Final answer:
The estimation of B2 using Fixed Effects or First Differences in the given model depends on the dataset's characteristics and the time variance of the birth year variable. The ability to estimate B2 is not determinable without additional data details.
Step-by-step explanation:
The question pertains to the estimation of a model that includes a fixed effect or a variable that changes over time for each individual (worker). Specifically, the model in question is yit= B0+B1xit1 + B2xit2 + ai + Eit, where Xit2 represents a worker's birth year. The assertion that B2 can be easily estimated using Fixed Effects (FE) or First Differences (FD) estimators relates to the fact that these methods are designed to control for unobserved heterogeneity when it's time-invariant. This is particularly relevant when dealing with data where the birth year, which does not change over time for an individual, might be correlated with other individual-specific, time-invariant characteristics.
The feasibility to estimate B2 reliably using FD or FE will depend on the nature of the data and the specific attributes of the birth year variable within the model. If the birth year is strictly exogenous and varies within the panel data set, then FD or FE can provide consistent estimates. However, if the birth year does not vary over time within individuals in the dataset, typically FE and FD estimators cannot estimate the effect of time-invariant variables. Whether B2 can be easily estimated is not determinable without further information about the dataset's structure, variation, and the exact econometric context.