BUSCADOR RECOLECTA

This dataset is the basis of the work titled “The short-run relationship between inequality and growth: evidence from OECD regions during the Great Recession”, published in Regional Studies (DOI: 10.1080/00343404.2018.1476752). This paper provides evidence on the relationship between income inequality and economic growth in Organisation for Economic Co-operation and Development (OECD) regions during the decade 2003–13. It combines household survey data and macroeconomic databases, covering over 200 comparable regions in 15 OECD countries. The econometric results, based on two alternative sets of instruments, highlight a general negative association between inequalities and economic growth since the start of the economic crisis. This relationship is sensitive to the type of urban structure. Higher inequalities seem to be more detrimental for growth in regions characterized by medium to large-sized cities, while regions characterized by small cities and rural areas are less affected.

Identifying integrated urban areas is an important issue for urban analysis and policy evaluation. In this paper, we provide a set of FUAs suitable for monitoring urbanization in Ecuador, a less developed country without commuting data. We do so substituting such socioeconomic flows by available information on road structure, which allow us to work with accessibility based on a varying travel time. In order to build Ecuadorean FUAs, we calibrate our methodology considering Colombian data. We perform several sensitivity analysis and robustness checks to Ecuador with alternative sources of socioeconomic flows. We conclude that the use of GIS data and the calibrated thresholds provide a set of FUAs close to the ones that would result of using commuting information.

This dataset refers to PERCEIVE tasks 2.2, 2.3, 2.4 and 2.5. These tasks analyze the data sets developed by PERCEIVE task 2.1 in order to identify, quantify and synthetize the most important variables to asses identification with EU by citizens. The results feed an update of the data set developed in task 2.1. Finally, these data is be used to model convergence of EU citizens' identification in the case study regions. Data consists of the quantitative statistical information used to produce all the results of WP2 and the indicators regarding the variables of interest obtained by means of different statistical techniques. Moreover, data on absorption of EU funds, provided by the EC and other research centres and collected in task 2.5, is be gathered in this data set, together with the results of convergence analysis. This data set is be used to evaluate the EU citizens’ perception of the EU project in relation to regional performance of the cohesion policy and institutional quality. WP2 uses primary data from the survey developed in WP1 (“PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.3: Survey at citizen level” data set) and also comparative case studies on EU countries and regions, coming also from WP1 (”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.1: The framework for the comparative analysis” and ”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.2: Focus group with Cohesion Policy practitioners” data sets). The data set incorporates data from existing sources including Eurostat and information resulting from the Survey conducted at WP1 of the PERCEIVE’s project. As regards secondary data, no additional treatment is needed. Info about the sources of such data, including references to technical details, is provided in the dataset's codebook. Datasets are available in CSV format, being the field delimiter « , » (comma). For further clarification, please look at the README files of every data subset.

This dataset refers to PERCEIVE tasks 2.4 and 2.5. These tasks analyze the data sets developed by PERCEIVE task 2.1 in order to identify, quantify and synthetize the most important variables to asses identification with EU by citizens. The results feed an update of the data set developed in task 2.1. Finally, these data is be used to model convergence of EU citizens' identification in the case study regions.
Data consists of the quantitative statistical information used to produce all the results of WP2 and the indicators regarding the variables of interest obtained by means of different statistical techniques. Moreover, data on absorption of EU funds, provided by the EC and other research centres and collected in task 2.5, is be gathered in this data set, together with the results of convergence analysis.
This data set is be used to evaluate the EU citizens’ perception of the EU project in relation to regional performance of the cohesion policy and institutional quality.
WP2 uses primary data from the survey developed in WP1 (“PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.3: Survey at citizen level” data set) and also comparative case studies on EU countries and regions, coming also from WP1 (”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.1: The framework for the comparative analysis” and ”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.2: Focus group with Cohesion Policy practitioners” data sets). The data set incorporates data from existing sources including Eurostat and information resulting from the Survey conducted at WP1 of the PERCEIVE’s project. As regards secondary data, no additional treatment is needed. Info about the sources of such data, including references to technical details, is provided in the dataset's codebook.

Datasets are available in CSV format, being the field delimiter « , » (comma). For further clarification, please look at the README files of every data subset., Part B of this dataset is available at http://hdl.handle.net/2445/139554 under embargoed access, This dataset refers to PERCEIVE tasks 2.2, 2.3, 2.4 and 2.5. These tasks analyze the data sets developed by PERCEIVE task 2.1 in order to identify, quantify and synthetize the most important variables to asses identification with EU by citizens. The results feed an update of the data set developed in task 2.1. Finally, these data is be used to model convergence of EU citizens' identification in the case study regions. Data consists of the quantitative statistical information used to produce all the results of WP2 and the indicators regarding the variables of interest obtained by means of different statistical techniques. Moreover, data on absorption of EU funds, provided by the EC and other research centres and collected in task 2.5, is be gathered in this data set, together with the results of convergence analysis. This data set is be used to evaluate the EU citizens’ perception of the EU project in relation to regional performance of the cohesion policy and institutional quality. WP2 uses primary data from the survey developed in WP1 (“PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.3: Survey at citizen level” data set) and also comparative case studies on EU countries and regions, coming also from WP1 (”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.1: The framework for the comparative analysis” and ”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.2: Focus group with Cohesion Policy practitioners” data sets). The data set incorporates data from existing sources including Eurostat and information resulting from the Survey conducted at WP1 of the PERCEIVE’s project. As regards secondary data, no additional treatment is needed. Info about the sources of such data, including references to technical details, is provided in the dataset's codebook.

Datasets are available in CSV format, being the field delimiter « , » (comma). For further clarification, please look at the README files of every data subset., Part A of this dataset is publicly available at http://hdl.handle.net/2445/137318, This dataset refers to PERCEIVE tasks 2.4 and 2.5. These tasks analyze the data sets developed by PERCEIVE task 2.1 in order to identify, quantify and synthetize the most important variables to asses identification with EU by citizens. The results feed an update of the data set developed in task 2.1. Finally, these data is be used to model convergence of EU citizens' identification in the case study regions. Data consists of the quantitative statistical information used to produce all the results of WP2 and the indicators regarding the variables of interest obtained by means of different statistical techniques. Moreover, data on absorption of EU funds, provided by the EC and other research centres and collected in task 2.5, is be gathered in this data set, together with the results of convergence analysis. This data set is be used to evaluate the EU citizens’ perception of the EU project in relation to regional performance of the cohesion policy and institutional quality. WP2 uses primary data from the survey developed in WP1 (“PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.3: Survey at citizen level” data set) and also comparative case studies on EU countries and regions, coming also from WP1 (”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.1: The framework for the comparative analysis” and ”PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Task1.2: Focus group with Cohesion Policy practitioners” data sets). The data set incorporates data from existing sources including Eurostat and information resulting from the Survey conducted at WP1 of the PERCEIVE’s project. As regards secondary data, no additional treatment is needed. Info about the sources of such data, including references to technical details, is provided in the dataset's codebook.

Dades associades a l'article: Vicente Royuela, Paolo Veneri & Raul Ramos (2018): The short-run relationship between inequality and growth: evidence from OECD regions during the Great Recession, Regional Studies, DOI: 10.1080/00343404.2018.1476752, This dataset is the basis of the work titled “The short-run relationship between inequality and growth: evidence from OECD regions during the Great Recession”, published in Regional Studies (DOI: 10.1080/00343404.2018.1476752). This paper provides evidence on the relationship between income inequality and economic growth in Organisation for Economic Co-operation and Development (OECD) regions during the decade 2003–13. It combines household survey data and macroeconomic databases, covering over 200 comparable regions in 15 OECD countries. The econometric results, based on two alternative sets of instruments, highlight a general negative association between inequalities and economic growth since the start of the economic crisis. This relationship is sensitive to the type of urban structure. Higher inequalities seem to be more detrimental for growth in regions characterized by medium to large-sized cities, while regions characterized by small cities and rural areas are less affected.

We provide the code for producing Functional Urban Areas by means of using OSM and Google maps data., Dades associades a l'article: Obaco A., Moisés; Royuela Mora, Vicente (2019): Identifying functional urban areas in Ecuador using a varying travel time approach,. Publicat a: Geographical Analysis, 2020, vol. 52, n. 1. (https://onlinelibrary.wiley.com/doi/10.1111/gean.12190). DOI: https://doi.org/10.1111/gean.12190., Podeu consultar l'article associat a: http://hdl.handle.net/2445/154578, Identifying integrated urban areas is an important issue for urban analysis and policy evaluation. In this paper, we provide a set of FUAs suitable for monitoring urbanization in Ecuador, a less developed country without commuting data. We do so substituting such socioeconomic flows by available information on road structure, which allow us to work with accessibility based on a varying travel time. In order to build Ecuadorean FUAs, we calibrate our methodology considering Colombian data. We perform several sensitivity analysis and robustness checks to Ecuador with alternative sources of socioeconomic flows. We conclude that the use of GIS data and the calibrated thresholds provide a set of FUAs close to the ones that would result of using commuting information.