Overview of results

This section provides a brief summary of the results of the survey, which are detailed in full in Sections 4 and 5; in addition some of the more informal findings are outlined in Section 3.1. To begin with the breakdown of respondents is show in Table 3.1. The even distribution between forester and non-forester shows the cross-sectoral nature of the study although it should be said that many of the so-called non-foresters often worked very closely with forestry issues. The high response rate within FAO reflects the techniques used; meetings arranged face to face rather than questionnaires sent by e-mail. Appendix 1 gives further details concerning respondents.

Table 3.1. Affiliations of survey respondents

Table 3.2 shows the distributions of examples by policy area, income and forest cover. The first number given in each cell of the table represents an example of a policy impact limited to the specific income and forest cover class. The additions refer to examples that spanned the specific class and another class, e.g. both high and low income countries with high forest cover. Overall, the main policy areas of interest are agriculture, energy, and transport, environment and nature protection and several policy areas associated with the institutional framework. The main points are that in low income/high forest cover countries a greater proportion of examples are associated with policies establishing the institutional framework than in high income/high forest cover countries. In the latter policies related to special economic sector are relatively more important. These results demonstrate the relative stages of development of high and low income countries: in low income countries the priority is to install a framework on which to base future socio-economic activity, whereas in high income countries priorities have generally switched to economic growth itself. The general absence of effects related to infrastructure policy results from the frequent inclusion of these policy types under the rural development policy group.

Table 3.2 Distribution of examples with respect to forest cover, income and the type of policy impacting forestry.

N.B. The first number given in each cell of the table represents an example of a policy impact limited to the specific income and forest cover class whilst the additions refer to examples that spanned more than one class.

Figure 3.1 shows the breakdown of policy effects by forest/socio-economic classification and policy area. The majority of examples were of policies affecting lowland forest in the humid tropics which to a large extent reflects the current deforestation trends. The greater proportion of examples in countries with low population densities is probably related to higher forest cover. No notable differences in the proportions of examples concerning different policy groups were evident across classes.

Figure 3.1 Distribution of examples by forest/socio-economic classification

The tables that follow show the distribution of examples by their positive or negative effect on some of the areas detailed in the analysis framework (Table 2.1). For simplicity only the sign (positive or negative) and not the scores (see Sections 4 and 5) were used in the analysis. As few examples affected several of the possible classes, only results tables for forest resources/cover and socio-economic effects are shown.

Table 3.3 shows the number of policy examples having positive and negative effects on forest resources/cover according to income, forest cover and policy group. Of the 71 examples collected in the survey 76% affected forest resources with the majority of negative examples in high forest cover countries attributable to agricultural policies (cash crops, subsistence crops and livestock) and positive examples attributable to environmental policy.

The most interesting result in Table 3.3 is the observation that in both high and low income countries with high forest cover there is a relative preponderance of policies resulting in reduction of the forest resource (negative effects), whereas in both high and low income countries with low forest cover the opposite is true. This suggests that the main explanatory variable for deforestation is forest cover itself. The assertion may therefore be made that the policies that result in deforestation are largely not the result of a lack of integration but result from the relative value ascribed to forest in the face of other national exigencies. Scarcity of forest results in an inflation in forest value that results in policies that more frequently have positive effects and less frequently have negative effects. Potential sources of bias outlined in Section 2.2 should, however, be taken into account. Nonetheless, this result highlights one of the key issues in international forestry, i.e. that at a national level forests are often seen as a consumable commodity, especially if forests are extensive. At the international level, however, forests are becoming scarcer and non-commodity values, especially climate change mitigation and biodiversity conservation, are becoming more apparent. Therefore, although an international agreement on forests and their values should be the main objective in confronting these issues the work here serves to demonstrate the ways in which public policy does in fact affect forests with a view to determining how policy may be ameliorated to better achieve desired objectives. The 45 examples that affected forest degradation/improvement showed a similar distribution to the results for forest resource effects shown below; there were, however, a lower proportion of positive examples with 33% positive as opposed to 43% below.

Table 3.3. Distribution of examples with impacts on forest resources/cover by policy group, national income and forest cover

N.B. The first number given in each cell of the table represents an example of a policy impact limited to the specific income and forest cover class whilst the additions refer to examples that spanned more than one class.

Only 12 of examples (17%) had effects on the management capacity of forests or the application and enforcement of policies. Of eight examples having positive effects, five were the result of policies establishing the institutional framework; specifically privatisation, and social policies. Three of the four examples having negative effects were due to policies establishing the institutional framework, with the other example being and international development policy. Examples in which processors of forest products (17 examples) or markets and demands for forest products (6 examples) were affected came mostly from policies establishing the institutional framework. The preponderance examples (76%) having positive effects on processors of forest products stemmed mainly from forest clearance in low-income countries in countries with high forest cover. The small number of examples affecting markets and demands for forest products (6) precluded meaningful interpretation.

Many examples were given of policies which affected the supply of forest products (37), of which 84% increased supply. Many of these were the side effect of forest clearance but also resulted from opening of forest areas under rural development programmes; nearly all examples relate to high forest cover countries. With respect to effects on soil and water resources, 38% of the 39 examples had positive effects, being evenly distributed amongst the three main policy groups with no conspicuous pattern other than a the prevalence of examples involving environmental policy. The examples having negative effects resulted mostly from policy related to special economic sectors with transport and agriculture dominating.

Table 3.4 shows the distribution of examples according to their socio-economic effects. In contrast to most of the other areas of impact there is a large predominance of positive effects, indeed, of the 71 examples in total 49 had positive socio-economic effects. It is of note that in high forest cover countries (both high and low income) the positive/negative balance of examples opposes that for examples affecting forest resources (Table 3.3) whereas, in low forest cover countries the balance is in the same direction. This suggests that, in general, forestry policies in low forestry cover countries benefit both forestry and people whereas in high forest cover countries, socio-economic benefits are at the expense of forests/forestry. This is perhaps not surprising given the scarcity argument outlined above, however, it also shows that policy can be formulated so that forests are sustainable managed for both socio-economic and environmental benefits.

Table 3.4 Distribution of examples with socio-economic effects on local people and forest users by policy group, national income and forest cover

N.B. The first number given in each cell of the table represents an example of a policy impact limited to the specific income and forest cover class whilst the additions refer to examples that spanned more than one class.

It is hoped that this work will assist policy implementation in such a way that win-win situations in which socio-economic benefits are achieved through forest management may be arrived at. To assist with this the following tables provide the reference numbers of examples (see top right corner of tables in sections 4 and 5) where to some extent win-win, lose-lose and win-lose situations occur. It is recognised that many of these will have costs not accounted for in the analysis framework, but they, nonetheless provide interesting insight. There were no examples of policies which had negative socio-economic effects and positive effects on forest resources.

Examples with positive socio-economic effects and positive effects on forest resources

Examples with negative socio-economic effects and negative effects on forest resources

Examples with positive socio-economic effects and negative effects on forest resources

The examples were relatively evenly spread with respect to continent of origin although almost all were from high forest area countries (81%, 13 examples) and of these 54% (7 examples) were from high-income countries. Two further examples were from low income low forest cover countries and the remaining example covered all high-income countries, both high and low forest cover. In contrast to examples of public policy affecting forestry (Figure 3.1) the majority were associated with temperate and boreal forest in an industrialised countries with market economies as shown in Table 3.6.

Table 3.5 Distribution of examples with respect to forest/socio-economic classification

The natural environment was the most commonly affected area as shown in Table 3.6 being positively affected in 12 of the 16 examples. The most frequent negative effects of forest policy were on special economic sectors. These were nearly all the result of policies preventing development in forest areas either for conservation or through competition for the control of land. The examples with negative effects on other forest users in low income, low forest cover countries were, on the whole, for similar reasons.

Table 3.6. Distribution of examples by area affected, national income and forest cover

N.B. The first number given in each cell of the table represents an example of a policy impact limited to the specific income and forest cover class whilst the additions refer to examples that spanned more than one class.