ECON3250 FALL 2010
Prelim Answer Key
Part I. See Wooldridge (2008) chapter 15 and Handout on Maximum Likelihood.
Part II.
1. (a) Test H0 :
1
= 0:06. Consider
T=
b1
0:06
0:107 0:06
= 3:357
=
0:014
SE (b1 )
d
By CLT, we know that T ! N (0; 1). Since jT j >
MULTIPLE CHOICECPA Adapted
Chapter 14 Long Term Liabilities
1.
On July 1, 2010, Spear Co. issued 1,000 of its 10%, $1,000 bonds at 99 plus accrued
interest. The bonds are dated April 1, 2010 and mature on April 1, 2020. Interest is
payable semiannually on
Test 1 Intermediate Accounting II Spring 2008 Chapters 14,15,16a Name: _ Use the following to answer questions 12: Cox Co. issued $100,000 of tenyear, 10% bonds that pay interest semiannually. The bonds are sold to yield 8%. 1. One step in calculating t
Chapter 8: Reporting and Interpreting Property, Plant, and Equipment; Intangibles; and Natural Resources
Classifying LongLived Assets
Longlived assets tangible and intangible resources owned by a business and used in its operations over several
years;
Chapter 7: Reporting and Interpreting Cost of Goods Sold and Inventory
Inventory management provide sufficient quantities of highquality inventory and to minimize costs of carrying inventory
Items Included in Inventory
Inventory is tangible property hel
Chapter 1: Financial Statements and Business Decisions
The Accounting System
Internal decision makers managers who need information about the companys business
activities to manage the operating, investing, and financing activities of the firm
External
Chapter 6: Reporting and Interpreting Sales Revenue, Receivables, and Cash
Accounting for Net Sales Revenue
Revenue realization principle requires that revenues be recorded when they are earned (delivery has occurred or
services have been rendered, there
Economics 345
Applied Econometrics
Problem Set 1: Solutions
Prof: Martin Farnham
Problem sets in this course are ungraded. An answer key will be posted on the website
within a few days of the release of each problem set. As noted in class, it is highly
re
Topic 14
Unbiased Estimation
14.1
Introduction
In creating a parameter estimator, a fundamental question is whether or not the estimator differs from the parameter
in a systematic manner. Lets examine this by looking a the computation of the mean and the
Distributions
Independence
Formal Modeling in Cognitive Science
Joint, Marginal, and Conditional Distributions
Miles Osborne (originally: Frank Keller)
School of Informatics
University of Edinburgh
[email protected]
February 4, 2008
Miles Osborne (origin
Econometrics
Problem Set #1
Nathaniel Higgins
[email protected]
B.1
Suppose that a high school student is preparing to take the SAT exam. Explain why his
or her eventual SAT score is properly viewed as a random variable.
Because if you knew everything tha
Political Science 100a/200a
Fall 2001
Probability, part II1
1
Random variables
Recall idea of a variable and types of variables: .
Will now redescribe in probability theory terms as a random variable. Here is a technical/mathematical denition:
Defn : A
Probability: proportion, percent, chance, likelihood

What have I been given?
Mean m and SD s _ sample size n and p, population proportion

Are np > 5 AND n(1  p) > 5 ?
Yes _No
Do I have sample size n AND probability is for an Average ?
NO_YES

_
P(X
Variance, Covariance and Correlation
Variance of a Single Random Variable
The variance of a random variable X with mean is given by
h
i
2
var(X ) 2 E X E (X )
E (X
)2
Z
)2 f (x ) dx
Z
(x
x 2 f (x ) dx
E (x 2 )
(39)
Z
2
xf (x )dx
E 2 (x )
The variance
Math 461
Introduction to Probability
A.J. Hildebrand
Joint distributions
Notes: Below X and Y are assumed to be continuous random variables. This case is, by far, the most important case. Analogous formulas, with sums replacing integrals and p.m.f.s inste
Random Sampling of Questions
1. The probability that rain is followed by rain is 0.8, a sunny day is followed by rain is 0.6. Find the probability that one has two rainy days then two sunny days. To get this, we must have had rain after rain, P (RR), the
Assumptions and Conditions (cont.)
Here are the assumptions and the
corresponding conditions you must check before
creating a confidence interval for a proportion:
Independence Assumption: The data values are
assumed to be independent from each other.
W
Math 461
Introduction to Probability
A.J. Hildebrand
Discrete Random Variables
Terminology and notations
Denition: Mathematically, a random variable (r.v.) on a sample space S is a function1 from S to the real numbers. More informally, a random variable
Math 461
Introduction to Probability
A.J. Hildebrand
Continuous Random Variables
Denition: A random variable X is called continuous if it satises P (X = x) = 0 for each x.1 Informally, this means that X assumes a continuum of values. By contrast, a discr
Covariance and Correlation
( c Robert J. Sering Not for reproduction or distribution)
We have seen how to summarize a databased relative frequency distribution by measures of location and spread, such as the sample mean and sample variance. Likewise,
we
Asymptotics
1 Example
Xi X iid ; 2 ; i = 1; 2; :; n 1X = Xi n i 1X 1X 1X ) EX = E Xi = EXi = = n i n i n i " # 1X 1 X 2 2 1 X : = V ar Xi = 2 V arXi = 2 = n i n i n i n V arX X ! 0 as n ! 1 ! as n ! 1:
V arX
2
Concepts
Probability Limits: Let Sn be a stat
CROSS SECTION AND PANEL ECONOMETRICS
Economics 3250
Fall 2010
Department of Economics, Cornell University
TR 11:40am12:55PM Baker Laboratory  335
INSTRUCTOR:
Prof. Francesca Molinari
OFFICE:
Uris Hall 492
TELEPHONE:
(607) 2556367
EMAIL:
[email protected]
Handout 6  Hypothesis Testing in Large Samples
Econ 325  Cross Section and Panel Econometrics
Spring 2004
Cornell University
Prof. Molinari
Before going to Hypothesis Testing, I need to give a denition that should have been in Handout
5. From this denit
Formulae Sheet for Tests
Econ 3250  Cross Section and Panel Econometrics
Fall 2010
Cornell University
Prof. Molinari
OLS
b=
b
Y
b
U
X 0X
1
X 0Y
1
= X b = X X 0X
b
Y =Y
=Y
where M = In
X (X 0 X )
1
X 0Y = P Y
Xb = Y
X 0 = In
where
1
X X 0X
P = X X 0X
X 0