PanelDataNotes-1 (1)

7/25/2019 PanelDataNotes-1 (1)

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Part 1: Introduction [1/45]

Econometric Analysis of Panel Data

William Greene

Department of Economics

Stern School of Business


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Panel Data Modeling

Outcome(s) yi Model specifcation: Behavioral description

Observation mechanism: Horizontal and time

Common eects built explicitly into the model:Observed and unobserved heterogeneity

Dynamic efects and behavior

esearch Community: !conomics" political science" sociolo#y: lon#itudinal"

$ransport" mar%etin#: stated choice experiments Health: repeated measures" mixed models

&rban ' re#ional economics: hierarchical models


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Starting Point

A Dynamic Linear Model

= +

= + + + + + +

i"t i"t i"t

i"t "i * i"t + i"t , i"t - i"t . i"t

Balestra/0erlove (1..)" +. 2tates" 3ears

4emand 5or 0atural 6as

2tructure

4emand: 6 6 ( )6 " 7 depreciation rate

0e8 4emand 6 9 0 0 3 3

= + + + + + + + +

i"t

i"t i * i"t + i"t , i"t - i"t . i"t i"t i"t

67#as demand

0 7 population

9 7 price

3 7 per capita income

educed ;orm

6 9 0 0 3 3 6


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Benefits of Panel Data

$ime and individual variation in behavior unobservablein cross sections or a##re#ate time series

Observable and unobservable individual hetero#eneity ich hierarchical structures

More complicated models

;eatures that cannot be modeled 8ith only crosssection or a##re#ate time series data alone

4ynamics in economic behavior


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Panel Data Sets

short panels? 0ational lon#itudinal survey o5 youth (0hu#e panels? rit= r5t7 i(rmt / r5t) it" i 7 "D"manyE t7"Dmany

!xchan#e rate data" essentially infnite $" lar#e 0

!ects: i7 vi


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Panel Data Sets



!ects: i7 vi


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Panel Data Sets



!ects: i7 vi


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Panel Data

otatin# panels: 2panish household survey 2panish incomeFsavin#s study

!Gciency analysis: !Gciency measurement in rotatin#panel data"I Heshmati" A"Applied Economics" +J" 11K"ppL 11/1+J

&L2L 2urvey o5 @ncome and 9ro#ram 9articipation (2@99)

9seudo panel: $ime series o5 (dierent) crosssectionsL !L#L" 3early & ;amily !xpenditure 2urveyE

"JJJ dierent householdsL Nhat can 8e learn5rom these

Hierarchical (nested) data sets: 2tudent outcome"by year" district" school" teacher


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SIPP Rotating PanelThe lessons learned from ISDP were incorporated into the initial design of SIPP, which was used for

the first 10 years of the survey. The original design of SIPP called for a nationally representative sample of

individuals 15 years of age and older to e selected in households in the civilian noninstitutionali!ed population.

Those individuals, along with others who suse"uently lived with them, were to e interviewed once every #

months over a $%&month period. To ease field procedures and spread the wor' evenly over the #&month reference

period for the interviewers, the (ensus )ureau randomly divided each panel into four rotation groups. *ach

rotation group was interviewed in a separate month. +our rotation groups thus constituted one cycle, called a

wave, of interviewing for the entire panel. t each interview, respondents were as'ed to provide informationcovering the # months since the previous interview. The #&month span was the reference period for the interview.

The first sample, the 1-# Panel, egan interviews in /ctoer 1-$ with sample memers in 1-, households.

The second sample, the 1-5 Panel, egan in +eruary 1-5. Suse"uent panels egan in +eruary of each

calendar year, resulting in concurrent administration of the survey in multiple panels.

The original goal was to have each panel cover eight waves. owever, a numer of panels were

terminated early ecause of insufficient funding. +or e2ample, the 1- Panel had si2 waves3 the 1-- Panel,

part of which was folded into the 1--0 Panel, was halted after three waves. In addition, the intent was for each

SIPP panel to have an initial sample si!e of %0,000 households. That target was rarely achieved3 again, udgetissues were usually the reason. The 1--4 redesign discussed elow6 entailed a numer of important changes.

+irst, the 1--4 Panel spans # years and encompasses 1% waves. The redesign has aandoned the overlapping

panel structure of the earlier SIPP, ut sample si!e has een sustantially increased7 the 1--4 Panel had an initial

sample si!e of #0,1 households.


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Panel Data


!Gciency analysis: !Gciency measurement in rotatin#panel data"I Heshmati" A"Applied Economics" +J" 11K"ppL 11/1+J


9seudo panel: $ime series o5 (dierent) crosssectionsL !L#L" 3early & ;amily !xpenditure 2urveyE

"JJJ dierent householdsL Nhat can 8e learn5rom these

Hierarchical (nested) data sets: 2tudent outcome"by year" district" school" teacher


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Pseudo Panel


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Panel Data


!Gciency analysis: !Gciency measurement in rotatin#

panel data"I Heshmati" A"Applied Economics" +J"11K" ppL 11/1+J


9seudo panel: $ime series o5 (dierent) cohortcross sectionsL !L#L" 3early & ;amily !xpenditure

2urveyE "JJJ dierent householdsL

Hierarchical (nested) data sets: 2tudentoutcome" by year" district" school" teacher


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Nested Panel Data

Ant8eiler" NL" 0ested andom !ectsDIPournal o5 !conometrics" J" *JJ" *1-/++

+ +

+ + + +

*

* c"s"t + c"t ,

K 1 " " "

2ulfde concentration(country"station"year7c"s"t)

7 Q Q (lo#649F%m ) Q lo#(F


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Cornwell and Rupert Data

Cornwell and Rupert Returns to Schooling Data, 595 Individuals, !ears(!xtracted 5rom 0


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29

Appli ation !ealt" Care Panel

Data

German Health Care Usage Data, 7,293 Individuals, Varying Numbers o !eriodsVariables in the ile are

Data downloaded from 8ournal of pplied *conometrics rchive. This is an unalanced panel. They can e used

for regression, count models, inary choice, ordered choice, and ivariate inary choice. "his is a large data set#

"here are altogether 27,32$ observations# "he number o observations ranges rom % to 7# &'re(uen)ies

are* %+%2, 2+%-79, 3+.2, /+92$, +%-%, $+%---, 7+..70# 9ote, the variale 9:;/)S elow tells how

many oservations there are for each person. This variale is repeated in each row of the data for the person. D1C"1 + %&Number o do)tor visits -0

H14!I"56 + %&Number o hosital visits -0

H45" + health satisa)tion, )oded - &lo80 %- &high0

D1CVI4 + number o do)tor visits in last three months

H14!VI4 + number o hosital visits in last )alendar year

!U:6IC + insured in ubli) health insuran)e + %; other8ise + -

5DD1N + insured by addon insuran)e + %; others8ise + - HHNINC + household nominal monthly net in)ome in German marID4 + )hildren under age %$ in the household + %; other8ise + -

?DUC + years o s)hooling

5G? + age in years

@5I?D + marital status


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Econometric Analysis of Panel Data

Overview


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Panel Data Econometrics

$his is an intermediate level" 9hL4L course in the areao5 Applied !conometrics dealin# 8ith 9anel 4ataL $heran#e o5 topics covered in the course 8ill span a

lar#e part o5 econometrics #enerally" thou#h 8e areparticularly interested in those techniWues as theyare adapted to the analysis o5 VpanelV or Vlon#itudinalVdata setsL $opics to be studied include specifcation"

estimation" and in5erence in the context o5 modelsthat include individual (frm" person" etcL) eectsL


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#"y a Course on $Panel Data%&

Microeconometrics and applications =contemporary broad feld in

economicsFeconometrics Behavioral modelin# @ndividual choice and response

A plat5orm 5or surveyin# econometricmodels and methods = most o5 the feld Tarious types ecent developments


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Prere'uisites

!conometrics @ or eWuivalent 9hL4L levelintroduction to econometrics

Mathematical statistics

Matrix al#ebra

Ne 8ill do some proo5s and derivationsL

Ne 8ill examine many empirical applicationsL

3ou 8ill apply the tools developed in thecourseL


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(e)t Readings $altagi %&'()*+ ain te-t. read chapters

(,&

/reene %&'(&*+ Recommended.read chapters (,&,0,((,(1

2ooldridge %&'('*+ Suggested.read chapters (,&,),(',((

Cameron and 3rivedi %&''5*+ "eryinteresting. icroeconometrics

Matyas and 2evestre (*JJK)E ecent surveyLContributed papersL

Hsiao(*J,)E Alternative to Balta#i

;rees (*JJ,)E Applications 5rom many areasL

Balta#i (*J, Handboo%)E 2urveys andspecial topics


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Course Applications

9roblem sets 9anel data sets: 2ee the course 8ebsite 2o5t8are: 0pac%a#es:? 2tata" 2A2" !Tie8s 9ro#rammin# environments: " Matlab" 6auss"

Mathematica Ne 8ill not use class time 5or so5t8are

instruction

>


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"ttp**people+stern+nyu+edu*wgreene*Econometrics

*PanelDataEconometrics+"tm


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Course ,utline


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Class Notes


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Pro-lem Sets


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Panel Data Sets


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,t"er Data Sets

ata sets !or "cono#etric $na%&sis


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Rosetta Stone for Data Sets

Stat (ransfer


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#"ere Do #e .o /rom !ere%

evie8 o5 5amiliar classical procedures

;undamental" 5amiliar re#ression extensionsE commoneects models

!ndo#eneity" instrumental variables" 6MM estimation 4ynamic models

Models o5 hetero#eneity

0onlinear models that carry 5or8ard the 5eatures o5the linear" static and dynamic common eects models

ecent developments in non/ and semiparametricapproaches


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Econometric Models


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Estimation Met"ods and Applications

Documents

PanelDataNotes-1 (1)