FIN 30220: Macroeconomics Labor Markets

The US Labor Market by the numbers…* Total Population 321M “Ineligible to work” 71M Under 16 years old Inmates of institutions (penal, mental, homes for the aged) Active duty military Employed 149M *As reported by the household survey (Bureau of Labor Statistics) Unemployed 8.5M Not Participating 92.5M To be considered “unemployed”, you must have looked for work over the last 30 days. Otherwise, you are “not participating”

Total Population 321M “Ineligible to work” 71M Employed 149M Unemployed 8.5M Not Participating 92.5M The US Labor Market by the numbers…* *As reported by the household survey (Bureau of Labor Statistics) Civilian Employment-Population Ratio Total employment divided by the eligible population Eligible Population = Employed + Unemployed + Not Participating *100 = 59.6% “Official” Unemployment Rate (U-3) Unemployment divided by the Labor Force Labor Force = Employed + Unemployed *100 = 5.4% Participation Rate labor force divided by the eligible population *100 = 63% 250

NBER Recession Dates Unemployment Rate Unemployment in the US *Source: Bureau of Labor Statistics Non Recession Average: 5.8% Recession Average: 6.1% Current = 5.5% December % May %

To be considered “employed” you only need to have a job (no distinction between full time or part time)To be considered “unemployed”, you must have looked for work over the last 30 days. Otherwise, you are “not participating”. Alternate Measures of Unemployment in the U.S. Discouraged Workers Persons who are not in the labor force Want to and are available to work Have looked for work over the year, but not over the last 4 weeks Specific reason cited for not looking for work is that they don’t believe there is a job available Marginally Attached Workers Persons who are not in the labor force Want to and are available to work Have looked for work over the year, but not over the last 4 weeks Any reason cited for lack of job search Part Time for Economic Reasons Working less than 35 hours per week Want to and are available to work full time Gave an economic reason (Hours cut, unable to find full time work) for lack of a full time job

Alternate Measures of Unemployment in the U.S. *From the latest household survey, BLS CategoryMay 2014 Eligible Population250M Labor Force157.5M Employed149M Unemployed8.5M Discouraged Workers600,000 Marginally Attached Workers1.8M Part time for Economic Reasons6.6M U-4 Unemployment Rate Unemployed plus discouraged workers divided by the labor force plus discouraged workers *100 = 5.8% U-5 Unemployment Rate Unemployed plus discouraged workers plus marginally attached divided by the Labor Force + discouraged workers + marginally attached *100 = 6.8% U-6 Unemployment Rate Unemployed plus discouraged workers plus marginally attached workers plus part time for economic reasons divided by the Labor Force + discouraged workers + marginally attached workers *100 = 10.9% Recall, the “official” (U-3) unemployment rate is 5.5% Note: U-1 unemployment deals with long term unemployment and U-2 deals with temporary jobs

Let’s look at the US over the years since the last recession… Peak = 10.0% October 2009 Current = 5.5% RecessionRecovery January %

Average = -361,000/mo. Average = 143,000/mo. Monthly change in payrolls 280,000 in May million jobs lost during the recession 10 million jobs gained since the end of the recession June 2009

Let’s do a back of the envelope calculation….population grows at around 1.5% per year. Let’s assume everybody enters the workforce at 16 and retires after 45 years. Now (2015) 45 years ago (1970) Eligible population = 107M 1.5% x 107M = 1.60M Entering the workforce 1.60M retiring Eligible population = 208M 1.5% x 205M = 3.12M Entering the workforce 3.12M – 1.60M = 1.52M / 12 = 126,000 per month! 16 years ago (1999) 61 Years ago (1954) 1.60M

8 million jobs lost during the recession 8,000,000 17,000 = 470 months To get back to “normal” (~40 years) 156,000 Jobs created - 126,000 to satisfy population growth 33,000 lost jobs recovered per month June ,000 Jobs created - 126,000 to satisfy population growth 17,000 lost jobs recovered per month Average = 143,000/mo.

Average = -177,000 Average = 265, ,000 Jobs created - 123,000 to satisfy population growth 142,000 lost jobs recovered per month 3,000, ,000 = 21 months To get back to “normal” (~2 years) 3,000,000 jobs lost For comparison purposes, during the recovery following the recession, we created almost twice as many jobs per month

Lets compare the current recession/recovery to the last few 2 years How can the unemployment rate drop so quickly with so few jobs being created? Beginning of recovery Recession Beginning

RecessionRecovery Let’s look at the US over the years since the last recession… January 2007October 2009May 2015 CategoryJan 2007 Eligible Population230M Labor Force153M Employed146M Unemployed7M Employment Rate63.5% Unemployment Rate4.6% Participation Rate66.5% CategoryOct 2009 Eligible Population237M Labor Force154M Employed139M Unemployed15M Employment Rate58.6% Unemployment Rate10.0% Participation Rate64.9% CategoryMay 2015 Eligible Population250M Labor Force157.5M Employed149M Unemployed8.5M Employment Rate59.6% Unemployment Rate5.5% Participation Rate63% The primary reason for the decline in the unemployment rate over the past 6 years is the drop in labor force participation! If we had the same participation rate today as we did in 2007, the unemployment rate would be 10.3%!

This decline in labor force participation began it’s decline prior to the last recession….. Recession Peak = 67.2% January 2001 Peak = 63% Current Beginning of Women’s Liberation Movement (1967 ) 59.7%

Labor Participation Rate - Women Labor Participation Rate - Men The Women’s Liberation movement isn’t 100% of this shift, but it’s a big part!

Labor Participation Rate: Labor Participation Rate: 55+ Some people claim that the drop is participation is baby boomers taking early retirement…not the case!!

A decline is participation isn’t the only thing “new” about our current situation… *From the latest household survey, BLS CategoryMay 2015 Unemployed (5.5%)8.5M100% Less than 5 weeks2.4M28% Between 5 and 14 weeks2.5M29% Between 15 and 26 weeks1.3M15% Over 26 weeks2.3M28% CategoryOct 2000 Unemployed (5.3%)6.6M100% Less than 5 weeks3M45% Between 5 and 14 weeks2.3M40% Between 15 and 26 weeks0.6M9% Over 26 weeks0.7M6% *From the Nov household survey, BLS

CategoryMay 2015 Unemployed (5.5%)8.5M 6.5 weeks2.4M 13 weeks2.5M 26 Weeks1.3M 52 weeks2.3M Let’s Simplify a little… AUGFEBMARAPRMAYJUNEJULYJANSEPTOCTNOVDEC So, our unemployed looks roughly like this for 2015… 2.3M 1.3M 2.5M 2.4M Total = 8.5 CategoryTotal for 2015 % for 2015 Unemployed34.1M100% 6.5 weeks19.2M56% 13 weeks10M29% 26 Weeks2.6M8% 52 weeks2.3M7% Duration of Unemployment Length of unemployment spell % of total unemployed in a year

Average = 15 weeks Current = 30 weeks It’s currently taking people twice as long as it used to find a job… Duration of unemployment

Wages in the US…* *In 2014, Based on a 40 hour work week, 50 weeks per year Average hourly compensation $25/hr. Montgomery Moran $7.25/hr. Minimum wage for tipped employees $13,489/hr. Steven Ells $13,471/hr. Howard Schultz $10,285/hr. Minimum wage (Federal) Average CEO Pay** **According to data compiled by the AFL-CIO, the average CEO pay at 327 of the nation's biggest companies $7,000/hr. $2.13/hr.

Median Weekly Real Earnings (2015 Dollars) Current $800/wk. (~$20/hr.*) *Based on a 40 hour week Jan $784/wk. (~$19.60/hr.*)

Median Weekly Real Earnings (2015 Dollars) Men $885/wk. (~$22/hr.) Women $724/wk. (~$18/hr.*) Women’s % of Men *Based on a 40 hour week

Index: 1947 = 100 Since the late 1970’s we have seen the emergence of a “wage gap”. That is, we see a difference between productivity and wages

Average Weekly Hours in the US Current 33.7hrs./wk hrs./wk. 12.5%

Real Median Household Income in the US (2013 Dollars) Current (2013) $52,000 January 1999 $57,000 January 1989 $53,000 10% Decline

GDP Time Trend (Average growth) The business cycle is a repeated pattern of recessions followed by recoveries Recession (Below Trend Growth) Recovery (Above Trend Growth) Peak Trough Peak Recall, that we are interested in understanding the business cycle…

After removing the long term trend, we end up with a series that looks like this (% deviation from trend) % Deviation From Trend Time 0 Trough Peak Recession GDP Recovery

Peak TroughIndustrial Production (% Deviation from Trend) Correlation =.77 Employment (% Deviation from Trend) Total Employment is highly pro-cyclical…

Trough Peak Deviation from Trend Correlation =.12 Real wages are pro-cyclical….barely!

At some point in time, you have a fixed number of trees (Capital) and workers Those workers/capital combine with productivity to produce apples (output) OR Those apples are allocated either towards consumption or investment (planting them to grow new trees) For a given capital stock and productivity level, labor markets determine total employment Recall the apple orchard story….

Labor Markets Total employment (total hours worked) Real wages Households choose how much to work Businesses choose how many hours to hire Equilibrium employment Equilibrium real wage

Labor Markets Recall that Output = Income Labor Income + Capital Income Predetermined Employment will determine total production (GDP) = = Labor Income

Labor Markets If real wages are too high, we have excess supply of labor…this should put downward pressure on wages If real wages are too low, we have excess demand for labor…this should put upward pressure on wages

Labor Demand We assume that labor markets are populated by perfectly competitive firms Why is this important? These firms are making hiring decisions to maximize profits. Capital costs (fixed) Nominal Wage rate (fixed) Price of Output (fixed)

These firms use a production process that exhibits diminishing marginal productivity – that is as labor rises, its contribution to production of output shrinks

These firms are making hiring decisions to maximize profits. Consider what happens to profits if we change labor a little bit… Value marginal product of labor Businesses equate the nominal value of an hour of labor with the nominal wage Businesses equate the real value of an hour of labor with the real wage OR

Profits are Decreasing Profits are increasing Profits are constant (maximized) Profits are maximized when benefits and costs are equated at the margin!

As wages fall, the marginal cost of labor for businesses drops. This allows them to profitably expand their workforces – even in the light of diminishing marginal returns to labor. So, these perfectly competitive businesses observe a real wage and make a profit maximizing decision of how much labor to hire. Those decisions are recorded in labor demand.

Suppose the economy experiences an increase in productivity…. This increase in productivity not only raises total output for every hour of labor worked, but increases the marginal product of every hour worked

As events occur that influence the value of labor at the margin these businesses re-evaluate their hiring decisions and adjust their workforce accordingly. This increase in labor productivity increases labor demanded.

Labor Supply Just as businesses make decisions to maximize profits, we make decisions to maximize our utility Make ourselves as happy as possible We only have a couple requirements for utility functions Utility is increasing in consumption (i.e. we like to buy things!) Utility is decreasing in labor (we don’t like to work) Utility exhibits diminishing marginal utility (the more we have of anything, the less it is worth to us at the margin) Leisure time Real Consumption Total Utility (Happiness)

Let’s suppose the following…you have a job opportunity that pays $12 an hour. You can work as much or as little as you want. Further, assume that the only good to buy is pizza and a pizza costs $10. Finally, assume that you have scholarship that pays you $20 per week (you don’t have to work for the stipend). How many hours would you choose to work? Hours available: 24 hrs./day - 8 hrs./day (sleep) 16 hrs./day*7 days/wk. = 112 hrs. Nominal Wage = $12/hr. Price (Pizza) = $10 Real Wage = 1.2 Pizza/Hr. Non-Labor Income = $20/wk. Real Non-Labor Income = 2 Pizza/wk. No Work Labor Income = $0 Stipend = $20 Total Income = $20 Pizzas Bought = 2 Work 30 Hrs. Labor Income = $360 Stipend = $20 Total Income = $380 Pizzas Bought = 38 Work 112 Hrs. Labor Income = $1,344 Stipend = $20 Total Income = $1,364 Pizzas Bought = (Real Wage)

What you choose to do depends on your preferences! Leisure time Real Consumption Total Utility (Happiness) 1 hour of leisure. What's that leisure worth to you? If you work 1 additional hour, what is it cost you? If you work 1 additional hour, what do you gain? Value of an hour of leisure 1.2 pizzas (the real wage). How much are those pizzas worth to you? Number of pizzas you get per hour of work (real wage) Value of a pizza

Just like with businesses, when we maximize our utility (happiness), we equate costs and benefits at the margin) Benefits of workingCost of working = Let’s rewrite this… Marginal Rate of Substitution Marginal Rate of substitution measures the value of leisure in terms of consumption

Leisure time Real Consumption Total Utility (Happiness) We only have a couple requirements for utility functions Utility is increasing in consumption (i.e. we like to buy things!) Utility is decreasing in labor (we don’t like to work) Utility exhibits diminishing marginal utility (the more we have of anything, the less it is worth to us at the margin) High marginal utility of leisure Low Marginal Utility of Consumption High MRS As you work more, consumption increases and the marginal utility of that consumption falls As you work more, leisure falls and the marginal utility of that leisure increases Low marginal utility of leisure High Marginal Utility of Consumption Low MRS

(Real Wage) Work 40 Hrs. Labor Income = $480 Stipend = $20 Total Income = $500 Pizzas Bought = 50 Utility is decreasingUtility is increasing Of all the affordable choices, the one that equates costs and benefits at the margin is the best choice!

Work 50 Hrs. (nominal wage = $15) Labor Income = $750 Stipend = $20 Total Income = $770 Pizzas Bought = 77 Suppose that you get a raise…your nominal wage increases to $15 (real wage is now 1.5) Possibility #1: Labor Supply Increases (Substitution Effect) The substitution effect generates a labor supply curve that’s upward sloping (normal)

Work 35 Hrs. (nominal wage = $15) Labor Income = $525 Stipend = $20 Total Income = $545 Pizzas Bought = 54.5 Suppose that you get a raise…you nominal wage increases to $15 (real wage is now 1.5) Possibility #2: Labor Supply decreases (Income Effect) The income effect generates a labor supply curve that’s downward sloping (weird)

So, which is it? Possibility #2: Labor Supply decreases (Income Effect) We usually assume the income effect dominates! Possibility #1: Labor Supply Increases (Substitution Effect) OR

Suppose that your stipend increases to $200/wk. (Wage rate is still $12) This is a pure income effect (the wage didn’t change, so there is no substitution effect) Labor supplied declines (labor supply shifts left) Work 30Hrs. (nominal wage = $12) Labor Income = $360 Stipend = $200 Total Income = $560 Pizzas Bought = 56

Labor Markets – Equilibrium Households choose how much to work Businesses choose how many hours to hire Real Wage Total Hours Now, we just need to put the pieces together and solve for an equilibrium wage

Labor Markets – Long Run dynamics Long term productivity growth raises the value of labor at the margin – increasing labor demand As our incomes rise, the value of our leisure time increases – labor supply drops Over the long term, real wages and employment rise

Labor Markets – Business cycle dynamics During economic expansions, labor productivity is above trend…the pushes labor demand up – employment and real wages rise above trend During recessions, labor productivity is below trend…this pushes labor demand down – employment and real wages fall below trend An increase (decrease) in employment raises (decreases) production.

% Deviation From Trend Time 0 Trough Peak Recession GDP Recovery During recessions, productivity declines. Labor demand falls – employment and real wages fall. During recoveries, productivity increases. Labor demand rises – employment and real wages increase. Real WageEmploymentProductivity GDP +++ Predicted Correlations Real Wages Employment Productivity

Correlations With GDP The only problem we have is explaining the low correlation between real wages and GDP Some Suggestions Are we valuing labor contracts correctly? Have we calculated real wages correctly? Do wages actually adjust (most labor contracts are fixed for extended periods) Does minimum wage affect this analysis? Is our story correct? Our story for labor supply says that higher wages increase hours worked In Theory Empirically At the individual level, labor supply is very inelastic At the macro level, there is labor supply is very elastic Real WageEmploymentProductivity Actual + (.12) + (.77) + (.67) Predicted +++

Example: Oil Price Shocks in the 1970’s Dollars per Barrel 1973 Arab Oil Embargo 1979 Iranian Revolution We can think about high oil prices as a negative shock to productivity…remember, we measure GDP as value added and (given that the US imports a lot of oil), high energy prices will lower value added

% Deviation From Trend Real Compensation (1972 – 1982) 1973 Arab Oil Embargo 1979 Iranian Revolution The high oil prices lowers the value of labor at the margin…labor demand falls and real wages drop

% Deviation From Trend Employment (1972 – 1982) 1973 Arab Oil Embargo 1979 Iranian Revolution The drop in labor demand also lowers the new equilibrium level of employment

% Deviation From Trend GDP (1972 – 1982) 1973 Arab Oil Embargo 1979 Iranian Revolution Lower employment will lower total production (GDP)

President Obama has proposed the following: Raise the minimum wage from its current level of $7.25/hr. to $10.10/hr. by 2016 Automatic cost of living adjustments thereafter Application: The Minimum Wage What do you think?

$7.25 (2009)

Minimum wages around the world

Adjusting for purchasing power changes the story a little….

Minimum wage laws vary by state….

In 2011, 73.9 million American workers age 16 and over were paid at hourly rates, representing 59.1 percent of all wage and salary workers. 16 million hourly workers earn less than the proposed $10.10 per hour 1.7 million earned exactly the prevailing Federal minimum wage of $7.25 per hour. About 2.2 million had wages below the minimum ($2.13/hr. is the minimum wage for tipped employees). Source: Department of Labor

Most minimum wage workers are part time Source: Department of Labor Percent of minimum wage workers

12 companies with most minimum-wage workers Darden Restaurants DineEquity Yum Brands

Highest wage retail companies $13.38/hr $11.27/hr $11/hr $10.20/hr $9.67/hr $9.48/hr $9.38/hr $9.32/hr $9.24/hr

Costco's CEO and president, Craig Jelinek, has publicly endorsed raising the federal minimum wage to $10.10 an hour, and he takes that to heart. The company's starting pay is $11.50 per hour, and the average employee wage is $21 per hour, not including overtime.

Microeconomic Argument for minimum wage increase: minimum wage workers are underpaid…but really, we are all underpaid in a competitive market! Labor supply ranks us by the value of our free time Labor demand ranks us by our productivity The equilibrium wage reflects the productivity/free time of the marginal worker For the average worker, they are being paid less than they are worth, but more than their time is worth.

Macroeconomic argument for minimum wage increase: Increasing the minimum wage would put more money into the economy, but does it? An increase to $10.10 would amount to a $2.85 per hour raise for those currently on minimum wage For a 40 hour week, that would amount to $5700 per year If we assume that all 16 million people affected got the full $5700, that would be an increase in income of $91.2B $91.2B represents around.5% of the US economy However, can this really be an increase in income? Unless an increase in the minimum wage makes us more productive, NO!

Microeconomic argument for increasing the minimum wage: We are creating a better distribution of income, but are we? Case #1: Rise in minimum wage results in increased unemployment So we have a transfer from one lower income group to another lower income group Case #2: Rise in minimum wage creates no job loss and business can’t pass the higher costs onto consumers Now we have a transfer from business owners to minimum wage workers Case #3: Rise in minimum wage creates no job loss, but businesses can pass the increased cost onto consumers Now we have a transfer from consumers to minimum wage workers