format where one row represents one observational unit for all points in time (for the example, the wide format would have only two (first example) or three (second example) rows of data with additional columns for each time-varying variable (income, age). Analysis A panel has the form where is the individual dimension and is the time dimension. A general panel data regression model is written as Different assumptions can be made on the precise structure of this general model. Two important models are the fixed effects model and the random effects model. Consider a generic panel data model: are individual-specific, time-invariant effects (for example in a panel of countries this could include geography, climate etc.) which are fixed over time., whereas is a time-varying random component. If is unobserved, and correlated with at least one of the independent variables, then it will cause omitted variable bias in a standard OLS regression. However, panel data methods, such as the fixed effects estimator or alternatively, the first-difference estimator can be used to control for it. If is not correlated with any of the independent variables, ordinary least squares linear regression methods can be used to yield unbiased and consistent estimates of the regression parameters. However, because is fixed over time, it will induce serial correlation in the error term of the regression. This means that more efficient estimation techniques are available. Random effects is one such method: it is a special case of feasible generalized least squares which controls for the structure of the serial correlation induced by . Dynamic panel data Dynamic panel data describes the case where a lag of the dependent variable is used as regressor: The presence of the lagged dependent variable violates strict exogeneity, that is, endogeneity may occur. The fixed effect estimator and the first differences estimator both rely on the assumption of strict exogeneity. Hence, if is believed to be correlated with one of the independent variables, an alternative estimation technique must be used. Instrumental variables or GMM techniques are commonly used in this situation, such as the Arellano–Bond estimator. Data sets which have a panel design Russia Longitudinal Monitoring Survey (RLMS) German Socio-Economic Panel (SOEP) Household, Income and Labour Dynamics in Australia Survey (HILDA) British Household Panel Survey (BHPS) Survey of Family Income and Employment (SoFIE) Survey of Income and Program Participation (SIPP) Lifelong Labour Market Database (LLMDB) Longitudinal Internet Studies for the Social