Productivity differences in the ASEAN community 1972-2017:

An interactive and automated exploration in R

knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
library(tidyverse)
library(rio)           # import stata files
library(ExPanDaR)      # explore panel data interactively  
library(DT)            # interactive tables
library(pmdplyr)       # managing panel and hierarchical data
library(panelr)        # managing panel  data
library(skimr)         # descriptive statistics
library(gganimate)     # animated figures
library(plotly)        # interactive figures
library(countrycode)   # add continent name
theme_set(theme_minimal())

# Change the presentation of decimal numbers to 4 and avoid scientific notation
options(prompt="R> ", digits=3, scipen=999)

Suggested citation:

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

This work is licensed under the Creative Commons Attribution-Share Alike 4.0 International License.

1 Original data source

• https://www.apo-tokyo.org/

• http://www.apo-tokyo-aepm.org/

• https://www.apo-tokyo.org/wedo/productivity-measurement/

• https://www.sanken.keio.ac.jp/keo/asia/APO_Productivity_Databook_2018.pdf

Sample data:

dat <- read_csv("output.csv")
head(dat)

2 Data transformations

2.1 Generate cross-sectional id

dat_panel <- dat %>% 
  group_by(year) %>% mutate(id = row_number(country))
head(dat_panel)

2.2 Set panel dataset

dat_panel <- dat_panel %>% 
  panel_data(id, year)

2.3 Generate log variables

• to avoid problems with small numbers, let us multiply all variables by 100

dat_panel <- dat_panel %>% 
  mutate(
    log_tfp100 = log(tfp*100), 
    log_lp100  = log(lp_hours*100 ),
    log_lp_emp100 = log(lp_emp*100),
    log_cp100 = log(cp*100)
  )

2.4 Descriptive statistics

3 Definitions of variables

df_definitions <- read_csv("df_def.csv") 
df_definitions

4 Interactive Table

# Define function for  interactive table
create_dt <- function(x){
  DT::datatable(x,
                extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                               buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
                               lengthMenu = list(c(10,25,50,-1),
                                                 c(10,25,50,"All"))))
}

• Remove the panel data setting

dat_panel <- unpanel(dat_panel)

• Select and order variables

dat_panel <- dat_panel %>% 
  select(
    country,
year,
tfp,
lp_hours,
lp_emp,
cp,
log_tfp100,
log_lp100,
log_lp_emp100,
log_cp100
  )

dat_panel %>% 
  create_dt() %>% 
  formatRound(columns =c(
"tfp",
"lp_hours",
"lp_emp",
"cp",
"log_tfp100",
"log_lp100",
"log_lp_emp100",
"log_cp100"
  ),
  digits = 4)

NA

5 Interactive and Automated exploration

• Initial exploration

Remove id column

# Run it in the console
ExPanD(
  df = dat_panel,
  df_def = df_definitions,
  export_nb_option = TRUE,
  title = "Productivity differences in the ASEAN community 1972-2017",
  abstract = paste("Suggested citation:  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")
    )

• Automated exploration: First you customize the exploration, export configuration file, and include it in the new set up of the exploration.

config_list_fromRDS <- readRDS("ExPanD.RDS")

# Run it in the console
ExPanD(
  df = dat_panel,
  df_def = df_definitions,
  export_nb_option = TRUE,
  config_list = config_list_fromRDS,
  title = "Productivity differences in the ASEAN community 1972-2017",
  abstract = paste("Suggested citation:  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")
    )

• Shiny Web App

https://carlosmendez777.shinyapps.io/data-productivity-asean-1972-2017

6 References

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