, and an approximation, where comparisons are made between agriculture at the farm gate and forestry at the level of producing seasoned, dressed timber, pulpwood, or peeled logs, seemed appropriate. The current prices were regarded as valid indicators of social benefits and costs. The authors further assumed that gross incomes resulting from a particular activity provide an approximate measure of the manner and degree to which economic activity in general is affected by that activity. In the methodical part an interesting discussion on the limiting factors in trying to attain optimum results in presented. It is suggested that the capital, regarded »as the sum of actual costs of short-term and long-term services and the costs imputed to any sacrifices of opportunities which may be involved in the use of certain factors of production but which are not covered by tran- sactions», is the limiting resource for long-term national aims in Australia. On the other hand, the policy-makers concerned with the use of land, according to the authors, tend to overlook therelative productivities of the non-landresources. Entrepreneurs who are bidding for tracts of land appear to view the problem similarly, being disposed to impute residual net incomes to land, thus establishing the maximumprice they are willing to offer. Thus, in the opinion of the authors, there is some justificationfor establishing quantitative criteria on the assumption that land is the limiting factor! results of this study are only partially available in printed form. Some results concerning the Blackwood Valley are included in Table 1. The forestry calculations refer to Pinus radiata on site quality 11. The sawn product of a4O year felling cycle was, according to Forest Department records, estimated at 8708 cu.ft. per acre; this corresponds to 1 185 cu.m round wood per hectare. The price per cu.ft. was £ (Austr.) 0.6978 resp. 0.222 Engl. £ per cu.ft. round wood. The net value, after deductions of costs, was 39.5 per cent of the gross value. There were some alternatives for agricultural calculations, one corresponding to 21 average farms, with 260 ha farm land area; this case is taken into Table 1. The others refer to better than average farms or hypothetical budgets. The butter price used in the calculations was 3.83 s./lb, whereof 0.69 s./lb as bounty; the export price was 3.03 s./lb. 1) A German study A paper presented by Abetz (1960) in a meeting of a Committee of Land Consolidation, is of interest in this connection. In his study, gross and net return, farm and family income from farming and farm forestry, are compared on the basis of data of the Green Report (Griiner Bericht) of 1957/58 and of the author’s calculations, based on studies on farm forests in South Baden (Siidba- den); generally the figures refer to the territory of Baden-Wiirttenberg. Large farms are not included in the study. Four types of cultivation: forage, grain combined with forage, grain combined with root crops, root crops combined with grain, are taken into account; forest consisting of spruce with normal age structure and a rotation period of 90 years, and site quality characterized by an average of 10.2 cu.m yearly growth by 100 years rotation is assumed. The price per cu.m has been estimated, according to the prices prevailing in April 1959 and with an arbitrary correction, at 56.0 DM. The labour requirements in forestry are estimated at 1 man-year per 30 ha forest land. The average results of farming are compared with those of forestry in Table 1. It is further stated that equal gross incomes have been obtained on a 26 ha forage farm and on a 33 ha forest area. Studies in the Northern Countries In the Northern Countries, especially since the latter half of the 1950’5, lively interest in comparative studies of land use has been evident.2) In Norway, a stipulation in the Land Law of 1955, enjoining the authorities to adopt social-economic evaluations as the basis of decisions concerning land use, was a starting point. Attempts to fit the trend of agricultural production to the trends of domestic consumption have initiated similar studies in Sweden. There has been interest in these studies also in Denmark and Finland. t) Australian £ is 0.796 English £. 2) In Finland, Jännes presented some calculations already 1939, followed by some criticisms and comments by Marttila (1939 a and b), Kaitera (1939) and Helander (1939). 2 299 300 The contributions of Krog (1954), Jorgensen (1956) and Hjelm (1956) are among the first and deserve to be reviewed here. Krog (1954) ha made the first comparative calculations on the social output of agriculture and forestry. He applies the data of national product calculations, thus aiming at the social output (gross output minus the value of material and services from other sectors, as well as the depreciation of the capital). This social output is set in relation to the agricultural area of the country. As to the forestry social output, this is estimated on the basis of the yield tables of Det Norske Skogsforsoksvesen (Norwegian Forestry Experi- ments) separately for the three best site quality classes, with respective yearly growths of 10.8, 8.2 and 6.1 cu.m per ha. Another estimate is made taking into account also the social income earned for the part of the produce of each type of forestland, in wood-working industries. Comparisons are made for the periods 1930 34, 1935 —39 and 1940 50, and the results of the last mentioned period are included in Table 1. JORGENSEN (1956) compares two alternative uses of a given forest area: continuous use as forest or turning it by reclamation under cultivation into an established new farm. Like Krog, be uses the yield tables taking into account the three best site classes. The agricultural data are the book-keeping results of six size classes of farms in the period 1952—53 from Norges Landbruks- -okonomiske Institutt. Two sets of calculations of net return and family farm income, average and marginal, are presented. The forestry marginal returns are estimated simply by omitting overhead costs, which are assumed to be unaffected by small changes in the area. A marginal return in agriculture, caused by an extension of the cultivated area, may in most cases be larger than an average return, because of the economics of scale (lower labour use per unit, lower costs of fixed capital). An extract of comparison, taking data from size class II (farm inn-mark area 7.22 ha) for agriculture, site class B for forestry, and interest rate 3 in both cases, is reproduced in Table 1. Introducing the marginal principle into the calculations is very important for a correct judgement of various cases of practical relevance. This principle is applied in some calculations presented in the same year by Hjelm(l9s6). Hjelm considers the use of land rent as a measure of the economic advantage of land use, but prefers its capitalized value (»income value», avkastningsvärde), a concept which is evidently more familiar to the foresters. This latter value is calculated either as an average within a size class, or, deriving from the function which indicates the relation of the income values to the size of farm, as a marginal value. In addition, the labour income, per hectare and man hour, is estimated in this case, assuming no rent to the land or the direct investments in land. The calculations on agriculture, although one can agree with the author as to some doubts about the applicability of the used data, are so detailed that not only four farm size classes, but also three different field sizes, and distances to fields, as well as five crop yield levels, have been examined. Two alternatives, one assuming that buildings and land equipment are not at hand and will have to be procured for continued management of the farm; the other implying that no investment is needed in this respect. The data are from book- keeping records (Jordbruksekonomiska undersökningen) 1950/51 1952/53, the 301 South and Central Sweden forested regions and Norrland being chosen as the study areas. The forestry calculations, elaborated by Professor Hagierg at Statens Skogsforskingsinstitut (Forest Research Institute), were based on standard figures for yields and costs in some comparable site quality classes in Smäland and Norrland, and two alternative price levels, one representing 1953/54 market prices, the other a price level 20 per cent below the 1954 prices. The gross prices include costs of logging, net prices were estimated by deducting both direct and indirect costs of logging. Four alternatives of transport costs were further presumed. There is no reference to the used rotation period; probably the optimum period is chosen. No marginal approach has been aimed at in the forestry calculations. It is interesting that Hagberg presents in his tables only land rent figures, while Hjelm in his diagrams has used capital values deduced from these. The large number of calculations for various situations facilitates the use of Hjelm’s study in practical planning. Rough comparisons can be easily made using the graphics presented. As a very general summing up it can be said that if buildings and land improvements are already at hand on the farm, the income value (discounted net revenue) is generally greater in this form than in forestry, provided that there will be a yield of 2 000 to 3 000 crop unitsper ha. There is still a wide margin between the best and the least favourable alternatives in forestry. In the calculations of Hjelm, the land rent in agriculture in most cases appears to be negative, as the family labour is priced according to the tariffs for hired workers. The figures chosen for Table 1, however, refer to the optimal cases, where the size and distance of the fields are favourable, the crop yield is 2 000 or 2 500 f.u. The figures of labour income are calculated by adding the land rent to the compensation of labour according to prevailing wages in forest work, and dividing the sum by the number of hours used per hectare in forestry. A research team was formed in 1957 in Norway to establish the principles to be applied in the economic comparisons of land in agriculture or forestry. In the report of the team (Anvendelse av jord 1959), recommendations for socio-economic as well as managerial calculations were presented. As relatively measurable criterions, rentability, liquidity and security were mentioned. Rentability was defined as the expected long term economic result (net return), the returns in different points of time were made commensurable by discount- ing with a fixed rate. The liquidity, according to the team, could not be expressed by one figure; the basic living costs of the enterpreneur, however, as well as the availability of credit were relevant in this evaluation. An assessing of the discount rate according to the degree of liquidity which was to be expected in future, was recommended to avoid crises of liquidity. The application of the theory of choice (valhandligsteori) was suggested. The evaluation of security was based either on a certain minimum of own capital, or a predetermined minimum of liquid net return; there was no unanimity on the measurability of this criterion. The team recommended both average and marginal calculations. In principle, the effects of the change in area were obtained by determining the difference of returns and costs of the whole enterprise before and after the change. The 302 prices of labour and capital were determined generally according to the principle of the opportunity cost. In the socio-economic calculations the use of import or export prices was recommended or consumer prices reduced by costs of process- ing and transportation. Some studies based on empirical data have been publiched, following the principles suggested by the team. In a study of Elstrand (1961), a budgeting method has been used to test the results in economy of a possible change of land use of two blocks of a farm. Thormodsaeter and Elstrand (1960) analyzed the book-keeping records of some twelve farms in Agder in 1950 57, to find out the returns from agriculture and forestry (see Table 1), and introdu- ced three alternative plans for improved combination of resources. Bjorä (1962), also using the budgeting method, tries to find optimum combinations of activities on various types of farms consisting of 6—12 hectares agricultural and 50—150 hectares forest land. The age composition of forests deviates from even-aged stands, and more refined calculation methods are therefore applied. The combination of forestry with milk production appears to be less advantageous than combining it with a farm plan with low labour requirements, such as sheep or grain farming. Some interesting calculations on the results of capital transfers between agriculture and forestry are also presented. Bossibil- ities of adjusting the fellings in time to the capital requirements are taken into consideration, and a formula of »balance quantum» the maximum yearly cut allowing a sustained yield is introduced. In a study, made jointly by Elstrand and Bjorä (1964), the marginal approach is applied to find out the capitalized value of land in agricultural or forest use. The marginal estimates are carried out in three different ways. The first method, which is based on farm records, is carried out by subtracting the total land value for farms of one size group from the total land value of farms of another size group. The difference is then divided with the difference in acreage for the two size groups and gives thus a rough estimate of the marginal land value (essentially the same method which was used by jorgensen and Hjelm). The second method which is also based on farm records, is marginal estimates derived from the Cobb-Douglas production functions. The third method comprises estimates of the land value when the land is used for certain enterprises such as barley, pasture, milk production or sheep. Both the average and marginal land values are positive in agricultural production when the price of labour is 2 Nkr or less per hour, according to the calculations by the first method; both the other methods give larger values than the first. In the calculations on forestry made by Bjorä, three different concepts are applied, viz. first the ground value (grunnverdi), soil value following the terminology of e.g. Buttrick (1948), which he regards as the average use value, (gjenomsnittlig bruksverdi) where (capitalized) costs varying with time are subtracted. If the time costs are not subtracted, one is dealing with the marginal use value (marginal bruksverdi). The second concept is the expectation value (venteverdi) which is applied in cases where forest production is already taking place. These may likewise be conceived either as average or marginal. Thirdly, the realization value (realisasjonsverdi), presenting the net value of potential fellings. The net loss, when e.g. land clearing has been effected at an unmature 303 stage of a timber stand, equals the difference between the expectation value and the realization value. In this treatise, there are some interesting graphics e.g. on the relative use values of land alternatively to be cleared for agricultural purposes or retained in forestry, when the age of timber stands or the price of labour varies (pp. 62 63). The loss of forest production is largest if the land is taken into cultivation when the trees are in age classes 30 —4O years. The capital loss is then in the best site quality class and dense stand nearly 16 000 Nkr/ha while in the third site class and less dense stands it is about 5 000 Nkr/ha. Agriculture cannot compensate such losses, and is competitive only where mature stands are removed, and the price of labour does not exceed 2 Nkr per hour. Among other recent studies, those of Ledje (1963) and Petrini (1964) in Sweden have brought forth interesting new aspects. Ledje uses data from the Sandby area in the Västland parish in Uppsala province for planning, in which linear and parametric programming are for the first time used. He introduces the afforestation of existing arable land as an alternative in his calculations, while annuities computed from future forest returns using three alternative discount rates are taken as comparable to gross margins (täckningsbidrag) in agricultural production. He presents calculations for three alternative farm sizes and three time periods of different lengths, representing to some extent also different levels of techniques and price ratios. In addition he takes the lease of additional arable land as a variable. In the parametric approach, the supply of capital is successively increased, which first extends the use of land for agricultural production up to leased areas, at a later stage diminishes it, even bringing arable land into afforestation, while the agricultural production tends increasingly to be transformed into utilization of purchased feeds (swine production). In this final stage, the calculations are scarcely interesting for our purposes. The comparison is between forestry and agricultural activities of a kind that do not require land resources. An attempt by Ledje to use dynamic linear programming in the same study deserves special attention. Recognizing the need to adjust the plan to the predictable changes in the resources and to take into account the transfers of accumulated capital from one period to another, the author has applied this method to find optimum combinations for two or three successive periods. Limited possibilities to variance in the premises (conditions) have, according to the author, diminished the practical value of the results. Petrini (1964) has in an interesting study tried to find out the views and supposed motives of Swedish farmers in regard to afforestation. As the economic motive, according to hypothesis, was predominant, a »normative study» to calculate the rational land use on eight selected farms in two areas (Halland and Hälsingland) was made, presuming several production alternatives and using linear programming. An optimal intensity level, approximately corresponding to the fourth highest among the farmers participating in the book-keeping accounts, is assumed for the calculation of the agricultural production. As to the forest production, the better half of the stand analyses, based on Yield Tables from the National Forest Survey and appropriate rotation periods, has been taken as the basis of calculation. 304 The results of the »normative study» indicate that the site class and the rotation period used in the afforestation calculations have considerable influence on the results. In the southern most region the afforestation opportunities are quite profitable if other conditions are favourable to this activity. In the lower part of northern Sweden, profitable afforestation situations occur very seldom. »The afforestation is possible for the lowest layout classes under the assumptions of restricted labour access and high site classes even if there is complete uncertainty concerning the future labour opportunities outside the farm.» As in the study of Ledje, activities which do not require land resources prove to be perhaps excessively competitive in the use of labour and capital as compared to area demanding activities. This may be a consequence of a temporary disproportion between the product prices, and posibly also in the labour use coefficients. (In the former activities the economics of scale plays a larger role). In corporating these activities into the plan tends to cause confusion in the comparison of land use. The »positive» study based on a questionnaire sent to 1421 farmers shows that »afforestation is not easily perceived in a situation of labour surplus on the farm. Afforestation is only weakly related to the labour opportunities outside the farm, since this activity is regarded as a complement to farming by most farmers. Longterm trends in the agricultural and forestry product prices seem to influence the afforestation» (but there is) »a great uncertainty in the expectations of future price tendencies.» »The technical development and the development of agricultural wages seem to be most important.» The »decision theoretical study», performed by Petrini, shows that the »expectations of future tendencies in agriculture and forestry are not of great relevance for the afforestation decision probably due to the fact that there are no prediction models for the estimation of future tendencies in technology and government policy.» When discussing future research projects Petrini states that »there is a great need to analyse in detail the computations in connection with the afforestation decision. To what extent, in which way, and in which situations, is the marginal principle used and understood by those owner-operators who have data for a relative comparison between land used for agricultural and forestry purposes.» These problems are the same that we are confronted with in our study, which mainly deals with decisions to change over land from forestry to agriculture. The present writer has made comparisons of net returns and social income obtained by book-keeping farms in Finland from agriculture and forestry per areal unit (Pihkala 1965). He has also divided the social income into the components labour income, capital return and land rent following the principle that the distribultion should be done in proportion to the input units and prevailing market prices (wages, rate of interest ant market rent). Another member of our group has made some marginal calculations on the contributions of agriculture and forestry to the national product (Holopainen 1967, pp. 99, 100). Table 1. Seleeted results of some previous studies on the comparative advantage of agriculture and forestry computed per hectare British Study Group Coutu- Thomson Treloar, Abetz Krog Jörgen- Elstrand, Elstrand, Hielm, Sweden Pihkala —Holopainen Selkirk Kerry Ellertsen Grainger Morison Baden- Norway 3 ) sen Thormod- BjorA Msk Norr- Finland Scotl. Wales Tennessee Murupara Blackwood W'iir- Nor- saeter Agder*) land 5 ) South Central North unreel, unreel, optimum plan 1 New Valley 2 ) ten- way3 ) Agder Fin- Fin- Fin- small large Zealand berg land land land farm farm Period 1961/62 1961/62 1960 1960 1960 1959/60 1957/58 1946-50 1952/53 1950-57 1958-60 1953/54 1953/54 1958/59-1962/63 Unit of money £ £ $ $ NZ £ Austr. £ DM. NKr. NKr. NKr. NKr. SKr. SKr. mk mk mk National product6 ) agr. .... 46.3 12.2 . 1064 . ..... 416') forestry .... 85.0 166.3 . 828 ca.600 ..... 352') Gross output agr. 5.62 .... 12.65 1334 1064 967 1977 3600 ..... forestry 11.55 .... 67.08 414 332 90 147 . 287 157 . . Social output or gross margin agr. . . GM2OO GM3OS 60.0 9.09 594 . . 1057 2160 . . 599 544 515 forestry ... 17 86.3») 57.75 378 . . 146 287 157 68 46 19 Net return per ha agr. .... . 2.71 14.85.6-99 -341 . . 141 -13 -38 forestry .... . . 269..76 . 175 88 39 26 7 Labour income per ha agr. . . 200 247 . 6.38 472 . . 862 1240 446 287 489 482 452 forestry . . -14 . 212 58 . 112 69 28 16 9 Labour income, aver, per hour/ day/or year agr. . . h 1.97 h 1.87 . y 1095 y2850 d 9.71 h2.16h 1.88 h2.78h 1.18h 1.03h 1.61 hi. 19 hi. 11 forestry .. --..y 6360 d48.90 h7.38h 3.71 h(ca.s:-h 3.11h 3.29h 1.61 hi. 19 hi. 11 Land rent, private, per ha agr. 1.58 4.35 ...... -171 . -577 60 27 45 15 13 forestry 9.00 5.18 . . . . . .90 . 96 64 22 19 16 4 Land rent, Nation, per ha agr. 1.12 3.83 ... . . . . .-- forestry 6.45 2.70 ... . . ...... *) Conservative timber price estimate. 2 ) Pinus radiata, S. Q. II (better than averagesoil). Rotation 40 years, growth in aver.29.6 cu. m (s) per ha/year. Net return of clear felling 20 £ per 100 cu. ft. round. Austr. £ = 0.7958 Engl. £. 3 ) Site class B (medium). *) Farm size class II (5 10 ha). Forest site quality class B, rotation 65 years. Volume cost 40 kr/cu. m, 3 per cent rate of interest. 6 ) Site class II in MSK, IV in Norrland. The results in agriculture of the farms with 9—lo hectares cultivated land, crop yields 25 or 20 fu. per ha, av. distance to field 500 m and size of field blocks 2 ha. 6 ) Includes the income obtained in industrial processing, subsidies generally excluded. 7 ) Country average. 306 111. Aim and scope of this study Decisions on land clearing, as well as on afforestation, are long-term decisions influenced by elements of uncertainty on future events and by time preferences of individuals. According to Heady (1952, p. 382) »it is time considerations in production which give rise to the real difficulties in decision making». Compari- sons of the alternative activities chosen through the decision are perhaps still more complicated, as the one activity, in this case agriculture, gives returns much sooner than the other, forestry, while the latter requires much less initial capital than the former. Another complicating factor is the greatly differing extent of employment offered by the alternative activities. In the conditions that are of special interest in a country like Finland, the fact that most of the said decisions are made in family enterprises where agriculture and forestry are carried on with combined resources, constitutes a third complicating factor, especially since there are other types of firms, devoted to forestry and processing of forest products, again with combined resources. Within the prevailing type of society, in which Government intervention of various kinds affects economic activity, there are further difficulties, since the decisions which are advantageous to private owners, may be less desirable from the point of view of society, i.e. of national economy. Finally, there is a complication caused by the fact that agricultural production can be expanded by using increasing amounts of purchased feeds and other capital goods. It is doubtful whether in such cases it is justifiable to speak of a return to the land. There are, moreover, difficulties which are mainly of a technical nature. In a country like Finland, where local soil types are varied and uneven, form- ing small figures, it is not easy to find forest and cultivated fields that are strictly comparable by natural conditions of growth. The management level not only of the fields, but also of the forests varies greatly and, for comparison purposes has to be considered very carefully. In addition reliable forecasting of production is undoubtedly one of the weakest points. One can scarcely proceed from the hypothesis that all land now in agricultural use is directly comparable to the land covered by forests; generally the forests cover soil of lower quality. It may be more realistic to assume, that recently cleared land areas are comparable to the adjoining forest areas. But even this is not necessarily so since farmers naturally choose the sites for agricultural use among the better localities of their possessions. 307 In the present study, the main interest is devoted to the following problems which are typical of situations where a decision relating to the transfer of a certain piece of land from forestry use to agricultural use has to be made. (1) How to estimate the continuous (sustained) return from a technical unit of land to the owner, owner-occupier or the national economy, in alternative uses, on most common soil types and market situations. This comparison refers on an average to the period of a production cycle in forestry (rotation) and does not take into account changes in the economic unit; (2) Should we estimate on the basis of factual results or to assume an optimum plan? (3) What is the comparability of short term results, (e.g. within 10 or 20 years) in various situations, where e.g. the age and volume of the timber stands vary; (4) The return to the investment eventually needed in connection with the transfer from one use to another; (5) What advantages may be expected from the transfer if an optimum use of the resources within an economic unit is the ultimate aim. It seems to the writer that the traditional approach, directed to estimate comparable land rents for both uses, is still the most advisable one, being more simple to understand and involving less complications than the comparisons of net discounted revenues. There is, admittedly, no difference in the ratios between the quantities indicated by these two methods of expression, provided that the same interest rate is used in discounting and capitalizing. In fact, often not only the agricultural, but also the forestry revenues, at least when the sustained yield principle has been followed, may in the long term calcula- tions be estimated as being continuous and may even, as the agricultural revenue, favour a simpler expression. There exist, on the other hand, so many differences of opinion on the rate to be used in discounting, and what is even more important, on the applicability of the same rate of interest in capitalizing the short run income or discounting remote future incomes that presenting to the reader many alternatives of rates is always needed, and the confusion caused by chosing between them is left to the reader. There are cases where the returns of single stands are rather continuous (un-even stands, Plenterwald), and land clearing is thus simply stopping the flow of forest income. Recent inventories of the tree stands of Finland, e.g., have indicated that especially the spruce stands have widely developed from the undergrowth of the older age classes (Mikola 1966, pp. 47, 16). Though the cases where the selective cuttings are going on periodically in nearly equal quantities may be rare, these may also be taken into account when examining the situations which the decision maker has to meet. In such cases the discount- ing of future incomes has no special relevance. But, it may be remarked, in most actual cases of land clearing, as well as afforestation, a choice must be made between immediate revenue from agri- cultural production or future revenue from forest. However, according to a widely held opinion among Finnish forest economists, the sustained yield principle applied in farm forests, allows some elasticity in the periodic fellings, so that e.g. the establishing of new plantations will soon justify larger yearly 308 cuttings, while land clearing, which may temporarily increase the supply of timber, only gradually allows reduced cutting. Whatever the case, the land rent can also be conceived as an annual payment (rental) which entitles to a future liquid asset (this is called annuity by Butt- rick). 1) One may imagine a market where securities granting future felling rights would be sold against annual payments. This rate would depend on the rate of discount and the prevailing opinion about the long-term develop- ment of timber prices and costs of felling, as well as in each single case, on the valuation of the growth and quality development of the stands. If such a market existed, the individual decision maker could always compare the returns of both land uses in liquid from. The imperfections of the market could perhaps lead to erroneous annuity values: uncertainty would play an excessive role, but in principle, there would be no difference, as all cost calculations involve some uncertainty in price forecasts. Although a market like this can scarcely be expected ever to become a reality, it is possible to imagine that a certain potential demand of such securities would arise not only on the part of the wood-working industries which would wish to guarantee the continuous flow of raw materials but also from pension funds and individuals who would be prepared to invest their money with full guarantee against inflation. On the potential supply side, on the other hand, would be the landowners whose preference for current income would be so strong that they would be ready to surrender their future income against a smaller present income. The price of time preference, i.e. the rate of discount, would then be determined for securities redeemable at different times by the supply and demand. Irrespective of the absence of such a market, a valuation of the present value of a future income is in fact taking place, e.g. to the extent of credit that is demanded or granted against mortgages on forest growing pieces of land. The traditional land rent approach does not, however, as shown in some contributions reviewed above, measure the other relevant dimensions of the comparison, viz. how to rate the share of other resources, labour and capital in the comparisons. The merits of both alternatives should in certain cases be judged, either by claiming high land rent and labour earnings to the worker simultaneously, or by relaxing the claim of high land rent in favour of labour income; or in some cases by regarding a low labour requirement as a merit. The alternatives may also be judged according to the rate of profit which accrues on investment, or, if capital is short, according to the need of investment or, if capital is short, according to the need of investment for a given level of income. In many practical cases, the most advantageous use of land presupposes an optimum combination of land use for agriculture and forestry within an economic unit. Since it appears that the problem of comparing the above land uses is a complicated one, and the finding of an answer of general applicability seems difficult, we shall now attempt to study cases of comparison. Vn(o,op) J) Ci. Buttrick (1943, p. 114). The formula of annual payment (AR) is AR = > where Vn is the value of a sum after it has been at interest for n years, p = rate 1-0 P n —1 of discounting. 309 IV. A field study on number of pioneer farms in four regions in Finland Method used in the field study Some calculations on the comparative advantage of land clearing as an alternative in efforts to improve the food situation during the first post-war years were made by the present author. These calculations were submitted to the Board of Pellonraivaus Oy, and aLand Settlement Investigation Committee, but were not published. As statistical averages were used in the calculations, it seemed difficult to claim for them a high degree of reliability. Since under the Land Settlement Programme, over 16 000 so-called »cold farms» had been established, i.e. holdings which received their land almost exclusively in the form of forest or peat land, a study of the productivity of the newly-cleared land on these farms was suggested. It seemed probable that also the original character of the forest land taken into cultivation could be ascertained and thus comparable calculations could be made on the alternative uses. After the financial means for a comparative study had been obtained, as mentioned in the preface, a study plan was made, in which the collection of primary data from three main areas representing differing climatical and market conditions was outlined. In each main area a few subareas were chosen, covering in most cases a group settlement area representing typical conditions, and in each subarea, a 50 per cent random sample was taken. In 1959 a hundred farms were thus selected in each main area, viz. in South Finland (SF) around Lahti— Kouvola —Heinola, in Middle Finland (MF) around Kuopio —lisalmi Joensuu, and in North Eastern Finland (NE) Salla—Kuusamo —Suomussalmi. Two years later, a fourth zone with again a hundred farms representing poor soils in Western Finland (W) around Ikaalinen —Parkano Karvia was adopted as a study object. In this area the study farms lay more widely apart than in the others. The North Eastern study area extends from 64°30’ latitude to 67°, and as climatic differences are rather large, it seems advisable to treat it as being divided into three subareas. These are, from South to North, Suomussalmi (Ssm), Kuusamo (Ku) and Salla (Sa). The location of the main study areas as well as the above mentioned subareas is illustrated in the map of Finland in Fig. I. 1) *) There are a few monographic descriptions of some subareas in our study (Mead 1951, Ehlers 1968, Mäki 1955, Kaukonen 1956, Pakkanen 1956, Rönty 1958). 310 It was hoped to find study areas representing typical pioneer farming areas, and farms with rather homogenous soil distribution. There were, however, relatively few cases, mainly in the SF main area, where only little variance in the soil type was discernible. In most areas there had been a tendency to provide the holdings with blocks of at least two types, mineral and peat soil. The maps of some subareas, reproduced in the mimeographed report, give some idea of the varying soil conditions.2). 2 ) Some maps are published by Lasola (1965). Fig. 1. Location of study areas. 311 All the farms chosen in the samples were not willing to cooperate in the study. The non-attendance varied mostly between 5 and 15 per cent, but was during the first year in the NE area nearly 50 per cent and in MF in 1962, as the result of a bad year, 40 per cent. In the NE area, a complementary enquiry was carried out in 1964 and the crop yields were recorded in this connection. The data on agricultural production A recording of crop yields and use of fertilizers and lime was organized on the study farms for a period of five years (1959—63), except in the last- mentioned main area, where records were kept only in 1961 63. The methods used in the crop estimation are described in detail by Lasola (1965, pp. 45 49, 119—123). Suffice it here to mention that grain and root crops as a rule were measured when stored, the hay crop was estimated counting the hay poles and weighing the hay of a sample of poles on the field. The objective method of crop estimation was applied in 1962 as a control, and in 1963 in most study areas as the only method. The cultivated areas reported upon by farmers were in principle checked by simple measurements; in 1962 field maps were drawn in cases where they were not previously available. The yield of arable land used on pasture was, in the study of Lasola, estimated on the basis of records on pasturing days, milk production and supp- lemental food given. Observations on pasture yields, however, were possible only in about two thirds of the cases (Lasola 1965, p. 101). There were further difficulties in dividing the yield between the whole-season pasture and the aftermath of hayfields, and in some cases of wood-land pastures. It therefore seemed advisable to estimate the pasturage in some other way, and partic- ularly by assuming an equal fodder unit yield on the grasslands used for pastures and on those cut for hay. In addition the aftermath is taken into consideration when estimating the utilizable yields of hay-fields as well as the grazed areas. The aftermath is estimated at 30 per cent in Southern and Western areas, at 25 in the MF area and at 20 per cent in the NE area. The latter figures are based on some experiments reported by Poijärvi (1934, pp. 120—121) and Pihkala and Lasola (1973, p. 385). The total crop yield and the average yield per hectare were expressed in Scandinavian fodder units (f.u.). In the respective calculations straw, tops and other byproducts were included in the rate used in agricultural statistics. The information on agriculture from study farms included also some data which facilitated the estimation of the animal production. No complete financial records were obtainable, and economic calculations were thus built on technical data and available information on prices. Some figures characterizing the land use and economic size of study farms The averages presented in Table 2 on the following page give an indication of the land resources of study farms, as well as of these farms as economic units. 312 Table 2. Figures characterizing the average economic size of study farms. T , , , i Milk Meadows „ , . T - ,armer ra e o^aj Cattle Milk deliveries + cleared r ° UC _npro , \\ras^e family land , . ' ive forest , , .J . crop f.u. units cows kg per pasture , . , , , , land ha size ha r D r \ , , forest ha land hayear land ha SF 4.4 8.95 16 620 6.9 4.2 W 5.5 6.13 9 325 5.3 3.0 MF 5.5 7.85 10 520 6.1 3.6 NE 6.9 5.56 8 400 5.5 3.3 Ssm 6.4 7.88 11 270 6.5 4.4 Ku 8.3 3.07 5 235 4.2 2.7 Sa 5.8 6.87 8 875 5.7 3.9 11317 0.78 14.42 1.01 0.65 5 733 0.25 39.86 4.15 5.74 6 210 0.60 43.25 7.27 4.80 4 548 4.10 104.44 33.81 57.29 9 082 0.06 86.06 28.05 30.93 4 639 3.66 91.55 39.76 73.73 7 281 7.88 128.55 30.47 53.71 According to the prevalent opinion, the average cultivated area of the study farms is below the optimum at least if agriculture forms the sole source of income; for their living the farmers evidently depend on forest returns and non-farmincome. It is not possible to detect the exact economic results obtained on these farms; the data collected would not be sufficient any way. Instead the collected data should be used for calculations of a general application, where the available data of the Profitability Investigation of the Agricultural Econom- ics Research Institute are used for completion. Relevant to this study are thus the crop yields and the inputs especially in the form of fertilizers and lime; as to the seed volume, standard values are used. There may be other inputs, improved seed, insecticides etc., as well as varying labour inputs in tilling, but in our opinion in the methods of cultivation, the average study farms scarcely differ from the level of progressive farms in their localities to such an extent that the different methods of cultivation would cause marked differences in hectare yields. The differences caused by the site quality and microclimatic variations, however, are noteworthy and relevant to this study. The main crops and the use of fertilizers and lime On the use of arable land for crops as well as on the crop yields in the main study areas, as well as in the three north-eastern subareas, data are presented in Table 3. The pattern of cultivation in the southern and northern study areas is markedly different. Bread grain and other marketable crops become less significant when moving northwards; only barley and potatoes are supplementary to grassland in the North Eastern main area. Crop yields generally decline; crop failures are more frequent towards the north. The year 1962 was unfavourable in the whole country, but especially in the main areas of Middle Finland and the North Eastern area, where grain and potatoes gave only half or one third of the normal yield, or even less; 1964 was again unfavourable in North Finland. It should be noted, however, that the hayfields in the North Eastern area have given rather high yields, thanks to heavy doses of nitrogen fertilizer. The potato crops are in the North Eastern area on an average fully comparable with the crops in the main area of South Finland. 313 Table 3. The percentage share of each of main crops of total arable area (A) and the crop yields per hectare, dt, or converted into f.u. (100) (B). Bread Feed Sugar Grassland Total Potatoes , , , , , , , Other Fallow Total grains grains beets for hay for past. grassl. A SF 15.0 27.5 2.0 1.4 38.4 11.7 50.1 2.1 1.9 100 W 7.2 30.9 2.5 0.6 39.5 13.0 52.5 1.5 4.8 100 MF 3.0 21.8 2.1 0.1 49.6 14.2 63.8 2.9 6.3 100 NE 0.2 14.2 1.6 62.7 19.9 76.9 1.4 100 Ssm 0.8 19.8 2.1 54.1 21.8 75.9 1.4 100 Ku 19.9 2.1 68.7 7.9 76.6 1.4 100 Sa 7.8 1.2 65.2 24.4 89.6 1.4 100 dt. f.u. 1) dt. dt. dt. f.u. 2 ) f.u.3 ) Fodder units4) f.u. 5) B gross net gross SF 18.8 17.5 175.4 204.0 38.4 27.2 20.0 20.9 20.1 26.99 W 12.6 14.3 146.1 133.6 39.1 22.5 20.3 17.4 16.7 23.87 MF 13.8 13.2 138.6 84.0 34.1 12.7 17.1 15.4 14.6 NE 10.3 143.7 45.3 17.8 17.4 17.8 17.4 22.62 Ssm 14.5 154.5 42.0 . 20.2 18.3 17.7 Ku 8.7 146.0 - 52.9 . 25.9 18.5 18.1 Sa 9.7 134.9 40.7 . 19.5 17.1 16.8 ') not including straw. 2 ) Estimate of Lasola (p. 101). 3) Estimate where aftermath is included and yield of pasture assumed to be equal to that of cut hayfield. 4) Including straw, tops etc,, not inch pasture or aftermath. 5) The fodder unit yields of the book-keeping farms (under 10 hectares) of the Profitability Investigation are presented for comparison. The figures in Table 4 indicate the volumes of plant nutrients in fertilizers and lime used for crops and cultivated pasture, in average per hectare, 1959 63.2) The value of plant nutrients per hectare, according to the prices paid at delivery points, is shown in the last column. Table 4. The use of plant nutrients in fertilizers and lime on the study farms, kg per hectare. Nitrogen Phosphorus Potassium Lime Value of plant nutrients 1)N P 205 K 2O CaO SF 32 54 28 72 75:57 W 21 32 27 117 54:66 MF 31 38 28 69 65:30 NE 60 66 89 32 127:96 Ssm 63 72 94 14 134:93 Ku 62 76 100 67 141:39 Sa 57 53 76 17 115:74 Average use in the country 22.2 37.3 27.1 1 ) In West Finland area 1961 63, in NE in most cases 1960 64. 2) Here, as well as in later calculations, the new Fmk, (1 $ = 3:22), according to the exchange rate of 1963, is used. 314 It is interesting to note that the use of plant nutrients in fertilizers has in all study areas, except Western Finland, been larger than the average in the whole country. The figures on the North Eastern area are unexpectedly high heavy fertilizing, especially of grassland, is, however, a fact on study farms, which in this respect are on a much higher intensity level than the average farms in these regions. (Also the hay crop yield is about 10 dt higher.) For economic calculation it would be important to know to what extent the used average doses of fertilizers correspond to the requirement for getting optimum economic results of respective agricultural production. Lasola (1965, pp. 102—107, 167) tried to examine the relation of crop yields and fertilizer inputs on the study farms, using the multiple regression analysis. A distinct positive correlation was found in SF and W between the volume of plant nutrients and crop yields in f.u., this was rather distinct also in the MF area; in the NE study area the results are somewhat unclear. The method is prabably not suitable for estimating the production funct'on of fertilizer inputs. 1) Other evidence shows that e.g. the hay crops of North Finland peat soils vary greatly irrepective of fertilizing (Valmari 1957 a, pp. 18 33; Puustjärvi 1959, pp. 88 90). The marketable crop and its value In Table 5, based mainly on figures presented in Table 3, the net crops of bread and feed grain, as well as of potatoes, are computed, subtracting the normal use of seed (rye 170 kg, spring wheat 260 kg, barley 220 kg, oats 200 kg, potato 2700 kg per hectare), and calculated per hectare of cultivated farm area. In this table the quantities are presented in fodder units. There is also an estimate on the value of the marketable crop. In this calculation are used the producer prices of regions covering the study areas, over the economic years 1959/60 1963/64 (Appendix I). An exception is made regarding potatoes, the cultivation of which on the study farms is mainly for family consumption. The quantities corresponding to the consumption figures observed by the Rural Consumption Investigation 1959/60 have been priced according to the retail prices recorded by the Bureau of Social Research, an average for 1959—63, while only the rest has been rated as per producer prices. *) E. g. Weinschenck (1966, p.93) stresses the danger of »hybrid production function», as well as the difficulty of quantifizing the climatic factor should this be used as an independent variable. Table 5. The marketable crop from arable land, by main study areas, per total area of cultivated land (inch pasture), (A) quantity in fodder units, (B) value in mks per ha. SF W MF NE Ssm Ku Sa A Bread grain 218 77 32 8 - - Feed grain 388 393 218 120 195 124 45 Potatoes 50 60 70 34 42 46 20 Sugar beet 57 23 713 553 320 154 245 170 65 B Bread grain 102:24 38:92 15:01 - - - - Feed grain 129:98 130:31 71:72 36:- 58:50 37:20 13:50 Potatoes 34:53 33:04 49:17 31:44 30:36 48:87 21:60 Sugar beet 27:65 9:89 294:40 212:09 135:90 67:44 88:86 86:07 35:10 The data on milk production No complete data on the animal production of the study farms could be obtained. However a number of milk herds kept records for milk herd recording associations. As practically all the farms regularly sent most of their marketable milk to comparatively few large dairies, relatively reliable datafor the estimation of this highly important market product were available for the study. Regard- ing other animal production there were less data. To complete these figures, the farm consumption of milk and direct sales to the consumers had to be estimated. For the former, the figures of the Rural Consumption Investigation (1959/60) on the annual consumption of farmer families in four regions (South Finland, Middle Finland, Ostrobothnia and North-East Finland), are available. If adjusted to the family size of the study farms in proportion with the number of family members, the estimated milk consumption figures of 1376, 1720, 1665 and 2249 kg (for the main study areas SF, W, MF and NE, respectively) can be used. The direct sales to consumers were estimated using figures from agricultural statistics. There may be, to a smaller extent, also consumption of home produced butter, and small quantities of cheese. Using the figures of the Rural Con- sumption Investigation, with similar adjustments as used for milk, the estimated volumes of home butter would be 4.3, 5.5, 16.9 and 23.5 kg per farm, respectively. Using the data on milk deliveries with the above mentioned complementary estimates, the following figures of milk production may be presented (Table 6). The figures of study farms which are members of the milk recording associations, and the regional averages of the associations are also tabulated. From the figures it appears that some differences exist in the milk produc- tion per cow between the main study areas. These differences may to some extent affect the net values of the non-marketable crops. A special calculation, as stated below, has been made on this item. 3 315 316 Table 6. Data on milk deliveries, estimate of milk production of the study farms, total and per cow, and average milk production per cow within milk recording associations and the Profitability Investigation farms of regions most closely covering the study areas, kg. SF W MF NE Subareas Ssm Ku Sa Aver. No. of cows .... 4.22 2.96 3.61 3.31 4.43 2.74 3.87 Yearly deliveries of milk, kg 12486 6489 7 019 6 709 10 692 4 639 7 281 Home use of milk, kg 1 376 1 720 1 665 2 249 2 087 2 705 1 890 Home use of butter, in milk equiv., kg 106 132 (405) (564) Direct sales of milk, kg 647 350 422 (405) (405) 342 300 Computed prod, kg ... 14 615 8 691 9 511 9 927 13 748 8 250 10 035 Computed prod, per cow, kg 3463 2936 2 635 2 999 3 103 3 010 2 593 Av. of milk recording study farms, kg 3 922 3 426 2 763 3 408 3 501 3 671 3 199 Av. of milk rec. associations, kg 4 268 3 860 3 650 3 097 3 206 3 380 2 987 Av. of bookkeeping Yearly deliveries of farms, & Le Roy Rogers 1965 b. Guide to Planning Farm Forestry Activities on Coastal Plain and Associated Soils in West Tennessee and Adjoining Areas. TVA, 44 p. (Stencil). Elstrand, E. 1961. Jord nyttet til jordbruk eller skogbruk. Norges Landbruksokonomiske Institutt' Saermeld. 31. 86 p. Oslo. —i> & Bjorä, E. 1954. Bruksverdier i jord- og skogbruk. 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(Summary: Factor cost prices in Finnish agriculture and industry compared with international market prices 1953 1958.) Suomen Pankin Taloustieteellisen Tutkimuslaitoksen julkaisuja B: 22. 155 p. Helsinki. Vuokila, Y. 1956. Etelä-Suomen hoidettujen kuusikoiden kehityksestä. (Summary: On the development of managed spruce stands in Southern Finland.) MTJ 48,1. 138 p. Hel- sinki. » 1967. Eriasteisin kasvatushakkuin käsiteltyjen männiköiden kasvu- ja tuotostaulukot maan eteläistä sisäosaa varten. (Summary: Growth and yield tables for pine stands treated with intermediate cuttings of varying degree for southern Central Finland.) MTJ 63,2. 123 p. Helsinki. Walker, K, R, 1956. The Forestry Commission and the Use of Hill Land. Scottish Journal of Political Economy, Vol. 7: 14 35. Weinschenck, G, 1966. Recent applications of quantitativeresearch in agricultural economics. Proceedings of the 12th International Conference of Agricultural Economists, p. 92 114. London. Westermarck, N. & Mel£n, A. 1962. Praktisk driftsplanläggning. Svenska Lantbrukssäll- skapens Förbund. Ser, B, 28. 153 p. Borgä, Wood: World trends and prospects. FAO. Rome 1967. Varon & Heady. 1961. Approximate and Exact Solution to Non-Linear Programming Problem with Separable Objective Function. Journal of Farm Economics 43,1: 57 70. Zapf, R. 1965. Zur Anwendung der linearen Optimierung in der landwirtschaftlichen Betrieb- splanung. Berichte iiber Landwirtschaft. NF. 179. 102 p. Selostus Metsämailla suoritettujen uudisraivausten taloudellisuudesta K. U. Pihkala Tutkimusselostuksessa käsitellään tehtävän määrittelyn jälkeen aikaisempia, maan maata- loudellisen ja metsätaloudellisen käytön taloudellisia vertailuja, jolloin erityistä huomiota on kiinnitetty menetelmiin. Eräitä lukuja tällaisista tutkimuksista on vertailevasti esitetty tau- lukossa 1, p. 305. Varsinaisen tutkimuksen aineisto on kerätty 1959 —63 n. neljältä sadalta metsämaalle pe- rustetulta asutustilalta neljältä eri pääalueelta Suomessa (vrt. kartta s. 310). Perustiedot maa- taloustuotannosta koskevat lähinnä satomääriä ja maidon toimituksia meijereihin, joiden pohjalta eräiden täydennysarviointien jälkeen ja käyttäen hyväksi alueellisia hintatietoja ja kirjanpitotilojen keskimääräisiä kustannuslukuja on arvioitu maatalouden antama todennäköi- nen kansantaloudellinen tulo (social output), puhdastuotto (taxable net return) ja maankorko (land rent) hehtaaria kohden. Viimeksi mainittuja laskettaessa on tehollisen työn hinnoitte- lussa sovellettu kahta vaihtoehtoa: 1. maaseudun teollisuustyöntekijäin 2. palkalla työskente- levän maataloustyöntekijän aikayksikköä kohden saama ansio. Metsän tuottoa koskevat arviot perustuvat osaksi tutkimustiloilla suoritettuihin havaintoihin metsätyypeistä ja puustosta, osaksi kasvu- ja tuottotaulukoihin. Keskimääräiset hakkuut oletetun edullisimman kierto- ajan kuluessa on arvioitu ja hinnoiteltu puutavaralajeittain, ja myös puun korjuusta saatava työansio on arvioitu. Päätulokset arvioista on esitetty neljän pääalueen ja kolmen pohjois- suomalaisen ala-alueen osalta taulukoissa 14 ja 19. yhteenvedon tapaan myös s. 338 339. 369 Kun uudisraivausten taloudellinen edullisuus vaihtelee tilakohtaisesti, on vastaavia tulos- lukuja pyritty selvittämään myöskin marginaalilaskelmilla, joissa on arvioitu viljelmän pelto- alan yhden hehtaarin, sekä myöskin sijoitetun pääoma- ja työyksikön lisäyksen vaikutus (Luku V). Kuten luvussa VII on esitetty, lineaariseen ohjelmointiin perustuva laskutapa on teoreettisesti parempi, mutta sen soveltaminen on jäänyt toisessa yhteydessä suoritettavaksi. Uudisraivausten edullisuutta arvioitaessa joudutaan kiinnittämään huomiota myös rai- vausten kustannuksiin ja niiden rahoitukseen. Edelleen joudutaan ottamaan huomioon myös menetettävän metsäntuotoksen arvo. Sitä arvioitaessa osoittautuu tärkeäksi mm. niiden puustojen kypsyysaste, jotka joutuvat raivauksen kohteeksi (Luku VI). Tulon menetyksen arvioinnissa on sovellettu kolmea vaihtoehtoista menettelyä, joista yksi tähtää odotusarvon koron (interest on expectation value), toinen kiertoajan jäljellä olevana jaksona saatavan vuotuistulon (annuity) ja kolmas seuraavana 10-vuotiskautena tapahtuvan arvokasvun (value growth) määrittämiseen. Kun puuston markkina-arvon korko (3 % mukaan) on vähennyste- kijänä otettava huomioon, menetys vaihtelee kiertoajan eri vaiheissa jopa moninkertaisesti (vrt. taul. 21). Laskelmien epävarma kohta on tietenkin tuleva hintakehitys, jota on vaikea arvioida. Taulukossa 22 s. 351 on vastaavia arviolukuja esitetty olettaen, että puun kanto- hinnat yleiseen hintatasoon verrattuina kohoaisivat kymmenvuotiskausittain 5 prosentilla. Uudisraivausten merkitystä joudutaan arvostelemaan myöskin kansantaloudelliselta kan- nalta. Vertailu perustuu tällöin nettokansantuotteeseen (NNP), joka saavutetaan kummankin tuotannon kautta. Tällaisissa laskelmissa on otettu huomioon myös alkutuotantoon perustuva toisen asteen tuotanto (kuljetukset, teollinen jalostus). Hinnoittelussa on maailmanmarkkinoilla liikkuvien tuotteiden osalta käytetty hintoja, joiden on arvioitu muodostuvan, jos tärkeimmät kulutusmaat siirtyisivät vapaan kaupan kannalle. Näillä perusteilla lasketut nettokansan- tuotteen arvot hehtaaria kohden tutkimusalueittain on yhteenvedon tapaan esitetty taulu- koissa 23 ja 24 sekä sivulla 360. Tähän tutkimukseen liittyviä tuloksia on aikaisemmin suomeksi esitetty julkaisuissa Lasola (1965), Maatalouskomitean mietintö (kom. miet. 1962:6 Liite VIII, 161 180), sekä Pihkala & Lasola (1973). 370 Appendix i Price structures relevant to this study The economic calculations of this study are based as a rule on the average nominal prices prevailing in the period 1959—63 (or assuming an alternative where to the prices of forest products an approximate 5 per cent increase per decade has been added). The price trends and fluctuations of agricultural and forest products before and during the study period are discussed in detail in an earlier study (Pihkala 1965, pp. 7 19). At the time of finishing the manuscript, price data of five years following the study period are available; these facilitate the levelling of cyclical variations especially characteristic of lumber prices, but do not give a reliable basis for long-term predictions. We do not venture on predictions in this connection, especially as the existing international forecasts only refer to the consumption assuming no changes in the relationship between the prices of wood and nearest substitutes (Wood: World Trends and Prospects. EAO, Rome 1967, p. 2.). The recent trends are visible in Figures 1 and 2. These, as well as other changes, are based on deflated prices, i.e. nominal prices divided by the index of wholesale prices (general index for home market goods). Political factors greatly influence the development of agricultural prices and rural wages; the latter, for their part, influence the stumpage prices. The inflationary tendencies which seem inevitably to be connected with post-war economic development, further aggravate the difficulties of price prediction. The prices of agricultural products were under the period of study regulated by theLaw on Farm Price Level of 1958, in which fixed prices were guaranteed for wheat and rye and target prices for milk, pork and eggs, to ensure to the farmers a stabilized income in relation to the cost items, including the wages of agricultural labourers. This law was to some extent revised in 1962. There were complementary decrees, regarding some other products; various subsidies were stipulated among others on a regional basis. For example, the milk prices were subsidized in Northern Finland and some other regions, and special subsidies were paid according to the number of milk cows. There was some surplus production in agriculture which had to be exported on export sub- sidies. Thus 18 200 to butter, 17 200 to cheese and 4 000 to milk powder was exported in 1959 63, corresponding to the processed produce of 16 per cent of the total milk production. The export prices were only about 40 per cent of the domestic wholesale prices. For the calcul- ation of the advantage to national economy, milk prices are reduced to an extent which is sufficient to pay the export premiums of the total gross value of the milk production. The five year average prices of agricultural products relevant to this study are collected into Table 2, where the regional averages of producer prices are taken for most products from the statistics of the Marketing Research Institute of the Pellervo-Society. 1) The milk prices ') The statistics are based on the prices paid by a sample of farmer cooperatives, weighed monthly by bought quantities. The regional division (South Finland, Central Finland and Ostrobothnia) corresponds only approximately to the division of this study. Only national averages are published (Pellervon Kalenteri). are actual prices received by the owners of study farms. They include the subsidies paid direct to the farmers. The subsidies paid according to the number of cows are mentioned separately, estimated as averages of study farms, differing in relation to the possibilities of sharing these subsidies. The prices of sugar beets are reported by factories and refer to prices paid on the farm. Although the relative increase in the price index of agricultural products after the period of study is small, there is more evidence of a future drop in the domestic prices of these products than of their rise or remaining at the present level. If the efforts aiming at economic integration succeed, the latter alternatives are presumably excluded. The prices of forestry products (see Table 1) have not been influenced by Government intervention except for a short period after 1957 when export levies were collected. As may be seen from Figure 1, teh fluctuations in stumpage prices have been large, while the increasep capacity of the wood-working industries has increased the demand of pine pulp wood, which especially in North Finland has greatly risen in value. This rise seems so convincing that it may justify correspondingly increased prices, reduced however by the depreciation of currency, as an alternative in this region. The wages of forest workers, as estimated by the statistics of the State Forestry Board, have shown a steady rise ever since the War, and the index of real wages, e.g. of lumber jacks with hourly wages shows an upward trend of 4.7 per cent per year. Eventually this trend may check the rise of stumpage prices, and even bring about a falling tendency. To the farm forest owners, performing the logging operations with family labour, this development is practically irrelevant. Table 1. The stumpage prices of forestry products, used in this study (1959 63), by study areas, mk per cu. m. (s), without bark. SF W MF Ssm Ku + Sa Saw logs 31.44 33.26 27.28 21.44 20.46 Spruce pulp wood 20.43 21.72 16.24 11.21 8.50 Pine pulp wood 13.55 14.11 10.79 3.86 (8.48) 2.07 (5.19) Birch fuel wood 6.90 7.42 3.06 1.50 0.24 Weighed av 21.90 20.68 15.35 11.45 9.90 There have been large differences in the stumpage prices of wood for different uses. Thus the average prices per cu. m. (s) of coniferous logs, spruce and pine pulp, and fuel wood of birch have been respectively 28:87, 17:49, 10:74 and 4:56 in the period 1959—63. The average price of the wood material increases with the age of the timber stand, with a larger saw log ratio in the older stands. This increase is accentuated by the fact that the logs in larger diameter classes are valued higher per volume unit. There is no overall information about the value re- lations, so that certain figures presented by Ronkanen (Footnote *) and Harve (Footnote 2) are used here with some modifications. The farmer refer to cubic foot price ratios for saw logs of various top diameters, conveyed to saw mills, the latter are relative values of whole trees with a varying technical cubic foot output. For our calculations, the different logging costs for logs of varying sizes, as well as the costs of water or road transport are deducted from the saw mill prices to obtain the stumpage value and their relations in the first alternative. In most calculations the latter ratios are applied, as the available data do not allow cutting into length computations. The relative figures involved are as follows: *) Tapion Taskukirja 1966, p. 393 (Heiskanen). 2 ) ref. Kallio 1957, p. 90-93. 7 371 372 Top measure of log 5" 6" 7" 8" 9" 10" 11" 12" Relative value, free at mill 74 89 96 100 104 111 122 126 Relative value, stumpage 54 80 92 100 107 119 137 144 Estimated volume of tree, cu. ft 7-7.9 8-8.9 9-9.9 10-10.9 11-11.9 12-12.9 13-13.9 14-14.9 Relative stumpage value of one cu. ft. sawn timber 91 94 97 100 103 106 109 111 The costs of logging decrease with an increasing diameter of the trees. An estimate in the conditions of NE area, applying rates of agreement on terms of work for the year 1961, gives the following time and cost figures; 1) Top measure 5* 6" 7" 8" 9" 10" 11" 12" Saw logs, m. hrs 0.133 0.126 0.120 0.115 0.112 0.109 0.107 0.105 h. hrs 0.037 0.035 0.034 0.033 0.033 0.032 0.032 0.031 Mk per cu. ft -:33.5 -:31.7 -:30.4 -:29.2 -:28.5 -:27.9 -:27.4 -:26.8 Ratio (8" = 100) 115 109 104 100 98 96 94 92 pine spruce Top measure 3" 4" 5" 3" 4" 5" Piled wood, m. hrs 8.99 4.89 3.35 9.60 5.24 3.81 h. hrs 0.63 0.63 0.63 0.63 0.63 0.63 per cu/m 18:83 10:83 7:83 20:03 11:53 8:83 Ratio (5" = 100) 240 138 100 227 131 100 As unequal logging costs are taken into account in stumpage price calculations, the logging costs, being also an income item to the farmers, are as a rule assumed to be constant. The time figures are, however, differentiated to some extent. Thus, so-called thin pulp wood, with a top diameter of 2", is estimated to require double work time as compared to 3" material so that the yields are very low (ca. 20 per cent of the normal, i.e. 5" top measure) for the thinning enthusiast owners2 ). % Aver. Deposit rate of savings banks 4.18 —6.06 4.67 Loan rate of commercial banks 6.90 —7.95 7.32 Discount rate of Bank of Finland 6 3/4 7.00 The depreciation of the mark, measured by the change in wholesale price indexes, has varied between —l.O and +9.5 per cent per year. The average depreciation has been 3.9 per sent per year. Note to complement the data on agriculture: Prices of fertilizers and lime, based on statistics published by the Pellervo-Society, per kg pure plant nutrients: For the more detailed explanations, see Pihkala & Lasola 1973, p. 419 ff. 2 ) The computations of Petterson (1963, p. 296 ff) in Sweden show that thinning operations yield a net return, if administration costs are not taken into account, from 60 —BO years onwards. Nitrogen (N), nitrate of lime 1:03 » nitrate of Ca and NH4 0:91 Phosphorus (P 206) 06 ) 0:57 Potassium (K 2 O) 0:34 Lime (35 % CaO) 20: 56 per to 0:06 The price of oil cakes has been estimated at an average of 0:55 per fodder unit. The cow subsidies, paid in certain zones in the Northern half of the country, per cow are: MF varying in different zones, 0 (3 subareas) 13:- (2 - * -) 24:- (5 - * -) NE all subareas 46: (7 * —) Table 2. Prices applied in the economic calculations. Average producer prices in the period 1959 63, by main areas and three North Eastern subareas, mk per kg. Country SF W MF NE Ssm Ku Sa average Wheat -:46.9 -:47.1 (-:47.7) - - -:47.4 Rye -:47.1 -:51.5 -:52.4 - -:52 - -:49.8 Barley (feed) -:28.3 -:33.2 -:27.8 -:28.7 . . . -:28.2 Oats (feed) -:30.1 -:27.6 -:29.6 .... -:27.1 Potatoes -:11.1 -:11.1 -:11.5 -:09.5 . . . -:12.3 Sugar beett -:09.7 -:09.7 . . . -:09.7 Milk -:33.5 -:33.4 -:33.8 -:38.1 -:36.4 -:39.7 -:38.2 -:31.3 Butter (exp. pr.) _______ 2:56 Skim milk -:04.7 -:04.7 -:04.1 -:04.2 . . . -:04 Beei I 2:98 2:98 2:82 2:93 . . . 2:84 II 2:68.6 2:68.6 2:48.8 2:59.6 . . . 2:52 Coniferous saw timber per cu/f 1:22 1:28 1:05 -:81 -:84 -:80 -:80 1:12.6 Spruce pulpwood, per pilde cu/m 13:90 14:50 10:90 6:40 7:65 5:80 5:80 11:98 Pilde pine wood, per piled cu/m 9:05 9:10 6:95 1:75 2:55 1:36 1:36 7:05 Birch firewood, per piled cu/m 3:50 3:80 1:55 -:38 -:85 -:15 -:15 2:43 Hone day 16:80 16:80 17:00 20:90 20:40 20:40 21:90 17:96 The producer prices of marketable crop products are averages for the period 1959—63 within regions covering the study areas. The figures of the Market Research Institute of the Pellervo Society are used in most cases. The prices of sugar beets are prices on the farm. The milk prices (except national average) include subsidies paid direct to farmers, but regional subsidies paid according to the number of cows are not included. There are regional subsidies also in some other prices, e g. rye. 373 374 Fig. 2. The stumpage prices of timber disposed from private forests, mk per cu. m (s), without bark, by regions. The prices deflated by the wholesale price indexes to the 1963 mark value. Fig. 3. The deflated prices of most relevant farm products and deflated indexes of farm wages. 375 APPENDIX 11. Method of estimation of beef production (1) Three economic alternatives for feeding beef calves I II 111 Age when mature, months 8 24 19 Slaughter weight, kg 110 235 167 Whole milk, kg 62 62 100 Skim milk, kg 950 680 1 521 Concentrates 240 120 30 whereof oil cakes 80 AIV-silage f.u 250 152 Hay * 100 704 498 Pasture i> 240 1 180 778 Total fodder units 701 2 345 1 622 Kg skim milk, per kg slaughter weight 8.65 2.89 9.11 F.u. non-marketable feed » 3.09 9.08 8.55 * concentrates » 2.18 0.511 0.180 Total feed » 6.37 9.978 9.772 (2) Beef production, estimated on the basis of the number of calf births and available skim milk SF W MF NE Ssm Ku Sa Calf births per hectare n 0.376 0.386 0.368 0.480 0.448 0.712 0.448 Skim milk available kg 1116 847 715 973 1085 1209 484 Skim milk requirement, kg I 356 367 350 456 426 676 426 II 256 262 250 326 305 484 305 11l 572 587 559 729 681 1082 681 Maximum beef prod. per ha, kg I 129.0 97.9 82.7 112.5 125.4 139.8 56.0 II 386.2 293.1 247.4 337.7 375.4 383.7 167.5 (3) Beef production, estimated on the basis of non-marketable (roughage) fodder. SF W MF NE Ssm Ku Sa Non-marketable fodder. available a 299 143 242 593 572 96 685 requirement, if all calves fed alt. I I) 128 131 125 163 152 242 152 II c 802 819 785 1024 956 1519 956 111 il 537 551 551 685 640 1016 640 376 Optimum use1 ) I e 72 127 89 29 21 96 111 f 227 16 153 564 551 640 Production on beef I 23.8 41.1 28.8 9.4 6.8 31.1 111 26.5 1.9 17.9 65.9 64,2 78.4 Total 49.8 43.0 46.7 75.3 71.0 31.1 74.8 Requirement of whole milk 29 24 27 44 42 18 48 skim milk 443 373 412 681 645 269 484) concentrates 54 90 65 28 26 68 41 Non-utilized skim milk 673 474 303 292 440 940 404 APPENDIX 111. Estimate on the fodder saving per hectare of total cultivated area, caused by more effective use of horses, when moving from the actual average size of farms to size class 11, which is assumed to be 15 ha in all study areas. (a) Total feed use and feed cost per farm (cf. Tables 9 and 10 pp. 319, 320.) Actual farm size; Subareas SF W MF NE Ssm Ku Sa Marketable feed, f.u. 237 203 216 136 162 105 181 Non-marketable feed, f.u 1503 1283 1383 861 1022 661 1142 Value, mk 378.81 323.59 343.88 217.08 257.86 166.85 288.13 Size class II (15 ha cultivated area, number of horses according to P. I.) Marketable feed, f.u. 298 307 307 260 260 260 260 Non-marketable feed. f.u 1884 1944 1944 1643 1643 1643 1643 Value, mk 475.14 490.11 490.11 414.40 414.40 414.40 414.40 (b) Value of feed, mk per ha Actual farm size 42.32 52.79 43.81 39.04 32.72 54.35 41.94 Size class II 31.67 32.67 32.67 27.62 27.62 27.62 27.62 Savings, mk/ha 10.65 20.12 11.14 11.42 5.10 26.73 14.32 Feed requirement per adult horse: grain 317 f.u., non-marketable fodder 2004 f.u. APPENDIX IV. The saving in costs of building capital per ha obtained by increase of cultivated area. assuming a) that no additional building space is needed, b) the building capital of I size class farms is stepwise substituted by respective capital of II size class, c) that larger building volume is necessary (type 1. barn). J) Optimum use is calculated aiming at the sum which corresponds to the available quantity of non-marketable fodder. To obtain the values on the rows e and f, the equation by + d(l x) = a is solved in regard to x, and the values on rows e and f are obtained multiplying the per animal use of non-marketable feed by product nx for values of row e and by n. (1 —x) for row f (n = number of calf births per ha). The values of alt. II (row c) are not relevant in this connection. 377 (1) Estimate based on Profitability Investigation (cf. Table 14, p. 71) a) cost items after 1 ha extension SF W+ MF NE Deprec. & rep 42.43 40.17 40.34 Inrerest (3 %) 38.63 39.85 42,35 saving per hectare caused by one hectare increase Deprec. & rep 5.63 5.30 5.75 Interest 5.12 5.26 6.03 b) differences between size classes I and II (see Table 14, p. 71) in farm size, ha 8.18 7,59 6.16 in deprec. & rep 12.67 9.64 16.35 in interest, mk 11.29 11.47 18.50 cost differences divided by difference in farm size deprec. & rep 1.55 1.27 2.65 interest 1.38 1.51 3.00 (2) Estimate based on actual farm size of study farms and cost figures of Land Settlement Investigation Committee a) cost items after 1 ha extension subareas SF W MF NE Ssm Ku Sa Deprec. & rep. 52.09 72.40 58.85 79.04 58.39 127.40 65.87 Interest 19.53 27.27 21.97 29.64 21.82 47.77 24.70 saving per hectare caused by one hectare increase Deprec. & rep. 5.83 11.82 7.20 14.22 7.10 41.50 9.50 Interest 2.19 4.45 2.80 5.34 2.19 15.56 3.60 c) differences between actual per hectare costs and costs if type 1. building is fully utilized (15 ha farm size) Deprec. & rep. -4.32 25.92 5.24 37.21 4.94 126.07 16.30 Interest -1.87 8.08 1.67 11.85 1.58 40.24 5.20 (3) A calculatory example of the saving of cost of building capital per hectare when cultivated area is increased by one hectare in the Kuusamo subarea, where the cultivated area per farm was during the study period in aver. 3.07 ha. Note the effect of moving to type 1. Average Type of Cost per hectare Change per 1 hectare size building deprec. interest increase & rep. % 3 deprec. interest 3.07 2 198.44 126.67 4.07 2 149.68 95.54 -48.76 -31.13 5.07 2 120.1576.70 -29,53 -18.84 6.07 2 100.3664.06 -19.07 -12.64 7.07 1 153.5497.99 +53.18 +37,60 8.07 1 134.5285.86 -19.02 -12.13 9.07 1 119.6976.39 -14.83 - 9.47 10.07 1 107.80 68.80 -11.89 - 7.59 11.07 1 98.06 62.59 - 9.74 - 6.21 12.07 1 89.94 57.40 - 8.12 - 5.19 13.07 1 83.06 53.01 - 6.88 - 4.39 14.07 1 77.15 49.24 - 5.91 - 3,77 15.00 1 72.37 46.19 - 4.78 - 3.05 Average saving within type 2 32.45 20,87 » » » » 1 1.14 6.48 * i> » whole scale 7.14 4.52 APPENDIX V. Standards applied in labour time estimations, and some averages of earlier date, man hours. Westermarck Hjelm Danish, stand. This Sipilä Sandvist & MeUSn 7.5 ha horse tractor study 1949 ') under 10 ha driven driven Autumn crops of grain 180 59 124 35 180 180 34 150 150 306 580 580 259 700 700 Spring grain 150 56 110 Potato 580 225 379 Sugar beet 700 264 349 Other root crops .. 650 650 650 Hay 90 56 61 48 90 90 7 30 -Pasture 30 - 15 Adult horse 150 125 150 Young cattle (24 m.) 130 40-48 130 Milk cow 220 herd size 3 305 345 450 » » 4 - 245 295 415 240 260 396» * 5 - - 208 » » 7 116 210 » * 8 - - 153 195 310 185 180 290» * 10 105 135 » • 12 - 123 168 285 150 160 280 -» » 15 - 95 111 Pig 100 kg 15 Sheep 8 APPENDIX VI. Forest production figures, by site types. 2) Site type Regional growth, per ha. National Survey Per cent Yearly growth cu. m (s) Logs cu. ft. Piled wood cu. m (p) Fuel wood cu. m (p) Value of yearly cut mk Same deducted by tzxes mk Rotation yrs Average value of stand mk South Finlands main area OMT 4.9 17.8 6.59 72.7 4.09 1.57 138.8 132.0 80 2048.1 MT 4.4 38.7 5.26 58.2 3.33 0.95 109.2 103.4 90 1785.3 VT 3.5 16.8 4.80 46.7 2.67 1.55 81.3 77.0 90 1418.0 CT 2.1 3.6 2.69 2.08 1.53 1.06 38.8 35.4 120 763.9 K 1 3,4 11.5 (4.80) (46.7) (2.67) (1.55) (81.3) (77.0) - 1418.0 (1.53) (1.06) (38.8) (35.4) - 763.9 3.00 1.55 81.3 77.0 - 1418.0 Rl 2.35 0.3 (2.69) (20.8) Ojik.-Drained peat 4.15 11.3 (4.79) 36.5 3.92 100.0 5.21 53.6 3.17 1.30 100.7 95.38 - 1646.8 Western main area OMT 4.7 3.1 5.93 65.4 3.68 1.41 124.9 118.8 80 1843.3 MT 4.0 9.1 4.73 52.4 3.00 0.86 98.3 93.1 90 1606.8 VT 2.8 38.0 4.32 42.0 2.40 1.40 73,2 69.3 90 1276.2 CT 1.8 34.0 2.42 18.7 1.38 0.95 34.9 31.9 120 687.5 Kl 2.9 7.6 (4.32) (42.0) (2.40) (1.40) (73.2) (69.3) - 1276.2 (1.38) (0.95) (34,9) (31.9) - 687.5 (2.40) (1.40) (73.2) (69.3) - 1276.2 Rl 1.7 8.2 (2.42) (18.7) Ojik 3.3 - (4.32) (42.0) 2.55 100.0 3.61 33.8 2.06 1.16 60.9 57.22 1075.4 *) Interpolated values 2) Growth figures are cu. m (s) .without bark. Forest production figures, by site types. (Continued). Site tyde Regional growth Per cent Yearly growth en. m (s) Logs cu. ft. Piled wood cu. m (p) Fuel wood cu. m. (p) Value of Value of yearly cut timber alt. 1 alt. 2 alt. 1 stand mk mk mk alt. 2. mk Middle Finland main area OMT 4.2 2.2 5.60 61.8 3.48 1.33 118.0 112.2 80 1740.9 MT 3.85 17.3 4.47 49.5 2.83 0.81 92.8 87.9 90 1517.5 2.27 1.32 69.1 65.4 90 1205.3 1.30 0.90 33.0 30.1 120 649.3 VT 2.8 35.3 4.08 39.7 CT 2.4 - 2.29 17.7 Kl 2.3 18.0 (2.29) (17.7) (1.30) (0.90) (33.0) (30.1) 649.3 Rl 1.7 10.3 (0.68) Ojik 2.5 16.9 (4.08) 39.7 2.27 1.32 69,1 65.4 1205.3 2.75 100.0 3.54 34.4 2.03 1.01 62.1 58.6 1068.6 Kainuu (Ssra) MT 2.3 10.3 (2.49) 13.3 1.97 0.43 25.95 (25.95) 1113 (1113) EVT 2.2 52.5 3.53 49.0 1.33 0.31 47.73 (51.89 1923 (2041) ECT 1.8 4.5 2.59 21.0 1.59 0.16 21.89 (26.82) 580 ( 738 Kl 1) 1.5 7.2 (2.03) (11.3) (1.01) (1.01) (15.33) (15.33) ( 658) ( 658) R 1 1.3 25.5 - - (0.94) (0.94) ( 3.09) ( 5.86) ( 133) ( 252) 28.9 1.29 0.53 30.61 33.72 1232 1331100.0 Upper NF (Ku) MT 2) - 16.3 (1.87) 10.0) (1.48) (0.32) (16.16) (16.16) ( 687) ( 687) (1.35) (0.15) (37.07) (41.08) (1368) (1553)EVT 3) 1.6 17.7 (3.60) (39.9) EMT 3 ) 1.3 23.0 (2.06) (20.6) (1.26) (0.76) (18.28) (20.88) ( 666) ( 800) CT, HMT 0.9 7.1 (1.05) ( 8.2) (0.60) (0.24) ( 8.19) ( 8.19) ( 534) ( 534) (1.09) (0.37) ( 6.79) ( 9.03) ( 210) ( 288) (0.71) (0.71) ( 1.07) ( 2.51) ( 45) ( 105) K 1 1.2 14.3 (1.53) ( 7.5) Rl 1.2 21.6 100.0 51.1 1.12 0.48 14.51 16.43 585 675 Upper NF (Sa) MT-VMT4) 1.6 5.6 (1.45) ( 7.8) (1.15) (0.25) (12.58) (12.58) ( 629) ( 629) EVT 1.2 24.8 2.80 31.0 1.05 0.12 28.83 (31.95) 1064 (1208 ) EMT 1.0 31.5 1.60 16.0 0.98 0.59 14.22 (16.24) 518 ( 622) HMT5) 0.7 25.3 0.82 6.4 0.47 0.19 6.37 ( 6.37) 415 ( 415) Kl (= ErCIT) ... - 7.4 1.19 5.8 0.85 0.29 5.28 (7.02) 163 (224) R 1 0.9 5.4 (0.90) - (0.55) (0.55) ( 0.83) ( 1.95) ( 35) ( 82) 100.0 15.21 0.84 0.33 13.66 15.33 582 657 *) Estimated to be 171.4 % of the figures of type ErQT in Upper NF. 2 ) Estimated to be 75 %of the figures of Kainuu. 3) Estimated to be 128.6 %of the figures of the same site type in Sa. *) Estimated to be 58.3 % of the figures of the same site type in Kainuu 6 ) For the estimation of diameter frequency distribution, the figures of Sir£n (1955, pp. 99 102) have been used. 379 380 APPENDIX VII Data used in the socio-economic calculations The basis of estimation of the socio-economic prices of agricultural products was the price level in international trade. As a simple approximation the Finnish import or export prices in the period 1959—63 were used. These prices were compared with the prices applied by Gulbrandsen (1969, p. 257) and the average producer prices in Denmark, and with the arithmetic averages of the EFTA and EEC-countries in 1961/62 (FAO, Prices . . . 1963). In our calculations the first mentioned prices were modified by an increase of 25 per cent, assumed in the case of general restoration of the free trade (Gulbrandsen, p. 47). Milk prices were in our calculations modified also by pricing the average liquid milk proportion in line with the actual producer prices. Thus international prices were not applied to this part of milk product- ion. For the estimation of average producer prices of milk the average processing costs of dairies from the year 1961 were used. These data are given in the statistics of Cooperative Dairies (Osuusmeijerien Liiketilasto). This gives the costs, apart from those of collected milk and depreciation of the capital, separately for dairies selling butter, cheese or liquid milk. Import or Gul- EFTA EEC Prlces , , Denmark appliedexport brandsen aver. aver. rr here price 1959-63 1961/62 1961/62 1961/62 1961/62 Rye -:20.5 .... -:25.6 Wheat -:25.2 -:18.7 -:23.9 -:32.9 -:30.4 -:31.5 Sugar beets -:04.9 . -:04 -:04.9 -:04.6 -:06.1 Potatoes . -:09.3 .... Butter 2:60.5 2:65 . . . 3:26 Edam-cheese 1:54.6 1:53 . . . 1:93 Liquid milk . —:24.3 .... Milk, producer price . -:17.8 -:26.2 -:24.5 -:21 Beef 2:73') 2:24 2:28 3:25 3:56 2:85 Feed grain -:18 . . . -:22.5 Oilcakes -:26.7 . . . -:33.4 To complete the transport cost data the statistics of the Cooperative Dairies (Suomen Osuusmeijerien Liiketilasto ) have been used. The depreciation has been estimated at 3 per cent of real estate and at 5 per cent of movables, assuming that these costs in the said groups are in the same proportion to the gross value of production. Thus tha costs, without those for transport, were 5.7, 8.8, 8.0 per cent of the gross value in the respective groups, or 7.55 per cent on averages for all dairies. As the use of milk per kg butter has in cooperative dairies been 19.4 kg, and per kg cheese respectively 7.5 kg, the costs per kg milk have been 1.86 and 3.26 p respectively, or when increased by transport costs, 3.36 and 4.76 p. Computed from the hypothetical free trade butter price (3.26), and noting the value of returned skim milk (0.04 per kg), the net farm price of factory milk would be 17.4 p in the case of butter production. In cheese production, the respective milk price would be 20.9 p per kg. If the figures of the year 1961 on the distribution of milk for different uses (Pellervon Ka- lenteri) are applied, the average socioeconomic producer price of milk, and the contribution of milk transport and processing to the NNP can be computed as follows (average of the whole country): ') Only the years 1959 and 1963. 381 Producer Contribution to NNP of % . Total price processing transport Liquid milk consumed 38.5 —:31,3 —:04.1 —:01 —:25.5 Factory milk, butter 54.3 —:17.44 —:02.1 —:01 —:19.6 cheese 7.2 -:20.9 -:03.9 -:01 -:24.9 Average - -:23.0 -:03.0 -:01 -:19.6 The actual farm prices, as presented in this Appendix, p. 373, varied in our study areas. As the differences were due to subsidies, we do not take these differences into account so that the same price is used for all study areas. There are no further complications in the estimation of socioeconomic prices, though some question marks might be applied to some single product prices. Compared with milk prices other prices play a rather small role in this study. The prices of fertilizers and lime were subsidized; in 1961 the Government paid 14.01 mill, mk to reduce the sum paid by farmers to 93.87 mill. mk. The socio-economic prices of fertilizers can thus be obtained multiplying by 1.149. For the duties on corn, bran and oil cakes ( —:08, —:O5 and —:O3 per kg), 4.8 mill, mk. were collected i.e. 0.25 per cent of the gross return of agriculture. To estimate the respective socio-economic advantages, the contribution to the net national product (NNP) of the activities in the processing industries and transport had to be estimated. The national averages of Industrial Statistics (Teollisuustilasto 1961) and Railway Statistics (Rautatietilasto 1961) were used for this purpose. A detailed study by Lindfors (1964) is very helpful when estimating the costs of lumber transport. In the Industrial Statistics the value added approximately represents the Gross Natinal Product (GNP), while the NNP is obtained by a deduction of the yearly depreciation value. In the statistics the values of fixed capital, separately for real estate and movables, are presented for certain factory groups, and for this study a 3 per cent depreciation is used for real estate and 5 per cent for movables 1). For further calculations, the overall total NNP is divided by the volume of raw material used (or in the case of slaughter houses, by the volume of product, i.e. the total weight of carcasses produced). The contribution of transport to the NNP plays a not insignificant role in the agricultural calculations, and a rather important role in the calculations relating to forestry. The Railway Statistics includes the freights paid for some agricultural products and requisites in 1961. Truck transports have to some extent superseded railway conveyance, and in the absence of statistics only rough estimates are possible. Assuming that the railway transport volumes for the year 1955 reflect approximately the total transport volume in 1961, and using the 1961 tariffs, the figures presented beneath are obtained for other products. These again are estimated on the basis of statistics of Cooperative Dairies, which generally pay for the milk transports Freight according to railway fariffs volume „ , , ,1 otal mk mill, mk per dt Grain and flour 999 1 394 1:39.5 Potatoes 10 31 3:10 Sugar beets 182 207 1:13.7 Milk products 2 087 3 985 1:90 Meat 20 112 5:60 The contributions to the NNP of transports were estimated using the percentage ratios 84 and 48, respectively for railway and truck transports. The former is based on the cost structure according to the Railway Statistics, the latter has been applied in the calculations of national income by the Central Office of Statistics. *) In some cases when information is imperfect, the depreciation in a subgroup is estimated assuming the same percentage depreciation of gross revenue as in a larger group. 382 Although we cannot feel entirely confident regarding the accuracy of these estimations, we may use the following approximations per unit, to indicate the contribution to the NNP, p/kg. Transport Processing Total Grain 1.17 6.71 7.88 Potatoes 3,10 3.10 Sugar beets 1.14 5.35 6.49 Milk 0.93 3.00 3.93 Meat 5.60 29.60 35.20 These figures are not differentiated according to regions, as the volumes transported are very difficult to determine since industrial statistics give only domestic averages. As the importance of transport is more obvious in the regional estimations on forestry, an attempt is made to figure out the average distance the lumber has to be conveyed to the processing plants, as well as the most probable distances the processed products have to travel, separately for each of our study areas. In most cases there are alternative transport possibilities, e.g. truck, railway or floating; in some cases, the most probable way of transport is so clear that alternatives seem to be superfluous. The assumed ways of transport and estimated distances (weighed by the productive forest acreage of subareas) are by the main study areas as follows: Study Way of transport Aver, distances of transport, in km area saw timber pulp wood Raw wood truck train truck train SF truck, floating 62 62 W truck, or train 87 87 MF truck, train 37 31 50 48 NE Ssm truck, train, floating 20 118 20 118 Ku truck, train 120 92 182 Sa truck, train 66 20 262 Processed products sawn timber pulp SF W 37 37 36 36 MF railway transports only NE 273 250 228 106 Ssm Ku 192 192 237 192 Sa 237 0 The costs of transport are estimated on the basis of the given distances and the data on the expenses per volume unit and road kilometre. The last mentioned data on unprocessed wood were found in an article by Lindfors, in which the overall average costs in the year 1961 are stated separately for different kinds of lumber, and for tractor, truck, railway and floating transport separately. The costs of transport of sawn timber and pulp were, however, obtained from Railway Statistics. As the costs of truck transport are greatly affected by the distance, and some data are available on the differences, these costs were modified in the final compu- tations by using graphical interpolation. The average costs used as the basis are the following: 383 Average transport costs mk per cu. m. or per to/km Tractor Truck Railway Floating Truck Truck 50 km 20 km Saw logs 0:358 0:119 0:036 0:019 0:0105 0:0195 Piled pulp wood 0:271 0:091 0:026 0:018 0:0084 0:014 Fuel wood 0:288 0:129 0:018 0:038 Sawn t.mber heavy . . 0:0465 battens, boards . . 0:046 Pulp . 0:047 It was not possible fo estimate the extent of floating transports for this study. Consequently, these are not taken into account, which means that the computed costs may have been to some extent overestimated. Floating may have some relevance especially in the MF and Ssm study areas. The contribution of transport to the NNP was estimated using the ratios already referred to (p. 11). When estimating the contribution of industrial processing, the figures based on Industrial Statistics were used. (For the detailed figures, see Finnish Study Group, 1969, Appendix I.) It was assumed that the contribution of the paper industry can be added to that of the pulp industry in the same proportion as the pulp used as raw material is in relation to the total pulp production. As the paper factories use 46.7 per cent of the pulp produced, and the contribution is 9:91 per ton pulp, whereas 3.8 cu. m. (s) is needed per ton pulp, the average contribution of the paper industry is 1:22 per cu. m, (s) total use of pulp wood. The figures presented here were applied in the computations of the NNP which is based on the primary production on the land of the study areas. NOTES AND ABREVIATIONS AA Asutustoiminnan Aikakauskirja. Journal of Colonization. AAF' Acta Agralia Fennica. AFF Acta Forestalia Fennica. FF Folia Forestalia. Institutum Forestale Fenniae. Helsinki. MA Maataloustieteellinen Aikakauskirja. Journal of the Scientific Agricultural Society of Finland, MAL Metsätaloudellinen Aikakauslehti. MT Metsätilasta. Forest Statistics. MTJ Metsätutkimuslaitoksen julkaisuja. Communicationes Instituti Forestalis Fenniae. Helsinki. STV Suomen tilastollinen vuosikirja. Statistical Year Book of Finland. Suo Suoviljelysyhdistyksen aikakauslehti. Journal of Peat Culture Society of Finland. SVT Suomen virallinen tilasto. Official statistics of Finland. TSK Tilastoa Suomen Karjantarkkailuyhdistysten toiminnasta. Statistics of the activity of milk recording societies in Finland. TSMT (P. I.) Tutkimuksia Suomen maatalouden kannattavuudesta. Investigations on the profitability of agriculture in Finland. Maatalouden taloudellisen tutkimuslai- toksen julkaisuja. Helsinki. dt = deciton (100 kg). fu. = Scandinavian fodder unit rehuyksikkö. cu. m, (p) = piled cu. m. pinokuutiometri cu. ra. (s) = cubic meter. Solid measure (with bark) kiintokuutiometri (kuorellinen) cu, ft. = cubic feet (techn. measure) teknillinen kuutiojalka.