Parameters, 4 linearity in, 42 stability, 273-279 Park test, 403-404, 422-423, 424 Parsimony principle, 46-47 Partial adjustment model, 673-675 combined with adaptive expectations model, 675-676 Partial autocorrelation function,

841-845 Partial correlation, 360 Partial correlation coefficients explanation, 230-231 interpretation, 231-232 Partial regression coefficients, 203 estimation of, 207-211 hypothesis testing about, 250-253 maximum likelihood estimators, 211 meaning of, 205-207 Partial slope coefficients, 205 Per capita gross national product, 213-215, 249-250 coefficients of, 244-245 Per capita personal consumption, 669 Percentage change, 176n Percent growth rate, 176n Perfect collinearity, 302, 343 Perfect multicollinearity; see

Multicollinearity Peripheral variables, 46 Permanent consumption, 46 Permanent income, 46 Permanent income hypothesis, 11,

166, 507 Personal consumption expenditures, 793-796 Personal disposable income, 793-796

PGNP; see Per capita gross national product Phillips curve, 20, 184-188 Phillips model of wages and prices, 721 Phillips-Perron unit root test, 818 Piece-wise linear regression, 317-319

Pindyck-Rubinfeld model of public spending, 755-756 Plim; see Probability limit Point estimation, 896 Point estimators, 63

with grouped data, 610-612 Poisson distribution, 895 Poisson probability distribution, 620

Poisson regression model, 561, 620-622 Polychotomous response variables, 581 Polynomial distributed lag models,

687-696 Polynomial regression, 226-229

reducing collinearity in, 369 Polytomous dependent variable, 322 Pooled data, 25, 28, 364-365, 636 Pooled regression, 275, 641 Population, 38 Population correlogram, 808 Population mean, 37n Population regression curve, 40 Population regression function, 41 estimating, 58-59 role in regression analysis, 49 stochastic specification of, 43-45

Population regression line, 40 Portfolio theory capital asset pricing model,

165-166 capital market line, 407 characteristic line, 166, 781 example, 168-169 market model, 166 Positive correlation, 70 Power curve, 909 Power function graph, 909 Power of a test, 137, 409n, 475n,

819-820, 908 Practical significance versus statistical significance, 138-139

Prais-Winsten transformation, 478,

482-483, 487 Precedence, 696 Precision, 76-79 Predetermined variables, 717n,

736-737 Prediction, 8-9; see also Forecasting Chow's prediction failure test, 543 and multicollinearity, 369-370 with multiple regression, 279 Prediction variable, 8-9 Predictive causality, 696 Pretest bias, 222n Pretesting, 516

PRF; see Population regression function Price elasticity, 20 Prices and money, 650

Principal components technique, 369 Probabilities, computing, 602-604 Probability, 870-871 Probability density function, 117,

118,872-877 Probability distribution, 121, 878-895 of an estimator, 897 f disturbances, 108 related to normal distribution, 159-161 Probability limit, 726-727 Probability statistics, 119 Probit model, 561, 608-615 and logit model, 614-615 maximum likelihood estimation,

633-635 multinomial, 623-624 ordinal, 623

for ungrouped data, 612-613 Producer price index, 312 Production function, 11

transcendental, 288 Productivity data, 97 Product operators, 869-870 Profit-cost margin function,

778-779 Progressive expectation, 670 Proportional change, 176n Proxy variable, 46, 527 Pseudo R2, 605-606 Psychological reasons for lags, 662 P test, 536

Pth autoregressive, 838 Purchasing power parity, 156-157 Pure autocorrelation, 475

correcting with generalized least squares, 477-484 versus model mis-specification, 475-476 Purely random process, 798 Pure random walk, 803 p value, 128, 137-138, 141

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