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+ + + + +Journal of Open Source Education +JOSE + +2577-3569 + +Open Journals + + + +173 +10.21105/jose.00173 + +Spatial data analysis with R: wrangling, visualization +and econometric models + + + +https://orcid.org/0000-0001-5866-1280 + +Prudencio-Vázquez +Jaime A. + + + + + +Economics Department, Universidad Autónoma Metropolitana, +Unidad Azcapotzalco, CDMX, México. + + + + +1 +3 +2022 + +7 +80 +173 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +-R software -Rstats -regional science -data visualization -spatial +autocorrelation -spatial econometrics + + + + + + Summary +

Spatial Analysis with R: wrangling, visualization and econometric + models (Análisis Espacial con R: manejo, visualización y modelos + econométricos) is a + full + open course in Spanish for the analysis of spatial + information in R software. The course is intended for Spanish-speaking + economics undergraduate students interested in acquiring technical + skills for quantitative analysis required by the regional sciences + (Fischer + & Nijkamp, 2014) and the spatial approach to economics + (Fujita + et al., 2000), but it could be useful for other students of + social sciences attracted by the topic.

+

The objective of the book is to guide the student, from a basic + practical approach, in the knowledge and handling of spatial + information exploration, analysis and modeling techniques through the + use of R + (R + Core Team, 2021) and RStudio, which are, respectively, a + program computer science and programming language focused on + statistical analysis and information visualization, on the one hand, + and an integrated development environment (IDE), on the other.

+

The course is presented in the form of an electronic book and it is + structured in five chapters of gradual learning. In Chapter 1, the + basics of R and RStudio are introduced using the exploratory data + analysis approach + (Croarkin + & Tobias, 2014) not only with the basic R package, but also + with the popular set of tools provided by tidyverse + (Wickham + et al., 2019), that is, the student is completely introduced to + the use of the software to propose and solve questions related to the + information structure. Chapter 2 shows how to create various types of + choropleth maps and the enormous styling customization flexibility for + this purpose via the tmap + (Tennekes, + 2018) package. Chapter 3 presents how to carry out an + exploratory analysis of spatial data where the student will find how + to define the interrelationships that take place in space through the + construction of spatial weight matrices and she will learn about + spatial autocorrelation and its implications in the information + analysis, through various packages such as spdep + (Bivand, + 2022) and rgeoda + (Li + & Anselin, 2022). Meanwhile, in Chapter 4, a synthetic + review of simple regression models is presented, emphasizing the + autocorrelation problem that could occur when estimating a linear + model with spatial data. Finally, in Chapter 5, two of the different + spatial econometric modeling alternatives available in R it is shown, + with spatialreg + (Bivand + et al., 2021).

+

The logic of each chapter integrates three elements: i) explanation + of the fundamental concepts covered, ii) the use of real information + in the software that serves to illustrate the highlighted concepts, + iii) exercises proposed for the student to delve into the topics + exposed.

+

The examples and exercises presented in the course are based on a + database on the situation of the COVID19 pandemic between March and + September 2020 in the Metropolitan Zone of the Valley of Mexico (Zona + Metropolitana del Valle de México), the largest metropolitan area in + Mexico, composed by 76 local administrative units or municipalities + with more than 21 million inhabitants. In addition, the database used + provides information on the economic structure at the municipal level + and a set of variables of sociodemographic characteristics from the + population census.

+ + + Story of the project +

The project arises and is fed by two academic experiences. The + first, which dates back to 2014, corresponds to my work as a teacher + of tools for spatial analysis through various introductory courses. + The second is a course on the use of R software that I taught in the + fall of 2020, from the Economics Department of the Autonomous + Metropolitan University (Universidad Autónoma Metropolitana Unidad + Azcapotzalco), based on Azcapotzalco, Mexico City.

+

As a result, multiple notes and materials were generated and + gradually incorporated into my teaching activity in the Spatial + Econometrics course, for which I have been responsible for more than 3 + years. Spatial Econometrics is part of the academic offer of the + specialization line of the Degree in Economics called “Economics of + Innovation: firms, networks and territory”, of the aforementioned + university. I frequently found myself in need of generating materials + for teaching the contents of Spatial Econometrics. Thus, instead of + isolated and unstructured materials, I decided to compile and order + with a coherent expository logic and gradual learning the set of + materials worked up to now and that now make up this course.

+

Since January 2022, when the integrated version of this series of + materials was put into circulation in the form of an electronic book, + the Spatial Econometrics course has been taught continuously in + quarterly promotions to almost 50 students.

+ + + Statement of Need +

Regional sciences are characterized by their multidisciplinary + character and their solid quantitative support + (Fischer + & Nijkamp, 2014). Although it is true that in all economics + Majors we find a solid repertoire of quantitative instruments: + mathematics, statistics and, of course, econometrics, the necessary + tools for analyzing reality from a spatial and regional perspective + are still scarce within economics, particularly at the undergraduate + level. + Analysis + of spatial data with R intends to be a contribution, albeit + minimal, to remedy this situation.

+

In addition, much of the literature on data management and analysis + of spatial information is still in a language other than Spanish, + mostly in English, which makes access to these tools difficult for + those who do not yet master the language. This becomes a barrier to + knowledge, notably in countries like Mexico where English proficiency + is still very low + (Inglés + Es Posible. Propuesta de Una Agenda Nacional, 2015; + Matt, + 2020). Thus, this material in Spanish becomes a gateway and + facilitates the learning process for the student interested in these + topics.

+

The book, focused on undergraduate students who are not specialists + in the subject, is intended to be an accessible material, because the + used language is didactic and as simple as possible, without losing + rigor.

+

As it is an introductory book, it recommends and invites the use of + multiple materials, both in Spanish and English, so that the student + deepens her own knowledge of spatial information management and the + computer platform in which it is carried out.

+ + + Suggestions for following the course +

Each chapter contains both theoretical and practical elements + related to the treatment of spatial data in the context of economics. + These are illustrated through segments of R code that are explained in + their logic and structure so that the student can not only replicate + the results, but also understand what each piece of code does. In + addition, throughout each chapter, exercises are proposed to deepen, + as a challenge, the knowledge about the tools that are exposed, for + which the answers are not provided.

+

The suggested way to follow the course is through the sequence + proposed by the structure of the book, from chapter 1 to 5, since the + tools are exposed gradually, trying to ensure adequate assimilation. + However, if the student feels already comfortable with handling one + topic, she can move on to the next one without difficulty.

+

Experience in the use of this material indicates that it can be + covered in 5 or 6 weeks, spending between 4.5 and 5 hours per week of + study. Chapter 1 can be covered in approximately 4.5 hours, however if + the student is not familiar with R and RStudio it could take a bit + longer. The choropleth mapping section would be smoothly covered in + about 3 hours. Meanwhile, Chapter 3 on the exploratory analysis of + spatial data, one of the central parts of the book, may require at + least 6 hours of study. Chapter 4, dedicated to the elementary review + of linear regression, can be covered in 3 hours of study, since some + previous knowledge on the subject is assumed, however, more time could + be required if the student needs to review these topics in greater + depth. Finally, Chapter 5, also central to this material, would + require around 6 hours of study.

+ + + Contributions +

This book is, to some extent, an effort to compile and systematize + multiple materials that the active R community, interested in spatial + analysis in Mexico and the world, selflessly shares.

+

I believe that this is how knowledge should always be: free, open + and collaborative, like the software that is used here. Thus, this + project is a living one, in permanent construction and modification, + so all comments and observations will be welcome, both from the + students who have used it, and from the teachers who consider it + appropriate to include it in their reference materials.

+

A guide on how to contribute to this project can be found in the + GitHub repository at + https://github.com/jaime-pru/Analisis-de-datos-espaciales/blob/main/How_to_contribute.md. + Interested people can also contact directly via e-mail + (japv@azc.uam.mx) or even in social media on + X. + All comments are welcome.

+ + + Acknowledgements +

The author thanks Montserrat Romero Martínez (vmrm@azc.uam.mx) and + Alvaro Martínez Rodríguez (amr@azc.uam.mx), assistants in the + Productive Relations Area, who were respectively in charge of + reviewing Preliminary materials for this book and its edition for + publication online with Bookdown on GitHub.

+ + + + + + + + + FischerManfred M. + NijkampPeter + + Handbook of regional science + 2014 + 10.1007/978-3-642-23430-9 + + + + + Inglés es posible. Propuesta de una agenda nacional + Instituto Mexicano para la Competitividad, A.C.; Inglés para la competitividad y la movilidad social; Consejo Empresarial Mexicano de Comercio Exterior, Inversión y Tecnología + 2015 + https://imco.org.mx/wp-content/uploads/2015/04/2015_Documento_completo_Ingles_es_posible.pdf + + + + + + FujitaMasahisa + KrugmanPaul + VenablesAnthony J. + + Economia espacial : Las ciudades, las regiones y el comercio internacional + Ariel + 2000 + + + + + + CroarkinC + TobiasP + + Engineering statistics handbook: E-handbook of statistical methods + NIST/SEMATECH + 2014 + 10.18434/M32189 + + + + + + WickhamHadley + AverickMara + BryanJennifer + ChangWinston + McGowanLucy D’Agostino + FrançoisRomain + GrolemundGarrett + HayesAlex + HenryLionel + HesterJim + KuhnMax + PedersenThomas Lin + MillerEvan + BacheStephan Milton + MüllerKirill + OomsJeroen + RobinsonDavid + SeidelDana Paige + SpinuVitalie + TakahashiKohske + VaughanDavis + WilkeClaus + WooKara + YutaniHiroaki + + Welcome to the tidyverse + Journal of Open Source Software + 2019 + 4 + 43 + 10.21105/joss.01686 + 1686 + + + + + + + TennekesMartijn + + tmap: Thematic maps in R + Journal of Statistical Software + 2018 + 84 + 6 + 10.18637/jss.v084.i06 + 1 + 39 + + + + + + BivandRoger + + R packages for analyzing spatial data: A comparative case study with areal data + Geographical Analysis + 2022 + 54 + 3 + 10.1111/gean.12319 + 488 + 518 + + + + + + LiXun + AnselinLuc + + Rgeoda: R library for spatial data analysis + 2022 + https://CRAN.R-project.org/package=rgeoda + 10.32614/CRAN.package.rgeoda + + + + + + BivandRoger + MilloGiovanni + PirasGianfranco + + A review of software for spatial econometrics in R + Mathematics + 2021 + 9 + 11 + https://www.mdpi.com/2227-7390/9/11/1276 + 10.3390/math9111276 + + + + + + Matt + + EF EPI 2019: El nivel de inglés en méxico sigue disminuyendo ‹ GO blog | EF blog mexico + EF Educación Internacional + 202009 + https://www.ef.com.mx/blog/language/nivel-de-ingles-en-mexico-sigue-disminuyendo/ + + + + + + R Core Team + + R: A language and environment for statistical computing + R Foundation for Statistical Computing + Vienna, Austria + 2021 + https://www.R-project.org/ + + + + +