The McGraw-Hill Series Economics essentials of economics brue, McConnell, and Flynn Essentials of Economics

see
Residual sum of squares)
RSS
R
(
see
Restricted residual sum
of squares)
RSS
UR
(
see
Unrestricted residual sum
of squares)
Runs test, 431–434, 892–893
RWM (
see
Random walk model)
S
∑
(summation operator), 801
∑∑
(double summation operator), 801
Sample autocorrelation function 
(SAFC), 114, 749
Sample correlation coefficient, 77
Sample correlogram, 749
Sample covariance, 749
Sample points, 802
Sample regression function (SRF), 42–45
Sample regression line, 44
Sample size, 835
Sample space, 802
Sample variance, 749
Sampling, 27, 824
Sampling distribution, 69n, 73, 109, 509
Sargan test, 669–670
Scalar, 838
Scalar matrix, 840
Scalar multiplication, 841
Scale effect, 23
Scale factors, 154–156
Scaling, 154–157
Scatter diagram (scattergram), 16
Scatterplot, 340–341
Schwarz’s information criterion (SIC), 
488, 494
Seasonal analysis, 290–295
Seasonality, 784
Second-order autoregressive (AR(2)), 776
Second-order moving average (MA(2)), 776
Second-order stationary, 740
Security market line (SML), 148
Seemingly unrelated regression (SURE)
model, 599n, 714n, 785n
Self-selection bias, 499
Semielasticity, 163
Semilog models, 162–166
Semilogarithmic regressions, 297–298, 314
Serial correlation, 412–414
Serial correlation model, 660
Shocks, 785
Short panel, 593
Short-run multiplier, 619
SIC (
see
Schwarz’s information criterion)
Signed minor, 846
Simple correlation coefficients, 213–215
Simple hypothesis, 113, 831
Simple regression analysis (
see
Two-
variable regression analysis)
Sims test of causality, 652n
Simultaneity test, 703–705
Simultaneous equations, 874
Simultaneous-equation bias, 679–683
Simultaneous-equation methods, 711–730
estimation approaches, 711–712
bias in indirect least-squares 
estimators, 735
examples, 724–729
indirect least squares, 715–718
recursive models and OLS, 712–714
standard errors of 2SLS estimators, 736
two-stage least squares, 718–724
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920
Subject Index
Simultaneous-equation models, 673–684
examples of, 674–679
nature of, 673–674
Simultaneous-equation regression 
models, 774
Single exponential smoothing, 774
Single-equation methods, 712
Single-equation model, 3
Single-equation regression models, 13, 774
Singular matrix, 844
Size:
of the statistical test, 108n
of unit root tests, 759
Size effect, 23
Skewness, 131, 132, 368, 815, 816
Slope, 3, 37
Slope drifter (
see
Differential slope
coefficients)
Slutsky property, 830
Small-sample properties, 826–828
SML (security market line), 148
Social Security Administration, 901
Spatial autocorrelation, 412
Spearman’s rank correlation coefficient, 86
Spearman’s rank correlation test, 380–382
Specification bias, 64
assumption regarding, 189, 367
excluded variable, 414–415
incorrect function form, 416
and multicollinearity, 344
in multiple regression, 200–201
Specification error, 64, 150
Spline functions, 296
Spurious correlation, 395
Spurious regression, 737, 747–748
Square matrix, 839, 847
Square root transformation, 393
SRF (
see
Sample regression function)
SRM (
see
Switching regression models)
St. Louis revised model, 728–729
Stability condition, 755n
Standard deviation, 810
Standard error(s):
defined, 69n
of estimate, 70
of least-squares estimates, 69–71
of least-squares estimators, 93
of OLS estimators, 194–195
of regression, 70
in 2SLS estimators, 736
Standard linear regression model 
(
see
Classical linear regression model)
Standard normal distribution, 100
Standardized normal distribution, 878
Standardized normal variable, 817
Standardized residuals, 430, 431
Standardized variables, 157–159, 183–184,
199–200
STATA, 898, 899
Statement of theory or hypothesis, 3
Stationarity, 22
Stationarity, tests of, 748–754
autocorrelation function/correlogram,
749–753
graphical analysis, 749
statistical significance of autocorrelation
coefficients, 753–754
Stationary stochastic processes, 740–741
Stationary time series, 737
Statistic (term), 44, 823
Statistical independence, 806–808
Statistical inference, 8
Statistical properties, 59, 69
Statistical relationships, 19, 20
Statistical Resources on the
Web/Economics, 901
Statistical significance:
of autocorrelation coefficients, 753–754
practical vs., 123–124
Statistical tables, 878–893
areas under standardized normal
distribution, 878
critical values of runs in runs test,
892–893
Durbin–Watson 
d
statistic, 888–891
1% and 5% critical Dickey–Fuller 
t
and
F
values for unit root tests, 893
percentage points of 
t
distribution, 879
upper percentage points of 
χ
2
distribution, 886–887
upper percentage points of 
F
distribution, 880–885
Statistically significant, 114
STAT-USA databases, 901
Steepest descent method, 529
Stepwise backward regression, 354
Stepwise forward regression, 354
Stochastic (term), 19n, 21
Stochastic disturbance, 40–42
Stochastic error term, 40, 174–175,
486–487
Stochastic explanatory variables, 510–511
Stochastic PRF, 48
Stochastic processes, 740–744
integrated, 746–747
nonstationary, 741–744
stationary, 740–741
trend stationary/difference stationary,
745–746
unit-root, 744
Stochastic regressor model, 63, 316–317
Stochastic time series, 745
Stochastic trend, 742, 745
Stock adjustment model, 632
Strictly exogenous regressors, 468
Strictly exogenous variables, 594, 602
Strictly white noise, 741n
Structural breaks, 758
Structural changes, testing for, 254–259,
758–759
Structural coefficients, 690
Structural equations, 690
Studentized residuals, 430n
Student’s 
t
distribution, 820
Student’s 
t
test, 755
Submatrix, 839
Subtraction, matrix, 841
Summation operator (

), 801
SURE model (
see
Seemingly unrelated
regression model)
Survival analysis, 580
Switching regression models (SRM), 
296n, 300
Symmetric matrix, 840
Symmetric variance–covariance 
matrix, 853
Systematic component, 40
T
T
(subscript), 21
T
(total number of observations), 21
T
distribution, 879
T
ratios, 330, 331, 337
τ
(tau) statistic, 755–757
T
test, 115–118, 249
Target variable, 9
Taylor’s series expansion, 530, 538
Taylor’s theorem, 537–538
Technology, 622
“Ten Commandments of Applied
Econometrics” (Peter Kennedy),
511
Test of significance, 115–119, 836–837
ANOVA in matrix notation, 860–861
χ
2
test, 118–119
confidence interval vs., 124
overall (
see
Overall significance testing)
t
test, 115–118
Test statistic, 115, 831
Tests of non-nested hypotheses, 488–492
Davidson–MacKinnon 
J
test, 490–492
discerning approach, 488–492
discrimination approach, 488
non-nested 
F
test, 488–489
Tests of specification errors, 474–482
Texas economy application, 789–790
TGARCH (threshold GARCH), 799
Theoretical econometrics, 10, 11
Theoretical probability distributions:
Bernoulli binomial distribution, 822
binomial distribution, 822–823
chi-square distribution, 819–820
F
distribution, 821–822
normal distribution, 816–819
Poisson distribution, 823
Student’s 
t
distribution, 820
Three-variable regression model:
adjusted 
R
2
, 201–207
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Subject Index
921
Cobb–Douglas production function,
207–209
estimation of partial regression
coefficients, 192–198
example, 198–200
interpretation of regression equation, 191
multiple coefficient of correlation, 198
multiple coefficient of determination,
196–197
notation/assumptions, 188–190