Articles containing the keyword 'non-industrial private forest'

In this study, logistic regression and neural networks were used to predict non-industrial private forests (NIPF) landowners’ choice of forest taxation basis. The main frame of reference of the study was the Finnish capital taxation reform of 1993. As a consequence of the reform, landowners were required to choose whether to be taxed according to site-productivity or realized-income during the coming transition period of thirteen years.

The most important factor affecting the landowners’ choice of taxation basis was the harvest rate during the transition period, i.e. the chosen timber management strategy. Furthermore, the estimated personal marginal tax rate and the intention to cut timber during next three years affected the choice. The descriptive landowner variables did not have any marked effect on the choice of forest taxation basis.

On average, logistic regression predicted 71% of the choices correctly; the corresponding figure for neural networks was 63%. In both methods, the choice of site-productivity taxation was predicted more accurately than the choice of realized-income taxation. An increase in the number of model variable did not significantly improve the results of neural networks and logistic regression.

• Pesonen, E-mail: mp@mm.unknown
• Kettunen, E-mail: ak@mm.unknown
• Räsänen, E-mail: pr@mm.unknown

For non-industrial private forest (NIPF) owners land with its timber production is an example of a capital asset. Developments in the asset’s value and yield depend not only on forest management but also on other factors that the owner cannot control, for example timber prices and the production circumstances, such as soil and climate. One important basis for decision making related to management strategy and, in the short run, to cutting and silvicultural activities is economic analysis and accounting. The owner has to decide whether to invest more in his property (planting, cleaning, building of forest roads) or disinvest (sell timber or the holding). He has to find ways to increase revenue and cut costs.

However, generally accepted accounting practices for NIPF owners are lacking. Applying business economic accounting principles and forestry accounting traditions, we outline a proposal for a profit and loss accounting and balance sheet for NIPF holdings with a view towards increasing economic awareness among private owners. Key concepts are net profit of the enterprise and calculated profit of the property. Other profit measurements that are used are gross margin, forestry margin, operating margin and operating profit. Calculated profit is based on adjusted net profit. The main concern, however, is to consider the change in the holding’s market value caused by changes in stock volume, quality and price. The contents of the accounting framework development here are applied to three management strategies. The return on investment (ROI) of forestry is compared with other investment alternatives.

• Hyder, E-mail: ah@mm.unknown
• Lönnstedt, E-mail: ll@mm.unknown
• Penttinen, E-mail: mp@mm.unknown

In the study, the potential allowable cut in the district of North-Savo, Eastern Finland was clarified  based on the non-industrial private forest landowners’ (NIPF) choices of timber management strategies. Alternative timber management strategies were generated, and the choices and factors affecting the choices of timber management strategies by NIPF landowners were studied. The choices of timber management strategies were solved by maximizing the utility functions of the NIPF landowners. The parameters of the utility functions were estimated using the Analytic Hierarchy Process (AHP).

The level of the potential allowable cut was compared to the cutting budgets based on the 7th and 8th National Forest Inventories (NFI7, NFI8) in Finland, to the combining of private forestry plans, and to the realized drain from non-industrial private forests. The potential allowable cut was calculated using the MELA system that has been used in calculating the national cutting budget.

The data consisted of the NIPF holdings that had been inventoried compartmentwise and had forestry plans made in 1984–92. The NIPF landowners’ choices of timber management strategies were clarified by a mail inquiry.

The most preferred strategy obtained was ”sustainability” (chosen by 62% of landowners). The second was ”finance” (17%) and the third ”savings” (11%). ”No cuttings”, and ”maximum cuttings” were the least preferred (9% and 1%, resp.). The factors promoting the choices of strategies with intensive cuttings were: a) ”farmer as forest owner” and ”owing fields”, b) ”increase in the size of the forest holding”, c) agriculture and forestry orientation in production, d) ”decreasing short-term stumpage earnings expectations”, e) ”increasing intensity of future cuttings”, and f) ”choice of forest taxation system based on site productivity”.

The potential allowable cut defined in the study was 20% higher than the average of the realized drain in 1988–93, which was at the same level as the cutting budget based on the combining of forestry plans in Eastern Finland. The potential allowable cut defined in the study was 12% lower than the NFI8-based greatest sustained allowable cut for the 1990. Using the method, timber management strategies can be clarified for private forest owners.

• Pesonen, E-mail: mp@mm.unknown

• Suuriniemi, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: is@nn.fi
• Matero, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: jukka.matero@uef.fi
• Hänninen, Finnish Forest Research Institute, Vantaa Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: hh@nn.fi
• Uusivuori, Finnish Forest Research Institute, Vantaa Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: ju@nn.fi

• Hokajärvi, Oulu University of Applied Sciences, School of Renewable Natural Resources, Metsäkouluntie 4–6, FI-90650 Oulu, Finland E-mail: raili.hokajarvi@oamk.fi
• Hujala, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: th@nn.fi
• Leskinen, University of Eastern Finland, Department of Geographical and Historical Studies, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lal@nn.fi
• Tikkanen, Oulu University of Applied Sciences, School of Renewable Natural Resources, Metsäkouluntie 4–6, FI-90650 Oulu, Finland E-mail: jt@nn.fi

• Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jyrki.kangas@metla.fi
• Leskinen, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: pl@nn.fi
• Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: tp@nn.fi

• Lausti, Helsinki School of Economics and Business Administration, Centre for Doctoral Programme, Runeberginkatu 15 A, FIN-00100 Helsinki, Finland E-mail: al@nn.fi
• Penttinen, Finnish Forest Research Institute, Helsinki Research Centre, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: markku.penttinen@metla.fi

• Karppinen, Finnish Forest Research Institute, Helsinki Research Centre, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: heimo.karppinen@helsinki.fi

• Kärhä, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: karha@forest.joensuu.fi
• Oinas, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: so@nn.fi

• Zhang, School of Forestry & Wildlife Sciences, Auburn University, AL 36849-5418, USA E-mail: yaoqi.zhang@auburn.edu
• Zhang, School of Forestry & Wildlife Sciences, Auburn University, AL 36849-5418, USA E-mail: dz@nn.us
• Schelhas, Southern Research Station, USDA Forest Service, Tuskegee University, AL, USA E-mail: js@nn.us

• Ripatti, Finnish Forest Research Institute, Helsinki Research Centre, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: pekka.ripatti@metla.fi