Dataset accompanying the publication "A Typology of Industries for Prioritising Infrastructure Investments: A Spatial Approach". The paper constructs a typology of industries to prioritise infrastructure investments in high-return areas in Peru. In doing so, we employ a combination of nonparametric and parametric methods. First, using nonparametric distance-based tests of industry localisation, we find that one-third of manufacturing industries exhibit a relatively high degree of industrial agglomeration. Then using GMM spatial logit models, we explore spatial and non-spatial factors that firms value when deciding where to locate. We find that spatial effects are a key factor of firm’s location, but its importance varies significantly across quartiles of concentration. Finally, we use GMM parameter estimates for agglomerated industries and geographical endowments to construct a typology of industries that differs according to their clustering degree, accessibility to markets, access to inputs, basic infrastructure levels and neighbouring effects. This setup is proposed to help policymakers to prioritise industrial policies in areas where infrastructure investments will generate the highest economic returns in Peru.

Nonparametric distance-based tests and spatial logit models estimated by GMM.

How to cite the database (APA style): Herrera-Catalán, P.; Chasco, C. (2023). A Typology of Industries for Prioritising Infrastructure Investments: A Spatial Approach [Data set & Code] (doi: https://doi.org/10.23728/b2share.ae42619333e64e33a54757ff1a53e38c). Source: Herrera-Catalán, P.; Chasco, C. A Typology of Industries for Prioritising Infrastructure Investments: A Spatial Approach. ECONRES Work-in-Progress 2023/02, Universidad Autónoma de Madrid. https://econresuam.wordpress.com/econres-work-in-progress