Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?

By A. Briant, Pierre-Philippe Combes, M. Lafourcade. 2010

322 citations recorded by the source corpus.

This paper evaluates, in the context of economic geography estimates, the magnitude of the distortions arising from the choice of a specific zoning system, which is also known as the Modifiable Areal Unit Problem (MAUP). We undertake three standard economic geography exercises (the analysis of spatial concentration, agglomeration economies, and trade determinants), using various French zoning systems differentiated according to the size and shape of their spatial units. While size might matter, especially when the dependent variable of a regression is not aggregated in the same way as the explanatory variables and/or the zoning system involves large spatial units, shape does so much less. In any case, both dimensions are of secondary importance compared to specification issues.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/099090ac6e18808c348ceb3665cd89883bb9e0df

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In Economics and Econometrics

Citations in the corpus

California Dreamin’: The Feeble Case for Cluster Policies (2011, background): “However, this co-location takes place at a larger spatial scale (up to 120 km) suggesting that the regional level might be most appropriate in this case.39 Second, a detailed analysis of spatial measurement errors is performed by Briant et al. (2010).”
Does rainfall matter for economic growth? Evidence from global sub-national data (1990–2014) (2019, unknown): “2010) -- a problem termed Modifiable Areal Unit Problem, or MAUP in the economic geography literature (Briant et al. 2010).”
Spatial concentration and plant-level productivity in France (2011, background): “2 ; more details about the impact of spatial zoning on economic geography ions, see Briant et al. (2010). m the point of view of the plant, the variables lit ; loc sz it and urb sz t operate an ive tripartition of local employment in manufacturing. where Sszt is the set of firms belonging to…”
Multilevel Approaches and the Firm‐Agglomeration Ambiguity in Economic Growth Studies (2012, unknown): “4 purpose as well (Duranton and Puga 2005, Briant et al. 2010). Recently, two strands of literature have focused on the micro-macro relationships of firms in their relevant contexts using multilevel analysis. On the one hand, urban economics and spatial econometrics consider the connection between h”
Accounting for Neighboring Effects in Measures of Spatial Concentration (2011, unknown): “4 For an updated discussion on the MAUP and its impact on economic geography estimates, see Briant et al. (2010).”
Spatial concentration and location dynamics in logistics:the case of a Dutch province (2013, unknown): “…(e.g. ﬁve-digit postal code areas) result in relatively many more areas without logistics employment (76% of all ﬁve-digit postal code areas versus 19% of the four-digit postal code), artiﬁcially increasing spatial concentration measures such as the locational Gini coeﬃcient (Briant et al., 2010).”
Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models (2016, background): “2 It is worth noting that there is growing empirical literature analyzing MAUP in several areas of urban and regional economics such as Yamamoto (2008), Briant et al. (2010), Fingleton (2011) and Menon (2012).”
A meta-analysis of estimates of urban agglomeration economies (2009, background): “…it seems that the sign reversal could arise from the addition of negative ‘outlier’ values for the elasticity estimates in 8 Using a different methodology, Briant et al. (2008) also test whether the use of spatial units of different size and shape affects the magnitude of agglomeration estimates.”
Agglomeration and Innovation (2014, background): “7 See Audretsch and Feldman (2004) for further discussion of knowledge production functions in a regional setting. square mile) of another metro area.”
The Empirics of Agglomeration Economies (2014, result): “Using density should reduce issues about mismeasurement of the size of the local economy, which is in line with Briant et al. (2010) who show that using more consistent empirical strategies largely reduces MAUP concerns.”