The Full Employment Mandate of the Federal Reserve: Its Origins and Importance

As we approach the 40th anniversary of the landmark Humphrey-Hawkins Act, this report underscores how the Federal Reserve's full employment mandate has made the Fed more accountable to working people. The report first traces the historical origins of the full employment mandate and highlights the pivotal but little-known role racial justice activists played in its creation. From the 1930s and through the rise of the civil rights movement, racial justice activists including Coretta Scott King, called for a coordinated federal effort to attain full employment. They envisioned an economy where every person who seeks employment can secure a job. King joined Congressional leaders Augustus Hawkins and Hubert Humphrey in eventually passing the landmark 1978 Full Employment and Balanced Growth Act (Humphrey-Hawkins) which legally required the Fed to pursue maximum employment.The report then turns to Federal Reserve monetary policy in the 1990's which offers an instructive model of what a full employment economy can look like. This real-world case study from our recent history shows that when labor markets tighten, workers begin to see broad-based wage gains, and persistent economic inequalities are reduced. Finally, the report underscores the continued importance of the full employment mandate today while providing an overview of proposed policies to eliminate or significantly curtail its effectiveness. In light of these findings, this report calls on Federal Reserve policymakers to use all tools at their disposal to fully realize the Fed's full employment mandate. Members of Congress must publicly affirm the importance of full employment while committing to reject any efforts to weaken or eliminate the full employment mandate. In particular, the Senate must reject nominees to the Board of Governors who have called for the narrowing of the Fed's mandate or who support policies that would undermine the Fed's ability to pursue full employment

Recent Developments in Trade Between the U.S. and the P.R.C.: A Legal and Economic Perspective

This paper presents the life story of a single small-business owner of immigrant background who wants his companyto grow. His business strategies are analysed both as a part of his own biographical work, and as they wereinfluenced and framed by broader political, economic and social processes. It is shown how his own personalqualities in combination with opportunity structures in the local market provided favourable conditions for hisbreak-in. Breaking out, however, seems to be presented with different types of barriers, such as lack of access tocapital, discrimination, and the fact that new markets may consist of different sorts of network that are in its turnmore difficult for new actors to enter. But even if newcomers often find these barriers difficult for to overcome,individuals are not just passive objects but also have the opportunity to realize their lives according to their own lifeplans

Monochromatic cycle partitions in local edge colourings

An edge colouring of a graph is said to be an $r$-local colouring if the edges incident to any vertex are coloured with at most $r$ colours. Generalising a result of Bessy and Thomass\'e, we prove that the vertex set of any $2$-locally coloured complete graph may be partitioned into two disjoint monochromatic cycles of different colours. Moreover, for any natural number $r$, we show that the vertex set of any $r$-locally coloured complete graph may be partitioned into $O(r^2 \log r)$ disjoint monochromatic cycles. This generalises a result of Erd\H{o}s, Gy\'arf\'as and Pyber.Comment: 10 page

Preprocessing Solar Images while Preserving their Latent Structure

Telescopes such as the Atmospheric Imaging Assembly aboard the Solar Dynamics Observatory, a NASA satellite, collect massive streams of high resolution images of the Sun through multiple wavelength filters. Reconstructing pixel-by-pixel thermal properties based on these images can be framed as an ill-posed inverse problem with Poisson noise, but this reconstruction is computationally expensive and there is disagreement among researchers about what regularization or prior assumptions are most appropriate. This article presents an image segmentation framework for preprocessing such images in order to reduce the data volume while preserving as much thermal information as possible for later downstream analyses. The resulting segmented images reflect thermal properties but do not depend on solving the ill-posed inverse problem. This allows users to avoid the Poisson inverse problem altogether or to tackle it on each of $\sim$10 segments rather than on each of $\sim$10$^7$ pixels, reducing computing time by a factor of $\sim$10$^6$. We employ a parametric class of dissimilarities that can be expressed as cosine dissimilarity functions or Hellinger distances between nonlinearly transformed vectors of multi-passband observations in each pixel. We develop a decision theoretic framework for choosing the dissimilarity that minimizes the expected loss that arises when estimating identifiable thermal properties based on segmented images rather than on a pixel-by-pixel basis. We also examine the efficacy of different dissimilarities for recovering clusters in the underlying thermal properties. The expected losses are computed under scientifically motivated prior distributions. Two simulation studies guide our choices of dissimilarity function. We illustrate our method by segmenting images of a coronal hole observed on 26 February 2015

Rounding Algorithms for a Geometric Embedding of Minimum Multiway Cut

The multiway-cut problem is, given a weighted graph and k >= 2 terminal nodes, to find a minimum-weight set of edges whose removal separates all the terminals. The problem is NP-hard, and even NP-hard to approximate within 1+delta for some small delta > 0. Calinescu, Karloff, and Rabani (1998) gave an algorithm with performance guarantee 3/2-1/k, based on a geometric relaxation of the problem. In this paper, we give improved randomized rounding schemes for their relaxation, yielding a 12/11-approximation algorithm for k=3 and a 1.3438-approximation algorithm in general. Our approach hinges on the observation that the problem of designing a randomized rounding scheme for a geometric relaxation is itself a linear programming problem. The paper explores computational solutions to this problem, and gives a proof that for a general class of geometric relaxations, there are always randomized rounding schemes that match the integrality gap.Comment: Conference version in ACM Symposium on Theory of Computing (1999). To appear in Mathematics of Operations Researc

Herd on the Street: Informational Inefficiencies in a Market with Short-Term Speculation

Standard models of informed speculation suggest that traders try to learn information that others do not have. This result implicitly relies on the assumption that speculators have long horizons, i.e, can hold the asset forever. By contrast, we show that if speculators have short horizons, they may herd on the same information, trying to learn what other informed traders also know. There can be multiple herding equilibria, and herding speculators may even choose to study information that is completely unrelated to fundamentals. These equilibria are informationally inefficient.