Samenvatting

Summary of the book "A Practical Guide to Using Econometrics"

13 bekeken 0 aankoop

Vak
Econometrics

Instelling
Radboud Universiteit Nijmegen (RU)

Summary of the covered chapters during the lectures of the book "A Practical Guide to Using Econometrics" Radboud University

[Meer zien]

Voorbeeld 3 van de 26 pagina's

Bekijk voorbeeld

Document laden...

Heel boek samengevat? Nee
Wat is er van het boek samengevat? H1-h9, h12, h16
Geupload op 20 maart 2019
Aantal pagina's 26
Geschreven in 2018/2019
Type Samenvatting

econometrics

Volgen

Brillantaisia_Coris.gaimard Lid sinds 8 jaar 116 documenten verkocht

€5,49

Ook beschikbaar in voordeelbundel v.a. €10,49

Toegevoegd

In winkelwagen Op verlanglijstje

100% tevredenheidsgarantie
Direct beschikbaar na betaling
Zowel online als in PDF
Je zit nergens aan vast

Ook beschikbaar in voordeelbundel (3)

Econometrics

€ 10,98 € 7,99

3x verkocht

2 items

1. College aantekeningen - Plenary lecture notes econometrics
2. Samenvatting - Summary of the book "a practical guide to using econometrics"
Meer zien

E&BE Bachelor 2 Block 3

€ 32,94 € 10,49 6 items

1. Samenvatting - Summary of investment management
2. College aantekeningen - Lecture notes investment management
3. College aantekeningen - Plenary lecture notes econometrics
4. Samenvatting - Summary of the book "fundamentals of futures and option markets"
5. College aantekeningen - Plenary lecture notes project financial instruments
6. Samenvatting - Summary of the book "a practical guide to using econometrics"
Meer zien

E&BE Bachelor 2

€ 114,29 € 30,49 21 items

1. College aantekeningen - Plenary lecture notes international economics
2. Samenvatting - Summary "international economics - trade and policy"
3. College aantekeningen - Lecture notes history of economics
4. Samenvatting - Summary of "economic methodology"
5. College aantekeningen - Lecture notes of the economic methodology plenary lectures
6. Samenvatting - Summary history of economic thought
7. Samenvatting - Summary of the book "institutional economics"
8. College aantekeningen - Plenary lecture notes of the course institutional economics
9. Samenvatting - Summary of investment management
10. College aantekeningen - Lecture notes investment management
11. College aantekeningen - Plenary lecture notes econometrics
12. Samenvatting - Summary of the book "fundamentals of futures and option markets"
13. College aantekeningen - Plenary lecture notes project financial instruments
14. Samenvatting - Summary of the book "a practical guide to using econometrics"
15. Samenvatting - Summary of the book "international financial management"
16. Samenvatting - Summary of the online additional readings of "international financial management"
17. Samenvatting - Summary of the book "intermediate accounting"
18. College aantekeningen - Plenary lectures multinational finance
19. College aantekeningen - Plenary lectures far
20. College aantekeningen - Tutorials corporate finance
21. Samenvatting - Summary corporate finance
Meer zien

Chapter 1: An Overview of Regression Analysis
1.1 What is Econometrics?
Econometrics is the quantitative measurement and analysis of actual economic and business phenomena.

Econometrics has three major uses:
1. Describing economic reality
2. Testing hypotheses about economic theory and policy
3. Forecasting future economic activity

A general and purely theoretical functional relationship like:
Q = β 0 + β 1 P+ β 2 P S + β 1 Yd (1.1)

Can become explicit:
Q = 27.7 – 0.11P + 0.03PS + 0.23Yd (1.2)
 The number 0.23 is called an estimated regression coefficient, and it is the ability to
estimate these coefficients that makes econometrics valuable.
 Yd = disposable income

1.2 What is regression analysis?
Econometricians use regression analysis to make quantitative estimates of economic relationships that
previously have been completely theoretical in nature.

Regression analysis is a statistical technique that attempts to “explain” movements in one variable, the
dependent variable, as a function of movements in a set of other variables, called the independent (or
explanatory) variables, through the quantification of one or more equations.

If the price of a good increases by one unit, then the quantity demanded decreases in average by a certain
amount, depending on the price elasticity of demand (defined as the percentage change in the quantity
demanded that is caused by a one percent increase in price).

If the quantity of capital employed increases by one unit, then the output increases by a certain amount, called
the marginal productivity of capital.

Regression analysis cannot confirm causality; it can only test the strength and direction of the quantitative
relationships involved.

The simplest single-equation regression model is:
(1.3) Y = β 0 + β 1X
 β 0 is the constant or intercept term; it indicates the value of Y when X equals zero.
 β 1 is the slope coefficient, and it indicates the amount that Y will change when X increases by one
unit.

For linear (i.e., straight-line) regression models, the response in the predicted value of Y due to a change in X is
(Y ¿ ¿ 2−Y 1) ∆Y
constant and equal to the slope coefficient β 1: = =β ¿1. For a linear model, the slope is
( X 2−X 1 ) ∆X
constant over the entire function.

By random we mean something that has its value determined entirely by chance.

A stochastic error term is a term that is added to a regression equation to introduce all of the variation in Y
that cannot be explained by the included Xs.

1

,2

, The addition of a stochastic error term () to equation 1.3 results in a typical regression equation:
(1.4) Y = β 0 + β 1X + 
 β 0 + β 1X is the deterministic component. The deterministic part of the equation may be
written: (1.5) E(YX) = β 0 + β 1X  the expected value of Y given X

If we include a specific reference to the observations, the single-equation linear regression model may be
written as: (1.7) Yi = β 0 + β 1Xi + i
 Yi = the ith observation of the dependent variable
 Xi = the ith observation of the independent variable
 I = the ith observation of the stochastic error term
 β 0, β 1 = the regression coefficients
 N = the number of observations

A multivariate (more than one variable) linear regression model:
Yi = β 0 + β 1X1i + β 2X2i + β 3X3i +i

Yi = β 0 + β 1 EXPi + β 2EDUi + β 3GENDi +i
 β 1 gives us the impact on wages of a one-year increase in experience, holding constant education
and gender.

1.3 the estimated regression equation
The quantified version of the theoretical regression equation is called the estimated regression equation and is
obtained from a sample is data for actual Xs and Ys. Although the theoretical equation is purely abstract in
nature: Y i=β 0 + β 1 X i+ ϵ i (1.12) the estimated regression equation has actual numbers in it:
Y^ i=103.40+ 6.38 X i(1.13)
Y^ i is the estimated or fitted value of Yi, and it represents the value of Y calculated from the
estimated regression equation for the ith observation.

^ i) and the actual value of the
The difference between the estimated value of the dependent variable (Y
^ i (1.15)
dependent variable (Yi) is defined as the residual (ei): ei = Yi - Y

Note the distinction between the residual in equation 1.15 and the error term: ϵ i =Y i −E(Y i Ι X i ) (1.16).

^ ), while the error
The residual is the difference between the observed Y and the estimated regression line ( Y
term is the difference between the observed Y and the true regression equation (the expected value of Y)

^ s will be to the Ys.
The smaller the residuals, the better the fit, and the closerY

The estimated regression model can be extended to more than one independent variable by adding the
additional Xs to the right side of the equation.

1.5 using regression to explain housing prices
Cross-sectional: all of the observations are from the same point in time and represent different individual
economic entities (like countries or, in this case, houses) from that same point in time.

PRICEi = β 0 + β 0SIZEi +ϵ i
 β 1 = 0.138 means that if size increases by 1 square foot, price will increase by 0.138 thousand dollars.
It measures the change in PRICEi associated with a one-unit increase in SIZEi. It’s the slope of the
regression line.
 β 0 is the estimate of the constant of intercept term.

Regression analysis cannot prove or even imply causality.

3

Voordelen van het kopen van samenvattingen bij Stuvia op een rij:

Verzekerd van kwaliteit door reviews

Stuvia-klanten hebben meer dan 700.000 samenvattingen beoordeeld. Zo weet je zeker dat je de beste documenten koopt!

Snel en makkelijk kopen

Je betaalt supersnel en eenmalig met iDeal, creditcard of Stuvia-tegoed voor de samenvatting. Zonder lidmaatschap.

Focus op de essentie

Samenvattingen worden geschreven voor en door anderen. Daarom zijn de samenvattingen altijd betrouwbaar en actueel. Zo kom je snel tot de kern!

Veelgestelde vragen

Wat krijg ik als ik dit document koop?

Je krijgt een PDF, die direct beschikbaar is na je aankoop. Het gekochte document is altijd, overal en oneindig toegankelijk via je profiel.

Tevredenheidsgarantie: hoe werkt dat?

Onze tevredenheidsgarantie zorgt ervoor dat je altijd een studiedocument vindt dat goed bij je past. Je vult een formulier in en onze klantenservice regelt de rest.

Van wie koop ik deze samenvatting?

Stuvia is een marktplaats, je koop dit document dus niet van ons, maar van verkoper Brillantaisia_Coris.gaimard. Stuvia faciliteert de betaling aan de verkoper.