Continuous elimination of the acreage of orchards in Slovakia has a negative impact on the overall fruit production. Improvement of the conditions could be achieved by introducing new technological systems into orchards and supporting the measures motivating farmers. Three investment strategies for planting apple orchards are presented in the paper: slim spindle, high density and extended orchards. Economic efficiency of the systems is evaluated through the return of investment, net current value and inner profit percentage. Within the assumption of the objective evaluation of input parameters, we can expect an acceptable economic efficiency of the investment only in the "slim spindle" technological system. The simplified deterministic evaluation of economic efficiency is further deepened with the identification of the relevant risk factors, followed by its quantification by the simulation processes. Taking the risk into account leads to a significant decrease of the economic attractiveness of investments.
This paper presents the results of stochastic parametric approach used in estimation of production frontier. The estimation of output oriented technical efficiency was based on the Stochastic Frontier analysis with cobb-Douglas production function. The model also included a dummy variable which expressed production conditions in which Slovak farms are operating. We divided farms into two groups regarding production conditions: productive regions (Pr) and less favorable area (LFA) regions. The data set included 79 Slovak farms operating in different regions in the 2003-2005 time periods. The following input variables are included in the model: capital, material, labour and agricultural land according to the LPiS system. Total output was used as the output variable. From the achieved results, we can conclude that the significant statistical differences in average technical efficiency were detected only in year 2005 between the farms of the mentioned production conditions. A higher level of variability in technical efficiency was detected in farms operating in productive regions compared to technical efficiency of farms in the LFA regions.Key words: less favorable area (LFA), subsidy, stochastic production frontier, panel data, output -oriented technical efficiency, cobb-Douglas production function Abstrakt: V príspevku sú prezentované výsledky stochastického parametrického prístupu odhadu produkčných hraníc. na báze odhadu stochastickej produkčnej funkcie s využitím cobb-Douglasovej produkčnej funkcie sú odvodené outputovo orientované miery technickej efektívnosti. Vzhľadom k rozdielnemu charakteru výrobných podmienok boli do modelu implementované kvalitatívne premenné, ktoré zohľadnili kvalitu výrobných podmienok. Údajovú základňu tvoria podnikové údaje 79 slovenských poľnohospodárskych podnikov hospodáriacich v rôznych výrobných podmienkach v rokoch 2003 až 2005. Komparatívna analýza rozdeľuje poľnohospodárske podniky do dvoch skupín : podniky hospodáriace v dobrých výrobných podmienkach t.j. podniky hospodáriace v produkčnej oblasti a podniky hospodáriace v znevýhodnených podmienkach. Ako vstupné premenné sú uvažované : celkový kapitál, materiál, počet pracovníkov, výmera poľnohospodárskej pôdy podľa systému LPiS a ako výstup celková produkcia poľnohospodárskeho podniku. z dosiahnutých výsledkov vyplý-va, že v roku 2005 existuje štatisticky preukazný rozdiel v priemernej úrovni technickej efektívnosti poľnohospodárskych podnikov. Vyššia variabilita v miere technickej efektívnosti bola zistená v podnikoch hospodáriacich v lepších produkčných podmienkach oproti podnikom hospodáriacim v horších podmienkach (LFA).Kľúčové slová: znevýhodnené oblasti (LFA), dotácie, stochastické produkčné fronty, panelové údaje, outputovo-orientovaná technická efektívnosť, cobb-Douglasová produkčná funkcia
Research background: Agriculture plays a vital role in producing food to ensure food security, but it is one of the biggest contributors to environmental pollution. One of the main goals of the new CAP is to set higher ambitions for environmental actions, which brings into the front the concept of agricultural eco-efficiency. The notion of eco-efficiency includes the economic and also ecological dimensions of sustainable agriculture. Purpose of the article: The main goal of this paper is to evaluate the eco-efficiency of agricultural production and its dynamics during the years 2013, 2015, and 2017 of NUTS 2 regions within the Visegrad 4 (V4), i. e. The Czech Republic, Slovakia, Hungary, and Poland. The part of the main goal is to verify the research hypothesis that all the biggest agriculture producers are eco-efficient. Methods: V4 regional eco-efficiency of the agricultural sector is expressed by the Malmquist productivity index and is estimated using the output-oriented Data envelopment analysis (DEA) model, under the assumption of constant return to scale (CRS). The Malmquist index is decomposed to technical eco-efficiency change (EC) and technological change (TC). Based on the eco-efficiency, technological and pure technical eco-efficiency change, V4 regions are classified into three groups: the most progressive regions, the progressive regions, and the regressive regions. Findings & value added: CZ02: Central Bohemia, CZ04: Northwest, HU33: Dél-Alföld, HU31: Észak-Magyarország, HU32: Észak-Alföld, PL21: Malopolskie, PL41: Wielkopolskie, SK01: Bratislava region, and SK02: Western Slovakia have an eco-effective agricultural sector, the remaining V4 regions have eco-ineffective agricultural sector. The research hypothesis that all the biggest agricultural producers are eco-effective is not confirmed. During the analyzed years, 19 V4 regions improve their agricultural eco-efficiency. The main contributor to eco-efficiency improvement is technological progress, which indicates that producers implement innovations that lead to more eco-efficiency agricultural production.
This study has focused on two main tasks: verifying the suitability of using stochastic frontier analysis on a transforming sector, and providing empirical evidence to explain the technical efficiency structure among farms in the time period [2000][2001][2002][2003][2004]. Two stochastic frontier model specifications were employed, the Battese and Coelli 1992 specification with the systematically time-varying inefficiency effect, and the Battese and Coelli 1995 one stage specification explaining technical inefficiency based on farm-specific variables. Our analyses were carried out at the commodity level, wheat production, where the accessibility of a data panel allowed us to enrich the calculation of the level of technical efficiency by the analysis of productivity changes within the chosen period of time, supports this idea as well.Key words: technical efficiency, total factor productivity index, stochastic frontier analysis Abstrakt: Analýza je zameraná na dva hlavné ciele: verifikácia vhodnosti použitia analýzy stochastických hraníc v transformujúcom sa primárnom sektore a poskytnutie empirických dôkazov na vysvetlenie štruktúry technickej efektívnosti fariem v sledovanom časovom horizonte rokov 2000-2004. V analýze boli použité dve špecifikácie modelov, Battese a Coelli 1992 so systematicky meniacim sa vplyvom neefektívnosti v čase, a Battese a Coelli 1995 -jednoetapová špecifikácia, ktorá vysvetľuje technickú neefektívnosť založenú na špecifických premenných fariem. Analýza bola uskutočnená na komoditnej úrovni, produkcia pšenice, kde dostupnosť panelu dát umožnila obohatiť výpočet mier technickej efektívnosti o analýzu zmien produktivity v čase.Kľúčové slová: technická efektívnosť, celková produktivita faktorov, analýza stochastických hraníc Supported by the Ministry of Education of the Slovak Republic (Grant Vo. VEGA G-292/01150 V-085-06-00 -Modeling of the EU agriculture policy impacts on economics situation of agricultural enterprises in SR).
Abstract:The primary goal of our analysis is to evaluate the effects of changes in the Slovak agriculture subsidy system on the selected farms located in different production areas between the years 2003 and 2004. Our comparative analysis divides the farms into two groups: The first group represents all those farms that operate in good farming conditions i.e. primarily the land is more productive (PA). The second group of farms operates in less favorable farming conditions (LFA). The regions differ from each other in terms of geographical position, location, production and climatic conditions, as well as the quality of land. We analyzed data of 119 farms.
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