To Punt or not to Punt: Policy Advice based on Observational Data

Rocky Long, second year head football coach of the San Diego State Aztecs, is facing a problem that is similar, in some respects, to what voters face.  Coach Long may choose to never punt the football once the Aztecs cross midfield, regardless of distance on fourth downs.  He is listening to advice suggesting that the strategies of many previous coaches were wrong.  Coach Long says “We had one of our professors in our business school … go over a system we are thinking about using.  We’ll have a chart come game time that will determine what we do in different situations.”

Voters must decide whether the policies of another Obama Administration will help turn the economy around and contribute to more job creation, or if the Romney campaign proposals will be more successful in achieving these goals.  Football and economic policy advice are both derived from observational, not experimental, data.  It is difficult to know what might happen if alternative policies were to be enacted.  Analysts look to history, in similar circumstances with similar policy options, and hope this provides useful guidance.

Coach Long’s decision apparently follows the strategy of high school coach Kevin Kelley of Pulaski Academy in Little Rock, Arkansas who has been remarkably successful.  But college football is not high school football.  The strategy also appears similar to advice given by Berkeley macroeconomist David Romer, who several years ago found that NFL teams kick surprisingly often on fourth down.

Romer concluded that teams are not pursuing strategies that would maximize their chance of winning the game.  Romer may be correct, but we should be cautious because his study is based purely on observational data.  It is possible that the real world problem is more complicated than the model used to analyze the data.  Whenever economics (or other social science) professors explain that agents motivated by self-interest are making choices not in their self-interest, the professors may have mis-specified their model or may misunderstand the real-world problem that people are attempting to solve.

Romer’s paper is interesting, well written, and well executed.  All of the criticisms raised here are ones that Romer acknowledges, but they aren’t enough to sway his opinion and policy advice.  The data Romer analyzed indicated that NFL teams rarely try for a first down on fourth down.  The primary question is why?  Romer’s explanation is myopia.  An alternative explanation is that a failed fourth down attempt will shift momentum in the game.

The key problem with observational data is that it is difficult to calculate the expected outcome from counterfactual decisions and policies.  Romer argues that teams are not optimizing because he believes they would be successful fairly often on fourth down and two yards to go.  He concludes this despite rarely seeing teams attempting this play.  So how does Romer “guesstimate” the likelihood of success on fourth down and two?  He looks at outcomes of third down plays with two yard to go in the first quarter of games.  He uses first quarter plays because once enough game time has elapsed and the score is uneven, both teams will adjust their game strategies.  He assumes that third down strategies and outcomes are very similar to what would happen on fourth down plays (if they actually were to occur) because he doesn’t have enough data on fourth down plays.  Even if he observed more fourth down plays, they would not be a random or representative sample of teams and/or game situations.  Romer’s assumptions are made out of necessity, not because they are realistic or accurate.

It is also important to note that Romer’s empirical model does not allow for momentum.  The value of having possession of the ball with first down and ten yards to go on a given yard line (say midfield) in his empirical model is completely independent of how one reached that position on the field.  In the language of dynamic programming, the state variables for the optimization problem include down and yardage, but not the sequence of plays leading up to that point.  He imposes this assumption, as good applied economists often do, to make the problem tractable.  He recognizes that momentum could matter and makes some supplemental calculations to show that teams don’t perform much differently immediately after very bad plays (fumbles, interceptions, blocked kicks, and long kickoff and punt returns by the opponent) and just after very good plays (touchdowns) than they do after typical plays.  This is, at best, a half-hearted attempt to determine whether there is momentum in NFL games.  The model simply doesn’t take the idea of momentum shifts seriously, but avoiding these shifts seems to be a key reason why coaches kick field goals rather than go for it on fourth down.

Rocky Long, at San Diego State, may follow the advice of economics and business school professors and forsake the punt.  But he should do so understanding how the policy advice was determined.  It is extremely difficult for economics professors to evaluate counterfactual policies- whether it is a forecast of what will happen if teams ran and passed on fourth down or a “guesstimate” of the 2012 unemployment rate had there been no stimulus package in 2009. 

Asking economics professors, the Congressional Budget Office or other forecasters to evaluate alternative policies and predict what might happen over the next decade also has limited value.  Many of these same professionals either didn’t forecast the recession or underestimated its severity.  Government economists and advisors didn’t know how deep the downturn was until a year or two later when the data came in.  Mis-estimation of the recession in the midst of the downturn is the explanation given for the woefully inaccurate prediction that the stimulus would keep the unemployment rate below 8%.

It is unwise to rely too heavily on economists as authorities on counterfactual policies.  Economists can’t easily determine what would have happened had there been no stimulus, or how the economy might perform if taxpayers earning more than $200,000 were to face higher marginal tax rates.  In fact they struggle to measure output and employment in real-time.  Predictions about hypothetical economic policies are as fraught with error as predictions about fourth down decisions that have rarely been tried in the past.

Two Million Fewer Full-time Jobs Created in this Recovery Compared to George W. Bush Recovery

Last week Nobel Prize winning economist Paul Krugman wrote “The best hypothesis about the US economy this past year and more is that it has been steadily adding jobs at a pace roughly fast enough to keep up with but not get ahead of population growth.”  Professor Krugman is correct.  Total employment in the U.S. stopped its recessionary decline in February of 2010, whether measured using the Bureau of Labor Statistics (BLS) household or establishment payroll surveys.  In the two and a half years since then the economy has steadily gained enough jobs to just keep pace with population growth and demographic changes.  This would be good news if starting from a position of full employment.  But starting from a labor market trough, after the worst recession since the Great Depression, the job market performance over the past 30 months is best described as treading water.  We can be relieved that employment did not fall even more, but what we have seen for the past 30 months is an extremely weak labor market recovery.

The labor market situation must be dismal when even one of President Obama’s strongest critics on economic policy, Jim Pethokoukis of the American Enterprise Institute, has understated the weakness of this jobs recovery.  In a recent post Pethokoukis observed that, according to BLS establishment payroll data, the “Bush jobs recovery” created 5 million private sector jobs while the “Obama jobs recovery” created 4.6 million private sector jobs.  Although true, that is only part of the story.

Pethokoukis didn’t raise two important issues.  First, in the “Bush jobs recovery” household employment grew more rapidly than payroll employment.  Economists can’t provide an exact accounting of the differences between the two employment series, but much of the difference is due to new start-ups, small businesses and the self-employed.  Small businesses and the self-employed are either underrepresented or missed entirely in payroll employment totals and births of establishments are very difficult to track.  However, it is clear that many people were starting their own businesses or taking jobs with small businesses in the “Bush jobs recovery.”

A focus on payroll employment also ignores the difference between part-time and full-time work.  In addition to the millions of jobs lost in the recession, millions more moved from full-time to part-time work.  For the labor market to fully recover, underemployed workers in part-time jobs must find full-time work.  Consider a comparison of gains in full-time jobs during the two most recent recoveries.  The “Bush jobs recovery” began in August 2003 while the “Obama jobs recovery” began in February 2010.  The comparison is over a 30 month periods because the most recent data available are from August 2012.  The “Bush jobs recovery” created about 5.59 million  full-time jobs in 30 months compared to 3.51 million in the “Obama jobs recovery.”  The 2003 -2006 recovery was not as robust as previous recoveries but still produced two million (59%) more full-time jobs in 30 months than have been created since February 2010.

Welch Consulting has developed an employment index based on the BLS household survey that accounts for differences between full-time and part-time work, as well as the changing age and gender distribution of the workforce, population changes, and seasonal effects.  The index has moved up and down since February 2010 but is imperceptibly different from 30 months ago.  No change in the Welch Index means the economy created full-time equivalent jobs at the same rate as population growth.  In contrast the Welch Index steadily increased from 2003 to 2006.

A side-by-side comparison of the two recoveries is easier if one compares percentage changes in the index relative to the employment trough (beginning of each jobs recovery).  The following chart shows that after 25 months the Welch Index gained 2.3% in the “Bush jobs recovery” compared to 1.8% in the “Obama jobs recovery.”  Just five months ago the difference in the two recoveries was modest.  In the past five months nearly all of the gains in full-time equivalent employment (relative to a growing population) have been lost.  The full-time equivalent employment to population ratio is no better than it was in February 2010, at the end of a deep and prolonged recession.  In contrast in the “Bush jobs recovery” full-time equivalent employment growth was accelerating and grew much faster than the adult population over the corresponding time period (September 2005 to February 2006).  By 30 months into the recovery the index had grown over 3%.

Recognizing that President Obama inherited an economic mess, the amount of job creation on his watch has been disappointing.  What looked promising in early spring 2012 has stalled and the hope for a “recovery summer” faded long ago.  The job creation record under President George Bush’s leadership was not only better at this stage in the recovery, it was improving.

Any President has a limited impact on the rate of job creation.  Economists may disagree about the magnitude of the effect of tax policy uncertainty on job creation, but none would advocate a system where businesses large and small are uncertain of tax rates just four months in the future.  Tax policy is, however, the responsibility of both the President and Congress.  The President has a much greater impact on the regulatory landscape through the executive branch.  Labor market regulations, such as those in the Fair Labor Standards Act, can also discourage hiring (and encourage outsourcing).  It is difficult to tell, at this time, how much the Obama Administration’s expansion of regulations has had a chilling effect on hiring.

The Obama campaign will remind us that in early 2009, for about six months, the economy was losing 700,000 to 800,000 jobs per month.  The more pressing issue, however, is which candidate has better policies to help employment grow relative to our population over the next decade.  Some policies require bipartisan cooperation in a divided Congress.  Other regulatory reforms are more directly under the control of the executive branch.  Let’s hope the Presidential debates challenge the candidates to describe regulatory reforms that will reduce the headwinds and even help foster job creation in the U.S.

Throwing Money at the Chicago Public Schools

Chicago public school teachers are on strike.  Issues include negotiations over possible pay increases, health care benefits, and job security over the next four years.  The negotiations in Chicago are important nationally because tough bargaining will be necessary for cities and states to gain control of the cost of compensation, health care and retirement benefits of public employees.  The bargaining between public administration officials and taxpayers on one side of the table and union leaders and public servants on the other will be instrumental in determining future tax rates, public debt and the quality and quantity of public services.  Moreover, because of the increase in Federal government funding of local governments, taxpayers in swing states such as Iowa, Wisconsin, Ohio and Virginia should be mindful of how their tax dollars have been spent in Chicago.  The funding of public elementary and secondary schools has become a Federal issue. The Chicago public school system is an excellent example of how education finance has changed over the past decade.

The Chicago public schools spent $12,193 per student in 2011.  This is a bit higher than the average for the state of Illinois and for the U.S. as a whole but is far less than the average in other large cities such as New York and Washington, DC.  In a series of tweets on Monday Josh Barro of Bloomberg View identified several reasons why teacher salaries are about the same in New York and Chicago but Chicago has lower expenditure per student: (1) class sizes are larger in Chicago, (2) a smaller fraction of students in Chicago are special needs students, (3) non-wage benefits are less expensive (and possibly less generous) in Chicago, and (4) the pension system for Chicago public school teachers is nut funded as well as the New York teacher pension system.

Federal funding of big city school districts is on the rise.  Nationwide about 12.5% of public school finances are provided by Federal aid.  Put differently for each $1 of local property taxes spent on schools the Federal government contributes 44 cents.  The Chicago public schools rely much more on Federal aid than the average district. About 23.3% of the finances of the Chicago schools are provided by Federal aid.  For each $1 in local property taxes in Chicago that are spent on schools, the Federal government contributes 59 cents.  These figures and the ones that follow are from Chicago public school budget documents.

The fact that the performance and efficiency of the Chicago public schools is now a Federal concern is a relatively recent phenomenon.  The following figure shows that, adjusting for inflation, Federal aid to the Chicago public schools increased by over 85% per student between 2002 and 2011.

Overall spending per student, after adjusting for inflation, has increased by 26.5% since 2002.  More than half of this additional funding has been paid for with Federal aid.  Moreover even though spending per student and Federal aid has fallen very slightly from 2009 to 2011 (adjusted for inflation) overall spending and Federal aid are much higher than just five years ago.

Where did the money go?  Enrollment in Chicago schools fell by 8% since 2002 so there is less reason to build new schools in Chicago than in cities with rapidly growing populations of school-age children.  Class sizes have not changed much in Chicago since 2002 despite the large increases in real spending per student.  The average class size increased from 22.6 to 23.2 for elementary students and fell from 20 to 19.8 in secondary schools.Everyone interested in the future fiscal health of our country should follow the Chicago negotiations between the teachers’ union and Mayor Emanuel.  Taxpayers throughout the country help finance schools in Chicago, New York and other large cities.  The administrators and teachers’ unions need to be responsive to their constituents, who now include taxpayers from across the country.  The Federal government provides more than $1.1 billion in aid to the Chicago schools per year.  This is not a large sum when one considers that the Federal government spends $1.1 billion every two and a half hours.  Nonetheless, quite the late great Illinois Senator Everett Dirksen “A billion here, a billion there, and pretty soon you’re talking real money.”

NFL Replacement Referees are Less Disruptive than the 2011 Player Lockout

Work stoppages are costly to labor and management.  One cost of a strike in professional sports is the diminished quality of play that results from missed practices.  Some teams and players, especially those with less experience, are harmed more by reductions in practice time.  In an earlier blog post I demonstrated that strikes in the NBA are associated with subsequent reductions in the shooting efficiency of players.  This post compares the impact of the NFL player lockout of 2011 to the referee lockout of 2012 on NFL game outcomes.

Itis clear to NFL fans that the replacement referees, used in the first two games of 2012, make more imistakes than experienced referees.  Although the lockout with referees seems to introduce additional noise into game outcomes, it appears that referee errors are largely uncorrelated with teams’ strengths and weaknesses.  In contrast, it appears that the lockout with players favored stronger and more experienced teams.

The player lockout of 2011 drastically reduced the amount of practice time prior to the beginning of the season.  One would expect this to have a larger effect on teams with less experienced players and teams that made more roster and coaching changes prior to the season.  Successful teams are likely to have greater stability in their personnel, have more experience playing as a team, and are less likely to change offensive or defensive coaching philosophies.  Therefore it would not be surprising that a loss in pre-season practice time harmed the weaker teams more than the stronger teams.  This is exactly what happened last year.  Final score differentials in NFL games were unusually high in the first two weeks of the 2011 season, immediately after the lockout.

In contrast there is less reason to expect that the use of replacement referees during the NFL’s lockout with the more experienced referees would tend to favor stronger or weaker teams.  In fact, the final score differentials in the two weeks of the 2012 season are only slightly higher than in earlier seasons despite the use of replacement referees.

The margin of victory in an NFL game includes signals of the opposing teams’ strengths and noise due to luck, player injuries, weather, and other factors.  These factors include the impact of a shortened training camp due to the player lockout in 2011 and the use of replacement referees in 2012.  The following chart shows the mean absolute score differential for games in the first two weeks of the 2009 through 2012 seasons.The mean score differential was 26% higher early in the 2011 season than it was in the first two weeks of the 2009 and 2010 seasons.  Games were more lopsided by about 2.66 points per game in the first two weeks of 2011.  If the team most disadvantaged by the shortened preseason always lost the game, the average impact of lost practice time is a 2.66 points advantage for the winning team.  If missed practices sometimes worked to the detriment of the winning team the average gross effect on scoring would be somewhat larger.  (If the impact of reduced practice time was uncorrelated with team strength the gross impact could be as high as a swing of 5.32 points per game.)  It seems likely that shortened practices altered outcomes by at least 3 to 4 points per game and sometimes worked to the disadvantage of the team that ultimately won the game.

In contrast there is a much smaller difference between the average margin of victory/loss between the 2009 and 2010 seasons and the first week of 2012.  Although replacement referees have affected the calls on the field, their impact on the typical score differential is only 41% of the increase caused by the players lockout.

Work stoppages and strikes are costly.  The 2011 player lockout caused game outcomes to be more uneven.  Weaker teams with more rookies and roster changes seemed to be harmed more than successful veteran teams by the lockout of players and loss of practice time.  The impact of the strike may have been as high as a swing of 3 to 4 points per game, on average.  In contrast the use of replacement referees in 2012 increased final score differentials by much less.

Employment Growth during Presidencies of Barack Obama and George W. Bush

The Welch Consulting Employment Index is 93.3 for August 2012, up 0.8% from August 2011 (seasonally adjusted).  An index value of 93.3 means that full-time equivalent employment (from the BLS household survey) is 6.7% below its level in the base year of 1997, after adjusting for both population growth and changes in the age distribution of the labor force.  The index has fallen over the past five months, it was 94.9 in March.  The index remains weak because part-time employment is higher than it has been historically and employment growth has barely exceeded population growth over the past two years.

The following chart compares employment changes in the first 44 months of the first terms of Presidents George W. Bush and Barack Obama.  George W. Bush took office when the employment index was 101.8, one of the highest values in the past 15 years, while the index had fallen to 96.9 by the time Barack Obama was inaugurated.   Nonetheless there has been a similar decline in employment during the first three and a half years of their administrations.  Between George W. Bush’s inauguration in January 2001 and August 2004 the employment index fell by 3.4%.  The corresponding change for President Obama’s first term is a 3.7% decline in the employment index between January 2009 and August 2012.

The similarities in the pattern of employment decline during these administrations becomes even more clear if the chart axes are adjusted to account for the differences in the state of the labor market between 2001 and 2009.

 

The first terms of the Bush and the Obama administrations have been characterized by steady declines in full-time-equivalent employment relative to the growth in the adult population.  The primary difference in the jobs record is that President Bush inherited an unusually strong labor market with a very low unemployment rate and a high rate of full-time equivalent employment. President Obama inherited a labor market that was already declining fairly rapidly.  After 44 months of their presidencies, however, the net percentage change in employment is remarkably similar across administrations.

Technical Note: Full-time equivalent employment equals full-time employment plus one half of part-time employment from the BLS household survey.  The Welch index adjusts for the changing age distribution of the population by fixing the age distribution of adults to the 1997 base year.  The Welch Index adjusts for population growth by fixing total population to its 1997 level.  Seasonal effects are removed in a regression framework using monthly indicator variables.

What Happened in Vegas? Its Not Better Off Than Four Years Ago

The question “are you better off than four years ago?”, first asked by Ronald Reagan in his campaign against Jimmy Carter in 1980, has a different answer for households in different parts of the country, and for workers who differ with respect to their occupation, age, education, race, gender and work experience.  The average answer to this question belies substantial inequality in changes in economic fortunes over the past four years.  There have been economic success stories even during the depths of the deepest recession since the Great Depression.  Some small businesses and start-ups have flourished.  The stock market and corporate profits have rebounded well in the past four years.  Many individuals have found work, moved from part-time to full-time work, received a promotion, or a substantial increase in their rate of pay.

At the other end of the spectrum, there is unlikely to be a group of workers more adversely affected by the recession and weak recovery than construction workers in areas where the real estate bubble burst.  Consider building construction workers in Las Vegas, Nevada.  Four years ago there were 17,500 workers employed in building construction.  Today there are only 5,100 meaning that employment has fallen by 71% over four years.

The Case-Shiller price index for residential housing in Las Vegas has fallen by 41% over the past four years.  This means that many of the unemployed and underemployed construction workers are underwater in their homes.  Moreover, given the glut of housing, the employment prospects for construction workers in Las Vegas is likely to remain weak for years to come.

What happened in Vegas, unfortunately, isn’t confined to Vegas.  There are a number of other cities and areas, from Riverside County, California to south Florida, that are casualties of the crash in real estate markets.  Many residents of these areas lost equity in their homes.  Others lost their jobs and have been underemployed for years.  Many small businesses, especially those dependent on real estate and construction, have failed.  So whenever pundits and journalists attempt to determine whether the typical American is better off than they were four years ago, remember that there are 300 million different answers to that question.  In some parts of the country the answer is clearly no, for far too many Americans.

Stubbornly High Unemployment

The Bureau of Labor Statistics has reported monthly unemployment rates for the past 775 months.  Through the first 733 months of reporting (until January 2009) the unemployment rate was above 8% in only 38 months.  There were 12 months of high unemployment in 1975 and 26 more from 1981 to 1983.  Since then we have experienced 42 straight months of unemployment in excess of 8% of our (shrinking) labor force.  We are in uncharted territory.  Unfortunately, it appears that the unemployment rate will not fall below 8% until some time in 2013.  Only time will tell what the scarring effects of extended periods of unemployment will mean for the future earnings of workers displaced by the 2007-2009 recession.

Unemployment and Democratic Mayors at the DNC

Last week the Los Angeles Times ran an interesting story highlighting the conflict between the messages delivered by Republican governors in the key swing states of Ohio, Virginia, Wisconsin and the theme of Mitt Romney’s presidential campaign.  Governors Kasich, McDonnell and Walker all spoke at the Republican National Convention and emphasized the economic turnarounds experienced by their states under Republican leadership.  The Los Angeles Times reported that the talk of job creation and falling unemployment rates in these three states “delighted” President Obama’s re-election team.

Last night five Democratic mayors, from Charlotte, Chicago, Los Angeles, Newark and San Antonio spoke at the Democratic National Convention.  Four of these five metropolitan areas have unemployment rates above the national average of 8.3%.  The only metropolitan area of the five with an unemployment rate below the national average is San Antonio with an unemployment rate of 7.3%.  (The Bureau of Labor Statistics reports unemployment by metropolitan area not cities themselves.)

Taken together, these five metropolitan areas have a combined labor force of nearly 14.5 million workers, and 1.43 million of them are unemployed.  This puts the aggregate unemployment rate for the metropolitan areas represented by the Democratic mayors who spoke last night at 9.9%.

It wasn’t always this way.  In 2007 the unemployment rate in all of these metro areas was below 5%.  Fewer than 675,000 workers were unemployed in the combined metro areas in 2007, for an aggregate unemployment rate of 4.7%.

Will the Los Angeles Times recognize the conflict between the President’s re-election campaign message and the plight of the millions of unemployed, underemployed and discouraged workers in cities governed by Democratic mayors?  Perhaps not because only one of the cities (Charlotte) highlighted at yesterday’s DNC is in a swing state. 

Given the electoral map, the Presidential campaign is likely to pass by many people suffering from the steep recession of 2007-2009 and the weak recovery of the past three years.  I suspect that voters in these cities and states are looking for solutions from their mayors, governors and elected representatives, whether they are Democrat or Republican, and are less concerned with assigning blame for our economic woes.

Why Has Job Growth Been So Slow? Fewer New Businesses

The rate of job creation over the past three years has been disappointing.  The Obama administration touts the fact that private sector employment has increased for 29 straight months.  But since February of 2010, when employment started to rebound, we have added 138,000 jobs per month (an annual growth rate of 1.27%).  Both parties agree that this is insufficient given the depth of the recession and the millions of unemployed, underemployed and discouraged workers in our economy.  An important reason for the disappointing growth in jobs is the slowdown in job creation from start-ups and new establishments.  The U.S. economy would create 2.65 million more jobs per year if new businesses were creating jobs at the same rate as in the 1990’s.

In 2011, for the first time in the 20 years that the Bureau of Labor Statistics has maintained these data, the number of jobs created at new establishments dropped below 5 million.  Job growth from newly formed establishments has declined by 38% since 1998, relative to total private sector employment.  In 2011 jobs created in new establishments accounted for 4.6% of private sector employment compared to 7.4%  of employment in 1998.  The decline in the share of jobs from new establishments has been steady over the past decade as shown by the following graph:

The dearth of start-ups is an important factor in understanding the anemic job growth in this recovery.  If new establishments were being formed at the same rate as in the 1990’s, the U.S. economy would be creating 221,000 more jobs per month (2.65 million more jobs per year).  Job creation would be 160% higher if job gains from new enterprises returned to the rates experienced in the 1990’s.

It is not clear why job growth from new establishments has dropped steadily over the past decade.  It is possible that each new business venture today creates fewer jobs in the U.S. due to outsourcing and technological change.  Regardless of the causes, job growth will not be robust as long as start-ups create fewer and fewer new jobs each year.  Changes in tax policy and regulations to create a business environment amenable for new businesses, that have historically been the engine of job creation, could help reverse this trend.