Fishing mode choice

Description

Data sample of 1,182 people from a survey conducted by Thomson and Crooke (1991) and analyzed by Herriges and Kling (1999). Cameron and Trivedi (2005).

Usage

fishing

Format

A data frame with 1182 observations and 16 variables:

mode

fishing mode choice, = 1 beach, = 2 pier, = 3 private boat, = 4 charter boat

price

price for chosen alternative, usd

crate

catch rate for chosen alternative, sum of per-hour catch rates of targeted species.

dbeach

= 1 if beach mode chosen, = 0 otherwise

dpier

= 1 if pier mode chosen, = 0 otherwise

dprivate

= 1 if private boat mode chosen, = 0 otherwise

dcharter

= 1 if charter boat mode chosen, = 0 otherwise

pbeach

price for beach mode, usd

ppier

price for pier mode, usd

pprivate

price for private boat mode, usd

pcharter

price for charter boat mode, usd

qbeach

catch rate for beach mode

qpier

catch rate for pier mode

qprivate

catch rate for private boat mode

qcharter

catch rate for charter boat mode

income

monthly income, usd

Section in Text

14.2 Binary Outcome Example: Fishing Mode Choice, pp. 464-6, 486

15.2 Choice of Fishing Mode, pp. 491-5

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Herriges, J. and Kling, C. (1999), "Nonlinear Income Effects in Random Utility Models," Review of Economics and Statistics, 81, 62-72.

Thomson, C., and Crooke, S. (1991), "Results of the Southern California Sportfish Economic Survey," NOAA Technical Memorandum, National Marine Fisheries Service, Southwest Fisheries Science Center.

Examples

summary(fishing)

Hourly wages

Description

Data from the Michigan Panel Survey of Income Dynamics, Individual Level Final Release 1993. Sample of 4856 women, extracted by Cameron and Trivedi (2005).

Usage

incpanel

Format

A data frame with 4856 observations and 9 variables:

intnum

interview number 1968

persnum

person number

age

age of individual in 1993

educatn

highest grade/year of school completed 1993

earnings

total labor income of individual received in 1992, dollars

hours

total annual work hours in 1992

sex

sex of individual,= 2 if female

kids

total number of children born to this individual

married

last known marital status: 1 = married, 2 = never married, 3 = widowed, 4 = divorced, 5 = separated, 8 = NA, 9 = no histories 85-93

Section in Text

9.2.1 Nonparametric density estimation, pp. 295 9.2.2 Nonparametric Regression, pp. 297

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Michigan Panel Study of Income Dynamics (PSID), https://psidonline.isr.umich.edu/

Examples

summary(incpanel)

Unemployment duration

Description

Data from the January Current Population Survey's Displaced Workers Supplements (DWS) for the years 1986, 1988, 1990, and 1992. Only individuals between 20 and 61 years old who were displaced from nonagricultural jobs due to plant closure, slack work, or abolished positions are included in the sample (McCall, 1996). Cameron and Trivedi (2005).

Usage

jobless

Format

A data frame with 3343 observations and 43 variables:

spell

length of spell (joblessness duration) in number of two-week intervals

censor1

= 1 if re-employed at full-time job

censor2

= 1 if re-employed at part-time job

censor3

= 1 if re-employed but left job: pt–ft status unknown

censor4

= 1 if still jobless

ui

= 1 if filed unemployment insurance claim

reprate

eligible replacement rate, weekly benefit amount divided by weekly earnings in the lost job,

logwage

log weekly earnings in lost job, 1985 prices

tenure

years tenure in lost job

disrate

eligible disregard rate

slack

= 1 if lost job due to slack work

abolpos

= 1 if lost job due to abolished position

explose

= 1 if expected to lose job

stateur

state unemployment rate, percent

houshead

= 1 if household head

married

= 1 if married

female

= 1 if female

child

= 1 if has children

ychild

= 1 if has children five age and under

nonwhite

= 1 if nonwhite

age

age

schlt12

= 1 if less than 12 years schooling

schgt12

= 1 if more than 12 years schooling

smsa

= 1 if resides in SMSA (standard metropolitan statistical area)

bluecoll

= 1 if los job blue collar

mining

= 1 if lost job in mining

constr

= 1 if lost job in construction

transp

= 1 if lost job in transportation

trade

= 1 if lost job in trade

fire

= 1 if lost job in finance, insurance and real estate sector

services

= 1 if lost job in services sector

pubadmin

= 1 if lost job in the public administration

year85

= 1 if year of job loss is 1985

year87

= 1 if year of job loss is 1987

year89

= 1 if year of job loss is 1989

midatl

= 1 if residence in Middle Atlantic

encen

= 1 if residence in East North Central

wncen

= 1 if residence in West North Central

southatl

= 1 if residence in South Atlantic

escen

= 1 if residence in East South Central

wscen

= 1 if residence in West South Central

mountain

= 1 if residence in Mountain region

pacific

= 1 if residence in Pacific region

Section in Text

17.11 Duration Example: Unemployment Duration, pp. 603-8, 632-6, 658-62

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

McCall, B. (1996), Unemployment Insurance Rules, Joblessness, and Part-time Work," Econometrica, 64, 647-682.

Examples

summary(jobless)

Hours worked and wages

Description

Data on 532 males over 10 years (1979-1988) from Ziliak (1997), collected from the Panel Study of Income Dynamics.

Usage

laborpanel

Format

A data frame with 5320 observations and 8 variables:

lnhr

log of annual hours worked

lnwg

log of of hourly wage

kids

number of children

ageh

age

agesq

quadratic age

disab

= 1 if bad health

id

identification code

year

interview year

Section in Text

21.3 Linear Panel Example: Hours and Wages, pp. 708-15

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Ziliak, J. (1997), "Efficient Estimation With Panel Data when Instruments are Predetermined: An Empirical Comparison of Moment-Condition Estimators," Journal of Business and Economic Statistics, 15, 419-431. https://amstat.tandfonline.com/doi/abs/10.1080/07350015.1997.10524720

Panel Study of Income Dynamics (PSID), https://psidonline.isr.umich.edu

Examples

summary(laborpanel)

Hours worked and wages (more precision)

Description

Data on 532 males over 10 years (1979-1988) from Ziliak (1997), with more significant digits (seven decimals) than the data originally posted on JBES website with two decimal places (Cameron and Trivedi, 2005).

Usage

laborpanelprec

Format

A data frame with 5320 observations and 8 variables:

lnhr

log of annual hours worked

lnwg

log of of hourly wage

kids

number of children

ageh

age

agesq

quadratic age

disab

= 1 if bad health

id

identification code

year

interview year

...

Section in Text

22.3 Panel GMM Example: Hours and Wages, pp. 754-6

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Ziliak, J. (1997), "Efficient Estimation With Panel Data when Instruments are Predetermined: An Empirical Comparison of Moment-Condition Estimators," Journal of Business and Economic Statistics, 15, 419-431. https://amstat.tandfonline.com/doi/abs/10.1080/07350015.1997.10524720

Panel Study of Income Dynamics (PSID), https://psidonline.isr.umich.edu

Examples

summary(laborpanelprec)

Training and earnings

Description

Data from the National Supported Work (NSW) demonstration project used by Lalonde (1986), and Dehejia and Wahba (1999, 2002). This sample has 185 observations in the treatment group and 2490 in the control group. The treatment sample consists of males who received training during 1976-1977. THe control group consists of male household heads under the age of 55 who are not retired, drawn from the PSID (Cameron and Trivedi, 2005).

Usage

nswproject

Format

A data frame with 2675 observations and 18 variables:

treat

= 1 if individual is in treatment group, = 0 if in control group

age

age in years

educ

education in years

black

= 1 if black

hisp

= 1 if hispanic

marr

= 1 if married

re74

real annual earnings in 1974 (pre-treatment), in 1982 usd

re75

real annual earnings in 1975 (pre-treatment), in 1982 usd

re78

real annual earnings in 1978 (post-treatment), in 1982 usd

u74

= 1 if unemployed in 1974

u75

= 1 if unemployed in 1975

agesq

age squared

educsq

educ squared

nodegree

= 1 if years of education < 12

re74sq

re74 squared

re75sq

re75 squared

u74black

interaction term u74 x black

u74hisp

interaction term u74 x hisp

Section in Text

25.8 Treatment Evaluation Example: The Effect of Training on Earnings, pp. 889-95

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Dehejia R. and Wahba S. (1999), "Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs," JASA, 1053-1062.

Dehejia R. and Wahba S. (2002), "Propensity-score Matching Methods for Nonexperimental Causal Studies", ReStat, 151-161

Lalonde, R. (1986), "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," AER, 604-620.

Examples

summary(nswproject)

Patents and R&D

Description

Panel data on patents and R&D expenditures. The sample includes 346 firms with five years of data from 1975 to 1979 used by Hall, Griliches, and Hausman (1986).

Usage

patentsrd

Format

A data frame with 346 observations and 25 variables:

cusip

Compustat's identifying number for the firm (Committee on Uniform Security Identification Procedures number).

ardssic

A two-digit code for the applied R&D industrial classification.

scisect

= 1 if firm is in the scientific sector.

logk

log of the book value of capital in 1972.

sumpat

sum of patents applied for between 1972-1979.

logr70

log of R&D spending in 1970, in 1972 dollars.

logr71

log of R&D spending in 1971, in 1972 dollars.

logr72

log of R&D spending in 1972, in 1972 dollars.

logr73

log of R&D spending in 1973, in 1972 dollars.

logr74

log of R&D spending in 1974, in 1972 dollars.

logr75

log of R&D spending in 1975, in 1972 dollars.

logr76

log of R&D spending in 1976, in 1972 dollars.

logr77

log of R&D spending in 1977, in 1972 dollars.

logr78

log of R&D spending in 1978, in 1972 dollars.

logr79

log of R&D spending in 1979, in 1972 dollars.

pat70

number of patents applied in the year that were eventually granted (1970).

pat71

number of patents applied in the year that were eventually granted (1971).

pat72

number of patents applied in the year that were eventually granted (1972).

pat73

number of patents applied in the year that were eventually granted (1973).

pat74

number of patents applied in the year that were eventually granted (1974).

pat75

number of patents applied in the year that were eventually granted (1975).

pat76

number of patents applied in the year that were eventually granted (1976).

pat77

number of patents applied in the year that were eventually granted (1977).

pat78

number of patents applied in the year that were eventually granted (1978).

pat79

number of patents applied in the year that were eventually granted (1979).

Section in Text

23.3 Nonlinear Panel Example: Patents and R&D, pp. 792-5

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Hall, B., Griliches, Z. and Hausman J. (1986), "Patents and R and D: Is There a Lag?," International Economic Review, 27, issue 2, p. 265-83.

Examples

summary(patentsrd)

Health expenditures and insurance plans

Description

Data from the RAND Health Insurance Experiment. The data comes from Deb and Trivedi (2002). It includes variables on the number of contacts with a medical doctor, medical expenditures, demographics, health status, and insurance status. Cameron and Trivedi (2005).

Usage

randhealth

Format

A data frame with 20,190 observations and 45 variables:

plan

health insurance plan number

site

one of six sites where experiment was conducted

coins

medical coinsurance

tookphys

took baseline physical

year

study year

zper

person id, leading digit is sit

black

= 1 if race of household head is black

income

income based on annual income

xage

age that year

female

= 1 if person is female

educdec

years of schooling of decision maker

time

time eligible during the year

outpdol

outpatient exp. excl. ment and

drugdol

drugs purchased, outpatient

suppdol

supplies purchased, outpatient

mentdol

psychotherapy exp., outpatient

inpdol

inpatient exp., facilities and md

meddol

annual medical expenditures in constant dollars, excluding dental and outpatient mental

totadm

number of hospital admissions

inpmis

missing any inpatient charges

mentvis

number psychotehrapy visits

mdvis

number face-to-face md visits

notmdvis

number face-to-face, not md visits

num

family size

mhi

mental health index, baseline

disea

number of chronic diseases

physlm

= 1 if person has physical limitation

ghindx

general health index, baseline

mdeoff

maximum expenditure offer

pioff

participation incentive

child

= 1 if age is less than 18

fchild

= 1 if female child

lfam

log of family size

lpi

log of annual participation incentive payment or 0 if no payment

idp

= 1 if individual deductible plan

logc

log(coinsurance + 1) where coinsurance rate is 0 to 100

fmde

log(max(medical deductible expenditure)) if idp=1 and mde>1, 0 otherwise

hlthg

= 1 if self-rated health is good

hlthf

= 1 if self-rated health is fair

hlthp

= 1 if self-rated health is poor, (omitted is excellent)

xghindx

ghi with imputation

linc

log of annual family income, usd

lnum

log of family size

lnmeddol

log of medical expenditures given meddol > 0; missing otherwise

binexp

= 1 if medical expenditures > 0

Section in Text

16.6 Selection Models, pp. 553-6, 565 20.3 Count Example: Contacts with Medical Doctor, p.671

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Deb, P. and Trivedi, P.K. (2002), "The Structure of Demand for Health Care: Latent Class versus Two-Part Models," Journal of Health Economics, 21, 601-625.

RAND Corporation. "RAND's Health Insurance Experiment ." https://www.rand.org/health-care/projects/hie.html

Examples

summary(randhealth)

Returns to schooling

Description

Data from the National Longitudinal Survey of Young Men. Cohort includes 3,010 males aged 24 to 34 years old in 1976, who were ages 14-24 when first interviewed in 1966. Cameron and Trivedi (2005)

Usage

schooling

Format

A data frame with 5226 observations and 101 variables:

id

identification code

black

= 1 if black race

imigrnt

= 1 if born in the US

hhead

person lived with at age 14 (in 1966)

mag_14

= 1 if magazines available at age 14

news_14

= 1 if newspapers available at age 14

lib_14

= 1 if library card available at age 14

num_sib

total number of siblings

fgrade

highest grade completed by father (1966)

mgrade

highest grade completed by mother (1966)

iq

IQ score in 1968

bdate

date of birth

gfill76

highest grade completed 1976, some values filled from prevs reports

wt76

sampling weights 1976

grade76

highest grade completed in 1976

grade66

highest grade completed in 1966

age76

age in 1976

age66

age in 1966

smsa76

current residence, = 1 if lived in central city in 1976

smsa66

current residence, = 1 if lived in central city in 1966

region

census region in 1966

col4

= 1 if there is a 4-year college nearby

mcol4

= 1 if male 4-year college nearby

col4pub

= 1 if public 4-year college nearby

south76

= 1 if lived in South in 1976

wage76

hourly wage in 1976, ln

exp76

work experience in 1976, years calculated as (10 + age66) - grade76 - 6

expsq76

experience 1976 squared, exp76^2/100

agesq76

age squared (1976)

reg1

region, = 1 if lived in region NE

reg2

region, = 1 if lived in region MidAtl

reg3

region, = 1 if lived in region ENC

reg4

region, = 1 if lived in region WNC

reg5

region, = 1 if lived in region SA

reg6

region, = 1 if lived in region ESC

reg7

region, = 1 if lived in region WSC

reg8

region, = 1 if lived in region M

reg9

region, = 1 if lived in region P

momdad14

= 1 if lived with both parents at age 14

sinmom14

= 1 if lived with mother only at age 14

nodaded

= 1 if father has no formal education

nomomed

= 1 if mother has no formal education

daded

mean grade level of father

momed

mean grade level of mother

famed

father's and mother's education

famed1

= 1 if mgrade> 12 & fgrade> 12

famed2

= 1 if mgrade>=12 & fgrade>=12

famed3

= 1 if mgrade==12 & fgrade==12

famed4

= 1 if mgrade>=12 & fgrade==-1

famed5

= 1 if fgrade>=12

famed6

= 1 if mgrade>=12 & fgrade> -1

famed7

= 1 if mgrade>=9 & fgrade>=9

famed8

= 1 if mgrade> -1 & fgrade> -1

famed9

= 1 if famed not in range 1-8

int76

= 1 if wt76 not missing

age1415

= 1 if in age group 14-15

age1617

= 1 if in age group 16-17

age1819

= 1 if in age group 18-19

age2021

= 1 if in age group 20-21

age2224

= 1 if in age group 22-24

cage1415

= 1 if in age group 14-15 and lived near college

cage1617

= 1 = 1 if in age group 16-17 and lived near college

cage1819

= 1 if in age group 18-19 and lived near college

cage2021

= 1 if in age group 20-21 and lived near college

cage2224

= 1 if in age group 22-24 and lived near college

cage66

age in 1966 and lived near college

a1

= 1 if age in 1966 is 14

a2

= 1 if age in 1966 is 15

a3

= 1 if age in 1966 is 16

a4

= 1 if age in 1966 is 17

a5

= 1 if age in 1966 is 18

a6

= 1 if age in 1966 is 19

a7

= 1 if age in 1966 is 20

a8

= 1 if age in 1966 is 21

a9

= 1 if age in 1966 is 22

a10

= 1 if age in 1966 is 23

a11

= 1 if age in 1966 is 24

ca1

= 1 if did not live near college in 1966

ca2

= 1 if lived near college and age in 1966 = 14

ca3

= 1 if lived near college and age in 1966 = 15

ca4

= 1 if lived near college and age in 1966 = 16

ca5

= 1 if lived near college and age in 1966 = 17

ca6

= 1 if lived near college and age in 1966 = 18

ca7

= 1 if lived near college and age in 1966 = 19

ca8

= 1 if lived near college and age in 1966 = 20

ca9

= 1 if lived near college and age in 1966 = 21

ca10

= 1 if lived near college and age in 1966 = 22

ca11

= 1 if lived near college and age in 1966 = 23

ca12

= 1 if lived near college and age in 1966 = 24

g25

grade level when 25 years old

g25i

= 1 if =g25 and intrvwed in year used for determining g25

intmo66

interview month in 1966, used to identify cases incl by Card

nlsflt

flag to identify if the case was used by Card

nsib

number of siblings

ns1

= 1 if the person has no siblings

ns2

= 1 if number of siblings is 2

ns3

= 1 if number of siblings is 3

ns4

= 1 if number of siblings is 4

ns5

= 1 if number of siblings is 6

ns6

= 1 if number of siblings is 9

ns7

= 1 if number of siblings is 18

Section in Text

4.9.6 Instrumental Variables Application, pp. 110-2

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Card, D. (1995), "Using Geographic Variation in College Proximity to Estimate the Returns to Schooling", in Aspects of Labor Market Behavior: Essays in Honor of John Vanderkamp, eds. L.N. Christofides et al., Toronto: University of Toronto Press, pp.201-221.

Kling, J.R. (2001) "Interpreting Instrumental Variables Estimates of the Return to Schooling," Journal of Business and Economic Statistics, 19, 358-364.

https://www.nlsinfo.org/content/cohorts/older-and-young-men

Examples

summary(schooling)

Strikes duration

Description

Data set on 566 contract strikes in U.S. manufacturing for the period 1968-76. The data has been used by Kennan (1985), Jaggia (1991), and others, and was originally published by the U.S. Department of Labor. Cameron and Trivedi (2005).

Usage

strikes

Format

A data frame with 566 observations and 2 variables:

dur

duration of the strike, number of days from the start of the strike.

gdp

measure of business cycle stage, deviation of monthly log industrial production in manufacturing.

Section in Text

17.2 Duration Models, pp. 574-5, 582

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

Kennan, J. (1985), "The Duration of Contract strikes in U.S. Manufacturing," Journal of Econometrics, 28, 5-28.

Jaggia, S. (1991), "Specification Tests Based on the Heterogeneous Generalized Gamma Model of Duration: With an Application to Kennan's Strike Data," Journal of Applied Econometrics, 6, 169–180.

Examples

summary(strikes)

Vietnam health care use (household level)

Description

Data from the World Bank's Vietnam Living Standards Survey of 1997-1998 at the household level. Sample extract by Cameron and Trivedi (2005).

Usage

vietnam_hh

Format

A data frame with 5999 observations and 8 variables:

sex

= 1 if head of household is female

age

age of head of household

educ

Highest education obtained by head of household

farm

= 1 for agricultural household

hhsize

household size

commune

commune code

lnhhexp

total household expenditure, ln

lnexp12m

household healthcare expenditure in the past 12 months, ln

Section in Text

24.7 Clustering Example: Vietnam Health Care Use, pp 848-53

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

World Bank Living Standards Survey 1997-1998 Vietnam. https://microdata.worldbank.org/index.php/catalog/2694

Examples

summary(vietnam_hh)

Vietnam health care use (individual level)

Description

Data from the World Bank's Vietnam Living Standards Survey of 1997-1998 at the individual level. Sample extract by Cameron and Trivedi (2005).

Usage

vietnam_ind

Format

A data frame with 27766 observations and 12 variables:

educ

Completed diploma level

sex

= 1 if respondent is male

age

age in years

married

= 1 for married person

illness

number of illnesses experienced in past 12 months

injury

= 1 if injured during survey period

illdays

number of illness days

actdays

number od days of limited activity

pharvis

number of direct pharmacy visits

insurance

= 1 if respondent has health insurance coverage

lnhhexp

total household expenditure, ln

commune

commune code

Section in Text

Section

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

World Bank Living Standards Survey 1997-1998 Vietnam. https://microdata.worldbank.org/index.php/catalog/2694

Examples

summary(vietnam_ind)

Household medical expenditure

Description

Data from the World Bank's 1997 Vietnam Living Standards Survey 1997-98 at the household level. Cameron and Trivedi (2005)

Usage

vietnamlss

Format

A data frame with 5999 observations and 9 variables:

sex

gender of household head, 1 = male; 2 = female

age

age of household head

educyr98

schooling year of household head

farm

type of household, = 1 if farm

urban98

= 1 if urban area, = 0 if rural area

hhsize

household size

lhhexp1

household total expenditure, ln

lhhex12m

household medical expenditure, ln

lnrlfood

household food expenditure, ln

Section in Text

4.6.4 Quantile Regression Example, pp. 88-90

Source

http://cameron.econ.ucdavis.edu/mmabook/mmadata.html

References

Cameron, A. and Trivedi, P. (2005), "Microeconometrics: Methods and Applications," Cambridge University Press, New York.

World Bank Living Standards Survey 1997-1998 Vietnam. https://microdata.worldbank.org/index.php/catalog/2694

Examples

summary(vietnamlss)