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Earnings Functions Attempt to Predict the Log of Earnings from a Set

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Essay

Earnings functions attempt to predict the log of earnings from a set of explanatory variables, both binary and continuous. You have allowed for an interaction between two continuous variables: education and tenure with the current employer. Your estimated equation is of the following type:  In Earn ^\widehat{\text { In Earn }} = β^\hat { \beta } 0 + β^\hat { \beta } 1 × Femme + β^\hat { \beta } 2 × Educ + β^\hat { \beta } 3 × Tenure + β^\hat { \beta } 4 x (Educ × Tenure)+ ∙∙∙
where Femme is a binary variable taking on the value of one for females and is zero otherwise, Educ is the number of years of education, and tenure is continuous years of work with the current employer. What is the effect of an additional year of education on earnings ("returns to education")for men? For women? If you allowed for the returns to education to differ for males and females, how would you respecify the above equation? What is the effect of an additional year of tenure with a current employer on earnings?


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Problem-Solving Abilities

The capacity to engage in a process that uses cognitive skills to achieve a goal or find an effective solution to a specific issue.

Bilingual Advantage

The cognitive benefits that come from being fluent in two languages, such as improved executive function and delayed onset of dementia.

Linguistic Determinism

The hypothesis that language shapes the way we think and determines what we can think about.

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A type of long-term memory for how to perform different actions and skills, essentially how to do things.

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