LABS_BONUS.knit

title: “LABOTARIO_BONUS”

author: “JESSICA PAOLA AGUILAR SERVIN”

date: “2023-03-11”

output: html_document

LABORATORIO PLOT HOOVER CURVE ##############################

INSTALAR PREVIAMENTE install.packages(“devtools”) install.packages(“devtools”, type = “win.binary”)

library(devtools)

## Loading required package: usethis

library(EconGeo)

## 
## Please cite EconGeo in publications as:

##  Balland, P.A. (2017) Economic Geography in R: Introduction to the EconGeo Package, Papers in Evolutionary Economic Geography, 17 (09): 1-75

generate vectors industrial

ind <- c(0, 10, 10, 30, 50)
pop <- c(10, 15, 20, 25, 30)

CHECK VECTOR

ind

## [1]  0 10 10 30 50

CHECK VECTOR POP

pop

## [1] 10 15 20 25 30

RUN THE FUNTION (30% de la poblacion produce 50% de los resultados industriales)

Hoover.curve (ind, pop)

COMPUTE HOOVER GINI

Hoover.Gini (ind, pop)

## [1] 0.31

################################# LABORTARIO GINI #################################
############################ LABORATORIO HOOVER GINI ############################
USAGE Hoover.Gini(MAT,POP)
GENERATE VECTORS OF INDUSTRIAL COUNT
`r ind <- c(0, 10, 10, 30, 50) pop <- c(10, 15, 20, 25, 30)`
RUN THE FUNCTION
`r Hoover.Gini (ind,pop)`
`## [1] 0.31`
GENERATE A REGION-INDUSTRY MATRIX
`r mat = matrix ( c (0, 10, 0, 0, 0, 15, 0, 0, 0, 20, 0, 0, 0, 25, 0, 1, 0, 30, 1, 1), ncol = 4, byrow = T) rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5") colnames(mat) <- c ("I1", "I2", "I3", "I4")`
RUN THE FUNCTION
`r Hoover.Gini (mat,pop)`
`## Industry Hoover.Gini ## 1 I1 NaN ## 2 I2 0.000 ## 3 I3 0.700 ## 4 I4 0.475`
RUN THE FUNCTION BY AGGREGATING ALL INDUSTRIES
`r Hoover.Gini (rowSums(mat),pop)`
`## [1] 0.015`
RUN THE FUNCTION #1 ONLY
`r Hoover.Gini (mat[,1],pop)`
`## [1] NaN`
RUN THE FUNCTION #2 ONLY (perfectamente proporcional)
`r Hoover.Gini (mat[,2],pop)`
`## [1] 0`
RUN THE FUNCTION #3 ONLY (30% produce el 100% de la producción)
`r Hoover.Gini (mat[,3], pop)`
`## [1] 0.7`
RUN THE FUNCTION #4 ONLY (55% produce el 100% de la producción)
`r Hoover.Gini (mat[,4], pop)`
`## [1] 0.475`

LABORATORIO LOCATIONAL GINI ##############################

GENERATE REGION- INDUSTRI MATRIX

mat = matrix (
  c (100, 0, 0, 0, 0,
     0, 15, 5, 70, 10,
     0, 20, 10, 20, 50,
     0, 25, 30, 5, 40,
     0, 40, 55, 5, 0), ncol = 5, byrow = T)
rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c ("I1", "I2", "I3", "I4", "I5")

RUN THE FUNCTION

locational.Gini (mat)

##   Industry Loc.Gini
## 1       I1     0.40
## 2       I2     0.18
## 3       I3     0.27
## 4       I4     0.31
## 5       I5     0.28

############################## LOCATIONAL.GINI_CURVE ##############################

GENERATE A RECION-INDUSTRI MATRIX

r mat = matrix ( c (100, 0, 0, 0, 0, 0, 15, 5, 70, 10, 0, 20, 10, 20, 50, 0, 25, 30, 5, 40, 0, 40, 55, 5, 0), ncol = 5, byrow = T) rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5") colnames(mat) <- c ("I1", "I2", "I3", "I4", "I5")

RUN THE FUNCTION (SHOWS INDUSTRY #5)

r locational.Gini.curve (mat)

r locational.Gini.curve (mat, pdf = TRUE)

## [1] "locational.Gini.curve.pdf has been saved to your current working directory"

LABORATORIO LORENZ.CURVE
#################################

GENERATE VECTORS OF INDUSTRIAL COUNT

ind <- c(0, 10, 10, 30, 50)

RUN THE FUNCTION

Lorenz.curve (ind)

Lorenz.curve (ind, pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (ind, plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
## [1] 0.0 0.0 0.1 0.2 0.5 1.0

GENERATE A REGION- INDUSTRY MATRIX

mat= matrix (
  c (0, 1, 0, 0,
     0, 1, 0, 0,
     0, 1, 0, 0,
     0, 1, 0, 1,
     0, 1, 1, 1), ncol = 4, byrow = T)
rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c ("I1", "I2", "I3", "I4")

RUN THE FUNCTION

Lorenz.curve (mat)

Lorenz.curve (mat, pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (mat, plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
##      R1  R2  R3  R4  R5 
##   0 NaN NaN NaN NaN NaN

RUN THE FUNCTION BY AGGREGATION ALL INDUSTRIES

Lorenz.curve (rowSums(mat))

Lorenz.curve (rowSums(mat), pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (rowSums(mat), plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
##          R1    R2    R3    R4    R5 
## 0.000 0.125 0.250 0.375 0.625 1.000

RUN THE FUNCTION FOR INDUSTRIY #1 ONLY (PERFECT EQUALITY)

Lorenz.curve (mat[,1])

Lorenz.curve (mat[,1], pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (mat[,1], plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
##      R1  R2  R3  R4  R5 
##   0 NaN NaN NaN NaN NaN

RUN THE FUNCTION FOR INDUSTRIY #2 ONLY (PERFECT EQUALITY)

Lorenz.curve (mat[,2])

Lorenz.curve (mat[,2], pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (mat[,2], plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
##      R1  R2  R3  R4  R5 
## 0.0 0.2 0.4 0.6 0.8 1.0

RUN THE FUNCTION FOR INDUSTRIY #3 ONLY (PERFECT UNEQUALITY)

Lorenz.curve (mat[,3])

Lorenz.curve (mat[,3], pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (mat[,3], plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
##    R1 R2 R3 R4 R5 
##  0  0  0  0  0  1

RUN THE FUNCTION FOR INDUSTRIY #4 ONLY (PERFECT UNEQUALITY)

Lorenz.curve (mat[,4])

Lorenz.curve (mat[,4], pdf = TRUE)

## [1] "Lorenz.curve.pdf has been saved to your current working directory"

Lorenz.curve (mat[,4], plot = FALSE)

## $cum.reg
## [1] 0.0 0.2 0.4 0.6 0.8 1.0
## 
## $cum.out
##      R1  R2  R3  R4  R5 
## 0.0 0.0 0.0 0.0 0.5 1.0

COMPARE THE DISTRIBUTION OF THE INDUSTRIES

par(mfrow=c(2,2))
Lorenz.curve (mat[,1])
Lorenz.curve (mat[,2])
Lorenz.curve (mat[,3])
Lorenz.curve (mat[,4])