Карта сайта Мастерской Своего Дела
- 07-2015 Conclusions and Extensions
- 07-2015 Applications of Test Principles to Econometrics
- 07-2015 Models and Their Specification
- 07-2015 Springer Texts in Business and Economics
- 07-2015 What Is Econometrics?
- 07-2015 A Brief History
- 07-2015 Critiques of Econometrics
- 07-2015 Looking Ahead
- 07-2015 Basic Statistical Concepts
- 07-2015 Methods of Estimation
- 07-2015 Properties of Estimators
- 07-2015 Hypothesis Testing
- 07-2015 Likelihood Ratio, Wald and Lagrange Multiplier Tests
- 07-2015 Confidence Intervals
- 07-2015 Descriptive Statistics
- 07-2015 Simple Linear Regression
- 07-2015 Least Squares Estimation and the Classical Assumptions
- 07-2015 Statistical Properties of Least Squares
- 07-2015 Estimation of a2
- 07-2015 Maximum Likelihood Estimation
- 07-2015 A Measure of Fit
- 07-2015 Prediction
- 07-2015 Residual Analysis
- 07-2015 Numerical Example
- 07-2015 Empirical Example
- 07-2015 Multiple Regression Analysis
- 07-2015 Least Squares Estimation
- 07-2015 Residual Interpretation of Multiple Regression Estimates
- 07-2015 Overspecification and Underspecification of the Regression Equation
- 07-2015 R-Squared Versus R-Bar-Squared
- 07-2015 Testing Linear Restrictions
- 07-2015 Dummy Variables
- 07-2015 Violations of the Classical Assumptions
- 07-2015 Stochastic Explanatory Variables
- 07-2015 Normality of the Disturbances
- 07-2015 Heteroskedasticity
- 07-2015 Autocorrelation
- 07-2015 Distributed Lags and Dynamic Models
- 07-2015 Infinite Distributed Lag
- 07-2015 Estimation and Testing of Dynamic Models with Serial Correlation
- 07-2015 A Lagged Dependent Variable Model with AR(1) Disturbances
- 07-2015 Autoregressive Distributed Lag
- 07-2015 The General Linear Model: The Basics
- 07-2015 Partitioned Regression and the Frisch-Waugh-Lovell Theorem
- 07-2015 Confidence Intervals and Test of Hypotheses
- 07-2015 Joint Confidence Intervals and Test of Hypotheses
- 07-2015 Restricted MLE and Restricted Least Squares
- 07-2015 Some Useful Matrix Properties
- 07-2015 Regression Diagnostics and Specification Tests
- 07-2015 Recursive Residuals
- 07-2015 Applications of Recursive Residuals
- 07-2015 Specification Tests
- 07-2015 Testing Linear Versus Log-Linear Functional Form
- 07-2015 Generalized Least Squares
- 07-2015 Special Forms
- 07-2015 Test of Hypotheses
- 07-2015 Prediction
- 07-2015 The W, LR and LM Statistics Revisited
- 07-2015 Seemingly Unrelated Regressions
- 07-2015 Seemingly Unrelated Regressions with Unequal Observations
- 07-2015 Simultaneous Equations Model
- 07-2015 Simultaneous Bias
- 07-2015 The Identification Problem
- 07-2015 Single Equation Estimation: Two-Stage Least Squares
- 07-2015 Spatial Lag Dependence
- 07-2015 Test for Over-Identification Restrictions
- 07-2015 Hausman's Specification Tes
- 07-2015 Pooling Time-Series of Cross-Section Data
- 07-2015 The Error Components Model
- 07-2015 The Fixed Effects Model
- 07-2015 Maximum Likelihood Estimation
- 07-2015 Empirical Example
- 07-2015 Testing in a Pooled Model
- 07-2015 Dynamic Panel Data Models
- 07-2015 Empirical Illustration
- 07-2015 Program Evaluation and Difference-in-Differences Estimator
- 07-2015 Limited Dependent Variables
- 07-2015 Functional Form: Logit and Probit
- 07-2015 Grouped Data
- 07-2015 Individual Data: Probit and Logit
- 07-2015 The Binary Response Model Regressio
- 07-2015 Asymptotic Variances for Predictions and Marginal Effects
- 07-2015 Goodness of Fit Measures
- 07-2015 Empirical Examples
- 07-2015 Multinomial Choice Models
- 07-2015 Unordered Response Models
- 07-2015 The Censored Regression Model
- 07-2015 The Truncated Regression Model
- 07-2015 Sample Selectivity
- 07-2015 Sample Selection and Non-response
- 07-2015 Time-Series Analysis
- 07-2015 The Box and Jenkins Method
- 07-2015 Vector Autoregression
- 07-2015 Trend Stationary Versus Difference Stationary
- 07-2015 Autoregressive Conditional Heteroskedasticity
- 07-2015 Comparing Biased and Unbiased Estimators
- 07-2015 Diagnostic Tests for Linear Regression Models
- 07-2015 Ищем инвесторов в наркоцентр около Милана, Италия
- 07-2015 What is Econometrics?
- 07-2015 A Review of Some Basic Statistical Concepts
- 07-2015 Independence and Simple Correlation
- 07-2015 The Binomial Distribution
- 07-2015 The Wald, LR, and LM Inequality. This is based on Baltagi (1994). The likelihood is given by Eq. (2.1) in the text
- 07-2015 Poisson Distribution
- 07-2015 The Uniform Density
- 07-2015 The Exponential Distribution
- 07-2015 The Gamma Distribution
- 07-2015 The t-distribution with r Degrees of Freedom
- 07-2015 Moment Generating Function (MGF)
- 07-2015 Moment Generating Function Method
- 07-2015 Best Linear Prediction. This is based on Amemiya (1994)
- 07-2015 The Best Predictor
- 07-2015 Simple Linear Regression
- 07-2015 Efficiency as Correlation. This is based on Zheng (1994)
- 07-2015 Adding 5 to each observation of Xi, adds 5 to the sample average X and it
- 07-2015 Dependent Variable: LNC
- 07-2015 Theil’s minimum mean square estimator of ". " can be written as
- 07-2015 Dependent Variable: LNEN
- 07-2015 Dependent Variable: LNRGDP
- 07-2015 For parts (b) and (c), SAS will automatically compute confidence intervals for the mean (CLM option) and for a specific observation (CLI option), see the
- 07-2015 Multiple Regression Analysis
- 07-2015 Simple Versus Multiple Regression Coefficients. This is based on Baltagi (1987)
- 07-2015 . Effect of Additional Regressors on R2
- 07-2015 Violations of the Classical Assumptions
- 07-2015 Weighted Least Squares. This is based on Kmenta (1986)
- 07-2015 TheAR(1) model. From (5.26), by continuous substitution just like (5.29), one could stop at ut_s to get
- 07-2015 Regressions with Non-zero Mean Disturbances
- 07-2015 ML Estimation of Linear Regression Model with AR(1) Errors and Two
- 07-2015 The backup regressions are given below: These are performed using SAS
- 07-2015 The backup regressions are given below
- 07-2015 Using EViews, Qt+i is simply Q(1) and one can set the sample range from 1954-1976
- 07-2015 The back up regressions are given below. These are performed using SAS
- 07-2015 Distributed Lags and Dynamic Models
- 07-2015 The General Linear Model: The Basics
- 07-2015 Regression Diagnostics and Specification Tests
- 07-2015 Generalized Least Squares
- 07-2015 Seemingly Unrelated Regressions
- 07-2015 Simultaneous Equations Model
- 07-2015 Pooling Time-Series of Cross-Section Data
- 07-2015 Variance-Covariance Matrix of Random Effects
- 07-2015 Limited Dependent Variables
- 07-2015 Time-Series Analysis
- 07-2015 Relative Efficiency of OLS Under Heteroskedasticity
- 07-2015 Financial Sector Assessment
- 07-2015 Financial Sector Assessments: Overall Framework and Executive Summary
- 07-2015 Overall Analytical and Assessment Framework — Executive Summary
- 07-2015 Annex 1.A Tailoring Financial Sector Assessment to Country Needs
- 07-2015 Indicators of Financial Structure, Development, and Soundness
- 07-2015 System-wide Indicators
- 07-2015 Breadth of the Financial System
Страницы:
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616