MARC Record from marc_nuls

LEADER: 04125cam 22003614a 4500
001 9922521390001661
005 20161129162342.0
008 991116s2000 enka b 001 0 eng
010 $a 99058736
015 $aGB99-U5692
019 $a43032065
020 $a0471999156 (alk. paper)
029 1 $aUKM$bb99U5692
035 $a(CSdNU)u101859-01national_inst
035 $a(OCoLC)42861788
035 $a(Sirsi) 01-AAM-7519
040 $aDLC$cDLC$dUKM$dMUQ$dOrPss
042 $apcc
049 $aCNUM
050 00 $aHB141$b.K644 2000
100 1 $aKoop, Gary.
245 10 $aAnalysis of economic data /$cby Gary Koop.
260 $aChichester ;$aNew York :$bJohn Wiley,$cc2000.
300 $axii, 226 p. :$bill. ;$c24 cm. +$e1 computer disk (3 1/2 in.)
504 $aIncludes bibliographical references and index.
505 0 $aOrganization of the book -- Useful background -- Basic data handling -- Types of economic data -- Obtaining data -- Working with data: graphical methods -- Working with data: descriptive statistics -- Advanced descriptive statistics -- Correlation -- Understanding correlation -- Understanding correlation through verbal reasoning -- Understanding why variables are correlated -- Understanding correlation through XY-plots -- Correlation between several variables -- Mathematical details -- An introduction to simple regression -- Regression as a best fitting line -- Interpreting OLS estimates -- Fitted values and R[superscript 2]: measuring the fit of a regression model -- Nonlinearity in regression -- Mathematical details -- Statistical aspects of regression -- Which factors affect the accuracy of the estimate [beta]? -- Calculating a confidence interval for [beta] -- Testing whether [beta] = 0 -- Hypothesis testing involving R[superscript 2]: the F-statistic -- Using statistical tables for testing whether [beta] = 0 -- Multiple regression -- Regression as a best fitting line -- Ordinary least squares estimation of the multiple regression model -- Statistical aspects of multiple regression -- Interpreting OLS estimates -- Pitfalls of using simple regression in a multiple regression context -- Omitted variables bias -- Multicollinearity -- Mathematical interpretation of regression coefficients -- Regression with dummy variables -- Simple regression with a dummy variable -- Multiple regression with dummy variables -- Multiple regression both dummy and non-dummy explanatory variables -- Interacting dummy and non-dummy variables -- What if the dependent variable is a dummy? -- Regression with time lags: distributed lag models -- Aside on lagged variables -- Aside on notation -- Selection of lag order -- Other distributed lag models -- Univariate time series analysis -- The autocorrelation function -- The autoregressive model for univariate time series -- Nonstationary versus stationary time series -- Extensions of the AR(1) model -- Testing in the AR(p) with deterministic trend model -- Mathematical intuition for the AR(1) model -- Regression with time series variables -- Time series regression when X and Y are stationary -- Time series regression when Y and X have unit roots: spurious regression -- Time series regression when Y and X have unit roots: cointegration -- Time series regression when Y and X are cointegrated: the error correction model -- Time series regression when Y and X have unit roots but are not cointegrated -- Applications of time series methods in macroeconomics and finance -- Volatility in asset prices -- Granger causality -- Vector autoregressions -- Hypothesis tests involving more than one coefficient -- Limitations and extensions -- Problems that occur when the dependent variable has particular forms -- Problems that occur when the errors have particular forms -- Problems that call for the use of multiple equation models.
650 0 $aEconometrics.
650 6 $aEconometrie.
948 $a03/25/2002$b04/16/2002
982 $aHB141$a.K644$a2000
983 $a31786101644760
994 $a92$bCNU
999 $aHB141 .K644 2000$wLC$c1$i31786101644760$d3/4/2004$f3/4/2004$g1 $lCIRCSTACKS$mNULS$rY$sY$tBOOK$u4/16/2002