R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

# === Opci n 1: Descargar de WDI (requiere internet) ===

        wdi <- WDI(
          country = "all",
          indicator = c(
            gdp_pc = "NY.GDP.PCAP.KD", 
            cons_pc = "NE.CON.PRVT.PC.KD"
          ), 
          start = 2015, 
          end = 2023
        ) %>%
          as_tibble() %>%
          filter(!is.na(gdp_pc), !is.na(cons_pc))
        
        df <-wdi %>%
        group_by(iso2c) %>%
        filter(year==max(year)) %>%
        ungroup()

Including Plots

You can also embed plots, for example:

## # A tibble: 224 × 8
##    country                     iso2c iso3c  year gdp_pc cons_pc  lgdp lcons
##    <chr>                       <chr> <chr> <int>  <dbl>   <dbl> <dbl> <dbl>
##  1 Africa Eastern and Southern ZH    AFE    2023  1413.    949.  7.25  6.86
##  2 Albania                     AL    ALB    2023  5445.   3872.  8.60  8.26
##  3 Algeria                     DZ    DZA    2023  4660.   1867.  8.45  7.53
##  4 American Samoa              AS    ASM    2022 13709.  10347.  9.53  9.24
##  5 Angola                      AO    AGO    2023  2335.   1343.  7.76  7.20
##  6 Arab World                  1A    ARB    2023  6321.   3467.  8.75  8.15
##  7 Argentina                   AR    ARG    2023 12933.   8672.  9.47  9.07
##  8 Armenia                     AM    ARM    2023  5197.   3563.  8.56  8.18
##  9 Aruba                       AW    ABW    2015 27458.  15194. 10.2   9.63
## 10 Australia                   AU    AUS    2023 61598.  33827. 11.0  10.4 
## # ℹ 214 more rows
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

## 
## Call:
## lm(formula = cons_pc ~ gdp_pc, data = df)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -19495.3  -1119.0   -512.6    791.8  14624.7 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.430e+03  2.739e+02   5.222 4.07e-07 ***
## gdp_pc      4.439e-01  1.056e-02  42.025  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3247 on 222 degrees of freedom
## Multiple R-squared:  0.8883, Adjusted R-squared:  0.8878 
## F-statistic:  1766 on 1 and 222 DF,  p-value: < 2.2e-16
## 
## Call:
## lm(formula = lcons ~ lgdp, data = df)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.8442 -0.1190  0.0037  0.1449  0.6026 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.46726    0.09516    4.91 1.76e-06 ***
## lgdp         0.89318    0.01064   83.94  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2202 on 222 degrees of freedom
## Multiple R-squared:  0.9695, Adjusted R-squared:  0.9693 
## F-statistic:  7046 on 1 and 222 DF,  p-value: < 2.2e-16

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