Spatial econometrics in R
|Kod Erasmus / ISCED:||
|Nazwa przedmiotu:||Spatial econometrics in R|
|Jednostka:||Wydział Nauk Ekonomicznych|
Przedmioty kierunkowe dla Data Science
Przedmioty kierunkowe do wyboru - studia II stopnia EP - grupa 1 (3*30h)
Przedmioty kierunkowe do wyboru - studia II stopnia EP - grupa 3 (1*30h)
Przedmioty kierunkowe do wyboru - studia II stopnia IE - grupa 1 (6*30h)
Przedmioty kierunkowe do wyboru - studia II stopnia IE - grupa 2 (2*30h)
Przedmioty kierunkowe do wyboru- studia I stopnia EP
Przedmioty wyboru kierunkowego dla studiów licencjackich FIM
Przedmioty wyboru kierunkowego dla studiów licencjackich IE
|Punkty ECTS i inne:||
(tylko po angielsku)
Spatial Econometrics deals with the problems of spatial dependence and spatial diversity, using geo-localized data. The main aim of the course is to familiarize students with the methods of analysis and testing of spatial dependence and the rules of estimation and interpretation of spatial models. Students will also learn the fundamentals of spatial research and visualization on maps of regional and point data. Students will work using the R software, hence part of the classes will be devoted to learn this software (prior knowledge of the R is not required). Classes are conducted as workshops – mostly based on practical aspects. The final grade is based on the prepared research project, alone or in groups and on the paper review (text in English chosen by the teacher).
(tylko po angielsku)
Methods of spatial econometrics and statistics are used in regional research, real estate market research, natural resources, environmental economics, public sector economics and international economics, innovation, insurance, etc., as well as business locations. Analysis of these issues using classical statistics and econometrics, which ignore spatial dependencies, give incorrect results. Spatial econometrics allow to see the relationship between neighborly observations and include this information in modelling. It complements traditional methods in relation to spatial problems, but requires specific data sets (geo-localized data and contour maps) and specialized econometric-statistical packages.
During the classes, the students get to know the methods for spatial econometrics, from the basics to the level enabling their own research. We use R software (Open Source available from www.r-project.org), so it can be used without restrictions and without costs both in scientific work and for commercial purposes.
• What is spatial econometrics? The specificity of spatial research, spatial effects - data, types of spatial dependency,
spatial diversity, relationships in space
• Visualization of regional and point data - determination of centroids, layered mapping, operation on spatial geometries
• Spatial weights matrix - construction, properties, operations, usage
• Formalization of spatial dependence - spatial lag operator, spatial autocorrelation measures (Moran’s I, LISA), spatial dependence testing
• Specification and testing of spatial models - models with one (SLX, SLM, SEM), two (SAC, SDM, SDEM) or three (GNS) spatial components, testing: AIC, BIC, LR, and Moran tests for residuals
• Complex models - spatial interaction models, panel models, cumulative models
• Clustering of spatial data, tessellation for point data
• Practical applications of spatial analyzes - based on selected articles
|Efekty uczenia się:||
(tylko po angielsku)
• Knows in details the methods and tools for describing economic and social phenomena in spatial terms. Knows statistics and spatial models. knows the sources of regional data acquisition. Knows how to use an advanced statistical program in the description of economic and social phenomena.
• By working with an open source licensed program and by using teaching materials created at WNE UW, knows and understands the basic concepts and principles in the field of industrial property and copyright protection and is able to use the tools made available on the principles of Open Source and Creative Commons
• Knows the application possibilities of the statistical methods presented and on this basis can create the business analyses
• On the basis of the spatial and panel data analysis, student has expanded knowledge about social spatial structures and their changes over time. Student is able to assess the influence of space on economic and social processes, analyze analytically the diversity and similarity of regions, define spatial regimes
• By critically analyzing the results of statistical surveys and economic theory student can use theoretical knowledge to describe and analyze the causes and course of social processes and phenomena, and can formulate his own opinions and critically select data and methods of analysis
• Can acquire regional data, map in a vector form and thanks to the ability to work with R software can graphically present spatial data, calculate spatial statistics, estimate the econometric spatial model and draw conclusions about spatial dependencies on the basis of the presented results.
• Is able to carry out spatial analysis. Is able to search for data, apply the description of statistical or econometric modeling. Student can present in writing and pass the entire research process as a report.
• Becoming acquainted with an advanced statistical program allows for expanding knowledge on his own and is a good introduction to learn object oriented programming.
• The method of passing the subject allow to be critical in relation to the presented models and correctly identify and resolve dilemmas using these methods in running own business or professional work
|Metody i kryteria oceniania:||
(tylko po angielsku)
Own research project (50%) - to carry out a quantitative spatial analysis study alone in a group of two. Possible theoretical works (eg comparison of methods, evaluation of the properties of the method) and thematic (analysis on empirical data).
The research project must include:
- introduction to the subject, putting a research hypothesis
- description of the data - source, spatial diversity, or changes in time
- specification of the problem / econometric model and expectations
- model estimation and diagnostics / spatial quantitative analysis
- interpretation of results and conclusions
Review of the assigned article (50%) - written (critical) review of the test selected by the teacher (texts in English)
The review of the article must include:
- purpose and area of the research - research questions / hypotheses, data used, geographical area
- spatial methods used in the study along with their own opinion on the appropriateness of their use - should be discussed for what purpose a specific method was used, what were the expectations of the results
- results of the study (in general) - was it possible to answer the question asked by the researcher whether spatial methods brought additional information in comparison with classical methods
- general opinion about the text, comments, comments, additional know-how
Zajęcia w cyklu "Semestr letni 2021/22" (zakończony)
Właścicielem praw autorskich jest Uniwersytet Warszawski, Wydział Nauk Ekonomicznych.