Introductory Econometrics: Using Monte Carlo Simulation with Microsoft ExcelThis highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics. |
Contents
User Guide | 1 |
DESCRIPTION | 10 |
Correlation | 20 |
33333333 | 53 |
References | 71 |
References | 91 |
References | 136 |
A Catalog of Functional Forms | 161 |
3 | 411 |
2230 | 445 |
References | 451 |
29 | 471 |
333333 | 477 |
References | 488 |
| 507 | |
Heteroskedasticity | 508 |
126 | 189 |
References | 194 |
Monte Carlo Simulation | 215 |
Review of Statistical Inference | 238 |
References | 278 |
The Measurement Box Model | 281 |
References | 302 |
The Classical Econometric Model | 316 |
References | 334 |
References | 376 |
References | 410 |
References | 557 |
51 | 573 |
| 603 | |
References | 661 |
Bootstrap | 709 |
Simultaneous Equations | 730 |
| 747 | |
| 761 | |
| 767 | |
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Common terms and phrases
add-in approximation b₁ b₂ bivariate regression button capita cell chance process chapter cigarettes classical econometric model Click compute confidence interval correlation coefficient crosstab data generation process data set displayed dummy variables elasticity Empirical Histogram equation error box error terms exact example expected value F-statistic Figure Forecast Error formula free throws functional form Gauss-Markov theorem graph of averages heteroskedasticity independent variables least squares linear estimators LINEST Math SAT Monte Carlo simulation multicollinearity multiple regression normally distributed null hypothesis number of observations OLS estimator OLS regression omitted variable omitted variable bias P-value percent PivotTable population average population parameter probability histogram random number random variable regression line repetitions RMSE sample average sample percentage sample slope sample statistic sampling distribution scatter diagram SD line sheet shows skiers slope estimator Solver Source squared residuals summary statistics tickets unbiased estimator univariate variance Verbal SAT wage yearly earnings zero