Effects of MAUP on spatial econometric models

Arbia, Giuseppe; Petrarca, Francesca

doi:10.1007/s12076-011-0065-9

Cited by 43 publications

(28 citation statements)

References 13 publications

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“…Moreover, Arbia and Petrarca (2011) present a general framework to investigate the effects of MAUP on spatial econometric models showing how the presence of spatial effects affects the classical results. Arbia and Petrarca (2011) concentrate on the loss in efficiency of the parameters' estimators due to aggregation.…”

Section: Spatial Panel Data Modelsmentioning

confidence: 99%

Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models

et al. 2015

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The goal of this paper is to evaluate the results of regional economic growth model estimations at multiple spatial scales using spatial panel data models. The spatial scales examined are minimum comparable areas, microregions, mesoregions and states between 1970 and 2000. Alternative spatial panel data models with fixed effects were systematically estimated across those spatial scales to demonstrate that the estimated coefficients change with the scale level. The results show that the conclusions obtained from growth regressions depend on the choice of spatial scale. First, the values of spatial spillover coefficients vary according to the spatial scale under analysis. In general, such coefficients are statistically significant at the MCA, microregional and mesoregional levels, however, at state level those coefficients are no longer statistically significant, suggesting that spatial spillovers are bounded in space. Moreover, the positive average-years-of-schooling direct effect coefficient increases as more aggregate spatial scales are used. Population density coefficients show that higher populated areas are harmful to economic growth, indicating that congestion effects are operating in all spatial scales, but their magnitudes vary across geographic scales. Finally, the club convergence hypothesis cannot be rejected suggesting that there are differences in the convergence processes between the north and south in Brazil. Furthermore, the paper discusses the potential theoretical reasons for different results found across estimations at different spatial scales. JEL Classification C23 · O18 · R11 MotivationThe goal of this paper was to evaluate the results of regional economic growth estimates at multiple spatial scales using alternative spatio-temporal models recently proposed in the spatial econometrics literature. During the last two decades, an increasing dissemination of spatial econometrics techniques has been observed among regional scientists, economists, and researchers in several fields (Anselin 1988;Lesage 1999;Conley 1999). The vast research of applied spatial econometrics on the interdependencies among spatial units and their effects on, among others, regional economic growth, trade flows, knowledge spillovers, migration, housing prices, tax interactions, and city's growth controls 1 is well known. However, this literature still lacks a better understanding of the potential reasons why models estimated at different geographic scales yield different results in the context of regional economic growth empirics. 2 Resende (2011) engages in an initial discussion on the determinants of Brazil's regional economic growth at a variety of geographic scales using a cross-sectional data set over the 1990s period. Resende (2013) improves this analysis by using standard panel data models across several spatial scales, but the process of economic growth in Brazil is only examined using non-spatial panel data models. This investigation refers back to the modifiable areal unit problem (MAUP), 3 but it s...

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Section: Spatial Panel Data Modelsmentioning

confidence: 99%

Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models

et al. 2015

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“…7 The effect of the selection of spatial units on analysis is in the statistical literature known as the modifiable areal unit problem (MAUP) (cf. Arbia, 1986;Unwin, 1996), delineated by commuter flows. Using data on job commuters across German districts, Eckey by and large, high-income regions match with high-wage regions.…”

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Market access, regional price level and wage disparities: the German case

Kosfeld

Eckey

2010

Jahrb Reg wiss

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract. In this paper we use the NEG framework of the Helpman model to investigate the spatial distribution of wages across German labour market regions under different assumptions. As the assumptions of equal regional price level and equal real wages are strongly rejected for the German economy, standard approaches may fail to reveal the role of market access in explaining regional wage disparities. In part substantial changes occur when market potential is measured with the aid of regional price levels. With the so-called price index approach, the importance of market access in explaining regional wage differentials is clearly revealed. When controlling for heterogeneity of labour force and spatial dependence, the relationship still remains highly significant. From the price index approach, limited demand linkages of reasonable reach are inferred. Terms of use: Documents inJEL classification: R11, R12, R15

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“…For example, Park & Hewings (2012) revealed that the degree of spatial dependency increases with the use of more disaggregated temporal data. Also, Arbia & Petrarca (2011) deal with the modifiable areal unit problem (MAUP), and showed that the estimated parameters changes with the aggregation of the spatial units. In this paper, since the focus is on the business cycle analysis of the six Great Lake states, and the more disaggregated temporal frequency is thought to best reveal the spatial dependency structure, monthly state level data are used.…”

Section: Notesmentioning

confidence: 99%

Competitive and Complementary Relationship between Regional Economies: A Study of the Great Lake States

Chung

Hewings²

2015

Spatial Economic Analysis

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Since regional economies are exposed to the region common shock, the degree of comovement of each region's business cycle is strong, possibly exaggerating or biasing the dependency on its neighbor regions. By separating out the common shock and the individual shocks using a multi-level dynamic factor model suggested by Bai and Wang, the possible misunderstanding of regional interdependency can be prevented. An application to the Great Lakes region revealed that much of the region-specific business activities can be explained by the region common shock, and the spillovers from neighbors are small or insignificant. Rapports de compétitivité et complémentaires entre économies régionales: une étude des états des Grands LacsRÉSUMÉ étant donné que les économies régionales sont exposées au choc commun de la région, la degré de parallélisme dans le cycle commercial de chaque région est élevé, en exagérant ou en faussant éventuellement la dépendance de ses régions avoisinantes. En séparant le choc commun des chocs individuels, à l'aide d'un modèle de facteur dynamique multi-niveaux du type proposé par Bai et Wang, il est possible d'éviter d'éventuels malentendus d'interdépendance régionale. Une application à la région des grands lacs a révélé qu'une grande partie des activités commerciales spécifiques à la région peuvent être expliquées par le choc commun de la région, et que les retombées de régions voisines sont faibles, voire insignifiantes.Relación competitiva y complementaria entre las economías regionales: un estudio de la Región de los Grandes Lagos RESUMEN dado que las economías regionales están expuestas al choque común regional, la proporción del comovimiento del ciclo comercial de cada región es elevada, posiblemente exagerando o influenciando la dependencia de sus regiones vecinas. A través de la separación del choque común y los Downloaded by [UQ Library] at 01:44 14 June 2015 choques individuales mediante un modelo de factor dinámico de multinivel sugerido por Bai y Wang, se puede evitar el posible malentendido de la interdependencia regional. Una aplicación a la Región de los Grandes Lagos reveló que una gran parte de las actividades comerciales específicas de la región puede explicarse mediante el choque común regional y los excedentes de las regiones vecinas son pequeños o insignificantes.区域经济体之间的竞争和互补关系 : 大湖国家研究摘要 : 由于区域经济体暴露于区域常见的震荡, 每个地区的商业周期一般都呈现很强的同步走向, 因而很可能会夸大或阻碍对相邻区域的依赖关系。通过采用 Bai and Wang 建议的多层次动态因素模型使共同震荡和个别震荡相分离的方法, 可以防止对区域相互依赖的误解。在大湖区的应用结果表明, 很多区域特有的商业活动可通过区域的共同震荡得到解释, 而邻国的溢出效应则往往很小或微不足道。

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Effects of MAUP on spatial econometric models

Abstract: Aggregation effect, Loss in efficiency, MAUP, SARAR models, Scale effect, Spatial econometric, C21, C31, C5,

Cited by 43 publications

References 13 publications

Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models

Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models

Market access, regional price level and wage disparities: the German case

Competitive and Complementary Relationship between Regional Economies: A Study of the Great Lake States

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