Introduction to Labor Economics Chapter 1

2 Labor Economics Goals: Study how labor markets work and explain why some outcomes are more likely to occur than others Why did female LFP increase in the 1900s? How does immigration affect wages, labor supply, opportunities, etc of native workers? How do minimum wages affect the unemployment rate? Do wage and tax subsidies affect the demand for labor? What impact do occupational and health regulations have on hiring, wages, etc.?

3 Labor Economics, cont. Do human capital investment subsidies improve the well- being of disadvantaged workers? Why does wage inequality exist? What impact does affirmative action have on earnings, the number of minorities a firm hires, etc? How do unions affect labor markets? How do unemployment benefits affect the incidence of and length of spells?

4 Labor Market Participants Workers Firms The Government Together (supply and demand) determine E* and w*

5 Labor Market Participants: Workers Suppliers of labor (aggregate individual decisions to derive an upward-sloping labor supply curve) Goal: Strive to maximize well-being (utility) subject to constraints Determine: Whether or not to work How many hours to work Which skills to acquire Whether or not to quit a job Which occupation to work in Whether to join a union How much effort to put forth at work

6 Labor Market Participants: Firms Demanders of labor (aggregate individual decisions to derive a downward-sloping labor demand curve) Goal: Strive to maximize profits subject to constraints Determine: How many workers to employ Which workers to hire How much to pay each worker Whether to hire additional workers Whether to fire workers How much capital to employ Working conditions Length of the workweek

7 Labor Market Participants: The Government Regulations determine ground rules in the labor market Taxes on earnings Training subsidies Payroll taxes Affirmative action laws Minimum wages Worker condition regulations Immigration laws

8 Appendix: Econometrics Regression analysis: the manipulation of available data to answer positive (what is) and normative (what should be) questions y = dependent variable x = independent (explanatory) variable(s) m = slope = interpretation: for a 1-unit change in x, by how much does y change?

9 Regression Example: GPA Hours = number of hours spent studying Regression analysis attempts to fit the data with a line by minimizing the sum of squared errors