ECO 1001 Lecture Notes - Lecture 1: Fallacy

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erinhound847

20 Sep 2016

School

St. John's University

Department

ECO - ECONOMICS

Course

ECO 1001

Professor

Tomic

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Document Summary

Fallacy of composition to conclude that if something is true for one part that it is true for the whole: usually an inaccurate conclusion because the economy works in cycles since costs and supply cannot increase infinitely. So if one thing is true at one time, it will most likely not always be true. Slope of a line: to solve: dy/dx (a. k. a. change in y/change in x or (y2-y1)/(x2-x1, the numerical value of the slope represents the change in y that corresponds to every 1 unit change in x. Ex) if the slope = 2, for every 1 increase in x, y increases by 2. Base = 1, target = 5, so we get (5-1)/1x100=400% change: applying to change in earnings from year to year: profits of abc were 12billion, up 10% from last year. Use equation of a line y = a+bx, where y=this years earnings, and b=percent increase of decrease.

Related Questions

TABLE 66 Stock Prices and Consumer Prices

CITY
Y = Rate of Change, Stock Prices, Percent Per Year
X = Rate of Change, Consumer Prices, Percent Per Year

CITY	Y	X
A	5	4.3
B	11.1	4.6
C	3.2	2.4
D	7.9	2.4
E	25.5	26.4
F	3.8	4.2
G	11.1	5.5
H	9.9	4.7
I	3.3	2.2
J	1.5	4
K	6.4	4
L	8.9	8.4
M	8.1	3.3
N	13.5	4.7
O	4.7	5.2
P	7.5	3.6
Q	4.73.	6
R	8	4
S	7.5	3.9
T	9	2.1

Table 66 gives data on percent change per year stock prices (Y) and consumer prices (X) for a cross section of 20 cities.

******************* answer in "SAS format" please********************* (if possible)

1) Plot the data in scattergram

2) Regress Y on X and examine the residuals from this regression. What do you observe?

3) Since the data for city(E) is unusual, repeat the regression in (2) dropping the data on city(E). Now examine the residuals from this regression. What do you observe?

4) If on the basis of the results in (2) you conclude that there was heteroscedasticity in the error variance but on the basis of the results in (3) you reverse your conclusion, what general conclusions do you draw?

State whether the following statements are true or false. Breifly justify your answer:

5) When autocorrelation is present, OLS estimators are biased as well as inefficient;

6) The R squared values of two models, one involving regression in the first-difference form and another in the level form, are not directly comparable.

7) In the presence of heterscedasticity the usual OLS method always overestimates the standard errors of estimators.

8) If a regression model is mis-specified (e.g., an important variable is ommitted), the OLS residuals will show a distinct pattern.

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ECO 1001 Lecture Notes - Lecture 1: Fallacy

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