Datasets:
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Gunawan, A. and Mendez, C. (2020). Provincial income, convergence clubs and structural change in Indonesia 2001-2017: An interactive and automated exploration in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/data-indonesia-34-provinces-clubs-2001-2017
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Mendez, C., Siew, S., Chan, R., and Tang, D. (2020). Productivity differences in the ASEAN community: An interactive and automated exploration in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/data-productivity-asean-1972-2017
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Mendez, C. (2020). Regional inequality across countries 1992-2012: An interactive and automated exploration in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/data-regional-lights-gdp-inequality-1992-2012
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Aginta, H.and Mendez, C. (2020). Provincial GDP and unemployment in Indonesia 1986-2018: An animated, automated, and interactive exploration in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/okun-indonesia-provinces-1986-2018
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Mendez, C. (2019). Overall efficiency, pure technical efficiency, and scale efficiency across provinces in Indonesia 1990 and 2010. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/efficiency-clusters-indonesia-1990-2010
Interactive Data Explorations:
Tutorials:
Spatial Analysis
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Mendez C. (2021). Measuring the evolution of spatial dependence and spatial inequality: A tutorial using Python. Available at https://deepnote.com/@carlos-mendez
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Mendez C. (2021). Introduction to exploratory space-time data analysis (ESTDA) using Python. Available at https://deepnote.com/@carlos-mendez
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Mendez C. (2021). Basic spatial econometrics using Python. Available at https://deepnote.com/@carlos-mendez
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Mendez C. (2020). Making maps in R: Using the sf and tmap Packages. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/tutorial-maps-in-r
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Mendez C. (2020). Spatial autocorrelation analysis in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/spatial-autocorrelation
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Santos-Marquez F. (2020) Local Moran’s I and multiple spatial scales in R. R Studio/RPubs. Available at https://rpubs.com/FelipeSantos/LISA_tmap_geoda
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Mendez C. (2020). Spatial regression analysis in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/tutorial-spatial-regression
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Mendez C. (2020). Geographically weighted regression models: A tutorial using the spgwr package in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/tutorial-gwr1
Convergence Analysis
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Mendez C. (2021). The augmented Solow model: A tutorial using R and Stata. Available at https://deepnote.com/@carlos-mendez
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Mendez C.(2020). Club convergence analysis in Stata. Available at https://github.com/quarcs-lab/mendez2020-convergence-clubs-code-data
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Mendez C. (2020). Classical sigma and beta convergence analysis in R: Using the REAT 2.1 Package. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/classical-convergence-reat21
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Mendez C. (2020). Univariate distribution dynamics in R: Using the ggridges package. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/univariate-distribution-dynamics
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Mendez C. (2020). Bivariate distribution dynamics analysis in R. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/tutorial-bivariate-distribution-dynamics
Time Series Analysis
- Mendez C. (2020). Long Run vs Short Run Decompositions in R: The HP filter vs the Hamilton filter. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/long-run-filters
Cross-sectional Analysis
- Mendez C. (2020). An interactive exploration of cross-sectional data: Using the package ExPanDaR to generate interactive web applications. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/explore-cross-section-interactively
Panel Data Analysis
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Mendez C. (2020). An interactive exploration of panel data: Using the package ExPanDaR to generate interactive web applications. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/explore-panel-interactively
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Mendez C. (2020). Wrangling and plotting panel data in R: Using the package panelr. R Studio/RPubs. Available at https://rpubs.com/quarcs-lab/learn-panelr
Other
- Santos-Marquez F. (2020). Using the missForest package for imputation of missing values . R Studio/RPubs. Available at https://rpubs.com/FelipeSantos/na_missforest