Panel Data Econometrics Flashcards

1
Q

What types of data are there?

A

Time series

Cross-sectional

Pooled

Panel

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2
Q

What is time series data?

A

Time series is a set of observations on the values that a variable takes at different times (daily, weekly, monthly, quarterly, annually, etc.).

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3
Q

What is cross-sectional data?

A

Cross-section are data on one or more variables collected at the same point in time.

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4
Q

What is pooled data?

A

Pooled data combine both time series and cross-sectional data. (Note: the cross sectional units differ i.e. in Year 1 we view firms A, B, C. in Year 2 we observe firms D, E, F)

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5
Q

What is panel data?

A

Panel or Longitudinal data are a special type of pooled data in which the same cross-sectional unit (a family or a firm) is surveyed over time.

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6
Q

What are Micro panels?

A
  • Data collected for a large number of individuals (in 100,000’s)
  • Collected over a short period of time
  • Can vary from a minimum of 2 years to a maximum rarely exceeding 10-20 years
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7
Q

What are Macro panels?

A
  • Usually include a number of countries over time
  • This may have a moderate number of countries (i.e. 20 OECD countries). Doesn’t normally exceed 100 countries
  • Observed annually over 20-60 years
  • Very high frequency data (i.e. stock indices varying over time)
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8
Q

What are the differences between macro and micro panels? (2)

A

Macro panels have to deal with such issues as non-stationarity, unit roots, structural breaks, cointegration (micro panels don’t have these issues)
Macro panels also may include cross-country dependence, which micro panels often don’t have to deal with due to firms/households being randomly sampled

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9
Q

What are the benefits of using panel data? (11)

A
  • Controlling for individual heterogeneity
  • Give more informative data, more variability, less collinearity between the variables, more degrees of freedom and more efficiency
  • Dynamics of adjustment (change, duration of economic stance, speed of adjustment to economic policy changes, intertemporal relations)
  • Identify and measure effects that are not detectible in pure-time series or pure-cross sectional data (i.e. does union membership increase wages? in panel data we can hold all other factors than job equal to see how much the wage changes)
  • Construct and test more complicated behavioural models than pure-time series or pure-cross sectional data
  • Biases resulting from aggregation over firms or individuals may be eliminated (micro panel data)
  • Give more informative data;
  • More variability (variation between states and variation within states);
  • Less collinearity among the variable;
  • More degrees of freedom;
  • More efficiency.
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10
Q

What are the limitations of using panel data? (5)

A

-Design and data collection problem (problems of coverage, nonresponse, recall, etc.)

  • Distortions in measurement error (i.e. incorrect recording of data, participants lying about habits etc.)
  • Selectivity problem (Self-selectivity, nonresponse, attrition)

–Self-Selectivity can be censored (one piece of info is missing i.e. wages), or truncated (multiple pieces of info are missing)

  • Short time-series dimension for micro panel
  • Cross-section dependence for macro panel
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11
Q

What are the sources of endogeneity? (3)

A
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