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Fall 2017

This lecture explores the concepts of unemployment, including its measurement, causes, and effects. It examines the distinction between frictional, structural, and cyclical unemployment and discusses their implications for policymakers. The lecture also analyzes the declining work hours among certain demographic groups and presents ongoing research on the relationship between manufacturing, housing, and labor demand.

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Fall 2017

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  1. Fall 2017 Macroeconomics Note: Lectures cannot be reprinted or distributed without express written consent of Erik Hurst.

  2. U.S. Non Farm Employment: 1970M1-2017M8 Note: Up through August 2017 (Shaded Years are Recessions)

  3. Unemployment Rate: 1970M1 – 2017M8

  4. Unemployment Duration: 1970M1 – 2017M8

  5. Broad Questions of Interest About Unemployment • What is a recession? • Why would unemployment continue to increase even though a recession has ended? • Why has the nature of unemployment coming out of recessions changed over time? • Why does unemployment exist? • Can policymakers affect the unemployment rate?

  6. How is Unemployment Measured? • Standardized Definition of the Unemployment Rate: Unemployed = jobless but looking for a job Labor Force = #Employed + #Unemployed Unemployment Rate = (# Unemployed) / (Labor Force) This is the definition used in most countries, including the U.S. U.S. data: http://stats.bls.gov/eag.table.html U.S. measurement details: http://stats.bls.gov/cps_htgm.htm Issues: Discouraged Workers, Underemployed, Measurement Issues • Readings: 18 and 19 from Reading List

  7. Components of Unemployment • Flow of people into the unemployment pool o Flow into unemployment from employment (job loss) o Flow into unemployment from out of labor force (stop being discouraged) • Flow of people out of the unemployment pool o Flow out of unemployment into employment (job finding) o Flow out of unemployment out of labor force (discouraged workers)

  8. A Few More Definitions • Labor Force Participation Rate o Labor Force/ Population (age 16+) • Employment Rate o Employed / Population (age 16+) o Employment rate defined out of total population as opposed to labor force. o Also referred to as employment to population rate (EPOP).

  9. Labor Force Participation Rate

  10. Employment to Population Rate: Men

  11. Employment to Population Rate: Men 25-54

  12. Employment to Population Rate: Men 16-24

  13. Employment to Population Rate: Women

  14. Employment to Population Rate: Women 25-54

  15. Types of Unemployment • Frictional Unemployment: Result of Matching Behavior between Firms and Workers. • Structural Unemployment: Result of Mismatch of Skills and Employer Needs • Cyclical Unemployment: Result of output being below full-employment. Individuals have the desire to work and the skills to work, yet cannot find a job. • Is Zero Unemployment a Reasonable Policy Goal? • No! Frictional and Structural Unemployment may be desirable (unavoidable).

  16. Why is the Distinction Important? • How much of the current unemployment is structural vs. cyclical? • This is a current debate among policy makers (and a question I am trying to answer in my own research) • Why could there be structural unemployment? o Some industries boomed inefficiently during the early 2000s (construction) and need to retrench. The jobs being created now are not in those industries (where unemployment is high). o Some industries were in secular decline during the 2000s (manufacturing). The jobs being created now are not in those industries. o Workers in manufacturing and construction need to be reallocated to other sectors.

  17. Some Other Labor Market Facts

  18. Ed < 16: 220 hours/year (13%) since 2000

  19. Ed ≥ 16: 160 hours/year (7.5%) since 2000 Ed < 16: 220 hours/year (13%) since 2000

  20. 21-30, Ed < 16: 270 hrs/year (18%) since 2000 31-55, Ed < 16: 190 hrs/year (10%) since 2000

  21. Summary: Declining Hours During 2000s (Excluding Full Time Students)

  22. Summary: Declining Hours During 2000s (Excluding Full Time Students)

  23. Summary: Declining Hours During 2000s (Excluding Full Time Students) • Summary • Very large declines in annual work hours in U.S. since 2000 • Declines are larger for men, less educated and young • Most of the adjustment on the extensive margin

  24. Summary: Declining Hours During 2000s (Excluding Full Time Students) • Question: Why have the hours of prime age workers fallen so sharply during the 2000s? • What explains the heterogeneity across groups?

  25. My Current Research Goal: o Explain declines in employment for less educated workers broadly o Explain why the declines were larger for young men. Focus on: o Labor demand stories (decline in manufacturing demand) o Labor supply stories (increases in leisure technology) Note: In topic 2, we will formally model the labor market deriving expressions for labor demand and labor supply from producer and consumer theory.

  26. Current Research:Manufacturing, Housing and Labor Demand

  27. Labor Demand and Less Educated Workers Big decline in manufacturing employment during the early 2000s. This usually depresses wages and employment of non-college individuals. Housing boom during the early 2000s lifted the employment and wages of lower skilled individuals (by propping up construction and housing related services). Housing boom “masked” the structural decline in manufacturing. The manufacturing decline is “permanent” while the housing boom was temporary. This is the focus of a series of papers with Kerwin Charles (Harris School) and Matt Notowidigdo (Northwestern). Preview some background patterns now. Will talk about the identification later in the course. About 40% of increase in non-employment during the 2000-2012 period can be explained by declining manufacturing.

  28. U.S. Manufacturing Employment, BLS

  29. U.S. Manufacturing Employment, BLS 3.5 Million Manufacturing Jobs Lost 2000-2007

  30. No Change During 2000s 6 p.p. decline 2000-2015

  31. Summary: Labor Demand Stories Housing boom “masked” the structural decline in manufacturing. The manufacturing decline is “permanent” while the housing boom was temporary. This is the focus of a series of papers I have with (with Kerwin Charles and Matt Notowidigdo). Structural forces have been weakening the labor market for low skilled workers (both men and women) since the early 2000s. Would have shown up before the Great Recession had it not been for the housing boom. Because of the housing boom, 2007 is not a “steady state” to which the labor market will return.

  32. Summary: Lasting Effect of Housing Boom This is the focus of another set of my research papers (with Kerwin Charles and Matt Notowidigdo). Housing boom causally deterred human capital for young households (both men and women). Mechanism – labor markets were relatively “hot” for young workers in places where a housing boom occurred. Affected community college and trade school enrollment. No effect on four year degrees. Effects were persistent! People who forwent college in their 20s (during the mid 2000s) did not go back to school in their 30s (after recession).

  33. Current Research:Changes in Leisure Technology and the Labor Supply of Young Men

  34. Major Innovations in Computer Leisure Technology Starting in Mid-2000s • Able to engage in leisure activities easily with others at different locations. • Social media – Facebook started in 2004; grew from 12 million to 360 million users between 2006 and 2009. • Video games – Sony, Microsoft and Nintendo all released consoles in 2005/2006 that allowed online capabilities. Video game revenues increased by 50 percent 2006-2009 (were flat between 2000 and 2006). • Large multiplayer online video games developed over same time period. World of Warcraft started around 2005 and had 10 million monthly users by 2009. • iPhone released in 2007. Smart phones take off. • Time series trends in leisure technologies occurred around same time as Great Recession. Need theory to tease the two apart.

  35. Changing Time Allocation of Men (Hours Per Week): Changes Between 2004-07 and 2012-15

  36. Hours per Week of Leisure Time, Young Men +2.5 +1.9 (+1.4)

  37. Hours per Week of Leisure Time, By Employment Status

  38. Distribution of Computer Time, Non-Working Young Men • Only one day of data for each individual

  39. Reported Happiness From General Social Survey, By Sex-Age-Skill Group

  40. U.S. Cohabitation With Parent or Close Relative, American Community Survey

  41. U.S. Cohabitation Patterns By Employment Status, Men 21-30, Ed = All American Community Survey

  42. Employment Rate Young and Older Men, OECD Country Average, (OECD Statistics)

  43. Big Picture Conclusions • Technology has had large effects on both labor demand and labor supply for lower skilled workers. • Particularly large effects for young men (who historically have a strong attachment to the labor force). • Is there anything on the horizon to change participation rates? • Long run consequences? Job prospects in their 30s? Budgetary aspects? • Social consequences?

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