Forest sector contribution to the National Economy: Example wood products value chains originating from Iringa region, Tanzania

The contribution of the forest sector to the national economy and to livelihood of people is often underestimated, particularly where its ripple effects in the economy are ignored, placing it in less advantageous position in decisions regarding resource allocation among sectors of a national economy. In order to depict the sector’s contribution to Tanzania’s economy, data was collected at macro (Input-Output tables for base year 2015) and micro (wood products value chains) levels. At macro level, analysis involved categorization of national production into (1) forest and related sector production (FRSP) and (2) other sector (non-forest related) production (OSP). Gross value added (GVA), Simple Output Multipliers (SOM) and net trade values were revealed. At micro level, a Participative Innovation Platform (PIP) workshop was conducted in one region, Iringa, purposively selected due to availability of data sources for variety of wood products value chains in the region. Also, a survey of 369 smallholders and 2 large-scale wood enterprises was done to acquire data to quantify the chains value added and its distribution into margins, wages and taxes. Results revealed that the forest sector was comprised of 6 out of 67 sectors of the national economy and contributed 4.26% to GVA. The study concluded that primary wood production from the forestry and logging sector was consumed mainly as final demand despite the low economic linkage of the sector in inducing output to national economy. Hence, investment in secondary and tertiary wood sectors should be encouraged to boost the forest sector’s contribution.

Highlights

Tanzania forest sector contributes 4.26% to gross value added.

The sector experiences a trade deficit of USD 148.71 million.

The chain involving smallholder wood producers face several problems.

Investment in secondary and tertiary wood sectors would raise contribution.

Analytical generalisation of studied cases permitted the overall model interpretation.

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Dr. Beatus John Temu, Author of this Scientific Article

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