Globally, forest ownership structure varies significantly between countries, with about 14% of the global forest controlled by individuals or communities referred to as non-industrial private forest (NIPF) owners [1
]. These owners account for 40% of the total forests available for wood supply in the area covered by an assessment of temperate and boreal forest resources in 55 countries [3
]. In many countries like Portugal (79%), Norway (79%), Finland (62%), and the US (62%), a significant share of total forest is managed by NIPF owners, mainly for wood supply [4
In Norway, about 26% of the land area is covered by productive forest, of which 84% of is privately owned and divided on about 127,000 properties [8
]. Privately owned forest dominates the supply of timber to industries, with 89% of harvest volumes [8
]. The forest and the related sector has historically been an important employer in many rural areas of Norway; its contribution to GDP declined from 2.5% in 1950 to 0.2% in 2017 [10
]. The significant decline in share of GDP is due to a strong reduction in timber prices over the last 70 years. Over the same time period, the forest growing stock has accumulated substantially and increment more than doubled [9
]. Harvest levels have increased over the last few years, while the share of owners refraining from harvest is increasing, with about half of owners not harvesting timber for sale over the last 20 years [9
]. Many of these properties are small, but together they constitute more than 20% of the productive forest area [9
]. On average, small properties have higher productivity and larger growing stock and thus possess higher possibilities for increased harvest than larger properties [9
The management strategies adopted by owners are based on their values and reasons for owning forest. These strategies ultimately determine the forest sustainability and functionality in catering to society’s demands of goods and services [14
]. To achieve the objectives of reduced greenhouse gas emissions, economic activity, and employment, the EU and Norway have asserted on policies of increased wood supply [12
]. Better knowledge of factors influencing NIPF owners’ forest management decisions (including harvest) and reasons for owning forest is important for designing policies [14
]. Studies of timber supply have been carried out in Norway [12
], but in contrast to other countries with sizeable private ownership base, a lack of knowledge of the attitudes and objectives of ownership among Norwegian forest owners restricts effective policy-making. In particular, more insight on owners that do not harvest is warranted because relatively little attention has been paid to this growing owner group. We will fill parts of both these voids by combining national-level harvest, income, and tax panel data with survey data of attitudes and objectives of ownership sampled on owners who harvest and those who do not. Several of the revealed-preferences studies use the tobit modelling approach [20
], while others use a two-step logit/probit and linear modeling approach [23
]. The stated-preferences framework constitutes another branch of timber supply studies that we are not incorporating in this study [12
In the two-step procedure, forest owners are first assumed to decide to harvest or not modelled by the probit model. If a positive decision is made, then the harvest volume is decided (linear model). In tobit modelling, both the decision to harvest and the volume are assumed to be determined together. Both modelling approaches can reflect reality well. It may be realistic that owners may first take the decision to harvest given prices and other factors and thereafter decide how much to harvest. For instance, total volume may be determined only when the harvest is complete, as more information about available timber volumes and forest conditions may be unveiled during the harvest operations. However, if they are using a management plan with periodic harvest volumes, forest owners may decide the timing of the prescribed harvest volumes; in this way, the decision to harvest and harvest volumes are taken together.
Although both the tobit and two-step approaches are well documented in the literature, we have not come across studies that compare the two. As the outcomes of modelling approaches cannot be directly compared between studies using different datasets, it is not clear how the choice between these two main econometric pathways steer the results. We fill part of that void by constructing models using the same dataset to compare the outcomes of the approaches directly. Another contribution of our study is the enhanced modelling used in conjunction with an extensive panel data set [29
With this study, we provide key insights to help better understand Norwegian NIPF owner characteristics and timber harvesting decisions. Our specific objectives were to (1) evaluate the differences in the socio-economic profiles, objectives, and attitudes between owners who do and do not harvest timber for sale in Norway; (2) analyze and compare the impact of different factors on timber harvesting behavior (decision-making modes) of NIPF owners using tobit and two-step probit and linear modelling.
The rest of this paper proceeds as follows. In Section 2
, we draw the hypotheses based on the literature review. Section 3
provides an overview of the theoretical background and econometric modelling techniques used to analyze the timber harvest behavior of NIPF owners. The results are presented in Section 4
, while the implications of the results are discussed in Section 5
and conclusions are drawn in Section 6
2. Literature Review and Hypotheses
The decision of forest owners to harvest/not harvest timber is guided by many factors [12
]. Among many variables, timber price, forest size, distance to property, ownership objectives, policy awareness, membership in a forest organization, and socio-economic factors such as age, gender, education, income, and net wealth have been emphasized in the following studies [22
]. However, their reported magnitude and statistical significance on timber harvesting intentions and intensities are not consistent across studies [30
]. For instance, timber price was found to affect NIPF owners’ harvesting behavior significantly in several studies [18
], while other studies found no or ambiguous response of NIPF owners to timber prices [27
Forest property size has been stressed as an essential factor influencing NIPF owners’ harvesting choices in many studies, although the direction and impact may vary based on the forest conditions [12
]. A positive association between the size of the forest land and NIPF owners’ intention to harvest timber was reported by [34
] and [21
] in the USA and Norway, respectively.
Increasing age restricts the interest of forest owners in timber harvesting because of their reduced requirement for income and the intention to sell or transfer the forest property in the near future [17
]. Conversely, a study conducted in Mississippi, USA found that older NIPF owners were more likely to supply woody biomass compared to younger landowners [41
]. Concerning gender, [42
] in Finland observed that female owners harvested 30% less timber than male owners, but harvested larger quantities when they did. The distance to forest property from the owner’s residence is inversely related to timber harvest due to weaker motivations for ownership [39
The higher level of income provides an opportunity for acquiring more forests and advanced equipment to improve harvesting efficiency, resulting in higher financial gains, and income may be positively related to intentions to make income from the forest. Therefore, a higher income may increase the probabilities of engaging in timber harvesting [17
]. On the other hand, other sources of income reduce the importance of timber. Hence, owners tend to prioritize conservation or recreation values in comparison to harvest [20
]. The above statements signify an ambiguous income–harvest relationship for forest owners [12
In a study conducted by [17
], education level had a significant impact on the willingness to harvest, with a marginal effect of 28%. This signifies that education enhances knowledge and understanding of forests as resources among forest owners. Studies by [23
] and [46
] in Norway and Sweden, respectively, found that owners with higher education harvested more. Conversely, [47
] in Canada and [48
] in Finland observed that forest owners with higher education attached greater importance to aesthetic and conservation values than to harvesting.
Public policies like forestry assistance and incentive programs are often designed to motivate owners to actively manage forest land [49
]. The main policy instrument in Norway is the “Forest Fund”. Forest owners have to set to aside a self-selected share between 4% and 40% of the forestry gross income for this fund. No tax is levied on the amount deposited in the fund, but if the forest owner decides to invest this amount in forestry activity, only 15% will be taxed [51
]. The tax waiver assistance results in higher after-tax income and incentivizes maintaining or establishing new stands [12
]. Therefore, we hypothesized that NIPF owners with greater knowledge of the Forest Fund would be more positive towards timber harvesting.
The reasons and objectives for owning forest property contribute significantly to the decision making of forest owners towards managing forests [52
]. Forest owners’ higher preference for non-timber benefits compared to timber harvesting is highlighted in many studies [17
]. Similarly, authors in [54
] also reported that owners’ forest management objective was to prioritize conservation or environment protection over the production of wood.
Based on the literature, we hypothesized that the factors specified in Table 1
impact timber supply.
NIPF owners possess a vast proportion of productive forest and play a paramount role in the sustainability of forests and the forest sector in Norway [73
]. However, a total of about 22% of the productive forest area had no timber harvest for sale during the last twenty years [8
]. In-depth analyses of factors influencing NIPF owners’ forest management decisions are warranted to formulate efficient policies that encourage sustainable supply of timber and non-timber services [17
]. Our study used a statistical approach to encompass the observed behavior of forest owners at different stages in the timber harvesting decision-making in Norway.
Forest area was significant in the probit and linear models, but with different sign and inversely related to timber harvest intensity in the linear model. The forest area was inversely related to timber supply because of the higher productivity and larger growing stock recorded on the smaller properties [9
]. The finding that forest property size affects harvesting decisions is consistent with earlier findings [21
]. We found that gender was a significant factor influencing timber harvesting across all models. In European and many other countries, significant gender differences are observed among private forest owners [73
]. Female forest owners place more emphasis on conservation values than their male counterparts, and hence are less inclined towards harvesting [45
]. Compared to male owners, female forest owners have been found to be older across Europe with less competence in forestry [76
] and low engagement in practical forestry [75
The results support our hypothesis that information on the Forest Fund has a strong significance in motivating NIPF owners towards timber harvesting in Norway. These type of forestry incentives are positively influencing timber harvesting activities [77
]. Hence, it should be noted that 40% of the forest owners possess a low level of awareness about and participation in these programmes. Sjølie et al. [12
] found that forest owner organizations were the main source of information for Active owners. Only a small share of Inactive forest owners (17%) were members of the forest organizations in comparison to Active owners (72%). The direction of effects remains to be elucidated, but higher participation in forest organization might raise awareness and encourage activity on forestland. Forest owners with a previous record of harvesting possess a sense of familiarity with forest policies, and hence have fewer reservations about starting a new activity [79
]. In contrast, forest owners with limited knowledge about the Forest Fund erroneously estimate taxes after timber harvest and the cost of stand establishment after harvesting [12
The statements that determined ownership objectives in our study are financial security from the timber harvesting. The financial attribute was the strongest separating factor between Active and Inactive NIPF owners. The results support our hypothesis that Active forest owners with economic objectives for managing their forests were positively inclined towards timber harvesting. Our study results are consistent with [18
], indicating that forest property is considered as an asset by forest owners to attain a sense of financial security and well-being. On the contrary, a number of studies recorded that NIPF owners do not recognize forests for financial security but more for recreation or other non-timber amenities [47
]. A total of 50% of Inactive forest owners did not visit their forest property during the last 12 months. The reason could be that a significant number of Inactive owners (21%) in the study were above 70 years of age and many lived far away from their property, which is consistent with findings from other countries [26
The European Union adopted an updated version of its renewable energy directive in 2018 [87
], committing to cover at least 32% of its energy from renewable sources by 2030. Norway is also covered by this directive, as it is part of the European Economic Area. Forest biomass is expected to contribute significantly to Europe’s renewable energy mix towards 2030. Currently, 8% of the total energy and about two-thirds of the bioenergy supplied in the EU stems from biomass; the total bioenergy supply from forests is projected to grow by 2030 [88
]. In this regard, the present study contributes to our understanding of the driving forces of timber supply, which may aid authorities in formulating policies that encourage more forest owners towards timber harvesting.
A larger harvest will also contribute to higher economic activities in rural areas and promote viable and sustainable rural communities. This will help to fulfil a core objective of Norway’s political agenda—to develop rural areas with proper population settlement patterns distributed over the country [82
]. The same concept is also adopted by the EU through the rural development policy of diversification of economic activity in rural areas [90
In this study, we followed a statistical modelling approach of probit-linear and tobit regression to determine the significance of various variables in different settings of forest owner timber harvesting decision-making. Comparing the modelling approaches, we believe that both the one-step and two-step approaches could realistically reflect forest owner decision-making. These two statistical pathways give two sets of results that vary in their assumptions. The probit/linear model result outcomes are more useful to be employed when harvesting timber is decided as two separate decisions—firstly harvest or not harvest, and secondly the quantity of timber to harvest. Whereas, when both decisions come at once, then results from the tobit model will have more relevance. Therefore, both models have significant contributions based on the situation of the forest owner. Furthermore, it needs to be validated which approach may reflect forest owners’ actual decision-making in different settings. This may vary according to the specific situation or forest owner and property characteristics. Better understanding of forest owner decision-making processes is a topic for future studies.
However, the given elasticity of supply with regard to price was very high in the linear model and insignificant in the probit model. In the tobit model, this elasticity was 0.66, about at the expected value consistent with the elasticities reported by previous studies [22
]. The higher elasticity in the linear model may be due to the fact that only positive harvest volumes were included in the model; and thus this elasticity applies to owners who had already made the decision to harvest.
Our study found that forest owners with economic objectives were more inclined to harvest, and that male owners harvested more than female owners. Across all three statistical models applied for the analysis, the two variables gender and economic objectives were observed to be significant in influencing timber harvest, whereas other variables like age, distance to property, timber price, knowledge of the forest fund, and property size also had an impact on harvesting in some models. Both modelling approaches (i.e., probit/linear and tobit) reflect forest owner decision-making. The suitability of the approaches in specific contexts could be further explored, as this study only compared and presented the outcomes of both statistical pathways.
Our study provides detailed insights about the factors influencing the timber harvesting behavior of NIPF owners in Norway. This study also identified the owner groups that may require special attention from forest policymakers and extension services, such as female owners and owners with limited knowledge on forest policy instruments. Policies and information campaigns may be more effective when directed to particular groups of forest owners. Policy-makers should consider these factors for designing effective and efficient forest policy instruments.