An empirical analysis based on transcripts of the U.S. Federal Open Market Committee from 1994 to 2008 suggests that differences in committee members’ policy differences can partly be explained by differences in regional data, particularly unemployment rates. Also, personal background may play some role: FOMC members with experience in the non-financial private and public sectors have historically been more dovish.
Hamza Bennani, Etienne Farvaque, Piotr Stanek, (2015), “FOMC members’ incentives to disagree: regional motives and background influences”, NBP Working Paper No. 221.
The below are excerpts from the paper. Headings, links and cursive text have been added.
Different views in the Federal Open Market Committee (FOMC)
“Even though the final decision is collective, FOMC members may have their own policy preferences shaped by their educational and professional backgrounds. Therefore, members of the committee may process the common information differently, and/or may take into account data that are not available to other members such as their individual macroeconomic projections…Even if the degree of disagreement does not show up in an officially expressed dissenting vote, several studies have now proven that FOMC members cast their votes about monetary policy while having different considerations from each other.”
Reasons for different views
“The most notable source of heterogeneity mentioned in the literature is the presence of a bias related to the regional origin. This comes from the fact that, as several FOMC members are representatives from different economic regions which may, at each point in time, be located at different positions of the business cycle, their favored policy decision may be influenced by the situation in their home district.”
“A driving force for such different perceptions can be the policymakers’ personal backgrounds, and notably their education.”
Measuring members preferences
“One could use the voting records but… there may be more shortcomings than gains to use them to derive the members’ preferences. This is notably the case if members vote strategically, if only because they do not want to appear on the losing side of a vote, which they can guess from the meetings’ inner workings or from before-meeting discussions. This may, however, not forbid them to express their real views during the meetings, in which case the transcripts are a better source of information. This is because policy go-around are closer to the initial preferences of FOMC members at a specific meeting. Moreover…even if dissenting votes are an indication of disagreement, they are a very coarse metric for evaluating how much an individual member of the FOMC disagrees with the proposed policy actions. Thus, we assume the rates favored by the members in transcripts to be closer to their true preferences.”
Measuring regional bias
“As the Reserve Banks regions do not coincide with the ones of the American States, nor with the Census regions, some data are not available at the adequate level (i.e., the one of the Reserve Banks’ districts). As this may have blurred the previous analyses, we choose to build new relevant data at the Fed’s district level to further improve the consistency of our analysis.”
“We present the results of the estimated reaction functions for the Federal Reserve districts
in the form of individual Taylor-type rules estimated separately for each district’s member, using the frequency of the FOMC meetings (8 regular meetings per year) covering the
period 1994-2008…The dependent variable we consider is the preferred policy rate expressed by the central banker…The estimates [in the table below] confirm the presence of a regional bias of FOMC members.”
Measuring personal backgrounds’ influence
“In the final step, we assess how much the ‘policy differential’ is related to the biographical
data of FOMC members. As explained above, the aim is to assess the influence of the
personal characteristics of monetary policy makers on their respective desired interest
rate with respect to the actual one, having purged for any regional bias they are also
“As can be seen [from the table below] for example, it appears that a background as Professor tends to be associated with a propensity to disagree on the dovish side, as the policy differential is significantly related to this category”
“Members of the FOMC with experiences in the private or the public sector appear to have a propensity to disagree on the dovish side (with regard to the reference category, i.e., members coming from the financial sector), as their background is negatively related to the policy differential, whatever the sign of this differential.”