Interpret the coefficient estimate on Married in column 2, commenting on both magnitude and statistical significance II. Consider a dataset of 545 men, who all worked every year from 1980 through 1987.You want to understand how certain demographic characteristics affect the wages ofthese men. The dependent variable in your regression is log(wage). Your independentvariables include: education (in years), race dummies (Black, Hispanic), experience (inyears), experience squared, a dummy for whether the individual is married (married),and a dummy for whether the individual is a member of a labor union (union). Standarderrors are in parentheses.log(wage)OLSFEEducation.091(.005)Black-.139(.024)Hispanic.016(.021)Experience.067.035(.014)-.0024(.003)Experience-squared-.0052(.0008) (.0007)Married.108.047(.016)(.018)Union.182.080(.017)(.019)Individual Fixed Effects?NoYesR-squared.15.67

Coefficient Estimate: The relationship between an independent variable and a dependent variable can be described by the coefficient estimate. It states that the mean change in the dependent variable for one unit of change in the independent variable with other variables as constant. Interpretation : Assuming dummy variables as 1 for married and 0 for unmarried, we can interpret that if the married coefficient is positive then the married group has more wage, and if it is negative then the married group will have less wage. Since the coefficient estimate of the marriage is 0.047 it can be said that the average wage is higher by 0.047 for married individuals.