Welcome to
PMBA0608: Economics/Statistics
Foundation
 Session 2: August 26
 Assignment 1 is posted: Due on or
before September 2
 Next time we will meet on Wednesday,
September 6 at 19:30-22:45
 Before next class, please study
 Chapters 1 through 4 of Mankiw
 Chapters 1 through 3 of Mendenhall,
Beaver & Beaver
What is statistics?
statistics is the
science of learning
from data
What are the uses of statistics in
your line of work?
 How much should your company spend on
advertising?
 Should your company increase the price of
good and services it produces?
 Should shoplifting detection devices be
hidden or should their presence be made
obvious?
 What will the rate of inflation be next year
Here is the question of my interest
these days
 What are the factors significantly
increase the probability of an
individual’s participation in Brazilian
shadow (underground) economy?
Population/Sample
 Problem: I don’t have the resources to
study the behavior of every individual who
lives in Brazil. (population size = N)
 Solution: Study the behavior of a
representative gorup (sample size = n).
 Here we are referring to sets of objects on
which measurements are to be taken.
Another distinction between
population and sample
 There is a population of
characteristics each individual poses
(N characteristics)
 I will look at of a sample of these
characteristics (n characteristics)
 Here are we are referring to a set of
measurements themselves.
What is the difference between
descriptive versus inferential
statistics?
1. Descriptive Stat.
 Organizes/summarizes/ aggregates
describes to understand better.
2. Inferential Stat.
 Uses sample information to draw
conclusions or make a prediction about
the population.
In my study
1. I will use descriptive statistics to
summarize my sample.
2. But my main goal is to use inferential
statistics to use sample information
to predict the probability of a
Brazilian participating in the shadow
market.
Is this descriptive to inferential?
The Size of Shadow Economy
(as a percentage of GDP in 1999-2000)
45
40
35
30
25
20
15
10
5
0
USA
Brazil
Average Average
OECD South and
Central
America
Is this descriptive to inferential?
(Source: http://www.forecasts.org/djia.htm)
Dow Jones Industrial Average Stock Index
Past Trend, Present Value & Future Projection
Five elements of statistical problem
1. Definition of objective
2. Design of experiment or sampling
procedure
3. Collection and analysis of data
(descriptive stat.)
4. Make inferences about the
population. (inferential stat.)
5. Measurement of the goodness of
inference.
Thinking like an economist
(Mankiw Chapter 2)
1. Casual observation: There seems
to be a lot of unofficial
(underground) employment in Brazil.
 Theory: The more complicated and
costly the employment laws the bigger
the size of underground employment.
 Does this theory always hold?
What if at the same time that employment
laws become more complicated, law
enforcement becomes more effective too?
 Then underground employment may
or may not grow.
2. Building a model
(mathematical/graphical)
 Assumption: All else remains constant
3. Theory: All else constant, the more
complicated and costly the
employment laws the bigger the
size of underground employment.
4. Testing the theory: More
observation
 Here is where ________ statistics
comes handy.
 What if the minimum wage is
lowered by 10%?
 Here is where _______statistics
comes handy.
5. Prediction: Underground
employment will shrink by 5%.
Economic resources (factors of
production)
 Are scarce
 Categories
1. Labor
•
Anyone who is hired to use his
mental/physical ability to produce a good or a
service
2. Capital
•
Produced means of further production
3. Land

Natural resources
4. Entrepreneur
•
Anyone who plans production and takes a risk
Circular Flow Model
 Shows how money as well as real goods,
services and resources flow through the
economy
 Most important assumptions
No government
No international trade
No financial institutions
Only 2 sectors in the economy:
 households and firms
 Only 2 markets: goods and factors of
production




Circular Flow Model
Revenue
goods &
services
Market for
goods and
services
Expenditures
goods &
services
Firms
factors of
production
Factors of
production
Cost
Households
Market for
factors of
Production
Income