Perfecting the Market's Knowledge of Monetary Policy

The rational expectations revolution made clear that a complete macro model requires a specification of the government's economic policy. We argue that monetary policy should be conducted in such a way that the market can predict policy actions. An implication of market success in predicting policy actions is that interest rates move ahead of the policy actions, and such a timing relationship may appear to some as the central bank following the market instead of leading it. Another implication of the market predicting policy actions is that nominal interest rate changes provide no useful information to the central bank about the strength of aggregate demand or inflationary expectations. Finally, failure of the market to predict policy actions reflects a problem that needs to be addressed.We explore the theoretical implications of a monetary policy that is completely specified and perfectly understood by the market. We construct a bare-bones model to illustrate the key concepts. Finally, we conduct an empirical investigation of these issues, especially in the context of monetary policy since 1988, when the establishment of the federal funds future market made available well-defined market information on expectations about Fed policy actions. We find that when the intended funds rate is changed, interest rates over the maturity spectrum respond to news measured by changes in the one-month-ahead funds futures yield but do not respond to the anticipated component of the change in the intended funds rate.     

The Influence of B to B Social Media Message Features on Brand Engagement: A Fluency Perspective

Purpose: Social media is increasingly drawing the attention and interest of business-to-business (B to B) organizations. Yet, B to B organizations remain cautious in their social media pursuits, in part based on a stated lack of understanding for best practices. The purpose of the current work is to take initial steps to address this challenge by identifying specific social media message features that influence online users’ engagement with B to B organizations.

Methodology/Approach: This work examines the Twitter feeds of the top 50 social B to B brands (as reported by Brandwatch in 2015) to examine the effects of message features (hashtags, text difficulty, embedded media, and message timing) on user engagement, captured in terms of Twitter likes and retweets.

Findings: We argue that message features that enhance fluency (e.g., images) should enhance engagement. In contrast, those that disrupt fluency (e.g., hasthags) should result in lower levels of engagement. Consistent with these predictions, we find that hashtags and text difficulty correlate to lower levels of engagement whereas embedded media in the form of images and video correlate to higher levels of engagement. Also consistent with the proposed fluency framework, we find that tweets from B to B organizations generate greater engagement on evenings and weekends.

Research Implications: This research applies a fluency lens to identify specific message features that influence online engagement. In doing so, it highlights fluency as a powerful construct for understanding the drivers of B to B social media brand engagement. More generally, this work suggests fluency as a valuable conceptual lens for developing effective B to B social media strategies. This research also speaks to the complexity of B to B social media strategies – organizations must go beyond content and platform decisions, to also consider the specific features of the message.

Practical Implications: Social media is becoming more and more important to B to B organizations and is as yet an underutilized engagement tool. The current work offers initial strategies regarding message features that business practitioners can incorporate into their content development strategies to strengthen engagement. Specifically, efforts should be made to attain high levels of fluency in B to B social media content development.

Originality/Value/Contribution of the Paper: The current work offers initial insights as to the importance of understanding not only how social media topics/content influence engagement, but also the influence of message features (e.g., hashtags, embedded media). In doing so, it highlights fluency as a novel conceptual lens for developing more effective B to B social media strategies. Finally, it draws on actual tweets from leading B to B brands to examine the proposed influence of message features on engagement.     

The food pyramid challenge

Pyramid Power is a 1‐hour programme designed to teach food choices, serving sizes and nutrition. Participants (19 women and 8 men) were challenged to follow the recommendation in a step‐by‐step manner. Evaluation, two months after the programme, resulted in two major areas of change. Participants improved their scoring of three food groups (bread‐cereal‐rice‐pasta, vegetable and fruit) and decreased the number of fat–sweet mentions. The programme and challenge provides a way for nutritionists to identify what participants are eating, to track progress and to identify future programme needs.     

Determinants of Differential Rent Changes: Mean Reversion versus the Usual Suspects

This is a hedonic regression study of the 2001–2004 and 2004–2007 rent growth of 18,000 rental units. Which variables matter: Location? Age? Rent level? Occupancy duration? Structure type? The answers deepen understanding of the rental market and help guide statistical agency practice. We document significant rent stickiness. Initial relative rent level is the best predictor, mainly because of mean reversion. (This problem likely extends well beyond the present study.) “Location” comes in second, though often not statistically significant: the relative value of location is persistent. Age and occupancy duration are also notable. Our findings support statistical agency practices.     

America Sees Important Market in China

Premier Wen told us that the best solution to the bilateral trade imbalance is not to reduce Chinese exports to the US, but to increase Chinese imports from the USA.     

Explaining the Rent–OER Inflation Divergence, 1999–2007

U.S. Rent inflation has often greatly exceeded Owners' Equivalent Rent (OER) Inflation. Why? Critics believe that the Bureau of Labor Statistics is making a faulty utilities adjustment to OER and that the Federal Reserve Board should focus only on Rent inflation. Both beliefs are misguided. Herein we decompose the historical Rent–OER inflation differential into its various determinants. The utilities adjustment, which is necessary, sometimes contributed, but is no smoking gun. The main culprit was an economically interesting pattern of differential rent inflation across locales within cities, one common to many cities. Surprisingly, rent control also played a role.     

Managing inventories for maximum benefit.

In many companies it is not feasible to go to just-in-time (JIT) inventory management practices. In these instances, an aggressive inventory-monitoring program is a must. This article describes a program that resulted in a 75-percent reduction of inventory over a five-year interval. The topics covered will be applicable to those companies where JIT is not the answer.     

Road Pricing I

Readers of Economic Affairs , the Journal of the IEA, are invited to contribute to this section notes on previous articles, other IEA publications, and emerging ideas in economics. All such contributions must be typed double-spaced, not exceed 750 words, and be addressed to Kenneth Smith, Letters & Comments Editor, Economic Affairs , 2 Lord North Street, London SW1P 3LB.