Using gret l for Principles of Econometrics, 4th Edition

Creating indicator variables

It is easy to create indicator variables in gretl. Suppose that we want to create a dummy variable to indicate that a house is large. Large in this case means one that is larger than 2500 square feet.

1 series ld = (sqft>25)

2 discrete ld

3 print ld sqft —byobs

The first line generates a variable called ld that takes the value 1 if the condition in parentheses is satisfied. It will be zero otherwise. The next line declares the variable to be discrete. Often this is unnecessary. “Gretl uses a simple heuristic to judge whether a given variable should be treated as discrete, but you also have the option of explicitly marking a variable as discrete, in which case the heuristic check is bypassed.” (Cottrell and Lucchetti, 2011, p. 53) That is what we did here. Also from the Gretl Users Guide:

To mark a variable as discrete you have two options.

1. From the graphical interface, select “Variable, Edit Attributes” from the menu. A dialog box will appear and, if the variable seems suitable, you will see a tick box labeled “Treat this variable as discrete”. This dialog box [see Figure 7.1 below] can also be invoked via the context menu (right-click on a variable and choose Edit attributes) or by pressing the F2 key.

2. From the command-line interface, via the discrete command. The command takes one or more arguments, which can be either variables or list of variables.

So, the discrete declaration for ld in line 2 is not strictly necessary. Printing the indicator and square feet by observation reveals that the homes where sqft > 25 in fact are the same as those where ld =1.

ld

sqft

1

0

23.46

2

0

20.03

3

1

27.77

4

0

20.17

5

1

26.45

6

0

21.56

Добавить комментарий

Using gret l for Principles of Econometrics, 4th Edition

Simulation

In appendix 10F of POE4, the authors conduct a Monte Carlo experiment comparing the performance of OLS and TSLS. The basic simulation is based on the model y = x …

Hausman Test

The Hausman test probes the consistency of the random effects estimator. The null hypothesis is that these estimates are consistent-that is, that the requirement of orthogonality of the model’s errors …

Time-Varying Volatility and ARCH Models: Introduction to Financial Econometrics

In this chapter we’ll estimate several models in which the variance of the dependent variable changes over time. These are broadly referred to as ARCH (autoregressive conditional heteroskedas - ticity) …

Как с нами связаться:

Украина:
г.Александрия
тел./факс +38 05235  77193 Бухгалтерия

+38 050 457 13 30 — Рашид - продажи новинок
e-mail: msd@msd.com.ua
Схема проезда к производственному офису:
Схема проезда к МСД

Партнеры МСД

Контакты для заказов оборудования:

Внимание! На этом сайте большинство материалов - техническая литература в помощь предпринимателю. Так же большинство производственного оборудования сегодня не актуально. Уточнить можно по почте: Эл. почта: msd@msd.com.ua

+38 050 512 1194 Александр
- телефон для консультаций и заказов спец.оборудования, дробилок, уловителей, дражираторов, гереторных насосов и инженерных решений.