v1
MTH403 (2013)- ADDITIONAL PROBLEMS IV
(1) Let g : C R be given by g (z ) = Re(z ); show that this is an
open map, but not a closed map.
(2) Find the number of zeros of 3ez z in the closed unit disc
centered at the origin.
(3) Let f be analytic in a nei
MTH403 (2013)- ADDITIONAL PROBLEMS V
(1) Show that any Mbius transformation, namely, a map of the
o
az +b
form (z ) = cz+d , a, b, c, d C is a composition of translations
dilations and inversion. What is the map if ad bc = 0?
(2) Given three distinct poin
Short Guides to Microeconometrics
Fall 2013
Kurt Schmidheiny
Unversitt Basel
a
Panel Data: Fixed and Random Eects
1
Introduction
In panel data, individuals (persons, rms, cities, . ) are observed at
several points in time (days, years, before and after tr
Panel data methods for microeconometrics using Stata
A. Colin Cameron
Univ. of California - Davis
Based on A. Colin Cameron and Pravin K. Trivedi,
Microeconometrics using Stata, Stata Press, forthcoming.
April 8, 2008
A. Colin Cameron
Univ. of California
Introduction to
Panel Data Analysis
Today's Plan
Structure of Panel Data
POLS
Fixed Effects methods
Random effects
Hausman test
Structure of Panel Data
Cross section units arranged over a time
period (longitudinal data).
No. of observations is N x T
Ge
The eﬀects of regressors on OLS coeﬃcients
L. Magee
Fall, 2007
———————————————————–
When regressors are put in or taken out of an OLS regression, the other OLS coeﬃcients usually change.
The following results may help to understand what is happening.
1
No
RANDOM EFFECTS REGRESSIONS
Random effects estimation
k
s
j=2
p =1
Yit = 1 + j X jit + p Z pi + t + it
k
Yit = 1 + j X jit + i + t + it
j=2
k
= 1 + j X jit + t + uit
j=2
When the observed variables of interest are constant for each individual, a fixed effe
Panel Data Course
Lecture 2
Today:
Todays lecture
More on TSCS/Panel Models.
Summary of fixed effect from last week.
Random Effects
Fixed effects versus random effects.
The Parks (or Parks-Kmenta) Method.
Stata Session:
Analysis of fixed and random e
REGRESSION ANALYSIS WITH PANEL DATA: INTRODUCTION
A panel data set, or longitudinal data set, is one where there are
repeated observations on the same units.
1
REGRESSION ANALYSIS WITH PANEL DATA: INTRODUCTION
A panel data set, or longitudinal data set, i
FIXED EFFECTS REGRESSIONS: WITHIN-GROUPS METHOD
Fixed effects estimation (within-groups method)
k
Yit = 1 + j X jit + i + t + it
j=2
The two main approaches to the fitting of models using panel data are known, for reasons
that will be explained in a momen
FIXED EFFECTS REGRESSIONS: LSDV METHOD
Fixed effects estimation (least squares dummy variable method)
k
Yit = 1 + j X jit + t + i + it
j=2
k
n
j=2
i =1
Yit = j X jit + t + i Ai + it
In the third version of the fixed effects approach, known as the least sq
Panel Data Course
Lecture 1
Today: Introduction to Panel Data
Some practical issues about the class.
Todays Lecture
Introduction and terminology.
Panel data variation.
Single-Equation Linear Model.
To pool or not to pool.
Unit heterogeneity: fixed ef
Panel Data Course
Lecture 4
Today:
More on Temporal Dynamics in TSCS/Panel Data.
First Difference Estimators.
Arellano and Bond.
Random Coefficient Models.
Stata Session.
More on Temporal Dynamics
in TSCS/Panel Data (1):
From last week:
Two options: (1) t
Panel Data Course
Lecture 3
Today:
From last week: Summary of the Parks Method.
Panel-Corrected Standard Errors.
Temporal Dynamics in TSCS/Panel Data.
Stata Session.
The Parks Method (1):
We can set up the following assumptions for our TSCS/Panel
model:
Assignment 2
On
Theoretical Concepts of Panel Data
Course: Eco 342
Instructor : Dr. Somesh K. Mathur
Note: Attempt all the questions. Submission is compulsory for all.
Q 1: Explain the following concepts in detail:
1. Cross-Section Data.
2. Time-Series Da
Case Study Problems
1.
Weight lifting
In weight lifting competitions the lifters are grouped into seven different categories based
on their body weights. There are two common lifting styles formalized in competitionjerk, in which the weight is lifted in t
In biology Dynamics of Malaria Spread
Background
Malaria is a tropical infections disease which menaces more people in the
world than any other disease
WHO reported in 1978, in Africa alone, one million die annually from
malaria before they reach the ag
Lecturenotes(Lec13)
Whatisamodel?
Wecomeacrossvarioustypesofmodelsinlifetheyallrepresentsomethingelseina
formwecancomprehend,e.g.atoymodelofcaroramapofacityoraroadmapofa
city etc. It always has a purpose without purpose or aim of the study the model
does
SystemCharacterization(L4)
RWPAs pointed out earlier, real world associated may be very complex and so modelling
incorporating all the features of the real world may in itself become very complicated and
unmanageable. This requires a simplification of the