Final answer:
To evaluate the effect of education on GDP from 2000 to 2015, one must consider data collection, model choice, and ways to address OLS biases, such as using panel analysis to control fixed effects, assuming no omitted variables that are correlated with education and GDP, and that errors over time are not autocorrelated.
Step-by-step explanation:
To evaluate the effect of education level on GDP for the period of 2000 to 2015, one should create a research plan that includes data collection, choice of model, and potential methods to address biases. An Ordinary Least Squares (OLS) regression might be biased for several reasons, including omitted variable bias, measurement errors, and simultaneity.
Panel analysis could eliminate some of these biases, particularly those associated with time-invariant characteristics of countries that could be correlated with both education level and GDP. Panel data allows for controlling fixed effects that might impact the relationship between education and GDP.
The assumptions required for a valid panel analysis would include no omitted time-varying variables that are correlated with both education and GDP, random errors that do not correlate with explanatory variables across time, and no autocorrelation of errors over time.