Category: Tara Sinclair

Originally published on November 18, 2013

The Future of Part-time Jobs in the US Economy

For some time, people have feared that firms will replace full-time jobs with part-time jobs in order to cut back on costly benefits and taxes. This speculation has been spurred by debate over the Affordable Care Act, which mandates that employers with more than 50 employees provide health-insurance coverage to those who work 30 or more hours per week.

Using data from job site Indeed.com, I recently explored both the supply and demand for part-time jobs.  There has been a relatively small increase on both sides, suggesting there may be benefits for some job seekers and employers in part-time jobs, but the vast majority of future employment will continue to be full-time.  You can read more on the Indeed blog by following the link.

Originally published on October 10, 2013

Janet Yellen leading the Fed – the Perspective of Two Female Economists

President Barack Obama’s nomination of Janet Yellen as the Federal Reserve’s next chair is historic, marking the first time a female has headed the central bank in its 100-year history. There is no question that Yellen, currently the Fed’s vice chair, is qualified to take the helm. But the nomination also has special significance for students at GW.

This is a link to an an op-ed today in the Hatchet about Janet Yellen that I co-authored with Amy Guisinger, Ph.D. candidate in economics and a research assistant at the Institute for International Economic Policy at the Elliott School of International Affairs.

Originally published on January 20, 2013

The American public as well as the rest of the world may be getting weary of all the budget wrangling in Congress these past few years, but the biggest fight of all may be still ahead.

To find out why the debt ceiling is not the way to control the national debt, please read my blog for the Huffington Post.

Originally published on July 27, 2012

The Bureau of Economic Analysis (BEA) released new US real GDP data today.  They released both the first estimate (called the ‘advance estimate’ to emphasize that they are using “incomplete source data”)  for the second quarter of 2012 as well as revised estimates for 2009 through the first quarter of 2012 as part of their “regular annual revision of the national income and product accounts (NIPAs)”. Unlike the last two years, this year’s revised estimates weren’t particularly surprising. So, we can be comforted by knowing that although the US economy looks to be as bad as we thought, at least it’s not worse.  Similarly, the estimate for US real GDP growth in the second quarter, although pretty sluggish (just 1.5 percent at an annual rate), was about what economists were expecting.

Since there doesn’t seem to be much new news to write about, and the “accuracy-timeliness tradeoff” of macroeconomic data releases just isn’t firing me up today (although, for those interested, here’s a presentation from a related talk I did in June), I thought I’d write about a different data series today.  It’s US real GDP per capita.  We don’t look at this number too often in the US, but a reporter friend of mine asked me about it today, so I took a look, and now I think it deserves more attention than it’s getting.

Here’s a graph to consider:

The top red line is annual US real GDP (in 2005 chained dollars on the right axis).  The lower blue line is annual US real GDP (in 2005 chained dollars) per capita (on the left axis).  The key thing to note is that both series peaked in 2007 and then dropped during the Great Recession of 2007-2009.  By 2011, US real GDP had returned to where it was in 2007 (and, although hard to tell by the scale of the graph, has now slightly surpassed the peak).  The per capita measure, however, is still well below its peak in 2007.  The problem is that the US population grows about 1% per year, and US real GDP hasn’t kept pace with that in the recovery.  I think the per capita measure gives us a better sense of the tepid recovery and emphasizes what US households are feeling.  I’ll be keeping a closer watch on this number in the future.

Originally published on July 22, 2012

I am generally not the sort to sign petitions or other declarations, particularly not ones called “manifestos”.  Last Friday, however, I ran into the Manifesto for Economic Sense when I read a very interesting post on the IMF’s staff report on the UK by Jonathan Portes (Director, National Institute of Economic and Social Research, London) in his nicely named blog, “Not the Treasury View” (referring to the UK Treasury).

After carefully reading the manifesto yesterday I decided to sign it and write about it here in this post.  I have become more and more concerned about the push towards “austerity” by governments around the world at this time when unemployment rates are in general well above their long-run averages.  My review of the historical evidence suggests that there is very little reason to think that austerity will do anything but make the global recovery even slower and more painful than it already is.  In signing the manifesto I am adding my voice to those of a growing number of economists calling for more government spending rather than less until we recover fully from the Great Recession.

First, here’s an illustrative graph using US data (for many European countries it is even more extreme).  The graph shows the broad U6 unemployment rate for the US: “Total unemployed persons, plus all ‘marginally attached’ workers, plus all persons employed part time for economic reasons, as a percent of the civilian labor force plus all ‘marginally attached’ workers.”  It also shows my estimates of the contribution of “permanent” movements in this measure as compared to “temporary” movements along with gray bars indicating recessions as dated by the NBER. The model I used is from my paper “Asymmetry in the Business Cycle:  Friedman’s Plucking Model with Correlated Innovations.”  I apply it here to the U6 unemployment rate to put it in terms of unemployment instead of production, but the results are similar if I use GDP.

According to most economic models, demand-focused policies will only affect the temporary component.  You can see that this means that based on the graph above I won’t advocate for these policies very often, but right now is one of those rare times.  It currently looks like the US is stuck with over 4 percentage points of excess (broad) unemployment.  If we could get more of these people working then they could increase production.  Why would economies produce less than their potential?  If you ask a business owner, they’ll say they cut back on production when they don’t see enough demand for their products.  So, we need demand from somewhere.

We have a simple equation for aggregate demand: (AD):  AD = C + I + NX + G.  C represents consumption spending by households, I represents investment spending by firms, NX represents net exports, and G represents government spending.  So, if AD is already less than what it could be, then we can’t cut back on government spending without further harm to the economy unless at least one of the other three forms of spending taking up the slack.  Let’s discuss the options in turn.

First, household consumption.  Some very interesting research suggests that having our economy so dependent on consumption spending is one of the reasons we got into the current mess.  For their individual well-being, households need to be cutting back on spending, not increasing spending right now.

The US was hoping exports might take up the slack, and there has been some movement in that direction, but now with Europe in their own mess and emerging economies slowing as well, it doesn’t look anyone can depend on exports right now.

In terms of firm investment, firms could be ramping up new projects, but firms won’t produce more if they don’t expect there to be buyers. Since households aren’t in a position to increase spending substantially any time soon, even record-low interest rates can’t entice firms if they don’t see any customers in the mood to buy.

With C, I, NX, and G all looking sluggish, we may be in for a very slow recovery.  What about the argument that monetary policy can be used to stimulate the economy and offset the impact of reduced government spending? Central banks are doing what they can, but in the US and Europe they are at the limits of their traditional tools.  They can use more unconventional approaches, but they are also finding themselves politically constrained by, in general, the same argument pushing austerity on governments.  Furthermore, loose monetary policy over several years does come with some negative side-effects.  I’m particularly concerned about households not having the incentive to save. If households are supposed to be cutting down their debt and saving more to put themselves in a better economic position for the future, then we shouldn’t be discouraging that behavior at the same time.

Once the economy fully recovers (which I do believe will happen one way or another eventually, but eventually could be many years out at the rate we’re going), then government spending can and should be reduced. But even when we’re back to producing all we can we don’t actually need to bring the average deficit to zero or have a plan to pay off the debt.  Despite the analogies being thrown around by various politicians, governments are not the same as households.  Countries are expected to go on in one form or another forever, so they just need to pay the interest on their debt, they never have to pay it off.  In fact, there are reasons governments should have at least some amount of debt.  For example, US government debt is considered a safe asset that many households want to hold to save for retirement.  It’s also the usual way that monetary policy is conducted – buying and selling government bonds – so we need enough government bonds to exist for central banks to conduct their regular business.

Of course we want our governments to choose carefully what to spend on and be responsible with our tax money, but the costs of government spending are incredibly low right now due to low interest rates and the stimulative effect of government spending on the economy when we’re below potential.  It seems like now is the perfect time for spending on those projects like roads and other infrastructure that people value.  That will be much better for the economy than austerity.

Originally published on March 11, 2012

Much has been made of the 227,000 jobs estimated to have been added to the US economy in February 2012 according to the Bureau of Labor Statistics (see, for example, this New York Times article from Friday).  This is a good number – anything greater than 150,000 generally results in a sigh of relief amongst economists – and better than expected.  For example, the Survey of Professional Forecasters released in the middle of February forecasted only 160,000 jobs to be created per month on average for the first three months of 2012.  Given that the January numbers were also revised up to 284,000, it looks like the forecasters are going to be way off this quarter (although they were even more pessimistic back in November – they had previously forecast only 121,000 jobs to be added per month for the first quarter of 2012).  These numbers are still well below what we’re used to seeing in a robust recovery, where monthly job creation on the order of 500,000 is not unusual, but they’re big enough that they more than cover new entrants to the labor market.  This means it should be whittling away at the unemployment rate.  So, why did the unemployment rate stay the same, at 8.3%, rather than drop?  This is actually the good news I have been waiting for.

Why would I possibly argue that an unemployment rate staying at 8.3% is good news?  Well, if jobs are being added but the unemployment rate isn’t dropping it means that more people must be out looking for jobs.  This is why the unemployment rate tends to lag in recoveries – people get discouraged when the labor market looks rough and stop looking for work.  As the economy starts to look better we may actually see the unemployment rate rise a bit with discouraged workers coming back into the labor market and again looking for jobs.  This is an exciting development since it suggests there is a bit more optimism for the economy out there.

Here are a couple of graphs for thought.  First, here’s the civilian participation rate, i.e. the percentage of the civilian population either employed or actively looking for a job:

As you can see, we have some way to go to get back to the peak of over 67% that we had in the late 1990s.  There are some reasons we may not get back to that level, in particular the aging of the population resulting in a greater proportion of our population in retirement, but it seems like we might expect to get back to near 66%, where we were before the Great Recession.  Currently we’re at only 63.9%.  But, that’s a little tick up from January’s 63.7%.  Hopefully that pattern will continue.  But, that may mean stagnating unemployment rates for a while.

If we’re looking for discouraged workers going back to the labor market, perhaps we should instead look at a broader definition of the unemployment rate.  Here is a graph of the U6 unemployment rate that includes discouraged workers and those that have part time jobs but want full time jobs:

Here we can see a strong decline of late – this is the good news that is hidden in the more narrow unemployment rate.  A number of people, including Paul Krugman, argued that this was the number we should be watching back in the recession.  It may also be the right one to watch in the recovery.

I should mention a couple of other perspectives on the reduced participation rate over the last few years.  The Economist magazine came out with an interesting article this week which discusses an argument from Alan Krueger, the chairman of the Council of Economic Advisers, that some of the discouraged workers went back to school so the lower participation rate of the last few years isn’t as bad as it may first appear.  I wouldn’t, however, push that idea so far as to claim that the Great Recession was good for these individuals or for the economy as a whole. That would be similar to arguing that a tornado is good for a town because they get to rebuild a nicer town afterwards.  If these people really thought that an education was going to make their lives better they could have gone to school instead of working – they originally made the choice to work instead of going to school.  I generally believe people know best about their life choices.  There may be some reasons to question that belief, but I think it’s a good place to start from.  Still, in the face of unemployment they chose to expand their education instead of facing the possibility of long-term unemployment.  This was probably a good choice for them and for the economy as a whole.

Returning to the relationship between labor force participation and the unemployment rate, one of my favorite blogs, the Federal Reserve Bank of Atlanta’s macroblog, had an interesting post on Friday.  The Atlanta Fed has a cool new tool on their website called the Jobs Calculator that was designed to calculate the net employment change needed to achieve a target unemployment rate after a specified number of months, but it can also be used to do several other fun thought experiments.  For example, in the blog post from Friday Julie Hotchkiss, an economist at the Atlanta Fed, used the Jobs Calculator to estimate what the unemployment rate would have been in February if there hadn’t been the tick up in the participation rate.  She estimates that it would have been about 8%, about three tenths below what it was reported to be in February.  I also find it interesting that the default settings show what the payroll numbers would need to be to keep the unemployment rate constant at its current value, holding constant the current participation rate.  Apparently it’s now below 95,000 jobs per month.  So, any month where we see job creation over that number means either the unemployment rate should fall or the participation rate has risen.  Either one of those is good news.

Originally published on February 12, 2012

As a regular contributor to the Philadelphia Fed’s Survey of Professional Forecasters (SPF) I am always curious about the forecasts my fellow contributors are making.  The latest set of forecasts came out on Friday and this time I was particularly focused on the unemployment rate forecasts.  There has been much talk about the importance of the unemployment rate at the time of the presidential election, and the SPF has been shown to produce pretty good forecasts of the US unemployment rate.  The unemployment rate for last month was 8.3%, a surprisingly good number.  The unemployment rate has fallen faster over the last few months than forecasters predicted in the SPF just last quarter, although some of the decline was due to people leaving the labor force rather than job creation.  Following the surprising performance of the unemployment rate generally, the SPF forecasters indeed changed their forecasts substantially this round.  Here’s a graph:

SPF Median Forecasts of the US Unemployment Rate

The key forecast I was looking at was for 2012Q4 – right around election time.  As you can see, the forecasters now see a much better labor market outlook for the end of 2012 than they did just three months ago.  The median forecast has dropped from 8.7% to 8.1%.  It has not, however, dropped below the threshold of 8% (my personal forecast is currently right at 8% for November 2012).  I think there is something to round numbers in human psychology, but I also recognize the importance of trends.  A declining unemployment rate, particularly one that is declining faster than previously predicted, looks good for the incumbent.  One question that remains for me, however, is has this decline come too soon?  If the improvement slows before the election, will voters forget that not so long ago we were wondering if the unemployment rate might go back up above 10% or at least not drop below 9% before the 2012 election?

Originally published on February 2, 2012

Happy Groundhog Day IIEP Blog Readers!

This morning I recorded an interview with Marketplace Morning Report, to be aired on February 2nd in honor of Groundhog Day.  The segment was about economic forecasting.  Originally the woman I was corresponding with to set up the interview wanted me to talk about my own forecasts.  Although I do prepare some forecasts for the Survey of Professional Forecasters, I regularly admit that I generally don’t trust economic forecasts, particularly my own.  Her response to my hesitation in sharing my forecasts with 5.9 million listeners (according to her count), was “as long as you’re a little more accurate than Pux Phil, I’m sure you’ll be fine.”   Sadly, I’m concerned that when it counts the most, economic forecasters may not be any more accurate than a groundhog.

You might think, hope even, that economic forecasters should be more reliable than a groundhog.  When it comes to recessions however, even the best forecasters out there seem to fail miserably to predict both when we’re going into one and when we’re coming out of one.  In fact, in an article I wrote with my colleagues Fred Joutz and H.O. Stekler, we found that although the Federal Reserve staff, quite possibly the best forecasters for the US economy overall, know whether or not we are in a recession currently, they cannot predict whether or not we will be in one just one quarter in advance.  This is a big problem since monetary policy actions tend to take at least a couple of quarters to take effect.

Researchers continue to search for ways to improve models that forecast recessions.  One of my favorite models is the one by Marcelle Chauvet and Jeremy Piger which currently suggests only a 2.7% probability of a recession.  But, even this model is just trying to catch a recession as it is going on, not predict it in advance.  Until researchers find a model that better predicts recessions, perhaps we should not expect so much from our forecasters and policymakers.  Maybe recessions are just unpredictable.  Or maybe we just need to find the right groundhog…

Originally published on January 29, 2012

Hello again readers of the IIEP blog!  Today I’d like to share with you a post I co-authored with Kathryn Vesey, Research Associate at the GW Regulatory Studies Center (where I am also affiliated), as well as a Master of Public Policy Candidate at The Trachtenberg School of Public Policy and Public Administration. She and I have been working on a project examining the impact of regulatory agency spending on the macroeconomy.

With the U.S. unemployment rate still painfully high at 8.5%, politicians in Washington and on the campaign trail continue debating over what steps government should take to help put Americans back to work. One popular argument in that vein has been that government regulation is the enemy of job creation, a claim that may be more driven by rhetorical salience than evidence. On this subject, a recent article in the Washington Post reports, “Economists who have studied the matter say that there is little evidence that regulations cause massive job loss in the economy, and that rolling them back would not lead to a boom in job creation.”

A recent empirical study conducted by the Phoenix Center for Advanced Legal and Economic Policy Studies tells a different story however. Using the Regulators’ Budget data as a proxy measure of regulation over time, this study estimates that reducing the total budget of all U.S. federal regulatory agencies by just 5% (or $2.8 billion) would result in an increase in real private-sector GDP of $75 billion annually, as well as 1.2 million more private sector jobs each year. They put it another way too, claiming that firing one regulatory agency staff member will create 98 jobs in the private sector.

This study’s provocative findings have been widely cited by politicians, advocacy organizations, and the media as evidence that cutting regulation will create jobs and grow the economy, even making an appearance in an official congressional report on the Regulatory Flexibility Improvements Act (U.S. House of Representatives 2011). But are these figures, which seem so surprisingly high, really definitive?

We set out to answer that question, first by attempting to replicate the authors’ study following their steps exactly. What we found is that when we use the same data and identical model specification, we do in fact arrive at the same dramatic results. However, we also find that those results are extremely sensitive to small alterations in the specification used.

For example, the Phoenix Center uses the “Regulators’ Budget as a share of private GDP” as the variable for regulatory activity in their Generalized Impulse Response Function (GIRF), which they then use to simulate a “regulatory shock” to observe how the other two variables in the model (private GDP per capita and private sector jobs) respond. However, we tried a number of small changes to the specification, for example replacing the Regulators’ Budget as a share of private GDP with the Regulators’ Budget measured in billions of 2005 dollars – a specification we argue is more appropriate, as it does not require holding private GDP constant in one variable while allowing it to vary in another.

This alternative model leads us to very different results. The Phoenix Center study found a statistically significant, negative relationship between the Regulators’ Budget and private sector GDP and employment. On the other hand, according to our preferred model, we find a positive relationship where a 5% increase in the Regulators’ Budget is associated with a 0.28% increase in private sector employment and a 0.14% increase in real private GDP. However, these results are not statistically significant and therefore indistinguishable from no effect.

This lack of statistical significance is not surprising for several reasons. First, there is bound to be much variation in private sector employment and private sector GDP not accounted for by this macroeconomic model with just three variables. Second, it is quite likely that different types of regulatory agency budgetary spending have diverse effects on the economy, and that these effects may vary at different times. And third, as is the case with more commonly used proxies for regulatory activity, such as number of pages in the Federal Register or Code of Federal Regulations, the Regulators’ Budget is a blunt measure of regulation. The taxpayer costs of staffing and running federal regulatory agencies (as measured by the Regulators’ Budget) may not correlate well with the societal impacts of the regulations they issue.

Of particular concern with respect to using Regulators’ Budget data as the proxy for regulation is one substantial outlier in the budget – Homeland Security budgetary spending (mostly attributed to the Transportation Security Administration (TSA)). As the graph below illustrates, this area of regulation has been by far the largest driver of regulatory agency spending growth in the last decade since the Department of Homeland Security was created after September 11th. Based on this insight, it would seem that this outlier may be partially responsible for the model’s lack of stability.

It is also important to recognize the limitations of vector autoregressive analysis in general and its applications in the Phoenix Center study in particular. Vector autoregressive models have been commonly used for macroeconomic analyses for 25 years. They can be extremely beneficial for describing data, and oftentimes for forecasting purposes too. However, as Stock and Watson discuss in a 2001 paper, “small VARs of two or three variables” – such as the one used in the Phoenix Center study – “are often unstable and thus poor predictors of the future.” Moreover, drawing structural inferences from VARs is difficult and requires one to make weighty assumptions.

Regulations have significant economic and social costs and benefits, as well as important distributional effects. The recent increase in awareness of this reality among citizens and politicians has the potential to affect positive changes to the U.S. regulatory system, making it smarter, more transparent, and more accountable. However, in order to keep the conversation constructive, it is important that the evidence drawn upon in the public discourse about regulation be meaningful and well-informed. Our ongoing analysis seeks to do that.

Originally published on January 20, 2012

Hello readers of the IIEP blog!  Since this is my first time posting here, let me briefly introduce myself.  I am an associate professor of economics and international affairs here at The George Washington University and an affiliate of the Institute for International Economic Policy (IIEP).  My specialty is empirical macroeconomics.  This means I get surprisingly excited about the new data we get from recessions – yes, someone has to be happy about recessions and that job falls to me. To be clear, recessions themselves don’t actually make me happy.  I definitely did not enjoy the last one here in the US and I don’t wish a recession on anyone.  However, the data we get from recessions, data that may help us to make better forecasts and policy decisions so that we can avoid recessions in the future, bring a certain twinkle to my eye.

One of my roles here is that I am IIEP’s resident Fed watcher.  Beyond actually being able to see the Federal Reserve building through the windows of the Institute, I regularly Google “Federal Reserve” and see what people at the Federal Reserve are up to and what the press and others are saying about the Fed.  After the excitement of the past few years I have recently reduced the frequency of my searches, having grown a bit weary of the Fed’s repeated forecasts of sluggish growth and promises of low interest rates until at least the middle of 2013. Yesterday, however, I thought to poke around a bit and found that in the flurry of academic activity at the end of the year I missed a major controversy.  Although the traditional comment period may have passed, I feel the need to blog about it – which brings me to my first IIEP blog post:

In my search for recent posts about the Fed I was drawn in by the clever title of the Daily Show’s “America’s Next TARP Model.” I enjoyed the part about the kitten known as Professor Butterscotch that was just about to get tenure – because he was an actual professor.  However, I did not enjoy the fundamental misunderstanding of the actions of the Federal Reserve evidenced in the piece.  In particular, under the video on the Daily Show’s website is the following caption:

“A Bloomberg report reveals that the U.S. government loaned banks $7.7 trillion in secret bailout funds at no interest and then borrowed the money back at interest.”

The first misunderstanding in this caption is that it was not the U.S. government who loaned these funds to banks.  Instead, it was the Federal Reserve, the US government-chartered central bank.  This is important because the Fed is charged with serving as the lender of last resort – and that’s the role it played when it lent money through the discount window to struggling banks in the height of the financial crisis.  On the rest of the misunderstandings, let me quote John Williams, President and Chief Executive Office of the Federal Reserve Bank of San Francisco from the FRBSF Economic Letter I happened to read yesterday as well:

“Now there are many myths associated with these emergency programs. I would like to take this opportunity to dispel some of them. First, these programs were not “secret.” The fact is that all of these programs were publicly announced and reported on regularly. Indeed, the amounts lent in each program were shown on Fed financial documents made public every week. The only thing that wasn’t disclosed at the time was the names of specific borrowers and the amounts lent to them. Second, this lending did not put taxpayer money at significant risk. All of the lending was backed by good collateral and the vast majority of it has been fully repaid. Indeed, these emergency lending programs alone generated an estimated $20 billion in interest income. That income, like all the net income the Fed generates after its expenses, went to the U.S. Treasury. Third, borrowers did not get below-market interest rates. Many of our programs charged penalty rates so that borrowers would want to go back to the private markets as soon as they opened up again. Fourth, the Fed is audited. Our financial books are subject to a stringent reporting process and regularly reviewed by Congress (see Board of Governors 2011).”

Let me emphasize what I think is the point John Stewart and others have been missing:  the net income from the lending programs went to the Treasury.  This means that yes, the banks made profits, but so did the U.S. government – on money created out of thin air!  This is where it really matters that it was the Fed that did the initial lending.  The Fed has the power, given to it by Congress, to create new money.  Lending the new money to banks, even if the banks turn around and lend it to the government, keeps the interest rate lower than it otherwise would be.  In particular the interest rate was lowered for government borrowing.  So, rather than costing the taxpayer money, the lending by the Fed lowered the interest the government had to pay and also prevented financial collapse.  This sounds to me like a win-win.

Why don’t we just let the government print the money so they can have it directly without having to sell bonds or even collect taxes?  We’ve seen what happens when countries do that – they no longer only print money based on the needs of the economy.  Instead, they end up printing money whenever there’s a bill they have to pay.  Eventually the increase in the supply of money devalues the currency.  It makes a lot of sense to have the power to print money in the hands of people whose reputations rely on keeping inflation low and who have to return the profits to the government.  This way the government, and therefore the taxpayers, gets the benefit of the printing of the new money while also maintaining a hopefully more stable value of the currency.

It is possible that in some other blog post I may criticize the Fed – I do not always agree with their actions or policies, and keeping interest rates so low for so long scares me.  But serving as the lender of last resort to prevent an economic catastrophe is exactly what Congress created the Fed to do, and I believe that’s what they did with their emergency lending programs.  And, they did it with little risk to the taxpayer.