Econometrics Overview and Models
70 Questions
1 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Match the following packages with their characteristics:

Menu-driven packages = Do not allow you to compute anything other than what's on the menu Command-driven packages = Typically quite flexible Eviews, RATS and Stata = Used for illustrations in the text MicroFit, PcGive, TSP and SHAZAM = Alternative econometrics programmes

Match the following journals with their content:

Journal of Applied Econometrics = Publish reviews of econometrics software Journal of Economic Surveys = Focus on software reviews

Match the following types of exercises with their purpose:

Technical questions = Check whether the reader has grasped the most important concepts Empirical exercises = Require the reader to use actual data Derivation exercises = Ask for proofs or technical details Proof exercises = Check understanding of key concepts

Match the following software with their categories:

<p>GAUSS, Matlab, Ox, S-Plus = Specialized software for specific methods or types of model Eviews, RATS and Stata = Econometrics programmes MicroFit, PcGive, TSP and SHAZAM = Alternative econometrics packages RATS and Stata = Specialized software for specific methods</p> Signup and view all the answers

Match the following packages with their usage:

<p>Eviews = Used for illustrations in the text RATS = Used for more advanced techniques Stata = Used for linear regression model MicroFit = Used for more advanced or tailored methods</p> Signup and view all the answers

Match the following characteristics with their types of packages:

<p>User-friendly = Menu-driven packages Flexible = Command-driven packages Limited functionality = Menu-driven packages Rich menu = Command-driven packages</p> Signup and view all the answers

Match the following types of software with their characteristics:

<p>Econometrics programmes = Used for linear regression model Specialized software = Used for specific methods or types of model Alternative econometrics packages = Used for more advanced techniques</p> Signup and view all the answers

Match the following resources with their content:

<p>Book's website = Software reviews Journal of Applied Econometrics = Software reviews Journal of Economic Surveys = Actual data for empirical exercises</p> Signup and view all the answers

Match the following types of exercises with their requirements:

<p>Technical questions = Require technical details or proofs Empirical exercises = Require actual data Derivation exercises = Check understanding of key concepts Proof exercises = Require actual data</p> Signup and view all the answers

Match the following packages with their advantages:

<p>Menu-driven packages = Easy to use Command-driven packages = Flexible Eviews, RATS and Stata = Easy to use MicroFit, PcGive, TSP and SHAZAM = Flexible</p> Signup and view all the answers

The ____________ test is used to test for heteroskedasticity.

<p>Breusch-Pagan</p> Signup and view all the answers

When testing for heteroskedasticity, the ____________ test is an alternative to the Breusch-Pagan test.

<p>White</p> Signup and view all the answers

The chapter discusses ____________ heteroskedasticity in section 4.3.5.

<p>multiplicative</p> Signup and view all the answers

Weighted ____________ Squares is a method used to address heteroskedasticity.

<p>Least</p> Signup and view all the answers

Section 4.4 of the chapter covers ____________ for heteroskedasticity.

<p>Testing</p> Signup and view all the answers

The ______ test is used to test for omitted variables in the normal linear regression model.

<p>Lagrange Multiplier</p> Signup and view all the answers

The ______ test is used to test for heteroskedasticity in the normal linear regression model.

<p>Lagrange Multiplier</p> Signup and view all the answers

The ______ method of estimation is used to estimate intertemporal asset pricing models.

<p>Generalized Instrumental Variables</p> Signup and view all the answers

Specification ______ are used to test the validity of the model assumptions.

<p>Tests</p> Signup and view all the answers

Quasi-______ likelihood and moment conditions tests are used to test for model assumptions.

<p>maximum</p> Signup and view all the answers

The Fama–MacBeth approach is a method used in ____________ inference.

<p>robust</p> Signup and view all the answers

Alternative Instrumental Variables Estimators are discussed in section ____________.

<p>10.2.6</p> Signup and view all the answers

Testing for ____________ and autocorrelation is an important step in regression analysis.

<p>heteroskedasticity</p> Signup and view all the answers

The ____________ test is used to test for unit roots in panel time series data.

<p>First Generation Panel</p> Signup and view all the answers

Panel cointegration tests are used to determine the presence of ____________ relationships between variables.

<p>long-run</p> Signup and view all the answers

What is the primary difference between a spurious regression and a cointegrated regression in the context of nonstationary variables?

<p>A spurious regression occurs when two nonstationary variables appear to be related, but the relationship is due to chance, whereas a cointegrated regression occurs when two nonstationary variables have a long-run relationship.</p> Signup and view all the answers

What is the purpose of an error-correction mechanism in a cointegrated system?

<p>An error-correction mechanism allows for the adjustment of the system back to its long-run equilibrium, following deviations from it.</p> Signup and view all the answers

How does a Vector Autoregressive (VAR) model differ from a univariate autoregressive model?

<p>A VAR model is a multivariate model that estimates the relationships between multiple variables, whereas a univariate autoregressive model only estimates the relationship between a single variable and its past values.</p> Signup and view all the answers

What is the purpose of testing for cointegration in a Vector Autoregressive (VAR) model?

<p>Testing for cointegration in a VAR model determines whether there exists a long-run relationship between the variables, and if so, the number of cointegrating relationships.</p> Signup and view all the answers

What is the advantage of using a multivariate approach, such as a VAR model, over a univariate approach in time series analysis?

<p>A multivariate approach, such as a VAR model, can capture the interactions and relationships between multiple variables, providing a more comprehensive understanding of the system.</p> Signup and view all the answers

What type of time series models are developed in Chapter 8, and what do they explain?

<p>Univariate time series models, which explain an economic variable from its own past.</p> Signup and view all the answers

What is the purpose of GARCH models in time series analysis?

<p>To model the conditional variance of a series.</p> Signup and view all the answers

What is the primary focus of Chapters 8 and 9 in terms of time series modeling?

<p>Unit roots, cointegration, and error-correction models.</p> Signup and view all the answers

What type of models are developed in Chapter 7, and what type of data do they typically handle?

<p>Probit, logit, tobit, and other models, which typically handle discrete, partly discrete, or duration data.</p> Signup and view all the answers

What is the significance of the last three decades in terms of time series modeling?

<p>Theoretical developments have been substantial, and many recent textbooks focus on this area almost exclusively.</p> Signup and view all the answers

What is the primary concern in sample selection bias, and how can it be addressed?

<p>The primary concern in sample selection bias is that the observed sample is not representative of the population, leading to biased estimates. This can be addressed using semi-parametric estimation of the sample selection model.</p> Signup and view all the answers

What is the difference between the Tobit model and the Tobit II model, and when would you use each?

<p>The Tobit model assumes that the dependent variable is censored, while the Tobit II model assumes that the dependent variable is both censored and truncated. The Tobit model is used when the data is censored, while the Tobit II model is used when the data is both censored and truncated.</p> Signup and view all the answers

What is the purpose of specification tests in binary choice models, and how do they differ from goodness-of-fit tests?

<p>Specification tests are used to test the assumptions of the binary choice model, such as the normality of the errors. They differ from goodness-of-fit tests, which evaluate the overall fit of the model to the data.</p> Signup and view all the answers

What is the difference between a hazard rate and a survival function in duration models, and how are they used?

<p>The hazard rate represents the probability of an event occurring at a given time, while the survival function represents the probability of an event not occurring at a given time. Both are used to model the duration of events in duration models.</p> Signup and view all the answers

What is the purpose of ordering in ordered response models, and how does it differ from binary response models?

<p>The purpose of ordering in ordered response models is to allow for multiple levels of response, whereas binary response models only allow for two levels of response. Ordered response models are used to model ordinal dependent variables.</p> Signup and view all the answers

Panel data are only available if we have repeated observations of the same countries.

<p>False</p> Signup and view all the answers

Cointegration and error-correction models can be used with panel data.

<p>True</p> Signup and view all the answers

Panel data has become less important in economics over recent decades.

<p>False</p> Signup and view all the answers

Unit roots and cointegration in a panel data setting is a topic that is not covered in the book.

<p>False</p> Signup and view all the answers

Panel data are only used for micro-economic analysis of households and firms.

<p>False</p> Signup and view all the answers

The Fixed Effects Model is a type of random effects model in panel data analysis.

<p>False</p> Signup and view all the answers

The First-difference Estimator is used to eliminate individual effects in panel data analysis.

<p>True</p> Signup and view all the answers

The Random Effects Model is more efficient than the Fixed Effects Model when the individual effects are correlated with the explanatory variables.

<p>False</p> Signup and view all the answers

Panel data analysis is only used for time series data.

<p>False</p> Signup and view all the answers

The chapter discusses panel data modeling in Chapter 9.

<p>False</p> Signup and view all the answers

The Fama–MacBeth approach is a method used in robust inference.

<p>True</p> Signup and view all the answers

Panel time series data can be used to test for heteroskedasticity and autocorrelation.

<p>False</p> Signup and view all the answers

The fixed effects logit model is a type of binary choice model.

<p>True</p> Signup and view all the answers

Dynamic linear models are used to model panel data with exogenous variables.

<p>True</p> Signup and view all the answers

The problem of initial conditions is specific to limited dependent variables models.

<p>True</p> Signup and view all the answers

What is the primary goal of econometrics in formulating a statistical model?

<p>To formulate hypotheses in terms of the model parameters and test their validity</p> Signup and view all the answers

What is an important job of an econometrician when evaluating a statistical model?

<p>To judge whether the resulting model is 'appropriate' for its intended purpose</p> Signup and view all the answers

What is a crucial consideration when using econometric techniques?

<p>The validity of the underlying assumptions</p> Signup and view all the answers

What is an example of a restriction that economic theory may imply on a statistical model?

<p>The efficient market hypothesis, implying that stock market returns are not predictable from their own past</p> Signup and view all the answers

What is the main approach of this book in guiding the reader through econometric techniques?

<p>Walking through the techniques in a structured way, skipping unnecessary side-paths</p> Signup and view all the answers

Which type of model is ideally suited for analyzing policy changes on an individual level?

<p>Panel data model</p> Signup and view all the answers

What is the primary purpose of econometric modeling?

<p>To specify and quantify relationships between variables</p> Signup and view all the answers

What type of relationships do cross-sectional models describe?

<p>Relationships between different variables measured at a given point in time for different units</p> Signup and view all the answers

What type of data is required for analyzing 'what if' questions using cross-sectional relationships?

<p>Cross-sectional data</p> Signup and view all the answers

What type of models describe differences between different individuals and changes in behavior over time?

<p>Panel data models</p> Signup and view all the answers

What has led to the increased attention to the modeling of macro-economic relationships and their dynamics?

<p>The concept of cointegration</p> Signup and view all the answers

What is the primary role of econometrics in empirical work in all fields of economics?

<p>To play a major role in almost all cases</p> Signup and view all the answers

What is the limitation of introductory econometrics textbooks for applied researchers?

<p>They provide insufficient coverage for applied researchers</p> Signup and view all the answers

What is the primary reason for the need for an accessible textbook on econometrics?

<p>The gap between introductory and advanced textbooks</p> Signup and view all the answers

What area of economics has required and stimulated many theoretical developments in econometrics?

<p>The empirical analysis of financial markets</p> Signup and view all the answers

Study Notes

Overview of Econometrics

  • Econometrics is at the heart of empirical research in economics and is no longer sufficient to simply run a few regressions and interpret the results.
  • The field has evolved significantly since the 1970s, with increased focus on macroeconomic relationships, microeconomic models, and financial markets.

Types of Models in Econometrics

  • Time series models: examine relationships between different variables measured at different points in time for a single unit.
  • Cross-sectional models: describe relationships between different variables measured at a given point in time for different units (e.g., households or firms).
  • Panel data models: simultaneously describe differences between different individuals and differences in behavior of a given individual over time.

Econometrics Textbooks

  • Introductory textbooks often provide insufficient coverage for applied researchers.
  • Advanced textbooks are often too technical or too detailed for the average economist to grasp the essential ideas.

Purpose of the Book

  • To provide an accessible textbook that discusses recent and relatively more advanced developments in econometrics.

Features of the Book

  • Exercises at the end of each chapter are intended to check whether the reader has grasped the most important concepts.
  • Empirical exercises require the reader to use actual data, available through the book's website.

Software for Econometrics

  • Various packages are available, including Eviews, RATS, Stata, MicroFit, PcGive, TSP, and SHAZAM.
  • Each package has its particular advantages and disadvantages.
  • A trade-off exists between user-friendliness and flexibility.

Contents of the Book

  • Page vi: Contents of the book, including chapters on alternative approaches to estimate causal effects, generalized instrumental variables estimator, and maximum likelihood estimation and specification tests.
  • Page 5.5: Alternative approaches to estimate causal effects.
  • Page 5.6: Generalized instrumental variables estimator.
  • Page 5.7: Institutions and economic development.
  • Page 5.8: Generalized method of moments.
  • Page 5.9: Illustration: estimating intertemporal asset pricing models.
  • Page 6: Maximum likelihood estimation and specification tests.
  • Page 7: Models with limited dependent variables.

Contents of a Statistics Textbook

  • The book covers various topics in statistics, including heteroskedasticity, instrumental variables, maximum likelihood estimation, and models with limited dependent variables.

Heteroskedasticity

  • Heteroskedasticity can be tested using various methods, including the Breusch-Pagan test and the White test.
  • Multiplicative heteroskedasticity is a specific type of heteroskedasticity.
  • Weighted least squares with arbitrary weights can be used to address heteroskedasticity.

Instrumental Variables

  • The generalized instrumental variables estimator is a method for estimating causal effects.
  • Two-stage least squares is a method for estimating instrumental variables.
  • Weak instruments are a problem that can arise in instrumental variables estimation.
  • Specification tests are used to test the validity of instrumental variables models.

Maximum Likelihood Estimation

  • Maximum likelihood estimation is a method for estimating parameters in statistical models.
  • The normal linear regression model is a specific type of model that can be estimated using maximum likelihood.
  • Specification tests are used to test the validity of maximum likelihood models.

Models with Limited Dependent Variables

  • Binary choice models are a type of model that can be used to analyze limited dependent variables.
  • The fixed effects logit model and the random effects probit model are specific types of binary choice models.
  • Tobit models are a type of model that can be used to analyze limited dependent variables.
  • Panel time series models are used to analyze data with multiple observations over time.

Chapter 9: Multivariate Time Series Models

  • Multivariate time series models are typically used in macroeconomics, where multiple economic variables are analyzed
  • Chapter 9 covers dynamic models with stationary variables, models with nonstationary variables, spurious regressions, cointegration, and error-correction mechanisms
  • Vector Autoregressive (VAR) models are also discussed in this chapter

Dynamic Models with Stationary Variables

  • Stationary variables have a constant mean and variance over time
  • Dynamic models with stationary variables can be used to analyze the relationship between multiple economic variables

Models with Nonstationary Variables

  • Nonstationary variables have a changing mean and/or variance over time
  • Examples of nonstationary variables include GDP, inflation rate, and stock prices
  • Cointegration is a concept that describes the long-run relationship between multiple nonstationary variables
  • Error-correction mechanisms are used to model the short-run dynamics of nonstationary variables

Cointegration

  • Cointegration occurs when two or more nonstationary variables have a long-run relationship
  • Cointegration implies that the variables move together in the long run, but can deviate from each other in the short run
  • Testing for cointegration is an important aspect of multivariate time series analysis

Vector Autoregressive (VAR) Models

  • VAR models are a type of multivariate time series model that can be used to analyze the relationships between multiple economic variables
  • VAR models can be used to forecast future values of multiple economic variables
  • Cointegration can be tested in a VAR model using the Johansen test

Panel Data Modelling

  • Panel data consists of repeated observations of the same units (e.g. households, firms, or countries) over time.
  • The use of panel data has become increasingly important in many areas of economics due to the availability of micro-economic panels of households and firms, and the ability to pool time series of several countries.
  • Panel data allows for a cross-sectional comparison of countries, providing additional information beyond a historical comparison of a country with its own past.

Types of Panel Data Models

  • Static Linear Model:
    • Fixed Effects Model
    • First-difference Estimator
    • Random Effects Model
  • Dynamic Linear Models:
    • Autoregressive Panel Data Model
    • Dynamic Models with Exogenous Variables
  • Models with Limited Dependent Variables:
    • Binary Choice Models
    • Fixed Effects Logit Model
    • Random Effects Probit Model
    • Tobit Models
  • Pseudo Panels and Repeated Cross-sections:
    • Fixed Effects Model
    • Instrumental Variables Interpretation
    • Dynamic Models

Important Concepts

  • Efficiency of Parameter Estimators
  • Identification of Parameters
  • Goodness-of-Fit
  • Alternative Instrumental Variables Estimators
  • Robust Inference
  • Testing for Heteroskedasticity and Autocorrelation
  • The Fama–MacBeth Approach
  • Heterogeneity
  • Panel Unit Root Tests
  • Panel Cointegration Tests
  • Incomplete Panels and Selection Bias

Econometrics

  • Econometricians formulate statistical models based on economic theory, confront them with data, and aim to come up with a specification that meets required goals.
  • The unknown elements in the specification, parameters, are estimated from a sample of available data.
  • Econometricians judge whether the resulting model is 'appropriate', checking assumptions and properties, and intended use, such as prediction or analysing policy changes.

Econometric Techniques and Assumptions

  • Numerous econometric techniques can be used, and their validity often depends on underlying assumptions.
  • Economic theory implies certain restrictions on the model, such as the efficient market hypothesis, which implies stock market returns are not predictable from their past.

Development of Econometrics

  • Since the 1970s, econometric methods have been increasingly employed in micro-economic models describing individual, household or firm behaviour.
  • Recent theoretical developments, such as cointegration, have generated increased attention to macro-economic relationships and their dynamics.
  • The empirical analysis of financial markets has required and stimulated many theoretical developments in econometrics.

Role of Econometrics in Economics

  • Econometrics plays a major role in empirical work in almost all fields of economics, and it is no longer sufficient to be able to run a few regressions and interpret the results.
  • There is a need for an accessible textbook that discusses recent and relatively more advanced developments in econometrics.

Types of Relationships in Econometrics

  • Cross-sectional relationships describe differences between units (e.g. households or firms) at a given point in time, explaining why they are different or behave differently.
  • Cross-sectional relationships can be used to analyse 'what if' questions under particular conditions.
  • Panel data, repeated observations over the same units, describe differences between individuals and differences in behaviour over time, suited for analysing policy changes on an individual level.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Quiz Team

Related Documents

Description

Explore the evolution and importance of econometrics in empirical research, including types of models such as time series models. Learn about macroeconomic relationships, microeconomic models, and financial markets.

More Like This

Econometrics Midterms Review Quiz
5 questions

Econometrics Midterms Review Quiz

IllustriousEnlightenment8241 avatar
IllustriousEnlightenment8241
Econometrics Quiz
5 questions

Econometrics Quiz

ProudMoldavite9987 avatar
ProudMoldavite9987
Economía: Modelo VAR
16 questions
Introduction to Econometrics
29 questions
Use Quizgecko on...
Browser
Browser