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Econ History Lesson 1: Summarizing Texts & Analyzing Data for Economic Comparisons - Prof., Apuntes de Historia Económica

Instructions for a university course in economic history offered by universidad carlos iii de madrid. The practical lesson focuses on summarizing texts and analyzing data using tools like gapminder to understand the relationship between variables such as female labor education, female fertility, and income per capita. Students are required to form hypotheses, export data, create graphs, and write reports.

Tipo: Apuntes

2014/2015

Subido el 02/03/2015

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ECONOMIC HISTORY:
PRACTICAL LESSON 1
PA: Alexandra López Cermeño
Social Sciences Department
Universidad Carlos III de Madrid
SPRING 2015
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ECONOMIC HISTORY:

PRACTICAL LESSON 1

PA: Alexandra López Cermeño

Social Sciences Department

Universidad Carlos III de Madrid

SPRING 2015

CONTACT

first)

  • Office: 18.2.C

Social Sciences Department

REMINDER: Assessment

Social Sciences Department

  • Maximum 5 points. Where:
    • 2 points: individual and team in-class assignments and

homework.

  • 0.5 points: participation.
  • 2.5 points:
    • INDIVIDUAL 1500-word essay due 8th of April. Instructions available in Aula Global.
    • ALTERNATIVELY: Presentation of a SUMMARY of one of the READINGS of the course that should coincide with the week that reading will be explained in class (individual or in pairs) + 1 page INDIVIDUAL report.

AGENDA

  1. Methodological issues: How to make a summary
  2. In practice: Gapminder.
  3. Small group practice. Concepts about economic

growth.

Social Sciences Department

Concept Map

Social Sciences Department

2. In practice: Gapminder

Social Sciences Department

  • Homework:
    • Hundreds of emails. Please pay attention in class my time

is scarce.

  • Most of the questions where already solved in the

instructions. Some of you did not even bother to read

them.

  • Please, use the SPELL CHECK. I have seen so many

ortographic mistakes I did not even bother at the end. It

denotes sloppyness.

Assignment potential answer example.

Social Sciences Department

Formulate a hypothesis of the causal relationship: “Some countries are richer than others because their female labour is better educated”

Most of your works did not have a hypothesis, had a very vague one or had three different hypothesis:

“…studies have always related the level of corruption of a country (…) is indirectly related to the increase of income inequality and porverty”.

“The latter women marry, the greater the gdp”

Assignment potential answer example.

Social Sciences Department

Formulate a hypothesis of the causal relationship: “Some countries are richer than others because their female fertility is lower”

Find your data and download them: http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx

Develop your arguments: (^) “This graph shows GDP per capita as a

measure of welfare in the vertical axis and the number of births per woman in the horizontal axis in a set of 64 countries including Less Developed and OECD countries. The data show a decreasing trend implying that the greater the number of children per women, the lower the GDP per capita. The reasons for this trend are manyfold…

… make a zoom,

this is adjust the scale of the graph:

¿Quién tiene razón?

Births, deaths and income

“The bubbles show a decreasing trend showing that countries with greatest gdp per capita have a lower mortality rate of 5- year old for 1000 births; and, viceversa, poorer countries have a greater mortality ratio.”

“Analizing the graph we can see a clear direct relationship between welfare and age of first marriage of women, obtaining a clear growing trend”

INVERSE CAUSALITY

Social Sciences Department

16

Primary Completion Rate and Income per person. In theory, the more schooling the greater the capacity of production

Inverse Causality

Escala: log o lin?

Historia Económica

19

…moving to Excel

Possibly there where problems with

– Exporting data (If you have problems downloading data,

try moving to another explorer).

– Choosing variables (too many or too little observations)

– Format of the graphs (log-lin, etc.)

– Did not manage to make graphs.

– Had problems with theory. Think about what you want to

show. You can show TWO trends in the same graph.