R

R2; see Coefficient of determination Ramsey's RESET test, 521-523 Random effects model, 647-649 compared to fixed effects model, 650-651 Random interval, 120, 121 Random parameters, 322 Random regressors, 337 Random shocks, 799 Random stochastic process, 796 Random variables, 5, 22, 25, 107,

871-872 Random walk with drift, 800-801 without drift, 799-800 pure, 803 Random walk model, 798-801

formula, 802 Random walk phenomenon, 79-793

Rank condition of identification,

750-753 Rank of a matrix, 922 Rate event data, 582 Rate of decline (or decay), 665 Rational expectations hypothesis, 672 Rational expectations schools, 562 Ratio scale, 30-31, 297 Ratio transformation, 367 Raw sum of squares, 167-168 R&D expenditures, 423-426 Real Gross national product, 99 Real rate of interest, 684-685 Real-time quote, 26 Reciprocal models, 183-190 Recursive least squares, 542-543 Recursive models, 764-767 Recursive residuals, 543 Reduced-form coefficients, 737-738

Reduced-form equations, 737-738

Reference category, 302 Reference hypothesis, 531 Region of acceptance, 129-130 Region of rejection, 130 Regressand, 580-582 Regression auxiliary, 361 versus causation, 22-23 coincident, 306 cointegrating, 822 concurrent, 307 versus correlation, 23-24 cross-section, 291-292 data matrix, 325 dissimilar, 307 historical, 142 law of, 17-18 linear, 42 origin of term, 17 parallel, 306

piece-wise linear, 317-319 polynomial, 369 pooled, 275

seemingly unrelated, 849n semilogarithmic, 320 spurious, 792, 806-807 standard error of, 78-79 standardized variables, 173-175 stepwise, 378 time-series, 291-292 unconstrained, 267 unrestricted, 267 Regression analysis, 7, 17-31;

see also Multiple regression analysis; Three-variable model; Two-variable model and analysis of variance,

140-142 conditional, 66-67 correctly specified, 73-75 data for, 25-30 definition, 18

evaluating results of, 146-150 evaluating results of normality tests, 147-149 hypothesis testing in, 107 measurement of scale variables, 30-31

modern interpretation, 18-21 origin of term, 17 primary objective in, 49 problem of prediction individual prediction, 142 mean prediction, 142-144 reporting results of, 145-146 software programs, 13

statistical versus deterministic relationships, 22 terminology and notation, 24-25

Regression coefficients, 41 confidence intervals, 121-126 partial, 203 estimators, 207-211 hypothesis testing about,

250-253 maximum likelihood estimation, 211 meaning of, 205-207 testing equality of, 264-266 Regression curve, population, 40 Regression fishing, 515-516 Regression line, 7-8 definition, 19 goodness of fit, 81-87 population, 40 sample, 48-49 Regression models; see also

Classical linear regression model analysis of variance, 304-306 ANOVA models, 298-301 constant elasticity model, 177 disequilibrium, 322, 323 distributed lag, 656 dummy variables, 297-323 dynamic, 448

effect of unit change in value of regressor, 613-614 Engel expenditure model,

182-183 exponential, 175-176, 565-566 functional forms, 175-191 choosing, 190-191 log-linear model, 175-178 reciprocal models, 183-190 semilog models, 178-183 in-parameter, 192 intrinsically linear/ nonlinear, 192 limited dependent variable, 616 linear/nonlinear, 5, 41, 42,

562-565 MWD test, 280-282 panel data, 320, 636-652 Poisson regression model, 620-622 polynomial, 226-229 with qualitative/quantitative regressors, 304-306 single-equation, 15, 836 switching, 318, 322-323

Was this article helpful?

0 0
Rules Of The Rich And Wealthy

Rules Of The Rich And Wealthy

Learning About The Rules Of The Rich And Wealthy Can Have Amazing Benefits For Your Life And Success. Discover the hidden rules and beat the rich at their own game. The general population has a love / hate kinship with riches. They resent those who have it, but spend their total lives attempting to get it for themselves. The reason an immense majority of individuals never accumulate a substantial savings is because they don't comprehend the nature of money or how it works.

Get My Free Ebook


Post a comment