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Spatial Econometric Analysis: Potential Contribution to the Economic Analysis of Smallholder Development

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Causal Inference in Econometrics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 622))

Abstract

The stars appear to be aligned for a sustained effort to improve information to rural development policy makers about the impact space has on the opportunities for development of the ubiquitous smallholder households in rural areas of Southeast Asian countries. The influences of spatially heterogeneous resource constraints on farming activities, distance to markets and institutions, and spatial interaction among smallholders can now be better accounted for in modelling work as a result of improvements in analytical methodologies, the growing availability of so-called ‘big data’ and access to spatially defined information in panel data sets. The scope for taking advantage of these advances is demonstrated with two examples from a Southeast Asian country, the Philippines: spillovers and neighbourhood effects in impact studies and the development of sophisticated spatial stochastic frontier models to measure and decompose productivity growth on smallholdings.

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  1. UNE Business School, University of New England, Armidale, NSW, Australia

    Renato Villano, Euan Fleming & Jonathan Moss

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  1. Renato Villano
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  2. Euan Fleming
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  1. School of Knowledge Science, Japan Advanced Ins. of Sci. & Tech, Ishikawa, Japan

    Van-Nam Huynh

  2. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  3. Faculty of Economics, Chiang Mai University, Chiangmai, Thailand

    Songsak Sriboonchitta

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Villano, R., Fleming, E., Moss, J. (2016). Spatial Econometric Analysis: Potential Contribution to the Economic Analysis of Smallholder Development. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S. (eds) Causal Inference in Econometrics. Studies in Computational Intelligence, vol 622. Springer, Cham. https://doi.org/10.1007/978-3-319-27284-9_3

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