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Match the following packages with their characteristics:
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:
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:
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:
Match the following software with their categories:
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Match the following packages with their usage:
Match the following packages with their usage:
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Match the following characteristics with their types of packages:
Match the following characteristics with their types of packages:
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Match the following types of software with their characteristics:
Match the following types of software with their characteristics:
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Match the following resources with their content:
Match the following resources with their content:
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Match the following types of exercises with their requirements:
Match the following types of exercises with their requirements:
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Match the following packages with their advantages:
Match the following packages with their advantages:
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The ____________ test is used to test for heteroskedasticity.
The ____________ test is used to test for heteroskedasticity.
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When testing for heteroskedasticity, the ____________ test is an alternative to the Breusch-Pagan test.
When testing for heteroskedasticity, the ____________ test is an alternative to the Breusch-Pagan test.
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The chapter discusses ____________ heteroskedasticity in section 4.3.5.
The chapter discusses ____________ heteroskedasticity in section 4.3.5.
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Weighted ____________ Squares is a method used to address heteroskedasticity.
Weighted ____________ Squares is a method used to address heteroskedasticity.
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Section 4.4 of the chapter covers ____________ for heteroskedasticity.
Section 4.4 of the chapter covers ____________ for heteroskedasticity.
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The ______ test is used to test for omitted variables in the normal linear regression model.
The ______ test is used to test for omitted variables in the normal linear regression model.
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The ______ test is used to test for heteroskedasticity in the normal linear regression model.
The ______ test is used to test for heteroskedasticity in the normal linear regression model.
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The ______ method of estimation is used to estimate intertemporal asset pricing models.
The ______ method of estimation is used to estimate intertemporal asset pricing models.
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Specification ______ are used to test the validity of the model assumptions.
Specification ______ are used to test the validity of the model assumptions.
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Quasi-______ likelihood and moment conditions tests are used to test for model assumptions.
Quasi-______ likelihood and moment conditions tests are used to test for model assumptions.
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The Fama–MacBeth approach is a method used in ____________ inference.
The Fama–MacBeth approach is a method used in ____________ inference.
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Alternative Instrumental Variables Estimators are discussed in section ____________.
Alternative Instrumental Variables Estimators are discussed in section ____________.
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Testing for ____________ and autocorrelation is an important step in regression analysis.
Testing for ____________ and autocorrelation is an important step in regression analysis.
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The ____________ test is used to test for unit roots in panel time series data.
The ____________ test is used to test for unit roots in panel time series data.
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Panel cointegration tests are used to determine the presence of ____________ relationships between variables.
Panel cointegration tests are used to determine the presence of ____________ relationships between variables.
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What is the primary difference between a spurious regression and a cointegrated regression in the context of nonstationary variables?
What is the primary difference between a spurious regression and a cointegrated regression in the context of nonstationary variables?
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What is the purpose of an error-correction mechanism in a cointegrated system?
What is the purpose of an error-correction mechanism in a cointegrated system?
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How does a Vector Autoregressive (VAR) model differ from a univariate autoregressive model?
How does a Vector Autoregressive (VAR) model differ from a univariate autoregressive model?
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What is the purpose of testing for cointegration in a Vector Autoregressive (VAR) model?
What is the purpose of testing for cointegration in a Vector Autoregressive (VAR) model?
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What is the advantage of using a multivariate approach, such as a VAR model, over a univariate approach in time series analysis?
What is the advantage of using a multivariate approach, such as a VAR model, over a univariate approach in time series analysis?
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What type of time series models are developed in Chapter 8, and what do they explain?
What type of time series models are developed in Chapter 8, and what do they explain?
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What is the purpose of GARCH models in time series analysis?
What is the purpose of GARCH models in time series analysis?
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What is the primary focus of Chapters 8 and 9 in terms of time series modeling?
What is the primary focus of Chapters 8 and 9 in terms of time series modeling?
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What type of models are developed in Chapter 7, and what type of data do they typically handle?
What type of models are developed in Chapter 7, and what type of data do they typically handle?
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What is the significance of the last three decades in terms of time series modeling?
What is the significance of the last three decades in terms of time series modeling?
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What is the primary concern in sample selection bias, and how can it be addressed?
What is the primary concern in sample selection bias, and how can it be addressed?
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What is the difference between the Tobit model and the Tobit II model, and when would you use each?
What is the difference between the Tobit model and the Tobit II model, and when would you use each?
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What is the purpose of specification tests in binary choice models, and how do they differ from goodness-of-fit tests?
What is the purpose of specification tests in binary choice models, and how do they differ from goodness-of-fit tests?
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What is the difference between a hazard rate and a survival function in duration models, and how are they used?
What is the difference between a hazard rate and a survival function in duration models, and how are they used?
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What is the purpose of ordering in ordered response models, and how does it differ from binary response models?
What is the purpose of ordering in ordered response models, and how does it differ from binary response models?
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Panel data are only available if we have repeated observations of the same countries.
Panel data are only available if we have repeated observations of the same countries.
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Cointegration and error-correction models can be used with panel data.
Cointegration and error-correction models can be used with panel data.
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Panel data has become less important in economics over recent decades.
Panel data has become less important in economics over recent decades.
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Unit roots and cointegration in a panel data setting is a topic that is not covered in the book.
Unit roots and cointegration in a panel data setting is a topic that is not covered in the book.
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Panel data are only used for micro-economic analysis of households and firms.
Panel data are only used for micro-economic analysis of households and firms.
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The Fixed Effects Model is a type of random effects model in panel data analysis.
The Fixed Effects Model is a type of random effects model in panel data analysis.
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The First-difference Estimator is used to eliminate individual effects in panel data analysis.
The First-difference Estimator is used to eliminate individual effects in panel data analysis.
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The Random Effects Model is more efficient than the Fixed Effects Model when the individual effects are correlated with the explanatory variables.
The Random Effects Model is more efficient than the Fixed Effects Model when the individual effects are correlated with the explanatory variables.
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Panel data analysis is only used for time series data.
Panel data analysis is only used for time series data.
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The chapter discusses panel data modeling in Chapter 9.
The chapter discusses panel data modeling in Chapter 9.
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The Fama–MacBeth approach is a method used in robust inference.
The Fama–MacBeth approach is a method used in robust inference.
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Panel time series data can be used to test for heteroskedasticity and autocorrelation.
Panel time series data can be used to test for heteroskedasticity and autocorrelation.
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The fixed effects logit model is a type of binary choice model.
The fixed effects logit model is a type of binary choice model.
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Dynamic linear models are used to model panel data with exogenous variables.
Dynamic linear models are used to model panel data with exogenous variables.
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The problem of initial conditions is specific to limited dependent variables models.
The problem of initial conditions is specific to limited dependent variables models.
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What is the primary goal of econometrics in formulating a statistical model?
What is the primary goal of econometrics in formulating a statistical model?
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What is an important job of an econometrician when evaluating a statistical model?
What is an important job of an econometrician when evaluating a statistical model?
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What is a crucial consideration when using econometric techniques?
What is a crucial consideration when using econometric techniques?
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What is an example of a restriction that economic theory may imply on a statistical model?
What is an example of a restriction that economic theory may imply on a statistical model?
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What is the main approach of this book in guiding the reader through econometric techniques?
What is the main approach of this book in guiding the reader through econometric techniques?
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Which type of model is ideally suited for analyzing policy changes on an individual level?
Which type of model is ideally suited for analyzing policy changes on an individual level?
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What is the primary purpose of econometric modeling?
What is the primary purpose of econometric modeling?
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What type of relationships do cross-sectional models describe?
What type of relationships do cross-sectional models describe?
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What type of data is required for analyzing 'what if' questions using cross-sectional relationships?
What type of data is required for analyzing 'what if' questions using cross-sectional relationships?
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What type of models describe differences between different individuals and changes in behavior over time?
What type of models describe differences between different individuals and changes in behavior over time?
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What has led to the increased attention to the modeling of macro-economic relationships and their dynamics?
What has led to the increased attention to the modeling of macro-economic relationships and their dynamics?
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What is the primary role of econometrics in empirical work in all fields of economics?
What is the primary role of econometrics in empirical work in all fields of economics?
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What is the limitation of introductory econometrics textbooks for applied researchers?
What is the limitation of introductory econometrics textbooks for applied researchers?
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What is the primary reason for the need for an accessible textbook on econometrics?
What is the primary reason for the need for an accessible textbook on econometrics?
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What area of economics has required and stimulated many theoretical developments in econometrics?
What area of economics has required and stimulated many theoretical developments in econometrics?
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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.
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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.
