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

This paper evaluates, in the context of economic geography estimates, the magnitude of the distortions arising from the choice of zoning system, which is also known as the Modifiable Areal Unit Problem (MAUP). We consider 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 spatial units, which are the two main determinants of the MAUP. While size matters a little, shape does so much less. Both dimensions seem to be of secondary importance compared to specification issues.MAUP ; concentration ;agglomeration ;wage equations ;gravity

DOTS TO BOXES: DO THE SIZE AND SHAPE OF SPATIAL UNITS JEOPARDIZE ECONOMIC GEOGRAPHY ESTIMATIONS?

This paper evaluates, in the context of economic geography estimates, the magnitude of the distortions arising from the choice of zoning system, which is also known as the Modifiable Areal Unit Problem (MAUP). We consider 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 spatial units, which are the two main determinants of the MAUP. While size matters a little, shape does so much less. Both dimensions seem to be of secondary importance compared to specification issues.MAUP, concentration, agglomeration, wage equations, gravity

A Treatise on the Geographical Scale of Agglomeration Externalities and the Modifiable Areal Unit Problem

The modifiable areal unit problem (MAUP) refers to the sensitivity of statistical research results to the initial spatial nomenclature used. Despite a substantial literature in the related field of geography on the potential influence of the MAUP, the urban economic modeling tradition has not paid much attention to this issue. In this article, we test to what extent the MAUP moderates the effect of agglomeration externalities on areal sectoral employment growth by varying the initial geographical scale of analysis. Using spatial cross-regressive modeling in which we account for spatial spillover effects of agglomeration externalities, we find different effects of agglomeration forces across geographical scales. As the MAUP is a theoretical as well as a methodological problem, research should not only work with proper statistical specifications of spatial agglomeration models incorporating different geographical scales, but also relate this more explicitly to hypotheses concerning the geographical scale at which agglomeration externalities operate

Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?

<p>Background: Geographical health inequalities are naturally described by the variation in health outcomes between areas (e.g. mortality rates). However, comparisons made between countries are hampered by our lack of understanding of the effect of the size of administrative units, and in particular the modifiable areal unit problem. Our objective was to assess how differences in geographic and administrative units used for disseminating data affect the description of health inequalities.</p> <p>Methods: Retrospective study of standard populations and deaths aggregated by administrative regions within 20 European countries, 1990-1991. Estimated populations and deaths in males aged 0-64 were in 5 year age bands. Poisson multilevel modelling was conducted of deaths as standardised mortality ratios. The variation between regions within countries was tested for relationships with the mean region population size and the unequal distribution of populations within each country measured using Gini coefficients.</p> <p>Results: There is evidence that countries whose regions vary more in population size show greater variation and hence greater apparent inequalities in mortality counts. The Gini coefficient, measuring inequalities in population size, ranged from 0.1 to 0.5 between countries; an increase of 0.1 was accompanied by a 12-14% increase in the standard deviation of the mortality rates between regions within a country.</p> <p>Conclusions: Apparently differing health inequalities between two countries may be due to differences in geographical structure per se, rather than having any underlying epidemiological cause. Inequalities may be inherently greater in countries whose regions are more unequally populated.</p&gt

Characterizing forest fragmentation : Distinguishing change in composition from configuration

This project was funded by the Government of Canada through the Mountain Pine Beetle Program, a three-year, $100 million program administered by Natural Resources Canada, Canadian Forest Service. Additional information on the Mountain Pine Beetle Program may be found at: http://mpb.cfs.nrcan.gc.ca.Forest fragmentation can generally be considered as two components: 1) compositional change representing forest loss, and 2) configurational change or change in the arrangement of forest land cover. Forest loss and configurational change occur simultaneously, resulting in difficulties isolating the impacts of each component. Measures of forest fragmentation typically consider forest loss and configurational change together. The ecological responses to forest loss and configurational change are different, thus motivating the creation of measures capable of isolating these separate components. In this research, we develop and demonstrate a measure, the proportion of landscape displacement from configuration (P), to quantify the relative contributions of forest loss and configurational change to forest fragmentation. Landscapes with statistically significant forest loss or configurational change are identified using neutral landscape simulations to generate underlying distributions for P. The new measure, P, is applied to a forest landscape where substantial forest loss has occurred from mountain pine beetle mitigation and salvage harvesting. The percent of forest cover and six LPIs (edge density, number of forest patches, area of largest forest patch, mean perimeter area ratio, corrected mean perimeter area ratio, and aggregation index) are used to quantify forest fragmentation and change. In our study area, significant forest loss occurs more frequently than significant configurational change. The P method we demonstrate is effective at identifying landscapes undergoing significant forest loss, significant configurational change, or experiencing a combination of both loss and configurational change.PostprintPeer reviewe

The Bright Side of MAUP: an Enquiry on the Determinants of Industrial Agglomeration in the United States

Using county employment data for US and two appositely developed zoning algorithms, I compare the industrial concentration of manufacturing sectors calculated following the standard metropolitan and micropolitan statistical areas definition with two other counterfactuals, obtained by “gerrymandering” the original sample of counties. The methodology allows i) to obtain an unbiased estimate of industrial agglomeration which significantly improves on existing indices, and ii) to provide a ranking of industries according to their responsiveness to labour market determinants of agglomeration. Results show that labour market determinants explain one quarter of the variation of spatial agglomeration across industries.Industrial Agglomerations, MAUP, Industrial Concentration

On proximity and hierarchy : exploring and modelling space using multilevel modelling and spatial econometrics

Spatial econometrics and also multilevel modelling techniques are increasingly part of the regional scientists‟ toolbox. Both approaches are used to model spatial autocorrelation in a wide variety of applications. However, it is not always clear on which basis researchers make a choice between spatial econometrics and spatial multilevel modelling. Therefore it is useful to compare both techniques. Spatial econometrics incorporates neighbouring areas into the model design; and thus interprets spatial proximity as defined in Tobler‟s first law of geography. On the other hand, multilevel modelling using geographical units takes a more hierarchical approach. In this case the first law of geography can be rephrased as „everything is related to everything else, but things in the same region are more related than things in different regions‟. The hierarchy (multilevel) and the proximity (spatial econometrics) approach are illustrated using Belgian mobility data and productivity data of European regions. One of the advantages of a multilevel model is that it can incorporate more than two levels (spatial scales). Another advantage is that a multilevel structure can easily reflect an administrative structure with different government levels. Spatial econometrics on the other hand works with a unique set of neighbours which has the advantage that there still is a relation between neighbouring municipalities separated by a regional boundary. The concept of distance can also more easily be incorporated in a spatial econometrics setting. Both spatial econometrics and spatial multilevel modelling proved to be valuable techniques in spatial research but more attention should go to the rationale why one of the two approaches is chosen. We conclude with some comments on models which make a combination of both techniques

Relationship between spatial proximity and travel-to-work distance : the effect of the compact city

In this paper, an assessment is made of the relationship between selected aspects of spatial proximity (density, diversity, minimum commuting distance, jobs-housing balance and job accessibility) and reported commuting distances in Flanders (Belgium). Results show that correlations may depend on the considered trip end. For example, a high residential density, a high degree of spatial diversity and a high level of job accessibility are all associated with a short commute by residents, while a high job density is associated with a long commute by employees. A jobs-housing balance close to one is associated with a short commute, both by residents and by employees. In general, it appears that the alleged sustainability benefits of the compact city model are still valid in a context of continuously expanding commuting trip lengths

The Geography of Urban Poverty

The Census Bureau reports poverty statistics annually based on American Community Survey (ACS) data. For the past two years this has included listing the ten places with the highest poverty rates and the ten with the lowest poverty rates. This study considers the interpretation of these statistics when different geographies form the analytical framework. As expected, interpretation of these statistics is influenced by the Modifiable Areal Unit Problem (MAUP) in geography