ECON301_Handout_01_1213_02

Observations on x and y can be made over time in

Info iconThis preview shows pages 3–6. Sign up to view the full content.

View Full Document Right Arrow Icon
Observations on X and Y can be made over time, in which case we speak of having “ time series ” data. o For example we may have data on Turkey’s GDP over 30 years (data collected over a period of time). Or they can be made over individuals, or groups of individuals, firms, or group of firms, countries, or group of countries, objects, geographical areas, etc., in which we speak of having “ cross section data ”. o For example we may have data on several countries’ GDP for one year (data collected at one point in time). Hence, the subscript t may refer to the t th year (quarter, month, day, etc) or to the t th individual or group (such as countries; Turkey, Germany, France, USA, Japan, etc. .). Data of both kinds can be combined to obtain “ pooled times and cross-section data ” or simply “ pooled data o For example we may have data on 20 countries’ GDP over 30 years. o There is a special type of pooled data, the panel or longitudinal data, also called micropanel data, in which the Instructor: Dr. Ozan ERUYGUR e-mail: [email protected] Lecture Notes 3
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
ECON 301 (01) - Introduction to Econometrics I March , 2012 METU - Department of Economics same cross-sectional unit (say, a family or firm) is surveyed over time (Gujarati, p.23). Hence, panel data is a special case of “pooled data”. The phrase "pooled data" is more general . It implies that the data have both a time-series and a cross- sectional dimension, but it includes the case where the individuals (or sections) are not the same. For example; some individuals drop out over time and are replaced by others. 4. Linearity Issue 3 1 0 t tt Y Xu ββ = ++ is nonlinear in the parameter 1 β . This model is an example of a nonlinear (in the parameter) regression model. Instructor: Dr. Ozan ERUYGUR e-mail: [email protected] Lecture Notes 4
Background image of page 4
ECON 301 (01) - Introduction to Econometrics I March , 2012 METU - Department of Economics 5. Stochastic Nature of Linear Regression Model The stochastic nature of the regression model implies that for every value of X there is a whole probability distribution of values of Y . Uncertainty concerning Y arises because of the presence of the stochastic disturbance u which, being random, imparts randomness to Y . o For example, consider a production function of a firm. o Suppose that output depends in some specified way on the quantity of labor (L) in accordance with firm’s technology. 01 t tt Output Labor u ββ = ++ This function may apply in the short run when the quantities of other factors are fixed. o In general, the same quantity of labor will lead to different quantities of output because of variations in weather , human performance , frequency of machine breakdowns , and many other factors. o Output, which is the dependent variable in this case, will depend not only on the quantity of labor input, but also on the large number of random causes, which we summarize in the form of the stochastic disturbance ( u ).
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 6
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

Page3 / 17

Observations on X and Y can be made over time in which case...

This preview shows document pages 3 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online