Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally-defined groups – such as segregation, isolation or concentration indexes – are often only capable of identifying just one aspect of this distribution. The strengths or weaknesses of any measure can only be comprehensively assessed empirically. This paper provides evidence on the empirical properties of various spatial measures of cultural diversity by using Monte Carlo replications of agent-based modeling (MC-ABM) simulations with synthetic data assigned to a realistic and detailed geographical context of the city of Amsterdam. Schelling’s classical segregation model is used as the theoretical engine to generate patterns of spatial clustering. The data inputs include the initial population, the number and shares of various cultural groups, and their preferences with respect to co-location. Our MC-ABM data generating process produces output maps that enable us to assess the performance of various spatial measures of cultural diversity under a range of demographic compositions and preferences. We find that, as our simulated city becomes more diverse, stable residential location equilibria are only possible when people, particularly minorities, become more tolerant. We test whether observed measures can be interpreted as revealing unobserved preferences for co-location of individuals with their own group and find that the segregation and isolation measures of spatial diversity are shown to be non-decreasing in increasing preference for within-group co-location, but the Gini coefficient and concentration measures are not.
{"title":"How Diverse Can Spatial Measures of Cultural Diversity Be? Results from Monte Carlo Simulations of an Agent-Based Model","authors":"Daniel Arribas-Bel, P. Nijkamp, J. Poot","doi":"10.2139/ssrn.2462417","DOIUrl":"https://doi.org/10.2139/ssrn.2462417","url":null,"abstract":"Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally-defined groups – such as segregation, isolation or concentration indexes – are often only capable of identifying just one aspect of this distribution. The strengths or weaknesses of any measure can only be comprehensively assessed empirically. This paper provides evidence on the empirical properties of various spatial measures of cultural diversity by using Monte Carlo replications of agent-based modeling (MC-ABM) simulations with synthetic data assigned to a realistic and detailed geographical context of the city of Amsterdam. Schelling’s classical segregation model is used as the theoretical engine to generate patterns of spatial clustering. The data inputs include the initial population, the number and shares of various cultural groups, and their preferences with respect to co-location. Our MC-ABM data generating process produces output maps that enable us to assess the performance of various spatial measures of cultural diversity under a range of demographic compositions and preferences. We find that, as our simulated city becomes more diverse, stable residential location equilibria are only possible when people, particularly minorities, become more tolerant. We test whether observed measures can be interpreted as revealing unobserved preferences for co-location of individuals with their own group and find that the segregation and isolation measures of spatial diversity are shown to be non-decreasing in increasing preference for within-group co-location, but the Gini coefficient and concentration measures are not.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"46 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113931497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a new method for finding causal relationships in spatiotemporal event data with potential applications in conflict research, criminology, and epidemiology. The method analyzes how different types of interventions affect subsequent levels of reactive events. Sliding spatiotemporal windows and statistical matching are used for robust and clean causal inference. Thereby, two well-described empirical problems in establishing causal relationships in event data analysis are resolved: the modifiable areal unit problem and selection bias. The paper presents the method formally and demonstrates its effectiveness in Monte Carlo simulations and an empirical example by showing how instances of civilian assistance to US forces changed in response to indiscriminate insurgent violence in Iraq.
{"title":"Matched Wake Analysis: Finding Causal Relationships in Spatiotemporal Event Data","authors":"Sebastian Schutte, K. Donnay","doi":"10.2139/ssrn.2425119","DOIUrl":"https://doi.org/10.2139/ssrn.2425119","url":null,"abstract":"This paper introduces a new method for finding causal relationships in spatiotemporal event data with potential applications in conflict research, criminology, and epidemiology. The method analyzes how different types of interventions affect subsequent levels of reactive events. Sliding spatiotemporal windows and statistical matching are used for robust and clean causal inference. Thereby, two well-described empirical problems in establishing causal relationships in event data analysis are resolved: the modifiable areal unit problem and selection bias. The paper presents the method formally and demonstrates its effectiveness in Monte Carlo simulations and an empirical example by showing how instances of civilian assistance to US forces changed in response to indiscriminate insurgent violence in Iraq.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"34 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122766894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spatial interaction models represent a class of models that are used for modelling origin-destination flow data. The focus of this paper is on the log-normal version of the model. In this context, we consider spatial econometric specifications that can be used to accommodate two types of dependence scenarios, one involving endogenous interaction and the other exogenous interaction. These model specifications replace the conventional assumption of independence between origin-destination flows with formal approaches that allow for two different types of spatial dependence in magnitudes. Endogenous interaction reflects situations where there is a reaction to feedback regarding flow magnitudes from regions neighbouring origin and destination regions. This type of interaction can be modelled using specifications proposed by LeSage and Pace (2008) who use spatial lags of the dependent variable to quantify the magnitude and extent of the feedback effects, hence the term endogenous interaction. Exogenous interaction represents a situation where spillovers arise from nearby (or perhaps even distant) regions, and these need to be taken into account when modelling observed variations in flows across the network of regions. In contrast to endogenous interaction, these contextual effects do not generate reactions to the spillovers, leading to a model specification that can be interpreted without considering changes in the long-run equilibrium state of the system of flows. As in the case of social networks, contextual effects are modelled using spatial lags of the explanatory variables that represent characteristics of neighbouring (or more generally connected) regions, but not spatial lags of the dependent variable, hence the term exogenous interaction. In addition to setting forth expressions for the true partial derivatives of non-spatial and endogenous spatial interaction models and associated scalar summary measures from Thomas-Agnan and LeSage (2014), we propose new scalar summary measures for the exogenous spatial interaction specification introduced here. An illustration applies the exogenous spatial interaction model to a flow matrix of teacher movements between 67 school districts in the state of Florida.
{"title":"Spatial Regression-Based Model Specifications for Exogenous and Endogenous Spatial Interaction","authors":"J. LeSage, M. Fischer","doi":"10.2139/ssrn.2420746","DOIUrl":"https://doi.org/10.2139/ssrn.2420746","url":null,"abstract":"Spatial interaction models represent a class of models that are used for modelling origin-destination flow data. The focus of this paper is on the log-normal version of the model. In this context, we consider spatial econometric specifications that can be used to accommodate two types of dependence scenarios, one involving endogenous interaction and the other exogenous interaction. These model specifications replace the conventional assumption of independence between origin-destination flows with formal approaches that allow for two different types of spatial dependence in magnitudes. Endogenous interaction reflects situations where there is a reaction to feedback regarding flow magnitudes from regions neighbouring origin and destination regions. This type of interaction can be modelled using specifications proposed by LeSage and Pace (2008) who use spatial lags of the dependent variable to quantify the magnitude and extent of the feedback effects, hence the term endogenous interaction. Exogenous interaction represents a situation where spillovers arise from nearby (or perhaps even distant) regions, and these need to be taken into account when modelling observed variations in flows across the network of regions. In contrast to endogenous interaction, these contextual effects do not generate reactions to the spillovers, leading to a model specification that can be interpreted without considering changes in the long-run equilibrium state of the system of flows. As in the case of social networks, contextual effects are modelled using spatial lags of the explanatory variables that represent characteristics of neighbouring (or more generally connected) regions, but not spatial lags of the dependent variable, hence the term exogenous interaction. In addition to setting forth expressions for the true partial derivatives of non-spatial and endogenous spatial interaction models and associated scalar summary measures from Thomas-Agnan and LeSage (2014), we propose new scalar summary measures for the exogenous spatial interaction specification introduced here. An illustration applies the exogenous spatial interaction model to a flow matrix of teacher movements between 67 school districts in the state of Florida.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123216405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is devoted to the understanding of the emergence of chaos in the discrete time version of the core-periphery model proposed by Currie and Kubin (2006). To this purpose, we present a careful and thorough analysis of the model, including proofs of relevant unproved statements. We are able to describe the sources of chaos and, in some cases, determine how to eliminate them. The analytical study is complemented by numerical simulations in Matlab.
{"title":"Core-Periphery Model in Discrete Time - An Analysis","authors":"L. Garrido-da-Silva","doi":"10.2139/ssrn.2402196","DOIUrl":"https://doi.org/10.2139/ssrn.2402196","url":null,"abstract":"This paper is devoted to the understanding of the emergence of chaos in the discrete time version of the core-periphery model proposed by Currie and Kubin (2006). To this purpose, we present a careful and thorough analysis of the model, including proofs of relevant unproved statements. We are able to describe the sources of chaos and, in some cases, determine how to eliminate them. The analytical study is complemented by numerical simulations in Matlab.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122955703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-02-21DOI: 10.7200/ESICM.146.0443.4
Magdalena Ferrán Aranaz, J. A. Marquez
The strong expansion of mortgage credit in Spain during the second half of the nineties was due to a decline in interest rates (a reduction that was greater in Spain than elsewhere in Europe) and also to a tremendous competition between financial institutions to increase market share. This expansive phase lasted until 2006, followed by a sharp turnaround in 2007. The aim of this paper is to illustrate the evolution of the mortgage market in different Spanish provinces. We have performed a comparative analysis of different regional trajectories using statistics on the number of monthly housing loans for the period between late 1995 and early 2012, applying sheaf methodology for the visual comparison of geographic time series. We conclude that the provinces that have been hit the hardest by the recent recession are those that reached the higher peaks during the expansionary cycle.
{"title":"Identifying Regional Differences in the Spanish Mortgage Market with Sheaf Methodology","authors":"Magdalena Ferrán Aranaz, J. A. Marquez","doi":"10.7200/ESICM.146.0443.4","DOIUrl":"https://doi.org/10.7200/ESICM.146.0443.4","url":null,"abstract":"The strong expansion of mortgage credit in Spain during the second half of the nineties was due to a decline in interest rates (a reduction that was greater in Spain than elsewhere in Europe) and also to a tremendous competition between financial institutions to increase market share. This expansive phase lasted until 2006, followed by a sharp turnaround in 2007. The aim of this paper is to illustrate the evolution of the mortgage market in different Spanish provinces. We have performed a comparative analysis of different regional trajectories using statistics on the number of monthly housing loans for the period between late 1995 and early 2012, applying sheaf methodology for the visual comparison of geographic time series. We conclude that the provinces that have been hit the hardest by the recent recession are those that reached the higher peaks during the expansionary cycle.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130516597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to identify the spatial effects of the main macroeconomic indicators of the eastern and western regions of Russia. These regions differ significantly in population density and the distances between cities. The main research question we are interested in is the following: how are events occurring in one of the western regions, such as economic growth or a decrease in the unemployment rate, effecting similar indicators in other western and eastern regions. The spatial effects of the western and eastern regions, when considered separately, may differ both qualitatively and with of the ‘flow on effect’. The determinants of the same macro-economic indicators in the eastern and western regions may also differ. In order to test the hypothesis of a possible difference in the spatial effects and determinants for these regions, we have developed a special class of model with four spatial matrices (west-west, east-east, west-east, and east-west) and a double set of control variables (one for each type of region). As the macroeconomic indicators monitor the rate of unemployment in the region, the real regional wage and GRP growth for the year were chosen for our models. We controlled the variables describing the socio-demographic situation in the region, migration processes, economic development, and export-import activity in the region. The models were estimated by the Arellano-Bond method on panel data for Russian regions over 2000-2010. Our analysis revealed, 1) a positive spatial correlation of the main macroeconomic indicators for the western regions, 2) both positive and negative externalities for the eastern regions and 3) the asymmetric influence of eastern and western regions on each other. Usually “impulses” from the western regions have a positive effect on the eastern regions, but the “impulses” from the eastern regions usually do not affect the western regions.
{"title":"The Asymmetric Spatial Effects for Eastern and Western Regions of Russia","authors":"O. Demidova","doi":"10.2139/ssrn.2392296","DOIUrl":"https://doi.org/10.2139/ssrn.2392296","url":null,"abstract":"The purpose of this study is to identify the spatial effects of the main macroeconomic indicators of the eastern and western regions of Russia. These regions differ significantly in population density and the distances between cities. The main research question we are interested in is the following: how are events occurring in one of the western regions, such as economic growth or a decrease in the unemployment rate, effecting similar indicators in other western and eastern regions. The spatial effects of the western and eastern regions, when considered separately, may differ both qualitatively and with of the ‘flow on effect’. The determinants of the same macro-economic indicators in the eastern and western regions may also differ. In order to test the hypothesis of a possible difference in the spatial effects and determinants for these regions, we have developed a special class of model with four spatial matrices (west-west, east-east, west-east, and east-west) and a double set of control variables (one for each type of region). As the macroeconomic indicators monitor the rate of unemployment in the region, the real regional wage and GRP growth for the year were chosen for our models. We controlled the variables describing the socio-demographic situation in the region, migration processes, economic development, and export-import activity in the region. The models were estimated by the Arellano-Bond method on panel data for Russian regions over 2000-2010. Our analysis revealed, 1) a positive spatial correlation of the main macroeconomic indicators for the western regions, 2) both positive and negative externalities for the eastern regions and 3) the asymmetric influence of eastern and western regions on each other. Usually “impulses” from the western regions have a positive effect on the eastern regions, but the “impulses” from the eastern regions usually do not affect the western regions.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122404943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines experience of economic corridor development in the South Asia Subregional Economic Cooperation (SASEC) region of South Asia. It lays out an applied framework for prioritizing trade-related interventions and investments according to the expected strength of their combined economic impacts. Along the way, and for the first time, the economic geography of northeastern South Asia has been comprehensively mapped. Computer-driven modeling traces the links between resulting spatial transformations to trade affecting productivity, and the spatial distribution of productivity. Spatial transformation and structural changes suggest another channel for welfare gains from trade. In this way the paper makes a novel contribution to the new economic geography literature.
{"title":"Evaluating Investments in Economic Corridor Development: Lessons from the South Asia Subregional Economic Cooperation Study","authors":"H. Brunner, Kislaya Prasad","doi":"10.2139/ssrn.2382528","DOIUrl":"https://doi.org/10.2139/ssrn.2382528","url":null,"abstract":"This paper examines experience of economic corridor development in the South Asia Subregional Economic Cooperation (SASEC) region of South Asia. It lays out an applied framework for prioritizing trade-related interventions and investments according to the expected strength of their combined economic impacts. Along the way, and for the first time, the economic geography of northeastern South Asia has been comprehensively mapped. Computer-driven modeling traces the links between resulting spatial transformations to trade affecting productivity, and the spatial distribution of productivity. Spatial transformation and structural changes suggest another channel for welfare gains from trade. In this way the paper makes a novel contribution to the new economic geography literature.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116024181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Dabara, Ankeli Ikpeme Anthony, O. Adeyanju, A. G. Odewande
The purpose of this study is to examine the perception of commercial property occupiers’ towards their lease structures, terms and duration (LSTD) in Ede, Nigeria. Questionnaire survey was carried out to elicit for information from the occupiers’ in the study area. The targeted population for the study consisted of 917 shops in prime commercial areas of Ede. The sample size adopted was 12% of the population. The random sampling technique was used in selection of the sample size for the study. Structured questionnaires were administered to shop owners in the study area, which totaled 150. However, only 113 questionnaires were retrieved (i.e 75% response rate). The results from the 113 responses were collated and analyzed using both descriptive and inferential statistics. The study revealed that most occupiers in the study area are satisfied with their current lease duration which is mostly of a year (renewable) duration; most of the occupiers are however dissatisfied with some of the terms in their lease structure. It was recommended that the government should intervene in the real estate rental market in Nigeria by harmonizing the LSTD in the country. Leases should also be structured in such a way that it will be acceptable and satisfactory to both the lessees and the lessors. This will help in the mitigation of the constant conflicts experienced among stakeholders in the Nigerian rental property market as well as address the mismatch between what occupiers’ desire and what lenders or lessors provide.
{"title":"Occupiers' Perception of Commercial Leases: Empirical Evidence from Ede, Nigeria","authors":"D. Dabara, Ankeli Ikpeme Anthony, O. Adeyanju, A. G. Odewande","doi":"10.2139/ssrn.2784504","DOIUrl":"https://doi.org/10.2139/ssrn.2784504","url":null,"abstract":"The purpose of this study is to examine the perception of commercial property occupiers’ towards their lease structures, terms and duration (LSTD) in Ede, Nigeria. Questionnaire survey was carried out to elicit for information from the occupiers’ in the study area. The targeted population for the study consisted of 917 shops in prime commercial areas of Ede. The sample size adopted was 12% of the population. The random sampling technique was used in selection of the sample size for the study. Structured questionnaires were administered to shop owners in the study area, which totaled 150. However, only 113 questionnaires were retrieved (i.e 75% response rate). The results from the 113 responses were collated and analyzed using both descriptive and inferential statistics. The study revealed that most occupiers in the study area are satisfied with their current lease duration which is mostly of a year (renewable) duration; most of the occupiers are however dissatisfied with some of the terms in their lease structure. It was recommended that the government should intervene in the real estate rental market in Nigeria by harmonizing the LSTD in the country. Leases should also be structured in such a way that it will be acceptable and satisfactory to both the lessees and the lessors. This will help in the mitigation of the constant conflicts experienced among stakeholders in the Nigerian rental property market as well as address the mismatch between what occupiers’ desire and what lenders or lessors provide.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"23 Suppl 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131164980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The impact of borrowing constraints on homeownership has been well established in the literature. Wealth is most likely to restrict homeownership followed by credit and income. Using recent movers from the 1979 National Longitudinal Survey of Youth and borrowing constraint definitions commonly used in the literature, we examine the impact of these constraints on the probability of homeownership during the housing market boom between 2003 and 2007. We show that whereas the pool of financially constrained households expanded, the marginal impact of borrowing constraints associated with income and credit quality declined during this period. The constraint associated with wealth, however, continued to have a negative impact on homeownership status, all else equal. The fact that lending standards became less strict is accepted; however the impact of this on homeownership has not been previously studied. Here we find that less restrictive underwriting does appear to have reduced the impact of income and credit quality on homeownership but the impact of the wealth constraint persists.
{"title":"Borrowing Constraints during the Housing Bubble","authors":"Irina Barakova, P. Calem, Susan M. Wachter","doi":"10.2139/ssrn.2229571","DOIUrl":"https://doi.org/10.2139/ssrn.2229571","url":null,"abstract":"The impact of borrowing constraints on homeownership has been well established in the literature. Wealth is most likely to restrict homeownership followed by credit and income. Using recent movers from the 1979 National Longitudinal Survey of Youth and borrowing constraint definitions commonly used in the literature, we examine the impact of these constraints on the probability of homeownership during the housing market boom between 2003 and 2007. We show that whereas the pool of financially constrained households expanded, the marginal impact of borrowing constraints associated with income and credit quality declined during this period. The constraint associated with wealth, however, continued to have a negative impact on homeownership status, all else equal. The fact that lending standards became less strict is accepted; however the impact of this on homeownership has not been previously studied. Here we find that less restrictive underwriting does appear to have reduced the impact of income and credit quality on homeownership but the impact of the wealth constraint persists.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130100027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article addresses the differentiated impacts of various sectors and branches in a multi-layer regional system. As a case-study the Cairngorms National Park (CNP) in Scotland is used. In this area, policy makers ”at different administrative levels” strongly emphasize the need for new sustainable economic development. We use a novel combination of stakeholder analysis with household questionnaires and interregional input-output analysis to define the most important local key-sectors as carriers for local sustainability. The methodological vehicle employed is based on microsimulation. This paper demonstrates how, even for small areas such as the CNP in Scotland, survey information combined with secondary data and existing input-output tables can be integrated into a useful policy tool.
{"title":"Assessment of Local Key Sectors in a Triple-Layer Spatial System","authors":"E. Leeuwen, Y. Ishikawa, P. Nijkamp","doi":"10.2139/ssrn.2328609","DOIUrl":"https://doi.org/10.2139/ssrn.2328609","url":null,"abstract":"This article addresses the differentiated impacts of various sectors and branches in a multi-layer regional system. As a case-study the Cairngorms National Park (CNP) in Scotland is used. In this area, policy makers ”at different administrative levels” strongly emphasize the need for new sustainable economic development. We use a novel combination of stakeholder analysis with household questionnaires and interregional input-output analysis to define the most important local key-sectors as carriers for local sustainability. The methodological vehicle employed is based on microsimulation. This paper demonstrates how, even for small areas such as the CNP in Scotland, survey information combined with secondary data and existing input-output tables can be integrated into a useful policy tool.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125124898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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