Archive for category Using economic data

The Sources of Economic Growth

Today a tweet came across my iPad screen from Matt Yglesias.  I follow Matt under my economics persona @GonzoEcon.  And I don’t hesitate to recommend him to others interested in current economic events.  But his brief post on Slate about the sources of economic growth bears a little discussion.

With the provocative title, “Nobody Knows Where Economic Growth Comes From” the post is obviously designed to draw attention.  Matt writes, “This element is sometimes called “total factor productivity” and sometimes called “technology,” but it represents a statistical discrepancy, not an inquiry into independently identifiable properties of technological growth.” [minor spelling error corrected from original.]

There’s only one problem with this claim: it’s about 50 years out of date.  Matt is clearly referring to the seminal work by Robert Solow[1] and Ed Denison[2] on the sources of economic growth.  His reference to what Solow and Denison called “the residual” is correct as far as it goes.  But there has been quite a bit of work done since then on growth.

The most recent research was by Paul Romer.[3] He developed “endogenous growth theory” which shows that an important growth-inducing element is human capital.  Since human capital can be transmitted and acquired at relatively low cost in many cases, endogenous growth theory seems to provide a path to development for many countries.

But economic policies alone are not enough.  Robert Hall and Charles Jones studied the effect of social infrastructure on growth.[4]  These ideas are not new, dating at least from Max Weber.[5]  What is new, however, are methodologies for quantifying some of these variables and including them in statistical analysis.

Economists have long emphasized the importance of factors such as the enforcement of property rights (including intellectual property), a uniform and consistent rule of law, lack of corruption, and a host of other variables.  Indeed, the World Bank publishes its Ease of Doing Business statistical table every year.[6]  Hall and Jones focus on a narrow, relatively quantifiable, set of statistics including:

  1. Distance from the equator (a proxy for migration from Western Europe where modern market economic thought was first developed);
  2. Measures of the extent to which Western European languages are spoken as the first language in each country;
  3. Predicted trade share of an economy using the variable constructed by Frankel and David Romer;[7]
  4. Ethnolinguistic fractionalization index (Taylor and Hudson[8]
  5. Religious affiliation (fractions of each country’s population that are Catholic, Muslim, Protestant, and Hindu);

The scatter diagram below shows at least a bit of positive correlation between real GDP per capita and an index of social infrastructure.

Hall and Jones scatter diagram

Hall and Jones scatter diagram

Statistics geeks will appreciate these results:

Hall and Jones Statistics (example)

Hall and Jones Statistics (example)

Economists continue to do research.  The best research tries to relate economic theory to real-world data.  Drs. Hall and Jones are outstanding practitioners of this science.  While their analysis of economic growth still leaves room for additional research, that is the point.  And that’s what keeps me interested in economics.



[1] See, for example, “A Contribution to the Theory of Economic Growth.” Quarterly Journal of Economics, 1956, and “Technical Progress, Capital Formation, and Economic Growth,” American Economic Review, 1962.

[2] Two examples: “Sources of Postwar Growth in Nine Western Countries,” American Economic Review, 1967, and “The Contribution of Capital to Economic Growth,” American Economic Review, 1980.

[3] Luis A. Rivera-Batiz and Paul M. Romer, “Economic Integration and Endogenous Growth.” Quarterly Journal of Economics, May, 1991. Dr. Romer is currently a visiting professor at New York University’s Stern School of Business.

[4] Hall, Robert E. and Charles I. Jones, “Why Do Some Countries Produce So Much More Output Per Worker Than Others?” Quarterly Journal of Economics, February, 1999.

[5] Weber, Max, The Protestant Ethic and the Spirit of Capitalism, 1904-1905.

[6] http://www.doingbusiness.org/rankings/ accessed August 6, 2012.

[7] Frankel, Jeffrey A., and David Romer, ”Trade and Growth: An Empirical Investigation,” NBER Working Paper No. 5476, 1996.

[8] Taylor, Charles L., and Michael C. Hudson, World Handbook of Political and Social Indicators (New Haven: Yale University Press, 1972).

, , , , , , , , , , , ,

No Comments

What Is A Recession?

What is a recession?  This question is prompted by an exchange over on Twitter.  First, the St. Louis Fed tweeted:

St. Louis Fed tweet

 

I replied:

Tony Lima tweet

Then Kathleen Hays (Twitter profile: The Hays Advantage, Host, Bloomberg Radio. Economy, finance, markets, politics. Monday-Friday 12-3pm ET – The Econoqueen lives!) asked:

Kathleen Hays tweet

Hmmm.  It’s been a while since anyone asked this question, so it’s probably time to review the rules.  Off the top, everyone concedes that the NBER Business Cycles Committee is the arbiter of when recessions begin and end.  Their statement of September 20, 2010 said the recession ended in June, 2009.

Dissenting Opinions

I’ve written about this before, but it bears repeating: the U.S. unemployment rate has been above 8 percent since January, 2009.  The labor force participation rate is around 60%, the lowest level in three decades (specifically, since May, 1973).  These are not signs of a healthy economy.  It’s my opinion that the recession never really ended.  Other, better-known, economists agree.  On September 2, 2011, Ken Rogoff said,  “We have never left the recession by any reasonable measure. If you’re 10 feet below water, and you come up a foot, you’re still drowning. The question of whether we are growing at 1% or falling at 1% is not the big issue. We’re in a different animal.”  And there’s this from CNN:

“John Silvia, chief economist for Wells Fargo Securities, said the economy remains at risk as long as most households are struggling with weak wages, rising prices and the loss of household wealth.

Silvia puts the chance of a new recession at 30% to 40%, up from 20% to 30% before Friday’s jobs report.

“A significant number of Americans have never seen a recovery,” Silvia said. “We’re just skating on really thin ice. We can’t take another shot.”

Technically, the recession ended in June 2009, according to the official definition from the National Bureau of Economic Research. But that group takes into account a wide range of economic indicators.

For the average household, the Great Recession never ended. In fact, eight in 10 Americans think we’re still on one, according to a newCNN/ORC poll.”

What Defines a Recession?

Once upon a time, defining a recession was easy: two consecutive calendar quarters of declining real GDP.  That’s easy to understand and transparent.  Economists understood the definition’s strengths (simplicity, transparency) and weaknesses (using a single variable to define a recession is not a good idea).

Enter the NBER,  Here’s what they have to say about business cycles:

“The NBER’s Business Cycle Dating Committee maintains a chronology of the U.S. business cycle. The chronology comprises alternating dates of peaks and troughs in economic activity. A recession is a period between a peak and a trough, and an expansion is a period between a trough and a peak. During a recession, a significant decline in economic activity spreads across the economy and can last from a few months to more than a year. Similarly, during an expansion, economic activity rises substantially, spreads across the economy, and usually lasts for several years.

In both recessions and expansions, brief reversals in economic activity may occur-a recession may include a short period of expansion followed by further decline; an expansion may include a short period of contraction followed by further growth. The Committee applies its judgment based on the above definitions of recessions and expansions and has no fixed rule to determine whether a contraction is only a short interruption of an expansion, or an expansion is only a short interruption of a contraction. The most recent example of such a judgment that was less than obvious was in 1980-1982, when the Committee determined that the contraction that began in 1981 was not a continuation of the one that began in 1980, but rather a separate full recession.

The Committee does not have a fixed definition of economic activity. It examines and compares the behavior of various measures of broad activity: real GDP measured on the product and income sides, economy-wide employment, and real income. The Committee also may consider indicators that do not cover the entire economy, such as real sales and the Federal Reserve’s index of industrial production (IP). The Committee’s use of these indicators in conjunction with the broad measures recognizes the issue of double-counting of sectors included in both those indicators and the broad measures. Still, a well-defined peak or trough in real sales or IP might help to determine the overall peak or trough dates, particularly if the economy-wide indicators are in conflict or do not have well-defined peaks or troughs.”

The Committee’s FAQ is also instructive in explaining why they no longer only look for two quarters of declining real GDP.

Let me translate.  Paraphrasing Humpty Dumpty’s conversation with Alice, ‘ ”When I use the word recession,’ Humpty Dumpty said in rather a scornful tone, ‘it means just what I choose it to mean — neither more nor less.
“The question is,” said Alice, “whether you can make words mean so many different things.”
“The question is,” said Humpty Dumpty, “which is to be master— that’s all.” ‘
(from Through the Looking Glass, and What Alice Found There, Lewis Carroll, 1871, ch. 6)

The NBER Business Cycles committee includes many smart economists, most of whom I admire greatly:

Robert Hall, Chair — Director of NBER’s Program of Research on Economic Fluctuations and Growth and Professor, Stanford University
Martin Feldstein – President Emeritus of NBER and Professor, Harvard Univerity
Jeffrey Frankel – Director of NBER’s Program on International Finance and Macroeconomics and Professor, Harvard University
Robert J. Gordon – NBER Research Associate and Professor, Northwestern University
James Poterba – President of NBER and Professor, M.I.T.
Christina Romer – Co-Director of NBER’s Program on Monetary Economics and Professor, University of California, Berkeley
David Romer – Co-Director of NBER’s Program on Monetary Economics and Professor, University of California, Berkeley
James H. Stock – Research Associate in the NBER’s Monetary Economics Program and Professor, Harvard University
Mark W. Watson – Research Associate in the NBER’s Economic Fluctuations and Growth Program and Professor, Princeton University”

But, after all, the Committee changed the definition of a recession, making it less transparent and more complicated.  A cynic might note that this change creates a demand for the services of economists to serve on the Business Cycles Committee.  But the change has been made.  I interpret that to mean that my opinion is as good as theirs.

The recession of 2008 has never ended.  Any talk of a “double-dip” is meaningless.

, , , ,

No Comments

Taxes Owed by 98,281 US Government Employees

U.S. Non-compliance Rate

There is over one billion dollars of taxes owed by 98,281 U.S. government employees.  Fully 36 employees in the Executive Office of the President owe back taxes of $833,970 covering an average of over two previous tax years. The White House delinquency rate is 2.01%. At least that’s better than the overall government delinquency rate of 3.33%.  The motto of the White House must be, “Learn from Tim Geithner.”

This figure covers only civilian, non-retired employees.  And admittedly a large chunk comes from the U.S. Postal Service. (I thought the Postal Service wasn’t part of the government any more.  I’ve been working for years to learn to type usps.com instead of usps.gov.)

This is part of the fascinating data set created by the Federal Employee/Retiree Delinquency Initiative (FERDI, IRS Part 5, Chapter 19, Section 18).  This story comes from Mark Segraves, reporter for WTOP radio in Washington, D.C.  According to him, “we may have posted FERDIs the past 5 years or so. I’ve been doing this story each year, IRS at first only released it under FOIA, now they just hand it over.”[1]  WTOP uses Scribd.com to post a lot of their raw data.  The Excel workbook is available both with the story on the station’s website and on Scribd.

Investor’s Business Daily has a vitriolic column.  And the story is spreading.  I’m working with Mark Segraves to pull together some historical data on non-compliance by the government compared to the general population.  For 2009, the Federal government civilian workforce had a non-compliance rate of 3.35%.  As far as I can tell from pulling together disparate data sets from the IRS, the general population had a non-compliance rate of 4.86%.[2]  The history of non-compliance in the 21st century is shown below.  When I’m reasonably confident that my dataset is correct I’ll post a link to the Excel workbook.  Stay tuned.



[1]   Segraves, Mark (2012).  Personal e-mail communication.

[2]   Noncompliance data is available here while data on total tax returns is here.  The overall data is from ” Selected Income and Tax Items in Current and Constant Dollars . Both links are to Excel workbooks, so don’t expect a web page to necessarily open.

, , , , , ,

1 Comment

Real Yields Turn Positive on 10-year TIPS

On January 18, real yields turned positive on 10-year TIPS.  Markets are possibly getting a bit more optimistic.  Here are a couple of representative real yield curves. Essentially, during the last week the real yield curve shifted up about 14 basis points. (To get the complete data in an Excel 2007 workbook, click here.)

Real Yield Curves

Nominal yields shifted up about 19 basis points in the longer maturities.  Thus there was an increase in inflation expectations of about 5 basis points.

Nominal Yield Curves

We can easily construct an inflation expectations curve.  Expected inflation is simply the difference between the nominal and real interest rate for each maturity.  Here’s what it looks like:

 

Inflation Expectations Curves

 

 

 

 

, , , , , ,

No Comments

The Planet Money Team Strikes Out

The December 18 New York Times Magazine includes an article by Adam Davidson, one of the founders of NPR’s “Planet Money” series.  In this case, the Planet Money team strikes out.

Mr. Davidson writes about looking for leading economic indicators, specifically variables that predict the future path of some other economic variable.  In this case, the variable of interest is real per capita disposable income.  Davidson’s preferred leading indicator:  “The amount of French Champagne that Americans consume has predicted — with nearly 90 percent accuracy — the average American income one year later.”  He offers the following graph as evidence.

Davidson's Result

Davidson's Result

With all due respect, Mr. Davidson should stick to reporting.  Economists have spent six decades using all sorts of statistical tools to understand consumption spending.  Frankly, an R2 of 0.90 is not even worth mentioning.  (I assume that the “90 percent accuracy” refers to the adjusted R2.)

As an example, let’s consider the economist’s standard fallback position when we know next to nothing about a variable: a simple regression of the variable on the number of the time period.  Davidson uses data from 1996 through 2010.  Based on the graph above, it’s pretty clear he’s using annual data.  That’s fifteen years of data.  I created a simple variable for time in which 1996 was numbered 1, 1997 was numbered 2, and so on until 2010, which was numbered 15.  I then did a regression of real disposable per capita income on time.  (Real per-capita disposable income was taken directly from the Bureau of Economic Analysis’s Table 7.1.  Data available via link from http://www.bea.gov. )  The statistics are shown below.  To summarize, my regression explains 98.5 percent of the variation, far better than champagne sales.  Of course, this result is not as sexy or marketable as Mr. Davidson’s.  If he wants to play in this sandbox, he should stop writing and get a Ph.D. in economics like the rest of us.

Coefficients

Standard Error

t Stat

p-level

H0 (2%) rejected?

Intercept

20,110.50476

336.9763

59.67929

0.E+0

Yes

Time

1,131.45357

37.06245

30.5283

1.73639E-13

Yes
Regression Statistics
R

0.9931

R Square

0.98624

Adjusted R Square

0.98518

S

620.17343

Total number of observations

15

My Model

My Model

, , , , ,

No Comments

Suspicious Data From the BLS

While sifting through the numbers from the November employment report,[1] I ran across what appears to be suspicious data from the BLS.  At the bottom of Table A-11 I found this:

HOUSEHOLD DATA

Table A-11. Unemployed persons by reason for unemployment

[Numbers in thousands]

Reason

Not seasonally adjusted

Seasonally adjusted

Nov.

Oct.

Nov.

Nov.

Oct.

Nov.

2010

2011

2011

2010

2011

2011

UNEMPLOYED AS A PERCENT OF THE

 

CIVILIAN LABOR FORCE

Job losers and persons who completed temporary jobs

5.8

4.8

4.7

6.2

5.2

4.9

Job leavers

0.6

0.7

0.7

0.6

0.7

0.7

Reentrants

2.2

2.2

2.1

2.2

2.2

2.2

New entrants

0.8

0.8

0.8

0.8

0.8

0.8

Source: Bureau of Labor Statistics, http://bls.gov/news.release/empsit.nr0.htm.  Accessed December 2, 2011.

Take a close look at those last three rows.  The numbers are virtually identical.  What’s especially troubling is that the seasonally adjusted figures are the same as those that are not seasonally adjusted.  I would expect a discrepancy in November due to seasonal holiday hiring.

I have no idea whether this is important or even real.  And, yes, I realize the numbers are small relative to the job losers and persons completing temporary jobs.  But this leads me to a bit more doubt about the veracity of the BLS numbers.

 



[1] Yes, I know I have too much time on my hands.  Table 11???

, , , , ,

No Comments

Use Market Data to Measure Expected Inflation

Introduction

Economists take it for granted that everyone knows the definition of the real interest rate: r = i – p where i is the nominal interest rate and p is the inflation rate.  The real interest rate measures the net transfer of purchasing power from borrowers to lenders.  Lenders will be repaid i dollars per hundred dollars loaned per year, but the purchasing power of those dollars will decrease by the inflation rate, p.  The purpose of this post is to show you how to use market data to measure expected inflation

In principle this is easy.  If the market interest rate is 3% and inflation is 1%, the real interest rate is 2%.  But if we want to look at future interest rates we need some measure of expected future inflation.

Individuals are, naturally, free to develop their own forecasts of the future inflation rate.  This article shows how to use publicly available data to calculate the market’s average expectation of future inflation rates.

TIPS

TIPS stands for Treasury Inflation-Protected Securities.  These securities are issued by the U.S. Department of Treasury.  Follow that link to learn the details of how it works (links to Treasury site).  Since TIPS are adjusted to compensate for inflation, their yield to maturity is the real interest rate.  It’s helpful to know that TIPS are issued in maturities of 5, 10, and 30 years.  The minimum purchase is a measly $100.

Calculating Expected Inflation

The expected future rate of inflation over 5, 10, and 30 year horizons is the difference between ordinary Treasury securities with those maturities and the yield on TIPS.  This is an approximation because coupon payments on ordinary Treasuries are constant, but the coupon (and maturation value) on TIPS securities adjust to the inflation rate.  But let’s not allow details to get in the way of a good story.

As of October 14, 2011, here’s what the markets are forecasting for expected inflation:

 

Maturity (years)

Nominal yield

TIPS yield

Expected Inflation

5

1.12%

-0.54%

1.66%

10

2.26%

0.28%

1.98%

30

3.22%

1.12%

2.10%

For those who want data sources, etc., e-mail me for an Excel 2011 workbook.

, , , , ,

2 Comments

I support error 451 - link opens in new window
Powered by Netfirms
Better Tag Cloud