Panel Data Econometrics Flashcards
What types of data are there?
Time series
Cross-sectional
Pooled
Panel
What is time series data?
Time series is a set of observations on the values that a variable takes at different times (daily, weekly, monthly, quarterly, annually, etc.).
What is cross-sectional data?
Cross-section are data on one or more variables collected at the same point in time.
What is pooled data?
•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)
What is panel data?
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.
What are Micro panels?
- 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
What are Macro panels?
- 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)
What are the differences between macro and micro panels? (2)
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
What are the benefits of using panel data? (11)
- 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.
What are the limitations of using panel data? (5)
-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
What are the sources of endogeneity? (3)