Suppose you have 500 observations and you regress (measured in rupees per hour) on experience in the labour market, (measures in years), and on experience in the labour market squared, . Your estimated OLS equation is with standard errors , and respectively (in brackets). The estimated equation implies
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Suppose you have 500 observations and you regress wage (measured in rupees per hour) on experience in the labour market, exper (measures in years), and on experience in the labour market squared, (exper²). Your estimated OLS equation is ŵâĝê=3.73+0.298 exper-0.0061 exper² with standard errors 0.35, 0.041 and 0.0009 respectively (in brackets). The estimated equation implies (A) The returns to experience is strictly increasing (B) The returns to experience is strictly diminishing (C) The returns to experience is constant (D) Experience has no statistically significant effect on wage
Also written as: Suppose you have 500 observations and you regress wage (measured in rupees per hour) on experience in the labour market, exper (measures in years), and on experience in the labour market squared, (exper^2). Your estimated OLS equation is wage_hat=3.73+0.298 exper-0.0061 exper^2 with standard errors 0.35, 0.041 and 0.0009 respectively (in brackets). The estimated equation implies
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This question is on Log, quadratic and other functional forms, part of Dummy variables and functional forms in Econometrics.
Choosing and interpreting log-log, semi-log, quadratic and reciprocal specifications.
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