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004_midterm_exam1_format.Rmd
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---
title: "Midterm Exam 1"
author:
- XXXXXXXX (Only code no name)
- XXXXXXXX (Only code no name)
- XXXXXXXX (Only code no name)
- XXXXXXXX (Only code no name)
- XXXXXXXX (Only code no name)
- XXXXXXXX (Only code no name)
date: ""
output:
word_document:
toc: yes
toc_depth: '3'
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE,
warning = FALSE,
message = FALSE,
fig.align = "center")
```
```{r libraries}
library(tidyverse)
library(knitr)
library(readxl)
```
# Labor clasification in Colombia
- The data below were estimated by **Departamento Nacional de Estadística - DANE** using the **Gran encuesta integrada de hogares - GEIH**:
```{r table, ft.align = 'center'}
data <- tibble(Indicator = c('Total Population (TP)',
'Working Age Population (WAP)',
'Economically Active Population (EAP)',
'Employed (E)',
'Unemployed (U)',
'Visible Unemployment (VU)',
'Invisible Unemployment (IU)',
'Economically Inactive Population (EIP)')) %>%
bind_cols(read_excel(path = '004_anexo_empleo_dic_2020.xlsx',
sheet = 2, range = 'IG29:IG36',
col_names = "Individuals")) %>%
mutate(Individuals = Individuals*1e3,
Indicator = factor(Indicator,
levels = c('Total Population (TP)',
'Working Age Population (WAP)',
'Economically Active Population (EAP)',
'Economically Inactive Population (EIP)',
'Employed (E)',
'Unemployed (U)',
'Visible Unemployment (VU)',
'Invisible Unemployment (IU)'))) %>%
arrange(Indicator) %>%
slice(1:3, 5,7)
data %>%
kable(caption = 'Some labor clasification data in Colombia on December 2020')
```
1. Calculate the Population below 10 or 12 years (Rural or Urban) **(4 points)**
2. Calculate the Economically Inactive Population (EIP) **(4 points)**
3. Calculate the Unemployed (U) **(4 points)**
4. Calculate the Invisible Unemployment (IU) **(3 points)**
# Main indicators of the labor market
Using the information and the results calculated above find:
5. Gross participation rate (GPR) **(3 points)**
6. Labor participation rate (LPR) ("Tasa Global de Participación" in Spanish) **(3 points)**
7. Unemployment rate (UR) **(3 points)**
8. Employment rate (ER) **(3 points)**
# Finding the truth about statements on twitter
- Enter into the Bank of the Republic (Colombia) using the route:
**http://www.banrep.gov.co/** > Estadísticas > Actividad económica, mercado laboral y cuentas financieras >
4. Mercado laboral > Tasas de ocupación y desempleo > Descargar y consultar: Total Nacional
- Enter into the link:
<**https://twitter.com/AlvaroUribeVel/status/1025061735554842625**>
9. Point out if the 9.1% value is true based on the Bank of the Republic (Colombia) information. **(3 points)**
10. Point out if in any of the presidential periods of Álvaro Uribe Vélez the *unemployment rate (UR)* was lower than 9.1% at some time. **(3 points)**
11. Point out if the hashtag on the twitter message is valid. **(3 points)**
# The goods market
This exercise is taken from:
**Oliver Blanchard (2017) Macroeconomics (7 Edition)** > Chapter 3 The Goods Market > Questions and Problems > Exercise 2
- The following equations refer to the goods market of an economy in billions of euros:
$$C_t = 480 + 0.5Y_{tD}$$
$$I_t = 110$$
$$T_t = 70$$
$$G_t = 250$$
12. Solve for the goods market equilibrium **(5 points)**
13. Find equilibrium disposable income $(Y_{tD})$ **(5 points)**
14. Find equilibrium consumption $(C_t)$ **(4 points)**