Econometric Analysis, 7^th and 8^th Editions

Links to Data Tables

Table F1.1 (csv format)	Table F1.1: Consumption and Income, 10 Yearly Observations, 2000-2009 Source: Economic Report of the President, 2015, Council of Economic Advisors C = Consumption and Y = Disposable Income
Table F2.1 (csv format)	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 (csv format)	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 (csv format)	U.S. Investment Data, 15 Yearly Observations, 2000-2014 Source: Economic Report of the President, U.S. Government Printing Office, Washington, D.C., 2016. The interest rate is the "prime rate." Year = Date, RealGNP = GNP Quantity Index, Invest = Nominal Investment in $T, GNPDefl = GNP Deflator, Interest = Interest rate = Prime rate. Infl = Yearly change in consumer price index. RealInv = Nominal investment/(.01*GNP Deflator)
Table F3.2 (JAE Archive)	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 to 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 F4.1 (csv format)	Table F4.2: Data on Sales of Monet Paintings (430 observations) Source: Author. Price = Sale Price in $ (million), Height = Height (inches), Width = Width (inches), Signed = Dummy variable = 1 if signed, 0 if not, Picture = ID number (identifies repeat sales), House = Code for auction house where sale took place.
Table F4.2 (csv format)	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 F4.3 (csv format)	Table F4.: Movie Buzz Data (62 Observations) Source: Author. Box = First run U.S. box office ($), MPRating = MPAA Rating code, 1=G, 2=PG, 3=PG13, 4=R, Budget = Production budget ($Mil), Starpowr = Index of star poser, Sequel = 1 if movie is a sequel, 0 if not, Action = 1 if action film, 0 if not, Comedy = 1 if comedy film, 0 if not, Animated = 1 if animated film, 0 if not, Horror = 1 if horror film, 0 if not, Addict = Trailer views at traileraddict.com, Cmngsoon = Message board comments at comingsoon.net, Fandango = Attention at fandango.com (see Example 4.12), Cntwait3 = Percentage of Fandango votes that can't wait to see.
Table F4.4 (csv format)	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 F4.5 (csv format)	Table F4.5: Filipelli Test Data (NIST) Source: National Institute of Standards and Technology (NIST), (www.itl.nist.gov/div898/strd/lls/data/Filip.shtml). Y = LHS variable, X = RHS variable, x^j, j=0,...,10 = regressors.
Table F5.1 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 F6.5 (csv format)	Table F6.5: Yearly Data on Baseball Attendance Source: Author Attendance and wins for 31 teams, unbalanced panel, 468 observations. Team = ID, 1,...,31, YearID = Year, Attend = Attendance, Wins = Number of games won. AvgSalry = Average salary of active players. AllStars = Number of AllStars on team. Ti = Number of years team is observed in data set.
Table F7.1 (JAE Archive)	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) to 10 (high), NEWHSAT =Health satisfaction, 0, . . . , 10; see note below, HANDDUM=Handicapped = 1; otherwise = 0, HANDPER =Degree of handicap in percent (0 to 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 (csv format)	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 (csv format)	Table F7.3: Expenditure and Default Data, 13,444 observations Source: Greene (1992) Cardhldr = Dummy variable, 1 if application for credit card accepted, 0 if not Default = 1 if defaulted 0 if not (observed when Cardhldr = 1, 10,499 observations), Age = Age in years plus twelfths of a year, Adepcnt = 1 + number of dependents, Acadmos = months living at current address, Majordrg = Number of major derogatory reports, Minordrg = Number of minor derogatory reports, Ownrent = 1 if owns their home, 0 if rent Income = Monthly income (divided by 10,000), Selfempl = 1 if self employed, 0 if not, Inc_per = Income divided by number of dependents, Exp_Inc = Ratio of monthly credit card expenditure to yearly income, Spending = Average monthly credit card expenditure (for Cardhldr = 1), Logspend = Log of spending.
Table F8.1 (csv format)	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 (csv format)	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 (Download from website)	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 to 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 (Download from website)	Table F10.1: Munnell Productivity Data, 48 Continental U.S. States, 17 years,1970 to 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 (csv format)	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 (csv format)	Table F10.3: Klein’s Model I , 22 Yearly Observations, 1920 to 1941 Source: Klein (1950). Year = Date, C = Consumption, P = Corporate profits, Wp = Private wage bill, I = Investment, K1 = previous year capital stock, X = GNP, Wg = Government wage bill, G = Government spending, T = Taxes.
Table F10.4 (csv format)	Table F10.4: Grunfeld Investment Data, 200 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 (csv format)	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 (csv format)	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 F14.2 (csv format)	Table F14.2: Spanish Dairy Farm Production Data Balanced Panel 247 farms, 6 years (1993-1998), 1482 Observations Source: Author, Antonio Alvarez, Luis Arias Farm = observation, 1-247, Year = Year, 93-98, Cows = number of cows, Land = Amount of land in hectares Milk = Output in liters Labor = Number of workers Feed = Amount of feed used Yit = Log of output X1 - X4 = Logs of inputs, in deviations of logs from sample mean of logs X11,X12,... = Translog terms, unique squares and cross products Year93,... = Year dummy variables, 1993-1998 TI = Number of observations for farm = 6
Table F15.1 (Proprietary)	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 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 F18.4 (csv format)	Table F18.4: Choice Data on Stated Choice Experiment for California Utilities. 361 individuals, unbalanced panel data, 8 to 12 choice situations (most are 12), 4 alternatives in each choice task. Total 17,232 observations. Source: Professor Kenneth Train (Revelt and Train (2000)). Person = Individual identifier, Ntask = Number of choice tasks, 8, 9, 10, 11, or 12, Nrec = 4 times Ntask = number of data rows for person, Choice = Choice indicator, 0/1, Price = price of plan, 7, 9, or 0 if TOD or SEAS = Price per kwh of service, Cntl = Contract length in years, 5, 1 or 0 if no long term contract. Local = Utility is familiar local firm, 1/0. Known = Utility is familiar but not local utility 1/0. TOD = Rate offer has time of day variation, 1/0. SEAS = Rate offer has seasonal variation, 1/0.
Table F19.1 (csv format)	Table F19.1: Panel Data on Costs for Swiss Railroads, 50 firms, 605 observations, unbalanced panel Source: Filippini, Farsi, Greene . Railroad = Id number, 1 to 50, Year = Year of observation, Ni = Number of years observed, repeated, Stops = Number of stops in network, Network = Number of KM of track, Rack = Feature of railroad, Narrow_t = Dummy variable for railroads with narrow track, Virage = 1 for railroads with curvy tracks, T = Time indicator, first year = 0, QP = Passenger output, passenger kilometers, QF = Freight, ton kilometers, CT = Total cost (1,000 Swiss franc), PL = Labor price, PK = Capital price, PE = Electricity price, Lnct = Log of CT/PE, Lnqp = Log of QP, Lnqf = Log of QF, Lnpk = Log of PK/PE, Lnpl = Log of PL/PE.
Table F19.2 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	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 (csv format)	Table C.1 Observations on Income and Education, 20 Observations Source: Data are artificial. I = Observation, Y = Income,