Econometrics

Econometrics

Econometrics is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships". Jan Tinbergen is one of the two founding fathers of econometrics. The other, Ragnar Frisch, also coined the term in the sense in which it is used today. A basic tool for econometrics is the multiple linear regression model. Econometric theory uses statistical theory and mathematical statistics to evaluate and develop econometric methods. Econometricians try to find estimators that have desirable statistical properties including unbiasedness, efficiency, and consistency. Applied econometrics uses theoretical econometrics and real-world data for assessing economic theories, developing econometric models, analysing economic history, and forecasting. (Wikipedia).

Econometrics
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Introduction to Econometrics Toolbox in MATLAB

Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Create a predictive time-series model of a stock index. For more videos, visit http://www.mathworks.com/products/econometrics/examples.html

From playlist Computational Finance

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Parametric and nonparametric tests

Parametric tests are most commonly used in healthcare research. They include tests such as Student's t-test and ANOVA. There is, however a rich set of non-parametric tests that are much more appropriate to use in certain circumstances.

From playlist Learning medical statistics with python and Jupyter notebooks

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Intro to Hypothesis Testing

What is a hypothesis test? The meaning of the null and alternate hypothesis, with examples. Overview of test statistics and confidence levels.

From playlist Hypothesis Tests and Critical Values

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2. Utilities, Endowments, and Equilibrium

Financial Theory (ECON 251) This lecture explains what an economic model is, and why it allows for counterfactual reasoning and often yields paradoxical conclusions. Typically, equilibrium is defined as the solution to a system of simultaneous equations. The most important economic mode

From playlist Financial Theory with John Geanakoplos

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A solar system, a simulation made with Excel

An Excel simulation of the solar system. You can see how things are recursively computed: the mutual gravity force from the locations, the accelerations, the velocities, and finally the updated locations. The solar eclipse is also shown. This is clip is intended to illustrate Chapter 24 Ap

From playlist Physics simulations

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Jean-Pierre Florens: Inverse problems in econometrics - Lecture 1/4

Recording during the thematic month on statistics - Week 2 : "Mathematical statistics and inverse problems" the 9 February, 2016 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide

From playlist Probability and Statistics

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Threshold Switching Models | Switching Models in Econometrics, Part 2

This is the second video in a two-part series that shows how to model time series data in the presence of regime shifts in MATLAB in this video, we use Threshold Switching Models from the Econometrics Toolbox to model inflation data across different inflationary regimes. Download the code

From playlist Switching Models in Econometrics

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Markov Switching Models | Switching Models in Econometrics, Part 1

This is the first video in a two-part series that shows how to model time series data in the presence of regime shifts in MATLAB. In this video, William Mueller uses Markov switching models from the Econometrics Toolbox to model unemployment data across different economic regimes. Downloa

From playlist Switching Models in Econometrics

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3. Computing Equilibrium

Financial Theory (ECON 251) Our understanding of the economy will be more tangible and vivid if we can in principle explain all the economic decisions of every agent in the economy. This lecture demonstrates, with two examples, how the theory lets us calculate equilibrium prices and all

From playlist Financial Theory with John Geanakoplos

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Sylvia Frühwirth-Schnatter: Bayesian econometrics in the Big Data Era

Abstract: Data mining methods based on finite mixture models are quite common in many areas of applied science, such as marketing, to segment data and to identify subgroups with specific features. Recent work shows that these methods are also useful in micro econometrics to analyze the beh

From playlist Probability and Statistics

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Machine Learning and Economics: An Introduction

Professor Susan Athey presents a high-level overview contrasting traditional econometrics with off-the-shelf machine learning.

From playlist Machine Learning & Causal Inference: A Short Course

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Jean-Pierre Florens: Inverse problems in econometrics - Lecture 2/4

Recording during the thematic month on statistics - Week 2 : "Mathematical statistics and inverse problems" the 9 February, 2016 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide

From playlist Probability and Statistics

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Simulating the economy as we simulate the climate... - Pollitt - Workshop 3 - CEB T3 2019

Pollitt (Cambridge Econometrics) / 04.12.2019 Simulating the economy as we simulate the climate: why most economists get it wrong ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/I

From playlist 2019 - T3 - The Mathematics of Climate and the Environment

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Applied Machine Learning: Secret Sauce

Professor Jann Spiess shares the secret sauce of applied machine learning.

From playlist Machine Learning & Causal Inference: A Short Course

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Introduction to Statistics

This lesson introduces some of the common vocabulary when studying statistics. Site: http://mathispower4u.com

From playlist Introduction to Statistics

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Applied Machine Learning: Introduction

Professor Jann Spiess presents an introduction to applied machine learning.

From playlist Machine Learning & Causal Inference: A Short Course

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Frequentist probability | P-value | Regression analysis | Statistics | Exploratory data analysis | Econometrica | Granger causality | Empirical evidence | Economic data | Estimator | Generalized method of moments | Efficiency (statistics) | Null hypothesis | Estimation theory | Supply and demand | Single-equation methods (econometrics) | Generalized least squares | Observational study | Bayesian statistics | Experiment | Parameter identification problem | Simultaneous equations model | The Review of Economics and Statistics | Model selection | Econometric model | Statistical model | Journal of Econometrics | Omitted-variable bias | Bias of an estimator | Statistical theory | Mathematical statistics | Journal of Business & Economic Statistics | Spurious relationship | Quasi-experiment | Control theory | Financial econometrics | Maximum likelihood estimation | Bayes estimator | System identification | Financial modeling | Linear regression | Ordinary least squares | The Econometrics Journal | Augmented Dickey–Fuller test | Econometric Theory | Statistical hypothesis testing | Spatial econometrics | Choice modelling | Journal of Applied Econometrics | Natural logarithm | Consistent estimator | Predetermined variables | Unit root | Statistical significance | Econometric Reviews