In a post two days ago, I highlighted the CBO report on the change in income inequality in the United States between 1979  and 2007.  The last sentence of that blogposting opines that the households represented in each quintile change over time; therefore, it’s not necessarily those who were in the top 1% in 1979 who made the massive gains in share of income and remained in the top 1% in 2007.

A recent Federal Reserve Bank of Minneapolis report highlights the dynamics of household movement across income quintiles during the 2001 to 2007 period.  The chart below shows that 44% of those in the bottom bracket in 2001 escaped to higher brackets by 2007 and that 34% of those in the highest quintile fell to at least the second quintile.  Longitudinal studies of particular households are most useful if we wish to understand what has happened to the distribution of household incomes over time.  The CBO study does not address the question, but the Panel Study of Income Dynamics selects a relative short and volatile period for its reference points.

How does this all matter?  It matters in that policy makers respond to such information to reshape both the regulatory structure and income tax  policies.  Given budgetary impasses that have characterized the past year, our legislators have not been able to reach any sort of consensus on how to do three things 1) ensure that the tax system creates appropriate incentives for generating growth,  2) put the US budgetary future on a sustainable path, and 3) create an efficient and equitable tax structure.  Will we again fail to take the opportunity to reach such desiderata?   What do you think?

The “official scorekeeper” for Congress, the Congressional Budget Office, has just released a report on how the distribution of household income has changed from 1979 (when coincidentally I came to Lawrence) to 2007.  Their bottom line result is displayed in the figure below.  The “CBO estimates that the dispersion of market income grew by about one-quarter between 1979 and 2007, while the dispersion of after-tax (and governmental transfers) income grew by about one third.”  In particular, the share of after-tax, after transfer household income that accrued to those with the highest 1% of income grew from 8% in 1979 to 17% in 2007.  One should be a bit cautious about these comparisons since the there is a lot of movement in and out of different income brackets.  In short, it’s unlikely that most of the households counted in the 1979 calculation are in the 2007 calculation.  I encourage you to read the summary or the full report.

David Zetland, in his aguanomics blog (www.aguanomics.com) posted the following Dilbert cartoon.  When someone asks you to do something (from a job or project perspective), think about the value of your time.

Most of you have probably never heard of either Tom Sargent or Chris Sims.  I’m not surprised; however, if you are an economics major at Lawrence, they have influenced how you have been taught.  I learned macroeconomics from Sargent.  His emphasis on the microfoundations of macroeconomics forms the base of how I think about macro questions.  In short,  a strong understanding of labor markets and how they work is critical to serious macroeconomic policy making.  Few of our decision-makers today understand that link.  Stated differently,  Okun’s Law (for every 2 percentage points that output is below potential output, the unemployment rate is 1 percentage point above its “natural” level) is an empirical relationship, not a theoretical one, that is if you are not a reductionist (to simple correlations.) Sargent convinced me that to reduce the unemployment rate in this country, one’s understanding must go well beyond how monetary and fiscal policy affect aggregate demand.

Chris Sims, a first rate econometrician, has addressed the fundamental questions of causality in macroeconomics, especially time series causality.  For those of you without a clue what this means, he tried to solve the chicken (money growth) and egg (GDP growth) problem; which came first?   His answer came in a 1972 American Economic Review paper entitled “Money, Income and Causality.”  Given his award, my students in Money and Monetary Policy will have an opportunity to work through this paper later this term.  Of course, Sims did not stop there.  No reductionist he, he broadened the question to ask of the variables that matter in macroeconomic discussion (Real GDP, Unemployment rate, stock of money, wages, the price level, and import prices), how do they relate to one other.  This paper, published in Econometrica in 1980 under the title “Macroeconomics and Reality”, is a much tougher read.  The conceptual direction and the results, however, are not hard to understand.  Sims argued that we should learn how the histories of each of these variables are related to each another.  He developed Vector Autoregression Techniques to answer this question.  These techniques have been embedded in contemporary econometrics software packages and in the work of many macroeconomists.  Despite the title of the paper, Sims did not believe he had found “the holy grail”, but he believed that an clear understanding of the time series relationships amongst the key macro  variables was essential to know where to look for it.

Of course, I am happy to discuss their work with any and all interested.  I am honored to have been a student of both of these creative economists and celebrate their receipt of the Nobel Prize in Economics for 2011.