東南アジア農村の生業構造を理解するための簡易調査手法 --生計多様度指数の標準化と簡便化--

Abstract

農村生業の把握は様々な学術研究や開発実践の基礎にあり、熱帯アジアやアフリカでは特に生業多様性（生業構造）が着目されてきた。しかし、十分に汎用性のある生業多様性の定量的指標は整備されておらず、比較研究やメタ研究を難しくしている。本研究は東南アジアにおける農村世帯の生業構造を表す定量的指標を軸とした簡易な調査手法の提案を目的とする。まず、既存の生業多様度指数を基にして、生計構造多様度指数（Structural Livelihood Diversity Index: SLDI）と生計配分多様度指数（Distributive Livelihood Diversity Index: DLDI）を定めた。次に、両者の標準化のために生計活動種別の12基本区分を設定した。加えて、簡便化した5段階の範囲区分を用意し、DLDIの簡易的な適用を可能にした。さらに、具体的な調査事例での算出と検討およびモンテカルロ法による精度評価をおこない、上記手法が東南アジア農村において一定程度の妥当性を持って適用できることを明らかにした。以上から、SLDIとDLDIの2指数と生計活動種別の12基本区分と占有割合データの5範囲区分の運用基準を合わせたパッケージを簡易生業構造調査法とした。

In the field of agriculture and rural development, a thorough understanding of rural livelihoods forms the basis of academic and development projects. Livelihood diversity (diversification) has been discussed often in the context of household economy, especially in the developing countries of Asia and Africa. However, methods for evaluating livelihood diversification have not yet been standardized to the point where they can be applied to comparative studies or meta-analyses. Therefore, this study aimed to develop a simple method for measuring the livelihood diversity of rural households in Southeast Asia based on common indices and standardized measures. First, two popular indices were selected: the Structural Livelihood Diversity Index (SLDI) and the Distributive Livelihood Diversity Index (DLDI), which is an inversed Simpson index. Then, to extend the potential application of the SLDI and DLDI, two additional measures were established. The first measure consisted of 12 general categories for classifying livelihood activities that are applicable to rural villages under the different ecological and socioeconomic conditions of the region. The second measure consisted of a scale comprising five grades for classifying ranges in the quantitative data. Finally, a package consisting of the two indices and the two measures could be practically applied to some cases on both the mainland and insular Southeast Asia. The accuracy of the developed method was verified using the Monte Carlo method.