Notes on Financial Frictions
Carl E. Walsh
October 2015
1
Financial Frictions in Credit Markets
Money has traditionally played a special role in macroeconomics and monetary theory
because of the relationship between the nominal stock of money and the aggr
Non-Numeric Values
Non-Numeric Values: Logical Values
Logicals are based on a simple premise; something is either true or
false.
These are used liberally in coding languages; they signal whether or
nota condition has been satisfied or whether a paramete
R: Lists and Data Frames,
Special Values, Classes, and
Coercion.
Lists of Objects: Definition and
Component Access
Creating a list is much like creating a vector. You supply the elements
that you want to include to the list() function, separated by comma
Ross, Westerfield, Jaffe, and Jordan's Spreadsheet Master
Corporate Finance, 11th edition
by Brad Jordan and Joe Smolira
Version 11.0
Chapter 7
In these spreadsheets, you will learn how to use the following Excel
Naming cells
Scenario Manager
One-way Data
R:Matrices
Dr. Aaron G. Meininger
Defining a Matrix:
Typically, we describe matrix A as an m x n matrix; m rows and n
columns. So we have a total of mn entries with each entry,ai,j
having a unique position.
To create a matrix in R, we use the matrix() c
GDPC96
CPIAUCSL
CPILFESL
PCEPI
lin
Billions of Cha lin
Index 1982-19 lin
Index 1982-19 lin
q
Quarterly
q
Monthly
q
Monthly
q
01/01/1980 1947-01-01 to 01/01/1980 1947-01-01 to 01/01/1980 1957-01-01 to 01/01/1980
Real Gross Domestic Product, Consumer
3 Deci
miig eginnal Eligh Selina!
Te all persons be it known that
Elnrimn mhnnqaenn
having completed the prescribed studies and satised the
requirements for the degree
Emir iphm
has EDCDIdinBIY been admitted to that degree with all the
rights, privileges and imm
1/22/17
Subhra B. Saha
1
Housekeeping
Section 2 students are turning in Assignment 7
today
Section 1 students will turn in Assignment 7
on Tuesday Nov 15
Assignment 7 was the last HW
No More Homework Assignments Due
1/22/17
Subhra B. Saha
2
Lec 8
Lec
Notes on the term structure
Carl E. Walsh
October 2015
1
Introduction
The distinction between real and nominal rates of interest is critical for understanding
monetary policy issues, but another important distinction is that between short-term and
long-te
Lesson 3
Structure of Data
Outline
Previous Lesson:
1. Samples
2. Properties of estimators
3. Hypothesis testing
This Lesson
1. Types of data
2. Indices and base dates
3. Data transformations
The text goes into more detail about graphing. I will leave thi
6. Decision Theory
Not actually covered in Varian or most undergrad micro text; lots of good advanced
books, but none at the right level. In order of decreasing accessibility, consider reading:
An Introduction to Bayesian Inference and Decision, by Robert
6. Decision Theory
Not actually covered in Varian or most undergrad micro text; lots of good advanced
books, but none at the right level. In order of decreasing accessibility, consider reading:
An Introduction to Bayesian Inference and Decision, by Robert
5. Notes on Risky Choice
Much of the material is covered in Varian Chapter 11. The Appendix below expands on
some technical points.
1. Risk vs uncertainty.
The opportunities considered so far (bundles of consumption goods) are riskless
in the sense that y
5. Notes on Risky Choice
Much of the material is covered in Varian Chapter 11. The Appendix below expands on
some technical points.
1. Risk vs uncertainty.
The opportunities considered so far (bundles of consumption goods) are riskless
in the sense that y
THE CFA SOCIETY, THE CFA &
THE RESEARCH CHALLENGE
Presented by
A member society of
What we will discuss
Investment Research Challenge
What it is / Key Dates
What you learn
How you can get involved
Introduction to
CFA San Francisco
The CFA Institute
T
Appendix G Statistical Tables
TABLE G.3b
5% Critical Values of the F Distribution
Numerator Degrees of Freedom
D
e
n
o
m
i
n
a
t
o
r
D
e
g
r
e
e
s
o
f
F
r
e
e
d
o
m
1
2
3
4
5
6
7
8
9
10
10
11
12
13
14
4.96
4.84
4.75
4.67
4.60
4.10
3.98
3.89
3.81
3.74
3.71
t Table
cum. prob
t .50
t .75
t .80
t .85
t .90
t .95
t .975
t .99
t .995
t .999
t .9995
one-tail
0.50
1.00
0.25
0.50
0.20
0.40
0.15
0.30
0.10
0.20
0.05
0.10
0.025
0.05
0.01
0.02
0.005
0.01
0.001
0.002
0.0005
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.00
Solving a basic forward-looking model using
Dynare
Carl E. Walsh
Nov. 2010
1
Introduction
This handout is designed to walk you through the steps necessary to numerically
solve a forward-looking model using Dynare. Examples of such models include
the basic