HISTORECO: Dataset on the Construction of Municipal-Level on Climate, Geography, and Economic Variables in Spain since 1950
Researcher:
Cazcarro Castellano, Ignacio
Congress:
XLIX International Conference on Regional Science
Participation type:
Comunicación oral
Other authors:
Cazcarro Castellano, Ignacio; Rodríguez-López, Guillermo; Serrano, Ana; Martín-Retortillo, Miguel
Year:
2025
Location:
Pamplona, España
Publication:
Cazcarro Castellano, Ignacio; Rodríguez-López, Guillermo; Serrano, Ana; Martín-Retortillo, Miguel (2025). HISTORECO: Dataset on the Construction of Municipal-Level on Climate, Geography, and Economic Variables in Spain since 1950.
This dataset is based on the construction of economic variables at the municipal level in Spain, covering the period from 1950 to the present. The main dataset includes active population and employment data, disaggregated by sector of activity and municipality (complemented with other socioeconomic data, on the type of municipality or society, specialization, etc.). This dataset fills a gap in the literature and databases regarding municipal-level economic data, allowing future studies to explore how various factors, such as rural depopulation and climate change, have influenced economic activities. The data are derived from censuses, statistical yearbooks, and business databases, employing advanced data extraction techniques and imputation methods. These data are useful for socioeconomic research, planning, and policy-making at local and regional levels
• These data provide a unique resource for exploring long-term socioeconomic trends at the municipal level in Spain, a field previously hindered by a lack of coherent data.
• Researchers can use this dataset to investigate factors affecting rural depopulation, urbanization trends, and economic transformations over the past 70 years.
• This period covers the economic development of Spain, a European periphery country, while this economy has been opening to the world economy.
• The dataset is highly adaptable for use in multidisciplinary studies, such as those focusing on climate change, geographical patterns, or regional development policies.
• Municipal-level granularity enables localized analysis, which is crucial for designing targeted policy interventions or conducting historical comparisons.
• This dataset can be integrated with other socio-demographic, land use, and climate data to explore complex interactions at the local level.
This dataset is based on the construction of economic variables at the municipal level in Spain, covering the period from 1950 to the present. The main dataset includes active population and employment data, disaggregated by sector of activity and municipality (complemented with other socioeconomic data, on the type of municipality or society, specialization, etc.). This dataset fills a gap in the literature and databases regarding municipal-level economic data, allowing future studies to explore how various factors, such as rural depopulation and climate change, have influenced economic activities. The data are derived from censuses, statistical yearbooks, and business databases, employing advanced data extraction techniques and imputation methods. These data are useful for socioeconomic research, planning, and policy-making at local and regional levels
• These data provide a unique resource for exploring long-term socioeconomic trends at the municipal level in Spain, a field previously hindered by a lack of coherent data.
• Researchers can use this dataset to investigate factors affecting rural depopulation, urbanization trends, and economic transformations over the past 70 years.
• This period covers the economic development of Spain, a European periphery country, while this economy has been opening to the world economy.
• The dataset is highly adaptable for use in multidisciplinary studies, such as those focusing on climate change, geographical patterns, or regional development policies.
• Municipal-level granularity enables localized analysis, which is crucial for designing targeted policy interventions or conducting historical comparisons.
• This dataset can be integrated with other socio-demographic, land use, and climate data to explore complex interactions at the local level.