Chapter 10 - Panel data
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What is panel data?

  • Data that only includes cross-sectional elements
  • Data that comprises both time series and cross-sectional elements (correct)
  • Data that is collected from a single entity over time
  • Data that only includes time series elements

    • What is the main advantage of using panel data techniques?

  • They can address a broader range of issues and examine how variables change dynamically over time (correct)
  • They allow for the contemporaneous relationships between the error terms in the equations.
  • They assume that the intercepts are constant across time and vary across entities.
  • They assume a constant relationship between explained and explanatory variables cross-sectionally and over time

    • What is the main advantage of using panel data techniques?

  • They can address a broader range of issues and examine how variables change dynamically over time (correct)
  • They allow for the contemporaneous relationships between the error terms in the equations.
  • They assume that the intercepts are constant across time and vary across entities.
  • They assume a constant relationship between explained and explanatory variables cross-sectionally and over time

    • What is panel data?

    <p>Data that comprises both time series and cross-sectional elements</p> Signup and view all the answers

    What is the difference between fixed effects and random effects models?

    <p>Random effects models have fewer parameters to estimate and should produce more efficient estimation than the fixed effects approach.</p> Signup and view all the answers

    What is the purpose of pooled regression?

    <p>To assume that the average values of variables and relationships between them are constant over time and across all cross-sectional units</p> Signup and view all the answers

    What is the difference between fixed effects and random effects models?

    <p>Random effects models have fewer parameters to estimate and should produce more efficient estimation than the fixed effects approach.</p> Signup and view all the answers

    What is the purpose of pooled regression?

    <p>To assume that the average values of variables and relationships between them are constant over time and across all cross-sectional units</p> Signup and view all the answers

    What is the difference between balanced and unbalanced panel data?

    <p>Unbalanced panel data has missing observations for some entities and/or time periods</p> Signup and view all the answers

    What is the within transformation used in panel data analysis?

    <p>Subtracting the time-mean of each entity away from the values of the variable</p> Signup and view all the answers

    What is the within transformation used in panel data analysis?

    <p>Subtracting the time-mean of each entity away from the values of the variable</p> Signup and view all the answers

    What is the difference between balanced and unbalanced panel data?

    <p>Unbalanced panel data has missing observations for some entities and/or time periods</p> Signup and view all the answers

    What is the seemingly unrelated regression (SUR) framework used for?

    <p>To model several closely related variables over time</p> Signup and view all the answers

    What is the seemingly unrelated regression (SUR) framework used for?

    <p>To model several closely related variables over time</p> Signup and view all the answers

    What is the within transformation?

    <p>Subtracting the time-mean of each entity away from the values of the variable</p> Signup and view all the answers

    What is the within transformation?

    <p>Subtracting the time-mean of each entity away from the values of the variable</p> Signup and view all the answers

    What is the main factor contributing to the decline in profitability of banks in the US since the 1980s?

    <p>Increased competition.</p> Signup and view all the answers

    What is the main factor contributing to the decline in profitability of banks in the US since the 1980s?

    <p>Increased competition.</p> Signup and view all the answers

    What is the purpose of fixed effects models?

    <p>To account for unobserved individual-specific effects that are correlated with the regressors</p> Signup and view all the answers

    What is the purpose of fixed effects models?

    <p>To account for unobserved individual-specific effects that are correlated with the regressors</p> Signup and view all the answers

    What is the fixed effects model appropriate for?

    <p>When there are unobserved individual-specific effects that are correlated with the regressors.</p> Signup and view all the answers

    What is the fixed effects model appropriate for?

    <p>When there are unobserved individual-specific effects that are correlated with the regressors.</p> Signup and view all the answers

    What is the purpose of the random effects model?

    <p>To propose different intercept terms for each entity</p> Signup and view all the answers

    What is the purpose of the random effects model?

    <p>To propose different intercept terms for each entity</p> Signup and view all the answers

    What is the two-way error component model used for?

    <p>To combine entity-fixed and time-fixed effects.</p> Signup and view all the answers

    What is the two-way error component model used for?

    <p>To combine entity-fixed and time-fixed effects.</p> Signup and view all the answers

    What is the difference between the fixed effects and random effects models?

    <p>The random effects model assumes that the intercepts are constant across time and vary across entities, while the fixed effects model assumes the opposite</p> Signup and view all the answers

    What is the difference between the fixed effects and random effects models?

    <p>The random effects model assumes that the intercepts are constant across time and vary across entities, while the fixed effects model assumes the opposite</p> Signup and view all the answers

    What is the purpose of seemingly unrelated regression (SUR)?

    <p>To model several closely related variables over time and allow for the contemporaneous relationships between the error terms in the equations</p> Signup and view all the answers

    What is the main concern raised about the UK retail banking sector?

    <p>Lack of sufficient competitive forces.</p> Signup and view all the answers

    What is the main concern raised about the UK retail banking sector?

    <p>Lack of sufficient competitive forces.</p> Signup and view all the answers

    What is the purpose of seemingly unrelated regression (SUR)?

    <p>To model several closely related variables over time and allow for the contemporaneous relationships between the error terms in the equations</p> Signup and view all the answers

    What is the main concern about the lack of sufficient competitive forces in British banking?

    <p>All of the above</p> Signup and view all the answers

    What is the transformation involved in the generalized least squares (GLS) procedure used in the random effects model?

    <p>Adding the time-mean of each entity to the values of the variable</p> Signup and view all the answers

    What is the transformation involved in the generalized least squares (GLS) procedure used in the random effects model?

    <p>Adding the time-mean of each entity to the values of the variable</p> Signup and view all the answers

    What is the main concern about the lack of sufficient competitive forces in British banking?

    <p>All of the above</p> Signup and view all the answers

    What is the main reason for the decline in the number of banks in the US since the 1980s?

    <p>Consolidation, with larger banks acquiring smaller ones.</p> Signup and view all the answers

    What is the main reason for the decline in the number of banks in the US since the 1980s?

    <p>Consolidation, with larger banks acquiring smaller ones.</p> Signup and view all the answers

    Study Notes

    1. Panel data comprises both time series and cross-sectional elements.
    2. A panel keeps the same entities and measures some quantity about them over time.
    3. Pooled regression assumes that the average values of variables and relationships between them are constant over time and across all cross-sectional units.
    4. Making full use of panel data has important advantages in addressing a broader range of issues and examining how variables change dynamically over time.
    5. Seemingly unrelated regression (SUR) framework can be used to model several closely related variables over time.
    6. SUR allows for the contemporaneous relationships between the error terms in the equations.
    7. Fixed effects models allow the intercept in the regression model to differ cross-sectionally but not over time, while all of the slope estimates are fixed both cross-sectionally and over time.
    8. There are balanced and unbalanced panel data, and the same techniques are used in both cases.
    9. The fixed effects model decomposes the disturbance term into an individual specific effect and the remainder disturbance that varies over time and entities.
    10. The fixed effects model is appropriate when there are unobserved individual-specific effects that are correlated with the regressors.
    • Panel data techniques assume a constant relationship between explained and explanatory variables cross-sectionally and over time.
    • The fixed effects model assumes that the intercepts are constant across time and vary across entities.
    • The within transformation involves subtracting the time-mean of each entity away from the values of the variable.
    • Time-fixed effects models assume that the average value of y changes over time but not cross-sectionally.
    • A two-way error component model combines entity-fixed and time-fixed effects.
    • The UK retail banking sector has undergone significant changes over the past 30 years due to deregulation, mergers, and technology.
    • Concerns have been raised about the lack of sufficient competitive forces in British banking.
    • The high concentration of market share among a small number of large banks and recurring profits are cited as evidence of insufficient competition.
    • Restrictive practices and barriers to entry are also mentioned as potential issues.
    • Fixed effects models can be used to investigate competition in banking.
    • Banks in the US have been experiencing a decline in profitability since the 1980s.
    • The decline in profitability is attributed to factors such as increased competition, deregulation, and technological advancements.
    • The profitability of banks is also affected by macroeconomic conditions.
    • However, revenue to total assets is largely unaffected by macroeconomic conditions.
    • Banks appear to have been more profitable when GDP was high.
    • Banks have responded to the decline in profitability by cutting costs and increasing efficiency.
    • Consolidation has also occurred in the banking industry, with larger banks acquiring smaller ones.
    • The number of banks in the US has decreased significantly since the 1980s.
    • The decline in the number of banks has been more pronounced in rural areas.
    • Despite the decline in the number of banks, access to banking services has not significantly decreased.
    1. The random effects model proposes different intercept terms for each entity.
    2. The intercepts are constant over time, and the relationships between variables are the same cross-sectionally and temporally.
    3. The intercepts for each cross-sectional unit are assumed to arise from a common intercept plus a random variable.
    4. The random deviation of each entity's intercept term is measured by the random variable.
    5. The random effects panel model requires that the cross-sectional error term has zero mean, is independent of the observation error term, has constant variance, and is independent of the explanatory variables.
    6. Parameters are estimated consistently but inefficiently by OLS, and a generalized least squares procedure is usually used.
    7. The transformation involved in this GLS procedure is to subtract a weighted mean of the observations over time.
    8. The random effects model is valid when the composite error term is uncorrelated with all of the explanatory variables.
    9. The random effects model has fewer parameters to estimate and should produce more efficient estimation than the fixed effects approach.
    10. A study by de Haas and van Lelyveld (2006) employs a random effects panel regression to examine whether domestic and foreign banks react differently to changes in economic activity and banking crises.

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    Description

    This quiz tests your knowledge of panel data techniques and their applications in the banking sector. It covers various models, including fixed effects and random effects, and their assumptions, advantages, and limitations. You will also learn about the factors affecting profitability in the US and UK banking industries, such as competition, deregulation, and technological advancements. Additionally, the quiz includes examples of studies that use panel data models to investigate the behavior and performance of domestic and foreign banks in different economic conditions. Whether you are a student

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