Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines

Understanding the causes of land use change is of great importance for issues of tropical deforestation, agricultural development and biodiversity conservation. Many quantitative studies, therefore, aim to link land use change to its causal `driving forces.¿ The epistemology of virtually all these studies is inductive, searching for correlations within relatively large, sometimes spatially explicit, datasets. This can be sound science but we here aim to exemplify that there is also scope for more deductive approaches that test a pre-defined explanatory theory. The paper first introduces the principles and merits of inductive and more deductive types of land use modeling. It then presents one integrated causal model that is subsequently specified to predict land use in an area in northeastern Philippines in a deductive manner, and tested against the observed land use in that area. The same set of land use data is also used in an inductive (multinomial regression) approach. With a goodness-of-prediction of 70% of the deductive model and a goodness-of-fit of 77% of the inductive model, both perform equally well, statistically. Because the deductive model explicitly contains not only the causal factors but also the causal mechanisms that explain land use, the deductive model then provides a more truly causal, as well as more theory-connected, understanding of land use. This provides land use scholarship with an invitation to add more deductive (theory-driven and theory-building) daring to its methodological repertoire.

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Main Authors: Overmars, K.P., de Groot, W.T., Huigen, M.G.A.
Format: Article/Letter to editor biblioteca
Language:English
Subjects:cover change, dynamics, ecology, forest fringe, framework, household life-cycles, proximate causes, tropical deforestation,
Online Access:https://research.wur.nl/en/publications/comparing-inductive-and-deductive-modeling-of-land-use-decisions-
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spelling dig-wur-nl-wurpubs-3555372024-12-04 Overmars, K.P. de Groot, W.T. Huigen, M.G.A. Article/Letter to editor Human Ecology 35 (2007) 4 ISSN: 0300-7839 Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines 2007 Understanding the causes of land use change is of great importance for issues of tropical deforestation, agricultural development and biodiversity conservation. Many quantitative studies, therefore, aim to link land use change to its causal `driving forces.¿ The epistemology of virtually all these studies is inductive, searching for correlations within relatively large, sometimes spatially explicit, datasets. This can be sound science but we here aim to exemplify that there is also scope for more deductive approaches that test a pre-defined explanatory theory. The paper first introduces the principles and merits of inductive and more deductive types of land use modeling. It then presents one integrated causal model that is subsequently specified to predict land use in an area in northeastern Philippines in a deductive manner, and tested against the observed land use in that area. The same set of land use data is also used in an inductive (multinomial regression) approach. With a goodness-of-prediction of 70% of the deductive model and a goodness-of-fit of 77% of the inductive model, both perform equally well, statistically. Because the deductive model explicitly contains not only the causal factors but also the causal mechanisms that explain land use, the deductive model then provides a more truly causal, as well as more theory-connected, understanding of land use. This provides land use scholarship with an invitation to add more deductive (theory-driven and theory-building) daring to its methodological repertoire. en application/pdf https://research.wur.nl/en/publications/comparing-inductive-and-deductive-modeling-of-land-use-decisions- 10.1007/s10745-006-9101-6 https://edepot.wur.nl/16905 cover change dynamics ecology forest fringe framework household life-cycles proximate causes tropical deforestation Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic cover change
dynamics
ecology
forest fringe
framework
household life-cycles
proximate causes
tropical deforestation
cover change
dynamics
ecology
forest fringe
framework
household life-cycles
proximate causes
tropical deforestation
spellingShingle cover change
dynamics
ecology
forest fringe
framework
household life-cycles
proximate causes
tropical deforestation
cover change
dynamics
ecology
forest fringe
framework
household life-cycles
proximate causes
tropical deforestation
Overmars, K.P.
de Groot, W.T.
Huigen, M.G.A.
Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines
description Understanding the causes of land use change is of great importance for issues of tropical deforestation, agricultural development and biodiversity conservation. Many quantitative studies, therefore, aim to link land use change to its causal `driving forces.¿ The epistemology of virtually all these studies is inductive, searching for correlations within relatively large, sometimes spatially explicit, datasets. This can be sound science but we here aim to exemplify that there is also scope for more deductive approaches that test a pre-defined explanatory theory. The paper first introduces the principles and merits of inductive and more deductive types of land use modeling. It then presents one integrated causal model that is subsequently specified to predict land use in an area in northeastern Philippines in a deductive manner, and tested against the observed land use in that area. The same set of land use data is also used in an inductive (multinomial regression) approach. With a goodness-of-prediction of 70% of the deductive model and a goodness-of-fit of 77% of the inductive model, both perform equally well, statistically. Because the deductive model explicitly contains not only the causal factors but also the causal mechanisms that explain land use, the deductive model then provides a more truly causal, as well as more theory-connected, understanding of land use. This provides land use scholarship with an invitation to add more deductive (theory-driven and theory-building) daring to its methodological repertoire.
format Article/Letter to editor
topic_facet cover change
dynamics
ecology
forest fringe
framework
household life-cycles
proximate causes
tropical deforestation
author Overmars, K.P.
de Groot, W.T.
Huigen, M.G.A.
author_facet Overmars, K.P.
de Groot, W.T.
Huigen, M.G.A.
author_sort Overmars, K.P.
title Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines
title_short Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines
title_full Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines
title_fullStr Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines
title_full_unstemmed Comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the Philippines
title_sort comparing inductive and deductive modeling of land use decisions: principles, a model and an illustration from the philippines
url https://research.wur.nl/en/publications/comparing-inductive-and-deductive-modeling-of-land-use-decisions-
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