## 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. |

### What people are saying - Write a review

User Review - Flag as inappropriate

Great book!

### Contents

User Guide | 1 |

Introduction | 10 |

References | 30 |

PivotTables | 53 |

References | 71 |

References | 91 |

References | 136 |

A Catalog of Functional Forms | 161 |

References | 334 |

References | 376 |

References | 410 |

References | 451 |

References | 488 |

507 | |

Heteroskedasticity | 508 |

References | 557 |

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 |

603 | |

References | 661 |

Bootstrap | 709 |

Simultaneous Equations | 730 |

747 | |

761 | |

### Other editions - View all

### Common terms and phrases

actual add-in analysis apply approximation autocorrelation bivariate bootstrap box model button called cell chance chapter Click coefficient column compute confidence constant contains correlation curve data generation process data set demonstrate dependent variable displays draw econometric empirical equal equation error terms exact example Excel expected value explain fact Figure Forecasted formula function given graph heteroskedasticity histogram hypothesis important included income increases independent intercept interval linear means measurement method Monte Carlo simulation normal normally distributed Note null observations obtain OLS estimator parameter percent population Predicted present probability problem quantity demanded question random variable reason regression line relationship repetitions reported residuals RMSE sample average sampling distribution sheet shows simply slope Source spread squares standard statistic Summary true unbiased wage weights workbook zero