Economics 144
Economic Forecasting
Lecture 1
Economic Forecasting:
The Basics
1
Todays Class
1 of 2
Overview of the course structure and
content
Why Study Economic Forecasting?
Resources
Overview of Economic Forecasting
Six Fundamental Considerations in
F
Economics 187
Economic Forecasting
Lecture 14
Unit Roots, Stochastic Trends, ARIMA,
Forecasting Models, and Smoothing
Dr. Randall R. Rojas
1
Todays Class
Stochastic Trends and Forecasting
Random Walk without Drif
Random Walk with Drif
ARIMA
Unit Root
Economics 144
Economic Forecasting
Lecture 13
Evaluating and Combining Forecasts
Part I (Theory)
Dr. Randall R. Rojas
1
Todays Class
Introduction
Evaluating a Single Forecast
Testing Properties of Optimal Forecasts
Assessing Optimality w.r.t. an Informati
Economics 187
Economic Forecasting
Lecture 16
Cointegration
Dr. Randall R. Rojas
1
Spurious Regressions
In reality, rw1 and rw2 are
completely unrelated.
Random Walk 1 (rw1):
Random Walk 2 (rw2):
2
Spurious Regressions
Suppose we did not know that
rw1 an
Economics 144: Homework 3 Solution
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: May 3, 2016
1. (60%) You will need to download the data from The U.S. Census Bureau
(https:/www.census.gov/econ/currentdata) according to the following steps:
Select Adv
Economics 144: Homework 1 Solution
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: April 12, 2016
1. (40%) The data file SleepData.dat consists of 706 observations from the study done by Biddle and
Hamermesh (1990) on the tradeoff between time spent sle
Economics 144: Homework 5
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: May 26, 2016
1. (50%) The file w-gs1yr.txt contains the U.S. weekly interest rates (in percentages) from January
5, 1962, to April 10, 2009. For this assignment you will fit an ap
Dr. Randall R. Rojas
Economics 144
Department of Economics
Economic Forecasting
UCLA
Winter, 2014
Midterm Exam
February 13, 2014
For full credit on a problem, you need to show all your work and the formula(s) used.
First Name
Last Name
UCLA ID #
Please do
Dr. Randall R. Rojas
Economics 144
Department of Economics
Economic Forecasting
UCLA
Spring, 2016
Midterm Exam
May 5, 2016
For full credit on a problem, you need to show all your work and the formula(s) used.
First Name
Last Name
UCLA ID #
Please do not s
Dr. Randall R. Rojas
Economics 144
Department of Economics
Economic Forecasting
UCLA
Winter, 2014
Midterm Exam
February 13, 2014
For full credit on a problem, you need to show all your work and the formula(s) used.
First Name
Last Name
UCLA ID #
Please do
Economics 144: Homework 3
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: May 3, 2016
1. (60%) You will need to download the data from The U.S. Census Bureau
(http:/www.census.gov/econ/currentdata) according to the following steps:
Select Advance Month
Economics 144: Homework 4
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: May 12, 2016
1. (40%) For this problem you will explore different ARMA model fits to the dataset usconsumption.
The observations are percentage changes in quarterly personal consu
Economics 187
Economic Forecasting
Lecture 17
State Space Models
Dr. Randall R. Rojas
1
State Space Models (SSM)
(e.g., Kalman Filter)
Q: Why would you use Filtering techniques instead of
e.g., ARIMA?
A: Smoothing techniques (such as filtering and
spect
Economics 144
Economic Forecasting
Lecture 15
Characterizing Cycles
Autoregressive Conditional Heteroscedasticity Models
(ARCH/GARCH)
Dr. Randall R. Rojas
1
Todays Class
The ARCH Family
ARCH Models
The ARCH(1) Process
The ARCH(p) Process
GARCH Models
Economics 144
Economic Forecasting
Lecture 12
VAR and IRF
Examples and Interpretation
Dr. Randall R. Rojas
1
Todays Class
Two Examples of
Vector Autoregressions (VAR)
Predicative Causality (Granger-Causality)
Impulse-Response Functions (IRF)
2
VAR(p)
Yonsei University
International Summer School
Law and Economics
Lecture 1
June 28, 2016
Instructor
Professor Tai-Yeong Chung ()
E-mail: tchung@yonsei.ac.kr
Office hour:
10 minutes after each class or
by appointment
Course Description
Law and Economics
7/21/2016
Izell v. Union Carbide Corp. (2014) [ Cal.App.4th ]
FindLaw > FindLaw California > Case Law > California Case Law > slip Cal.App.4th 2014/b245085
Do Another California Case Law Search
Cases Citing This Case
Izell v. Union Carbide Corp. (2014) ,
7/21/2016
Popescu v. Apple Inc. (2016) [ Cal.App.4th ]
FindLaw > FindLaw California > Case Law > California Case Law > slip Cal.App.4th 2016/h040508
Do Another California Case Law Search
Cases Citing This Case
Popescu v. Apple Inc. (2016) , Cal.App.4th
[N
6/30/2016
Yonsei University
International Summer School
Law and Economics
Lecture 7
Negligence rule: summary
Assuming perfect compensation and each
legal standard equal to the efficient level of
care, every form of the negligence rule
gives the injurer a
Yonsei University
International Summer School
Law and Economics
Lecture 4
Example - property
A corn farmer and a cattle rancher live beside one
another. In isolation, each business would have $200k
(thousand) in profits.
But if nothing is done, the catt
Yonsei University
International Summer School
Law and Economics
Lecture 3
Basic assumptions of
economic analysis of law
1) Rational agents
cf. A reasonable person
2) Pursuing self-interest
3) Social welfare efficiency
Property example 1
1
Property example
6/30/2016
Yonsei University
International Summer School
Law and Economics
Lecture 6
1. Tort Law: Introduction
A tort is a legal wrong.
from the Latin word tortus which meant
wrong.
Tort refers to that body of the law which
will allow an injured person
Yonsei University
International Summer School
Law and Economics
Lecture 5
Extension: Polinskys example
Case
BOOMER V. ATLANTIC CEMENT CO., INC.
309 N.Y.S.2d 312 257 N.E.2d 87
(Court of Appeals of New York, 1970)
1
Public vs. Private Goods
Public goods c
Law and econ notes
Chapter 1
What is economic analyzes of law
Economics provides a scientific theory to predict the effects of legal
sanctions on behavior.
Sanctions are like prices
Provides behavioral theory to predict how people respond to laws
Eco
Economics 144
Economic Forecasting
Lecture 1
Economic Forecasting: The Basics
Dr. Randall R. Rojas
Todays Class
1 of 2
Overview of the course structure and content
Why Study Economic Forecasting?
Resources
Overview of Economic Forecasting
Six Fundamental
Economics 144: Homework 5
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: May 26, 2016
1. (50%) The file w-gs1yr.txt contains the U.S. weekly interest rates (in percentages) from January
5, 1962, to April 10, 2009. For this assignment you will fit an ap
Economics 144: Homework 1
Spring 2016, UCLA
Instructor: Dr. Rojas
Due Date: April 12, 2016
1. (40%) The data file SleepData.dat consists of 706 observations from the study done by Biddle and
Hamermesh (1990) on the tradeoff between time spent sleeping and
Economics 144
Economic Forecasting
Lecture 7
Characterizing Cycles
Moving Average Models
Dr. Randall R. Rojas
1
Todays Class
Covariance Stationary Time Series
White Noise
The Lag Operator
Wolds Theorem
Characteristics of the MA(q) Process
Example: MA(1) P
Economics 144
Economic Forecasting
Lecture 6
White Noise
Dr. Randall R. Rojas
1
Todays Class
White Noise
White Noise Example
R Demo
2
White Noise
1 of 3
Time Series Process: Let y denote the observed
series of interest.
Where t (shock) is uncorrelated ove