## Aaron Smith

Chapter 1 - introduction to econometrics.

Lecture Slides:       Powerpoint     PDF

Learning Objectives

• Define and describe the basics of econometrics
• Describe how to do an econometric study
• Do Good Teachers Produce Better Student Outcomes?
• Does the Law of Demand Hold for Electricity?
• Is it Possible to Forecast Stock Returns?

What We Learned

• Econometrics is about making sense of economic data.
• Three steps to conducting econometric analysis. (1) State the purpose of the analysis, (2) Formulate the research design and specify the econometric model, (3) Apply statistical theory.

• My presentations

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## ECONOMETRICS Chapter # 1: Introduction Domodar N. Gujarati

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## Presentation on theme: "ECONOMETRICS Chapter # 1: Introduction Domodar N. Gujarati"— Presentation transcript:

CHAPTER 1: THE NATURE OF REGRESSION ANALYSIS

Regression Analysis Using Excel. Econometrics Econometrics is simply the statistical analysis of economic phenomena Here, we just summarize some of the.

LINEAR REGRESSION MODEL

Building and Testing a Theory Steps Decide on what it is you want to explain or predict. 2. Identify the variables that you believe are important.

Functions of Statistics

The Multiple Regression Model Prepared by Vera Tabakova, East Carolina University.

Linear Regression.

Chapter Ten1 CHAPTER TEN Aggregate Demand I. Chapter Ten2 The Great Depression caused many economists to question the validity of classical economic theory.

Introduction to Hypothesis Testing

Introduction: What is Econometrics?

PENGERTIAN EKONOMETRIKA Al muizzuddin fazaalloh. WHAT IS ECONOMETRICS? Literally interpreted, econometrics means “economic measurement.” Econometrics,

THE NATURE OF REGRESSION ANALYSIS Al Muizzuddin F.

Econometrics I Summer 2011/2012 Course Guarantor: prof. Ing. Zlata Sojková, CSc., Lecturer: Ing. Martina Hanová, PhD.

Relationships Among Variables

Econometrics 1. Lecture 1 Syllabus Introduction of Econometrics: Why we study econometrics? 2.

Hypothesis Testing in Linear Regression Analysis

SIMULTANEOUS EQUATION MODELS

Econometrics I

Class Notes

Professor W. Greene Department of Economics Office: MEC 7-90, Ph. 998-0876 e-mail: [email protected] Home page: http://people.stern.nyu.edu/wgreene

Abstract: This is an intermediate level, Ph.D. course in Applied Econometrics . Topics to be studied include specification, estimation, and inference in the context of models that include then extend beyond the standard linear multiple regression framework. After a review of the linear model, we will develop the asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models. We will then turn to instrumental variables, maximum likelihood, generalized method of moments (GMM), and two step estimation methods. Inference techniques used in the linear regression framework such as t and F tests will be extended to include Wald, Lagrange multiplier and likelihood ratio and tests for nonnested hypotheses such as the Hausman specification test. Specific modelling frameworks will include the linear regression model and extensions to models for panel data, multiple equation models, and models for discrete choice.

Notes: The following list points to the class discussion notes for Econometrics I. These are Power Point (.pptx) files and pdf documents (.pdf).

## Browse Course Material

Course info.

• Prof. Victor Chernozhukov

As taught in.

• Econometrics

## Learning Resource Types

Lecture notes.

Lecture notes by Victor Chernozhukov (MIT) and Ivan Fernandez-Val (BU).

LEC # TOPIC
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Below are the data and codes for this lecture, in case you want to apply this one day.

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Below are the data and codes for this lecture, in case you want to apply this one day.

Data and Codes

## Introduction to Econometrics

Aug 10, 2012

850 likes | 2.55k Views

Introduction to Econometrics. Lecture 1 Introduction and overview of the course Definition, scope and methodology of econometrics A review of the simple (bivariate) linear regression model. Objectives. To provide you with information about

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• oup gujarati

## Presentation Transcript

Introduction to Econometrics Lecture 1 Introduction and overview of the course Definition, scope and methodology of econometrics A review of the simple (bivariate) linear regression model

Objectives To provide you with information about the subject of econometrics and the topics that we shall cover in the unit the learning teaching and assessment arrangements for the unit To review the simple bivariate linear regression model

Learning and Teaching Lectures and accompanying notes Problems classes (seminars) Computer lab sessions Office hours and “econometrics café” sessions Text books Web pages and links the econmet wiki One minute e-mail and FAQs

Recommended texts Dougherty, C (2007) Introduction to Econometrics, Third Edition, OUP Gujarati, D N and Porter, DC (2009) Basic Econometrics, Fifth Edition, McGraw-Hill Kennedy, P (2003) A Guide to Econometrics, Fifth Edition, Blackwell Koop, G (2008) Introduction to Econometrics, John Wiley & Sons and others available in the Library in section 330.0182

Computer software for the lab classes The regression tool in Excel PcGive EViews

assessment end of unit exam (50% weighting) portfolio of practical solutions (20% weighting) assignment/report (30% weighting)

econometrics The measurement of economic relationships

econometrics “the application of mathematical statistics to economic data to lend empirical support to models constructed by mathematical economics and to obtain numerical estimates” (Samuelson et al., Econometrica, 1954)

aims of econometric modelling explanation policy evaluation forecasting

types of data cross-section time-series panel

types of model simple bivariate linear non-linear bivariate multiple regression dynamic simultaneous equation other (e.g. logit and probit) panel

Example: sales-advertising relationship suppose we wish to test the hypothesis that a firm’s sales are dependent upon it’s advertising the simplest model is sales = a + b*advertising + u where a and b are parameters to be estimated, u is an unobservable error term - a random disturbance this is an example of a simple bivariate regression model

sales and advertising time series plot

general notation for the simple bivariate linear model for i = 1,2,…….n With time series data we tend use t rather than i as the subscript and T as the sample size

model specification the equation(s) – variables and functional form a priori restrictions on parameters stochastic assumptions (assumptions about the disturbance term)

assumptions about u mean zero constant variance independent between observations independent of the X variable

The role of the disturbance term Reasons for the disturbance omitted influences on Y errors of measurement errors in variables non-linearity random nature of human behaviour

Econometric “problems” Reasons for the disturbance autocorrelation heteroskedasticity bias multicollinearity

Plant X Y FITTED Y 1 100 40 42.32 2 200 50 48.21 3 300 50 54.11 4 400 70 60.00 5 500 65 65.89 6 600 65 71.79 7 700 80 77.68 The unlikely case of control over sample design

• More by User

Simple delayed effects modelsDistributed lag models and the Koyck transformationA review of the Partial Adjustment MechanismAutoregressive modelsAutoregressive Distributed Lag (ADL) modelsError Correction models (ECM). Dynamic model formulations. Yt = a b Xt-1 utChanges in X affect Y but with a known lag (in this case one period). Provided the length of the lag is known, or is easily established, this raises no new problems. Indeed it can be helpful from a forecasting point of 9456

782 views • 22 slides

## Econometrics

Econometrics. Lecture Notes Hayashi, Chapter 6f Large Sample Theory. Sample Mean. Given a serially correlated process {y t }, what is the asymptotic properties of the sample mean? What are the restrictions on covariance stationary processes for the consistency of the sample mean?.

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Econometrics. Degree of Business Administration and Management. What is econometrics? Econometric models Types of econometric models Assumptions of the econometric model. 1. Econometrics. Etymology of the word Econometrics = oiko-nomos + metrics

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2. Announcements . Read Chapters 4 and 5 for Tuesday (see syllabus)Remember to attend lab todayPlease bring the Stata lab book with youLab assignments will be due (which means sending an email with the requested work to both your TA and me) by 10:00 on the Tuesday following lab. Please write th

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Introduction to Econometrics. Lecture 7 Heteroskedasticity and some further diagnostic testing. Topics to be covered. Heteroskedasticity Some further diagnostic testing Normality of the disturbances Multicollinearity. Econometric problems. Heteroskedasticity.

667 views • 18 slides

Introduction to Econometrics. Lecture 10 Simultaneous equations models. Single equations or systems of equations?. Even if we are only interested in one particular equation (e.g. a demand function or a consumption function) we may have to consider it as part of a system of equations.

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Introduction to Econometrics. Lecture 9 More on Dynamic Models Modelling Strategies. Dynamic model formulations. Simple delayed effects models Distributed lag models and the Koyck transformation A review of the Partial Adjustment Mechanism Autoregressive models

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Introduction to Econometrics. Lecture2 Bivariate regression models Interpreting least squares regression results: goodness of fit and significance tests Forecasting with a simple regression model. Recommended reading. DOUGHERTY Introduction to Econometrics Chapter 2 OR

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Introduction to Econometrics. Lecture 5 Extensions to the multiple regression model. Lecture plan. logarithmic transformations - log-linear (constant elasticity) models dummy variables for qualitative factors

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Introduction to Econometrics. To allow for random disturbances, we must write the model as Y = b 0 + b 1 X + u , where u is a disturbance term with E(u) = 0.

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Introduction to Econometrics. Week 2 Lecture 2 More on bivariate regression models A recap on sampling distributions and standard errors The story of the t-distribution An introduction to forecasting with a simple regression model. Sampling distributions and standard errors.

287 views • 13 slides

Introduction to Econometrics. Lecture 8 Autocorrelation. Econometric problems. Topics to be covered. Overview of autocorrelation First-order autocorrelation and the Durbin-Watson test Higher-order autocorrelation and the Breusch-Godfrey test Dealing with autocorrelation

562 views • 16 slides

## INTRODUCTION ECONOMETRICS I

INTRODUCTION ECONOMETRICS I. MAXIMA. “Without data you are just one more person with an opinion” (Anonymous) Even the most beautiful theory is just aesthetics without empirical evidence… but you have to make sure that you interpret properly your data. INTRODUCTION.

518 views • 23 slides

## Business Modeling Introduction to Econometrics

Lecturer : Ing. Martina Hanová, PhD. . Business Modeling Introduction to Econometrics. „ Econometrics may be defined as the social science in which the tools of economic theory, mathematics, and statistical inference are applied to the analysis of economic phenomena.“

529 views • 19 slides

Econometrics I Summer 2011/2012 Course Guarantor :  prof. Ing. Zlata Sojková, CSc ., Lecturer : Ing. Martina Hanová, PhD. . Introduction to Econometrics.

412 views • 14 slides

Introduction to Econometrics. Week 4 Multiple regression models. Lecture plan. the need for additional regressors classical assumptions and least squares estimation extended to allow for several regressors interpreting the results t tests of individual parameter values

518 views • 22 slides

## INTRODUCTION APPLIED ECONOMETRICS

INTRODUCTION APPLIED ECONOMETRICS. BASICS I. BASIC PROBLEM I. Endogeneity Circularity Egg and chicken Causality and correlation: two very different concepts!!. BASIC PROBLEM I. Interpretation of any graph/table implies many assumptions.

424 views • 13 slides

INTRODUCTION ECONOMETRICS I. BASICS I. BASIC PROBLEM I. Endogeneity Circularity Egg and chicken Causality and correlation: two very different concepts!!. BASIC PROBLEM I. Interpretation of any graph/table implies many assumptions. However, these assumptions are almost never explicit.

265 views • 13 slides

Introduction to Econometrics. What do I expect of you before you come to class? Print out the slides. Read the chapter, and as you read, write questions down on the slides. Therefore, when I am lecturing, I do not expect it to be the first time you are hearing about a concept.

705 views • 51 slides

## ES5611 Introduction to Econometrics

ES5611 Introduction to Econometrics. Introductory remarks What is Econometrics? What is this course like?. Slides by Ken Clark, adapted from P. Anderson, 2004. Introductory Remarks. Lecturer: Ken Clark, N.5.6, Dover Street email: [email protected]

701 views • 31 slides

Introduction to Econometrics. Lecture 6 Testing restrictions. Lecture plan. Testing restrictions about individual parameters groups of parameters. t-tests for individual parameters zero value under H 0 Some other value under H 0. F-tests for groups of parameters

350 views • 10 slides

Introduction to Econometrics. The Statistical Analysis of Economic (and related) Data. Brief Overview of the Course. This course is about using data to measure causal effects. In this course you will:. Review of Probability and Statistics (SW Chapters 2, 3).

855 views • 63 slides

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## Economics & Econometrics Major for College

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• Economics Seminar Series presents Joanna Lahey, Texas A&M University

## Economics Seminar Series

Joanna Lahey, Texas A&M University

## Joanna Lahey, Texas A&M University

(with marianne wanamaker), presentation title: "effects of restrictive abortion legislation on cohort mortality: evidence from 19th century law variation".

Permissive abortion policy is thought to improve the average well-being of children ever born, as evidenced by recent studies based on 20th century US data. Using 19th century restrictive abortion policy, we demonstrate a more nuanced relationship between policy and child well-being. Despite increased birth rates among abortion-restricted cohorts, we find little evidence of changes in well-being at birth through the standard channel of child selection, consistent with predictions from a generalized model. However, children in these larger cohorts were far more susceptible to mortality from infectious disease throughout childhood, implying different mechanisms linking abortion policy to child well-being.

DATE: Friday, September 8, 2023

TIME: 3:30-5:00 p.m.

LOCATION: Fronczak 444

• Washington State University

## WSU leaders give presentation on endowments and investing strategies

Leaders from the WSU Foundation and the university’s Finance and Administration team provided an overview of investments and endowments during a livestreamed presentation Wednesday afternoon.

Explanations of how endowments function, the different investing strategies the foundation and the university follow, and the tools used to maximize returns for the benefit of students and the wider university community were discussed by WSU Foundation President Mike Connell and Vice President for Finance and Administration Leslie Brunelli.

The complete presentation is available to watch online .

Central to the discussion was the distinction between the WSU Foundation and the university itself. While the former does support the latter, it was established long after the university and is responsible for investing private donations and funds that don’t include student tuition or state tax dollars.

The WSU Foundation manages approximately \$722 million spread across more than 2,900 endowment accounts. The vast majority of that funding comes from private donors seeking to support a specific cause, such as scholarships for students, endowed faculty or deanships, as well as specific programs and activities.

When a donation is made, the foundation enters into agreement with the donor to invest the funds and use revenue generated in support of the agreed upon cause, Connell explained. On average, 4% of the endowment total is distributed each year. That amounted to \$27 million in endowment distributions from the Foundation in fiscal year 2024.

The WSU Foundation uses an outside firm, Mercer, to assess the best way to allocate its funds. The largest portion of its funds, about 23%, are in U.S. equities, while significant portions are invested in private and international equities as well as hedge funds and real assets.

The Foundation does not purchase shares in individual companies. Rather, fund managers working on behalf of the university use tools like index funds to diversify investments in pursuit of maximized returns while minimizing risk. As an example, Connell noted that Mercer couldn’t provide WSU a figure on how much of the Foundation’s funds are invested in fossil fuels, but it can give an assessment in terms of the energy sector, amounting to 6-7 percent of the total endowment. And that figure include fossil fuel companies as well as companies working on green energy.

Brunelli noted that the university itself, meanwhile, invests some tuition dollars as well as funding from the state as its able. State law restricts the investment of these funds by separate 501c3 organizations like the WSU Foundation. Tuition and state funding are invested on behalf of WSU by the state’s treasurer’s office, with priority given to managing liquidity to ensure the university can pay its bills. Because of this, the university takes a more short-term and risk-adverse position compared to the foundation, Brunelli said.

As WSU and institutions of higher education continue to grapple with rising costs, Brunelli noted that private support and its facilitation by the foundation will be even more critical moving forward to ensure the long-term health of the institution.

Recent news.

## Full Transcript of Kamala Harris’s Democratic Convention Speech

The vice president’s remarks lasted roughly 35 minutes on the final night of the convention in Chicago.

By The New York Times

• Aug. 23, 2024

This is a transcript of Vice President Kamala Harris’s speech on Thursday night in which she formally accepted the Democratic Party’s nomination for the presidency.

So, let me start by thanking my most incredible husband, Doug. For being an incredible partner to me, an incredible father to Cole and Ella, and happy anniversary, Dougie. I love you so very much.

To our president, Joe Biden. When I think about the path that we have traveled together, Joe, I am filled with gratitude. Your record is extraordinary, as history will show, and your character is inspiring. And Doug and I love you and Jill, and are forever thankful to you both.

And to Coach Tim Walz. You are going to be an incredible vice president. And to the delegates and everyone who has put your faith in our campaign, your support is humbling.

So, America, the path that led me here in recent weeks was, no doubt, unexpected. But I’m no stranger to unlikely journeys. So, my mother, our mother, Shyamala Harris, had one of her own. And I miss her every day, and especially right now. And I know she’s looking down smiling. I know that.

So, my mother was 19 when she crossed the world alone, traveling from India to California with an unshakable dream to be the scientist who would cure breast cancer.

We are having trouble retrieving the article content.

Thank you for your patience while we verify access.

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#### IMAGES

1. PPT

2. PPT

3. PPT

4. PPT

5. PPT

6. WHAT IS ECONOMETRICS?. What is econometrics is simply answered…

#### VIDEO

1. Mastering Econometrics and Statistics for Quant Finance

2. ECONOMETRICS

3. Econometrics

4. Gauss Markov Theory

5. Careers in Econometrics (Part-II)

6. Econometrics

1. Chapter 1

Econometrics is about making sense of economic data. Three steps to conducting econometric analysis. (1) State the purpose of the analysis, (2) Formulate the research design and specify the econometric model, (3) Apply statistical theory. Click here to read the chapter (link works only for UC affiliates) Lecture Slides: Powerpoint PDF Learning ...

2. An Introduction to Econometrics

Download ppt "An Introduction to Econometrics". Principles of Econometrics, 4th Edition Chapter Contents 1.1 Why Study Econometrics 1.2 What is Econometrics 1.3 The Econometric Model 1.4 How Do We Obtain Data 1.5 Statistical Inference 1.6 A Research Format Principles of Econometrics, 4th Edition Chapter 1: An Introduction to Econometrics Page *.

3. PDF Notes on Econometrics I

I will categorize three broad areas that most econometric courses will fall into (note that this list is not a universally acknowledged taxonomy, but I ﬁnd it a useful heuristic): 1.Reduced form estimation - This is the type of econometrics that is most often used for Labor Economics and Public Eco-nomics.

4. PDF Econ 480-3 Introduction to Econometrics

Y is determined and may come from physics, economics, etc. The e ect of X j on Y holding X j and U constant (i.e., ceteris paribus) is determined by g. If gis di erentiable, then it is given by D X j g(X;U). If we assume further that g(X;U) = X0 + U; then the ceteris paribus e ect of X j on Y is simply j. We may normalize

5. PDF Introductory Econometrics Slides

Introductory Econometrics Slides Rolf Tschernig & Harry Haupt University of Regensburg University of Passau August 2020 1 1These slides were originally designed for the course "Intensive Course in Econometrics" that Rolf Tschernig and Harry Haupt created for the TEMPUS Project "New Curricula in Trade Theory and Econometrics" in 2009.

6. Lecture Slides in Econometrics

Bayesian methods in econometrics. James D Hamilton, University of California, San Diego. Bayesian statistics and its application to econometrics - lecture slides and notes from a course that ran from 2013 to 2015. The Powerpoint presentation comprises nearly 100 slides.

7. Econometrics

Introduction to econometric models and techniques, simultaneous equations, program evaluation, emphasizing regression. Advanced topics include instrumental variables, panel data methods, measurement error, and limited dependent variable models. May not count toward HASS requirement.

8. PDF ECON4150

nd Mark. M. Watson, Introduction to Econometrics (3rd. edition update. son, 2015.Chapter 1-12, 13.1-13.5 and 13.7, 14.1-14.6 and 14.8. Lecture slidesExam:Written examination on 25 May at 02:30 (3 hours) Open book examin. ll printed and written resources, in addition to calculator, are allowe.

9. 1 Introduction To Econometrics

Ppt 1 Introduction to Econometrics - Free download as Powerpoint Presentation (.ppt), PDF File (.pdf), Text File (.txt) or view presentation slides online. This document provides an introduction to econometrics. It discusses how econometrics is used to model empirical economic relationships and support decision making. Econometrics combines insights from economics, statistics, mathematics and ...

10. Introduction Econometrics

Introduction Econometrics.ppt - Free download as Powerpoint Presentation (.ppt / .pptx), PDF File (.pdf), Text File (.txt) or view presentation slides online. This document discusses econometrics and provides definitions and examples. It defines econometrics as the application of statistical methods to economic data. Econometrics allows economists to empirically test economic theories and ...

11. ECONOMETRICS Chapter # 1: Introduction Domodar N. Gujarati

Estimation of the parameters of the econometric model 6. Hypothesis testing 7. Forecasting or prediction 8. Using the model for control or policy purposes. To illustrate the preceding steps, let us consider the well-known Keynesian theory of consumption. 6 1. Statement of Economic Theory or Hypothesis.

12. Econometrics I: Class Notes

Notes: The following list points to the class discussion notes for Econometrics I. These are Power Point (.pptx) files and pdf documents (.pdf). 1. Introduction: Paradigm of Econometrics ( pptx) ( pdf) 2. The Linear Regression Model: Regression and Projection ( pptx) ( pdf) 3. Linear Least Squares, Regression Fit, Transformations ( pptx) ( pdf) 4.

13. Lecture Notes

Treatment Effects (PDF) Below are the data and codes for this lecture, in case you want to apply this one day. Data and Codes. R-code and data for lectures 11-12. R-code NPA Functions (R) R-code 401k-ATE (R) Data for Lecture 10 (DTA) R-code for 401k-QTE (R) This section contains the lecture notes used in the course.

14. PPT

IntroductionMethodology of Econometrics (8) Using model for control or policy purposes Y=4000= -231.8+0.7194 X X 5882 MPC = 0.72, an income of \$5882 Bill will produce an expenditure of \$4000 Bill. By fiscal and monetary policy, Government can manipulate the control variable X to get the desired level of target variable Y.

15. Lecture Slides in Advanced Econometrics and Quantitative Techniques

Slides, syllabus and reading list from an AEA Continuing Education short course run in January 2022. The course "examines the interplay between data design, and statistical inference and decisions. We will examine classic sampling and experimental designs, but also alternatives such as adaptive randomization designs and multi-armed bandits ...

16. PPT

Presentation Transcript. Introduction to Econometrics Lecture 1 Introduction and overview of the course Definition, scope and methodology of econometrics A review of the simple (bivariate) linear regression model. Objectives To provide you with information about the subject of econometrics and the topics that we shall cover in the unit the ...

17. Economics & Econometrics Major

Economics & Econometrics Major for College Presentation . Education . Premium Google Slides theme, PowerPoint template, and Canva presentation template . If you want to study economics or econometrics (or both), be prepared to feel comfortable with numbers! But first, let's use this new template, which is totally customizable, to create a ...

18. PDF TheLife-cycleofConcentratedIndustries