Econometric Analysis, 7th Edtion, Data Sets

Econometric Analysis, 7th Edition

Links to Data Tables

table 4.1 is Monet paintings dataTable 4.3 is movie buzz data19.1 is Swiss railroad data

Table F1.1 Table F1.1: Consumption and Income, 10 Yearly Observations, 1970-1979
Source: Economic Report of the President, 1987, Council of Economic Advisors

C = Consumption and
Y = Disposable Income

Table F2.1 Table F2.1: Consumption and Income, 11 Yearly Observations, 1940-1950
Source: Economic Report of the President, U.S. Government Printing Office, Washington, D.C., 1983.

Year = Date,
X = Disposable Income,
C = Consumption.
W = War years dummy variable, 1 in 1942-1945, 0 other years.

Table F2.2 The U.S. Gasoline Market, 52 Yearly Observations, 1953-2004
Source: These data were compiled by Professor Chris Bell, Department of Economics, University of North Carolina, Asheville. Sources: www.bea.gov and www.bls.gov

Year = Year, 1953-2004,
GasExp = Total U.S. gasoline expenditure,
Pop = U.S. total population in thousands
GasP = Price index for gasoline,
Income = Per capita disposable income,
Pnc = Price index for new cars,
Puc = Price index for used cars,
Ppt = Price index for public transportation,
Pd = Aggregate price index for consumer durables,
Pn = Aggregate price index for consumer nondurables,
Ps = Aggregate price index for consumer services.

Table F3.1 U.S. Investment Data, 15 Yearly Observations, 1968-1982
Source: Economic Report of the President, U.S. Government Printing Office, Washington, D.C., 1983. CPI 1967 is 79.06.
The interest rate is the average yearly discount rate at the New York Federal Reserve Bank.

Year = Date,
GNP = Nominal GNP,
Invest = Nominal Investment,
CPI = Consumer price index,
Interest = Interest rate.

Table F3.2 Koop and Tobias (2004) labor Market Experience Data
Source: See the article for details on construction. The data file is in two parts. The first file contains the panel of 17,919 observations on the Person ID and 4 time-varying variables. The second file contains time invariant variables for the individual or the 2,178 households.

Column 1 = Person id (ranging from 1–2, 178),
Column 2 = Education,
Column 3 = Log of hourly wage,
Column 4 = Potential experience,
Column 5 = Time trend.
Column 1 = Time invariant ability,
Column 2 = Mother’s education,
Column 3 = Father’s education,
Column 4 = Dummy variable for residence in a broken home,
Column 5 = Number of siblings.

Table F4.2 Table F4.2: The Longley Data, 15 Yearly Observations, 1947-1962
Source: Longley, (1967).

Employ = Employment (1000s),
Price = GNP deflator,
GNP = Nominal GNP (millions),
Armed = Armed forces,
Year = Date.

Table F4.4 Table F4.4: Cost Function, 158 1970 Cross Section Firm Level Observations
Source: Christensen and Greene (1976). Note the file contains 35 extra observations.
These are the holding companies. Christensen and Greene used only the first 123 observations. Use observations 1-123 to replicate Christensen and Greene.

Id = Observation,
Year = 1970 for all observations
Cost = Total cost,
Q = Total output,
Pl = Wage rate,
Sl = cost share for labor ,
Pk = Capital price index,
Sk = Cost share for capital,
Pf = Fuel price,
Sf = Cost share for fuel

Table F5.1 Table F5.1: Labor Supply Data From Mroz (1987), 753 Observations
Source: 1976 Panel Study of Income Dynamics, Mroz(1987).

LFP = A dummy variable = 1 if woman worked in 1975, else 0
WHRS = Wife's hours of work in 1975
KL6 = Number of children less than 6 years old in household
K618 = Number of children between ages 6 and 18 in household
WA = Wife's age
WE = Wife's educational attainment, in years
WW = Wife's average hourly earnings, in 1975 dollars
RPWG = Wife's wage reported at the time of the 1976 interview (not = 1975 estimated wage)
HHRS = Husband's hours worked in 1975
HA = Husband's age
HE = Husband's educational attainment, in years
HW = Husband's wage, in 1975 dollars
FAMINC = Family income, in 1975 dollars
WMED = Wife's mother's educational attainment, in years
WFED = Wife's father's educational attainment, in years
UN = Unemployment rate in county of residence, in percentage points.
CIT = Dummy variable = 1 if live in large city (SMSA), else 0
AX = Actual years of wife's previous labor market experience

Table F5.2 Table F5.2: Macroeconomics Data Set, Quarterly, 1950I to 2000IV, 204 Quarterly Observations
Source: Department of Commerce, BEA website and www.economagic.com

Year = Date
Qtr = Quarter
Realgdp = Real GDP ($bil)
Realcons = Real consumption expenditures
Realinvs = Real investment by private sector
Realgovt = Real government expenditures
Realdpi = Real disposable personal income
CPI_U = Consumer price index
M1 = Nominal money stock
Tbilrate = Quarterly average of month end 90 day t bill rate
Unemp = Unemployment rate
Pop = Population, mil. interpolate of year end figures using constant growth rate per quarter
Infl = Rate of inflation (first observation is missing)
Realint = Ex post real interest rate = Tbilrate - Infl. (First observation missing)

Table F5.3 Table F5.3: Production Data For SIC 33: Primary Metals, 27 Statewide Observations
Source and Note: Data are per establishment, labor is a measure of labor input, and capital is the gross value of
plant and equipment. A scale factor used to normalize the capital figure in the original study has been
omitted. Further details on construction of the data are given in Aigner, et al. (1977) and in
Hildebrand and Liu (1957).

Obs = Observation number
Valueadd = Value added,
Labor = Labor input,
Capital = Capital stock.

Table F6.1 Table F6.1: Cost Data for U.S. Airlines, 90 Oservations On 6 Firms For 15 Years, 1970-1984
Source: These data are a subset of a larger data set provided to the author by Professor Moshe Kim.
They were originally constructed by Christensen Associates of Madison, Wisconsin.

I = Airline,
T = Year,
Q = Output, in revenue passenger miles, index number,
C = Total cost, in $1000,
PF = Fuel price,
LF = Load factor, the average capacity utilization of the fleet.

Table F6.2 Table F6.2: Cost Function Data, 145 U.S. Electricity Producers, 1955 Data; Nerlove
Source: Nerlove (1960) and Christensen and Greene (1976)
Note: The data file contains several extra observations that are aggregates of commonly owned firms.
Use only the first 145 observations for analysis.

Firm = Observation,
Year = 1955 for all observations
Cost = Total cost,
Output = Total output,
Pl = Wage rate,
Sl = Cost share for labor,
Pk = Capital price index,
Sk = Cost share for capital,
Pf = Fuel price,
Sf = Cost share for fuel

Table F6.3 Table F6.3: World Health Organization Data used for the analysis of efficiency in health care outcomes in the year 2000 World Health Report. The original data were provided by WHO, The World Health Organization [Evans et al. (2000) and www.who.int]. Variables marked with * were updated in Greene (2004).

COMP =Composite measure of health care attainment,
DALE =Disability adjusted life expectancy (other measure),
YEAR =1993, . . . , 1997,
TIME =1, 2, 3, 4, 5, T93, T94, T95, T96, T97 = year dummy variables,
HEXP =Per capita health expenditure,
HC3 =Educational attainment,
SMALL =Indicator for states, provinces, etc. (These are additional observations.)
SMALL > 0 implies internal political unit, = 0 implies country observation,
COUNTRY=Number assigned to country,
GROUPTI =Number of observations whenSMALL=0. Usually 5, some=1, one country=4,
OECD =Dummy variable for OECD country (30 countries),
GINI =Gini coefficient for income inequality,
GEFF =World bank measure of government effectiveness,*
VOICE =World bank measure of democratization of the political process,*
TROPICS =Dummy variable for tropical location,
POPDEN =Population density,*
PUBTHE =Proportion of health expenditure paid by bublic authorities,
GDPC =Normalized per capita GDP.

Table F6.4 Table F6.4: Solow’s Technological Change Data, 41 Yearly Observations, 1909-1949
Source: Solow (1957, p. 314). Several Variables are omitted.

year = Date,
Q = Output,
K = Capital/labor ratio,
A = Index of technology.

Table F7.1 Table F7.1: German Health Care Data, Unbalanced Panel, 7,293 Individuals, 27,326 Observations
Source: Riphahn, Wambach, Million (2003)

ID =Person - identification number,
FEMALE =Female = 1; male = 0,
YEAR =Calendar year of the observation,
AGE =Age in years,
HSAT =Health satisfaction, coded 0 (low)–10 (high),
NEWHSAT =Health satisfaction, 0, . . . , 10; see note below,
HANDDUM=Handicapped = 1; otherwise = 0,
HANDPER =Degree of handicap in percent (0–100),
HHNINC =Household nominal monthly net income in German marks/10,000,
HHKIDS =Children under age 16 in the household = 1; otherwise = 0,
EDUC =Years of schooling,
MARRIED =Married = 1; otherwise = 0,
HAUPTS =Highest schooling degree is Hauptschul degree = 1; otherwise = 0,
REALS =Highest schooling degree is Realschul degree = 1; otherwise = 0,
FACHHS =Highest schooling degree is Polytechnical degree = 1; otherwise = 0,
ABITUR =Highest schooling degree is Abitur = 1; otherwise = 0,
UNIV =Highest schooling degree is university degree = 1; otherwise = 0,
WORKING=Employed = 1; otherwise = 0,
BLUEC =Blue-collar employee = 1; otherwise = 0,
WHITEC =White-collar employee = 1; otherwise = 0,
SELF =Self-employed = 1; otherwise = 0,
BEAMT =Civil servant = 1; otherwise = 0,
DOCVIS =Number of doctor visits in last three months,
HOSPVIS =Number of hospital visits in last calendar year,
PUBLIC =Insured in public health insurance = 1; otherwise = 0,
ADDON =Insured by add-on insurance = 1; otherwise = 0,
NUMOBS = Number of observations for this person. Repeated in each row of data (added to data set).
NEWHSAT = HSAT; 40 observations on HSAT recorded between 6 and 7 were changed to 7 (added to data set).

Table F7.2 Table F7.2: Statewide Data on Transportation Equipment Manufacturing, 25 Observations
Source: A Zellner and N. Revankar (1970, p. 249).
Note: “Value added,” “Capital,” and “Labor” are in millions of 1957 dollars.
Data used for regression examples are per establishment. Raw data are used for the stochastic frontier application in Chapter 16.

State = Observation,
ValueAdd = output,
Capita = capital input,
Labor = labor input,
Nfirm = number of firms.

Table F7.3 Table F7.3: Expenditure and Default Data, 1319 observations
Source: Greene (1992)

Cardhldr = Dummy variable, 1 if application for credit card accepted, 0 if not
Majordrg = Number of major derogatory reports
Age = Age n years plus twelfths of a year
Income = Yearly income (divided by 10,000)
Exp_Inc = Ratio of monthly credit card expenditure to yearly income
Avgexp = Average monthly credit card expenditure
Ownrent = 1 if owns their home, 0 if rent
Selfempl = 1 if self employed, 0 if not.
Depndt = 1 + number of dependents
Inc_per = Income divided by number of dependents
Cur_add = months living at current address
Major = number of major credit cards held
Active = number of active credit accounts

Table F8.1 Table F8.1: Cornwell and Rupert, Labor Market Data, 595 Individuals, 7 years
Source: Cornwell and Rupert (1988)

EXP =Work experience,
WKS =Weeks worked,
OCC =Occupation, 1 if blue collar,
IND =1 if manufacturing industry,
SOUTH =1 if resides in south,
SMSA =1 if resides in a city (SMSA),
MS =1 if married,
FEM =1 if female,
UNION =1 if wage set by union contract,
ED =Years of education,
BLK =1 if individual is black,
LWAGE=Log of wage.

Table F9.1 Table F9.1: Income and Expenditure Data. 100 Cross Section Observations
Source: Greene (1992)

MDR = Number of derogatory reports
Acc = Credit card application accepted (1=yes),
Age = Age in years+ 12ths of a year,
Income = Income, divided by 10,000 ,
Avgexp = Avg. monthly credit card expenditure,
Ownrent = OwnRent, individual owns (1) or rents (0) home.
Selfempl = Self employed (1=yes, 0=no)

Table F9.2 Table F9.2: Baltagi and Griffin OECD gasoline consumption data. 18 OECD countries, 19 years.
Source: Baltagi (2005)

COUNTRY =Name of country,
YEAR =Year, 1960–1978,
LGASPCAR=Log of consumption per car,
LINCOMEP=Log of per capita income,
LRPMG =Log of real price of gasoline,
LCARPCAP =Log of per capita number of cars.

Table F10.1 Table F10.1: Munnell Productivity Data, 48 Continental U.S. States, 17 years,1970–1986
Source: Baltagi (2005), Munnell (1990)

STATE = State name,
ST ABB=State abbreviation,
YR =Year, 1970, . . . ,1986,
PCAP =Public capital,
HWY =Highway capital,
WATER =Water utility capital,
UTIL =Utility capital,
PC =Private capital,
GSP =Gross state product,
EMP =Employment,

Table F10.2 Table F10.2: Manufacturing Costs, U.S. Economy, 25 Yearly Observations, 1947-1971
Source: Berndt and Wood (1975)

Year = Date,
Cost = Cost index,
K = Capital cost share,
L = Labor cost share,
E = Energy cost share,
M = Materials cost share,
Pk = Capital price,
Pl = Labor price,
Pe = Energy price,
Pm = materials price.

Table F10.3 Table F10.3: Klein’s Model I , 22 Yearly Observations, 1920-1941
Source: Klein (1950).

Year = Date,
C = Consumption,
P = Corporate profits,
Wp = Private wage bill,
I = Investment,
K1 = previous year’s capital stock,
X = GNP,
Wg = Government wage bill,
G = Government spending,
T = Taxes.

Table F10.4 Table F10.4: Grunfeld Investment Data, 100 Yearly Observations On 10 Firms For 1935-1954
Sources: Moody’s Industrial Manual, Survey of Current Business

I = Gross investment, from Moody’s Industrial Manual and annual reports of corporations;
F = Value of the firm from Bank and Quotation Record and Moody’s Industrial Manual;
C = Stock of plant and equipment, from Survey of Current Business.

Table F13.1 Table 13.1: Dahlberg and Johanssen - Municipal Expenditure Data,
Data From 265 Municipalities for 9 Years, 1979-1987, 2385 Observations
Source: Dahlberg and Johanssen (2000), Journal of Applied Econometrics data archive.

ID = Identification
Year = Date
Expend = Expenditure
Revenue = Revenue from taxes and fees
Grants = Grants from Central Government

Table F14.1 Table F14.1: Program Effectiveness, 32 Cross Section Observations
Source: Spector and Mazzeo (1980).

Obs = observation,
TUCE = Test score on economics test,
PSI = participation in program,
GRADE = Grade increase (1) or decrease (0) indicator

Table F15.1 Table F15.1: Bertschek and Lechner Binary Choice Data, Yearly Data 1993-1998 on 1,270 Firms
Source: Bertcshek and Lechner (1998)
Note: These data are proprietary. They are not listed on the website.

yit = 1 if firm i realized a product innovation in year t and 0 if not.
xit1 =constant term,
xit2 = log of sales,
xit3 = relative size = ratio of employment in business unit to employment in the industry,
xit4 = ratio of industry imports to (industry sales + imports),
xit5 = ratio of industry foreign direct investment to (industry sales + imports),
xit6 = productivity = ratio of industry value added to industry employment,
xit7 = dummy variable indicating firm is in the raw materials sector,
xit8 = dummy variable indicating firm is in the investment goods sector.

Table F17.1 Table F17.1: Burnett Analysis of Liberal Arts College Gender Economics Courses, 132 Observations
Source: Data provided by the author; Burnett (1997).

y1 =Presence of a gender economics course (0/1),
y2 =Presence of a women’s studies program on the campus (0/1),
z2 =Academic reputation of the college, coded 1 (best), 2, . . . to 141,
z3 =Size of the full time economics faculty, a count,
z4 =Percentage of the economics faculty that are women, proportion (0 to 1),
z5 =Religious affiliation of the college, 0 = no, 1 = yes,
z6 =Percentage of the college faculty that are women, proportion (0 to 1),
z7 - z10 =Regional dummy variables, South, Midwest, Northeast, West.

Table F17.2 Table F17.2: Fair, Redbook Survey on Extramarital Affairs, 6,366 Observations.
Source: Fair (1978). Data provided by the author.

id =Identification number,
C =Constant, value = 1,
yrb=Constructed measure of time spent in extramarital affairs,
v1 =Rating of the marriage, coded 1 to 4,
v2 =Age, in years, aggregated,
v3 =Number of years married,
v4=Number of children, top coded at 5,
v5=Religiosity, 1 to 4, 1 = not, 4 = very,
v6=Education, coded 9, 12, 14, 16, 17, 20,
v7=Occupation,
v8=Husband’s occupation.

Table F18.1 F18.1 Fair’s (1977) Extramarital Affairs Data, 601 Cross Section observations.
Source: Fair (1977) and http://fairmodel.econ.yale.edu/rayfair/pdf/1978ADAT.ZIP.
Several variables not used are denoted X1, ..., X5.)

y = Number of affairs in the past year,
z1 = Sex,
z2 = Age,
z3 = Number of years married,
z4 = Children,
z5 = Religiousness,
z6 = Education,
z7 = Occupation,
z8 = Self rating of marriage.

Table F18.2 Table F18.2: Data Used to Study Travel Mode Choice, 840 Observations On 4 Modes For 210 Individuals.
Source: Greene and Hensher (1997).

Mode = choice; Air, Train, Bus, or Car,
Ttme = terminal waiting time, 0 for car
Invc = in vehicle cost - cost component,
Invt = travel time, in vehicle,
GC = generalized cost measure,
Hinc = household income,
Psize = party size in mode chosen.

Table F18.3 Table F18.3: Ship Accidents, 40 Observations On 5 Types In 4 Vintages And 2 Service Periods
Source: McCullagh and Nelder (1983).

Type = Ship type,
TA, TB, TC, TD, TE = Type indicators,
Y6064, Y6569, Y7074, Y7579 = Year constructed indicators,
O6064, O7579 = Years operated indicators,
Months = Measure of service amount,
Acc = Accidents.

Table F19.2 Table F19.2: Strike Duration Data, 63 Observations In 9 years, 1968-1976
Source: Kennan (1985).

Year = Date,
T = Strike duration in days.
Prod = Unanticipated output,

Table F19.3 Table F19.3: LaLonde (1986) Earnings Data, 2,490 Control Observations and 185 Treatment Observations
Source: LaLonde (1986). The data are no longer available at the NBER source posted by Erdehejia.

t =Treatment dummy variable,
age =Age in years,
educ =Education in years,
marr =Dummy variable for married,
black =Dummy variable for black,
hisp =Dummy variable for Hispanic,
nodegree=Dummy for no degree (not used),
re74 =Real earnings in 1974, scaled by 10,000,
re75 =Real earnings in 1975, scaled by 10,000,
re78 =Real earnings in 1978, scaled by 10,000,
age2 =Age squared,
educ2 =Educ squared,
re742 =Re74 squared
re752 =Re75 squared
blacku74=Black times 1(re74 = 0).

Table F20.1 Table F20.1: Bollerslev and Ghysels Exchange Rate Data, 1974 Daily Observations,
Source Bollerslev (1986).

Y = Nominal return on Mark/Pound exchange rate, daily

Table F21.1 Table F21.1: Money, Output, And Price Deflator Data, 136 Quarterly Observations, 1950-1983.
Source: National Income and Product Accounts, U.S. Department of Commerce, Bureau of Economic Analysis,
Survey of Current Business: Business Statistics,

Y = Nominal GNP,
M1 = M1 measure of money stock,
P = Implicit price deflator for GNP

Table C.1 Table C.1 Observations on Income and Education, 20 Observations
Source: Data are artificial.

I = Observation,
Y = Income,

Table F1.1	Table F1.1: Consumption and Income, 10 Yearly Observations, 1970-1979 Source: Economic Report of the President, 1987, Council of Economic Advisors C = Consumption and Y = Disposable Income
Table F2.1	Table F2.1: Consumption and Income, 11 Yearly Observations, 1940-1950 Source: Economic Report of the President, U.S. Government Printing Office, Washington, D.C., 1983. Year = Date, X = Disposable Income, C = Consumption. W = War years dummy variable, 1 in 1942-1945, 0 other years.
Table F2.2	The U.S. Gasoline Market, 52 Yearly Observations, 1953-2004 Source: These data were compiled by Professor Chris Bell, Department of Economics, University of North Carolina, Asheville. Sources: www.bea.gov and www.bls.gov Year = Year, 1953-2004, GasExp = Total U.S. gasoline expenditure, Pop = U.S. total population in thousands GasP = Price index for gasoline, Income = Per capita disposable income, Pnc = Price index for new cars, Puc = Price index for used cars, Ppt = Price index for public transportation, Pd = Aggregate price index for consumer durables, Pn = Aggregate price index for consumer nondurables, Ps = Aggregate price index for consumer services.
Table F3.1	U.S. Investment Data, 15 Yearly Observations, 1968-1982 Source: Economic Report of the President, U.S. Government Printing Office, Washington, D.C., 1983. CPI 1967 is 79.06. The interest rate is the average yearly discount rate at the New York Federal Reserve Bank. Year = Date, GNP = Nominal GNP, Invest = Nominal Investment, CPI = Consumer price index, Interest = Interest rate.
Table F3.2	Koop and Tobias (2004) labor Market Experience Data Source: See the article for details on construction. The data file is in two parts. The first file contains the panel of 17,919 observations on the Person ID and 4 time-varying variables. The second file contains time invariant variables for the individual or the 2,178 households. Column 1 = Person id (ranging from 1–2, 178), Column 2 = Education, Column 3 = Log of hourly wage, Column 4 = Potential experience, Column 5 = Time trend. Column 1 = Time invariant ability, Column 2 = Mother’s education, Column 3 = Father’s education, Column 4 = Dummy variable for residence in a broken home, Column 5 = Number of siblings.
Table F4.2	Table F4.2: The Longley Data, 15 Yearly Observations, 1947-1962 Source: Longley, (1967). Employ = Employment (1000s), Price = GNP deflator, GNP = Nominal GNP (millions), Armed = Armed forces, Year = Date.
Table F4.4	Table F4.4: Cost Function, 158 1970 Cross Section Firm Level Observations Source: Christensen and Greene (1976). Note the file contains 35 extra observations. These are the holding companies. Christensen and Greene used only the first 123 observations. Use observations 1-123 to replicate Christensen and Greene. Id = Observation, Year = 1970 for all observations Cost = Total cost, Q = Total output, Pl = Wage rate, Sl = cost share for labor , Pk = Capital price index, Sk = Cost share for capital, Pf = Fuel price, Sf = Cost share for fuel
Table F5.1	Table F5.1: Labor Supply Data From Mroz (1987), 753 Observations Source: 1976 Panel Study of Income Dynamics, Mroz(1987). LFP = A dummy variable = 1 if woman worked in 1975, else 0 WHRS = Wife's hours of work in 1975 KL6 = Number of children less than 6 years old in household K618 = Number of children between ages 6 and 18 in household WA = Wife's age WE = Wife's educational attainment, in years WW = Wife's average hourly earnings, in 1975 dollars RPWG = Wife's wage reported at the time of the 1976 interview (not = 1975 estimated wage) HHRS = Husband's hours worked in 1975 HA = Husband's age HE = Husband's educational attainment, in years HW = Husband's wage, in 1975 dollars FAMINC = Family income, in 1975 dollars WMED = Wife's mother's educational attainment, in years WFED = Wife's father's educational attainment, in years UN = Unemployment rate in county of residence, in percentage points. CIT = Dummy variable = 1 if live in large city (SMSA), else 0 AX = Actual years of wife's previous labor market experience
Table F5.2	Table F5.2: Macroeconomics Data Set, Quarterly, 1950I to 2000IV, 204 Quarterly Observations Source: Department of Commerce, BEA website and www.economagic.com Year = Date Qtr = Quarter Realgdp = Real GDP ($bil) Realcons = Real consumption expenditures Realinvs = Real investment by private sector Realgovt = Real government expenditures Realdpi = Real disposable personal income CPI_U = Consumer price index M1 = Nominal money stock Tbilrate = Quarterly average of month end 90 day t bill rate Unemp = Unemployment rate Pop = Population, mil. interpolate of year end figures using constant growth rate per quarter Infl = Rate of inflation (first observation is missing) Realint = Ex post real interest rate = Tbilrate - Infl. (First observation missing)
Table F5.3	Table F5.3: Production Data For SIC 33: Primary Metals, 27 Statewide Observations Source and Note: Data are per establishment, labor is a measure of labor input, and capital is the gross value of plant and equipment. A scale factor used to normalize the capital figure in the original study has been omitted. Further details on construction of the data are given in Aigner, et al. (1977) and in Hildebrand and Liu (1957). Obs = Observation number Valueadd = Value added, Labor = Labor input, Capital = Capital stock.
Table F6.1	Table F6.1: Cost Data for U.S. Airlines, 90 Oservations On 6 Firms For 15 Years, 1970-1984 Source: These data are a subset of a larger data set provided to the author by Professor Moshe Kim. They were originally constructed by Christensen Associates of Madison, Wisconsin. I = Airline, T = Year, Q = Output, in revenue passenger miles, index number, C = Total cost, in $1000, PF = Fuel price, LF = Load factor, the average capacity utilization of the fleet.
Table F6.2	Table F6.2: Cost Function Data, 145 U.S. Electricity Producers, 1955 Data; Nerlove Source: Nerlove (1960) and Christensen and Greene (1976) Note: The data file contains several extra observations that are aggregates of commonly owned firms. Use only the first 145 observations for analysis. Firm = Observation, Year = 1955 for all observations Cost = Total cost, Output = Total output, Pl = Wage rate, Sl = Cost share for labor, Pk = Capital price index, Sk = Cost share for capital, Pf = Fuel price, Sf = Cost share for fuel
Table F6.3	Table F6.3: World Health Organization Data used for the analysis of efficiency in health care outcomes in the year 2000 World Health Report. The original data were provided by WHO, The World Health Organization [Evans et al. (2000) and www.who.int]. Variables marked with * were updated in Greene (2004). COMP =Composite measure of health care attainment, DALE =Disability adjusted life expectancy (other measure), YEAR =1993, . . . , 1997, TIME =1, 2, 3, 4, 5, T93, T94, T95, T96, T97 = year dummy variables, HEXP =Per capita health expenditure, HC3 =Educational attainment, SMALL =Indicator for states, provinces, etc. (These are additional observations.) SMALL > 0 implies internal political unit, = 0 implies country observation, COUNTRY=Number assigned to country, GROUPTI =Number of observations whenSMALL=0. Usually 5, some=1, one country=4, OECD =Dummy variable for OECD country (30 countries), GINI =Gini coefficient for income inequality, GEFF =World bank measure of government effectiveness,* VOICE =World bank measure of democratization of the political process,* TROPICS =Dummy variable for tropical location, POPDEN =Population density,* PUBTHE =Proportion of health expenditure paid by bublic authorities, GDPC =Normalized per capita GDP.
Table F6.4	Table F6.4: Solow’s Technological Change Data, 41 Yearly Observations, 1909-1949 Source: Solow (1957, p. 314). Several Variables are omitted. year = Date, Q = Output, K = Capital/labor ratio, A = Index of technology.
Table F7.1	Table F7.1: German Health Care Data, Unbalanced Panel, 7,293 Individuals, 27,326 Observations Source: Riphahn, Wambach, Million (2003) ID =Person - identification number, FEMALE =Female = 1; male = 0, YEAR =Calendar year of the observation, AGE =Age in years, HSAT =Health satisfaction, coded 0 (low)–10 (high), NEWHSAT =Health satisfaction, 0, . . . , 10; see note below, HANDDUM=Handicapped = 1; otherwise = 0, HANDPER =Degree of handicap in percent (0–100), HHNINC =Household nominal monthly net income in German marks/10,000, HHKIDS =Children under age 16 in the household = 1; otherwise = 0, EDUC =Years of schooling, MARRIED =Married = 1; otherwise = 0, HAUPTS =Highest schooling degree is Hauptschul degree = 1; otherwise = 0, REALS =Highest schooling degree is Realschul degree = 1; otherwise = 0, FACHHS =Highest schooling degree is Polytechnical degree = 1; otherwise = 0, ABITUR =Highest schooling degree is Abitur = 1; otherwise = 0, UNIV =Highest schooling degree is university degree = 1; otherwise = 0, WORKING=Employed = 1; otherwise = 0, BLUEC =Blue-collar employee = 1; otherwise = 0, WHITEC =White-collar employee = 1; otherwise = 0, SELF =Self-employed = 1; otherwise = 0, BEAMT =Civil servant = 1; otherwise = 0, DOCVIS =Number of doctor visits in last three months, HOSPVIS =Number of hospital visits in last calendar year, PUBLIC =Insured in public health insurance = 1; otherwise = 0, ADDON =Insured by add-on insurance = 1; otherwise = 0, NUMOBS = Number of observations for this person. Repeated in each row of data (added to data set). NEWHSAT = HSAT; 40 observations on HSAT recorded between 6 and 7 were changed to 7 (added to data set).
Table F7.2	Table F7.2: Statewide Data on Transportation Equipment Manufacturing, 25 Observations Source: A Zellner and N. Revankar (1970, p. 249). Note: “Value added,” “Capital,” and “Labor” are in millions of 1957 dollars. Data used for regression examples are per establishment. Raw data are used for the stochastic frontier application in Chapter 16. State = Observation, ValueAdd = output, Capita = capital input, Labor = labor input, Nfirm = number of firms.
Table F7.3	Table F7.3: Expenditure and Default Data, 1319 observations Source: Greene (1992) Cardhldr = Dummy variable, 1 if application for credit card accepted, 0 if not Majordrg = Number of major derogatory reports Age = Age n years plus twelfths of a year Income = Yearly income (divided by 10,000) Exp_Inc = Ratio of monthly credit card expenditure to yearly income Avgexp = Average monthly credit card expenditure Ownrent = 1 if owns their home, 0 if rent Selfempl = 1 if self employed, 0 if not. Depndt = 1 + number of dependents Inc_per = Income divided by number of dependents Cur_add = months living at current address Major = number of major credit cards held Active = number of active credit accounts
Table F8.1	Table F8.1: Cornwell and Rupert, Labor Market Data, 595 Individuals, 7 years Source: Cornwell and Rupert (1988) EXP =Work experience, WKS =Weeks worked, OCC =Occupation, 1 if blue collar, IND =1 if manufacturing industry, SOUTH =1 if resides in south, SMSA =1 if resides in a city (SMSA), MS =1 if married, FEM =1 if female, UNION =1 if wage set by union contract, ED =Years of education, BLK =1 if individual is black, LWAGE=Log of wage.
Table F9.1	Table F9.1: Income and Expenditure Data. 100 Cross Section Observations Source: Greene (1992) MDR = Number of derogatory reports Acc = Credit card application accepted (1=yes), Age = Age in years+ 12ths of a year, Income = Income, divided by 10,000 , Avgexp = Avg. monthly credit card expenditure, Ownrent = OwnRent, individual owns (1) or rents (0) home. Selfempl = Self employed (1=yes, 0=no)
Table F9.2	Table F9.2: Baltagi and Griffin OECD gasoline consumption data. 18 OECD countries, 19 years. Source: Baltagi (2005) COUNTRY =Name of country, YEAR =Year, 1960–1978, LGASPCAR=Log of consumption per car, LINCOMEP=Log of per capita income, LRPMG =Log of real price of gasoline, LCARPCAP =Log of per capita number of cars.
Table F10.1	Table F10.1: Munnell Productivity Data, 48 Continental U.S. States, 17 years,1970–1986 Source: Baltagi (2005), Munnell (1990) STATE = State name, ST ABB=State abbreviation, YR =Year, 1970, . . . ,1986, PCAP =Public capital, HWY =Highway capital, WATER =Water utility capital, UTIL =Utility capital, PC =Private capital, GSP =Gross state product, EMP =Employment,
Table F10.2	Table F10.2: Manufacturing Costs, U.S. Economy, 25 Yearly Observations, 1947-1971 Source: Berndt and Wood (1975) Year = Date, Cost = Cost index, K = Capital cost share, L = Labor cost share, E = Energy cost share, M = Materials cost share, Pk = Capital price, Pl = Labor price, Pe = Energy price, Pm = materials price.
Table F10.3	Table F10.3: Klein’s Model I , 22 Yearly Observations, 1920-1941 Source: Klein (1950). Year = Date, C = Consumption, P = Corporate profits, Wp = Private wage bill, I = Investment, K1 = previous year’s capital stock, X = GNP, Wg = Government wage bill, G = Government spending, T = Taxes.
Table F10.4	Table F10.4: Grunfeld Investment Data, 100 Yearly Observations On 10 Firms For 1935-1954 Sources: Moody’s Industrial Manual, Survey of Current Business I = Gross investment, from Moody’s Industrial Manual and annual reports of corporations; F = Value of the firm from Bank and Quotation Record and Moody’s Industrial Manual; C = Stock of plant and equipment, from Survey of Current Business.
Table F13.1	Table 13.1: Dahlberg and Johanssen - Municipal Expenditure Data, Data From 265 Municipalities for 9 Years, 1979-1987, 2385 Observations Source: Dahlberg and Johanssen (2000), Journal of Applied Econometrics data archive. ID = Identification Year = Date Expend = Expenditure Revenue = Revenue from taxes and fees Grants = Grants from Central Government
Table F14.1	Table F14.1: Program Effectiveness, 32 Cross Section Observations Source: Spector and Mazzeo (1980). Obs = observation, TUCE = Test score on economics test, PSI = participation in program, GRADE = Grade increase (1) or decrease (0) indicator
Table F15.1	Table F15.1: Bertschek and Lechner Binary Choice Data, Yearly Data 1993-1998 on 1,270 Firms Source: Bertcshek and Lechner (1998) Note: These data are proprietary. They are not listed on the website. yit = 1 if firm i realized a product innovation in year t and 0 if not. xit1 =constant term, xit2 = log of sales, xit3 = relative size = ratio of employment in business unit to employment in the industry, xit4 = ratio of industry imports to (industry sales + imports), xit5 = ratio of industry foreign direct investment to (industry sales + imports), xit6 = productivity = ratio of industry value added to industry employment, xit7 = dummy variable indicating firm is in the raw materials sector, xit8 = dummy variable indicating firm is in the investment goods sector.
Table F17.1	Table F17.1: Burnett Analysis of Liberal Arts College Gender Economics Courses, 132 Observations Source: Data provided by the author; Burnett (1997). y1 =Presence of a gender economics course (0/1), y2 =Presence of a women’s studies program on the campus (0/1), z2 =Academic reputation of the college, coded 1 (best), 2, . . . to 141, z3 =Size of the full time economics faculty, a count, z4 =Percentage of the economics faculty that are women, proportion (0 to 1), z5 =Religious affiliation of the college, 0 = no, 1 = yes, z6 =Percentage of the college faculty that are women, proportion (0 to 1), z7 - z10 =Regional dummy variables, South, Midwest, Northeast, West.
Table F17.2	Table F17.2: Fair, Redbook Survey on Extramarital Affairs, 6,366 Observations. Source: Fair (1978). Data provided by the author. id =Identification number, C =Constant, value = 1, yrb=Constructed measure of time spent in extramarital affairs, v1 =Rating of the marriage, coded 1 to 4, v2 =Age, in years, aggregated, v3 =Number of years married, v4=Number of children, top coded at 5, v5=Religiosity, 1 to 4, 1 = not, 4 = very, v6=Education, coded 9, 12, 14, 16, 17, 20, v7=Occupation, v8=Husband’s occupation.
Table F18.1	F18.1 Fair’s (1977) Extramarital Affairs Data, 601 Cross Section observations. Source: Fair (1977) and http://fairmodel.econ.yale.edu/rayfair/pdf/1978ADAT.ZIP. Several variables not used are denoted X1, ..., X5.) y = Number of affairs in the past year, z1 = Sex, z2 = Age, z3 = Number of years married, z4 = Children, z5 = Religiousness, z6 = Education, z7 = Occupation, z8 = Self rating of marriage.
Table F18.2	Table F18.2: Data Used to Study Travel Mode Choice, 840 Observations On 4 Modes For 210 Individuals. Source: Greene and Hensher (1997). Mode = choice; Air, Train, Bus, or Car, Ttme = terminal waiting time, 0 for car Invc = in vehicle cost - cost component, Invt = travel time, in vehicle, GC = generalized cost measure, Hinc = household income, Psize = party size in mode chosen.
Table F18.3	Table F18.3: Ship Accidents, 40 Observations On 5 Types In 4 Vintages And 2 Service Periods Source: McCullagh and Nelder (1983). Type = Ship type, TA, TB, TC, TD, TE = Type indicators, Y6064, Y6569, Y7074, Y7579 = Year constructed indicators, O6064, O7579 = Years operated indicators, Months = Measure of service amount, Acc = Accidents.
Table F19.2	Table F19.2: Strike Duration Data, 63 Observations In 9 years, 1968-1976 Source: Kennan (1985). Year = Date, T = Strike duration in days. Prod = Unanticipated output,
Table F19.3	Table F19.3: LaLonde (1986) Earnings Data, 2,490 Control Observations and 185 Treatment Observations Source: LaLonde (1986). The data are no longer available at the NBER source posted by Erdehejia. t =Treatment dummy variable, age =Age in years, educ =Education in years, marr =Dummy variable for married, black =Dummy variable for black, hisp =Dummy variable for Hispanic, nodegree=Dummy for no degree (not used), re74 =Real earnings in 1974, scaled by 10,000, re75 =Real earnings in 1975, scaled by 10,000, re78 =Real earnings in 1978, scaled by 10,000, age2 =Age squared, educ2 =Educ squared, re742 =Re74 squared re752 =Re75 squared blacku74=Black times 1(re74 = 0).
Table F20.1	Table F20.1: Bollerslev and Ghysels Exchange Rate Data, 1974 Daily Observations, Source Bollerslev (1986). Y = Nominal return on Mark/Pound exchange rate, daily
Table F21.1	Table F21.1: Money, Output, And Price Deflator Data, 136 Quarterly Observations, 1950-1983. Source: National Income and Product Accounts, U.S. Department of Commerce, Bureau of Economic Analysis, Survey of Current Business: Business Statistics, Y = Nominal GNP, M1 = M1 measure of money stock, P = Implicit price deflator for GNP
Table C.1	Table C.1 Observations on Income and Education, 20 Observations Source: Data are artificial. I = Observation, Y = Income,