unlike cross-sectional data, ordering is important here!
behaviour of economic subject (and the resulting indicators) evolve in a gradual manner in time
lags in economic behaviour (oil prices today affect next month’s
actions)
typically, observations cannot be considered independent across time
→ require more complex econometric techniques
year
T-bill
infl
dispInc
C_ndur
popul
1994
4.95
2.6
4778.2
1390.5
260,660
1995
5.21
2.8
4945.8
1421.9
263,034
…
…
…
…
…
…
Pooled Cross Sections
25
both cross-sectional and time-series features
data collected in multiple (typically, two) points in time
ordering is not crucial, year is recorded as an additional variable
often used to evaluate the effect of a policy change
collect data before and after the policy change and see how the relationship between the variables changes
note: in the second time period, the cross-sectional units need be neither distinct from nor identical to those in the first period
obs
year
hprice
sq_feet
bdrms
bthrms
1
2005
105,000
1400
3
1
……
……
……
……
……
……
250
2005
198,500
2350
5
3
251
2008
95,600
1800
3
2
……
……
……
……
……
……
550
2008
119,900
2150
4
2
Panel (or Longitudinal) Data
26
several cross-sectional units, a time series for each unit (time series with equal length)
unlike with pooled cross sections, the same units are measured over
time
more difficult /costly to obtain the data
have several advantages over (pooled) cross sections (for problem where panel data make sense)
unit
year
popul
murders
unemp
police
1
2008
293,700
5
6.3
358
1
2010
299,500
7
7.4
396
2
2008
53,450
2
7.2
51
2
2010
51,970
1
8.1
51
……
……
……
……
……
……
Leicester
Salisbury
can be treated as pooled cross section (but: loss of information)
Introductory Econometrics
LECTURE 1:
INTRODUCTION