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Estimates of Potential Output and the Neutral Rate for the U.S. Economy
  • Language: en
  • Pages: 31

Estimates of Potential Output and the Neutral Rate for the U.S. Economy

Estimates of potential output and the neutral short-term interest rate play important roles in policy making. However, such estimates are associated with significant uncertainty and subject to significant revisions. This paper extends the structural multivariate filter methodology by adding a monetary policy block, which allows estimating the neutral rate of interest for the U.S. economy. The addition of the monetary policy block further improves the reliability of the structural multivariate filter.

Analysis of Images, Social Networks and Texts
  • Language: en
  • Pages: 376

Analysis of Images, Social Networks and Texts

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Recent Trends in Analysis of Images, Social Networks and Texts
  • Language: en
  • Pages: 333

Recent Trends in Analysis of Images, Social Networks and Texts

Zusammenfassung: This book constitutes the refereed proceedings of the 11th International Conference on Recent Trends in Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023. The 19 full papers 2 short papers and 1 demo paper included in this book were carefully reviewed and selected from 52 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; Network Analysis; Theoretical Machine Learning and Optimization; and Demo Paper

Multivariate Filter Estimation of Potential Output for the United States: An Extension with Labor Market Hysteresis
  • Language: en
  • Pages: 35

Multivariate Filter Estimation of Potential Output for the United States: An Extension with Labor Market Hysteresis

This paper extends the multivariate filter approach of estimating potential output developed by Alichi and others (2018) to incorporate labor market hysteresis. This extension captures the idea that long and deep recessions (expansions) cause persistent damage (improvement) to the labor market, thereby reducing (increasing) potential output. Applying the model to U.S. data results in significantly smaller estimates of output gaps, and higher estimates of the NAIRU, after the global financial crisis, compared to estimates without hysteresis. The smaller output gaps partly explain the absence of persistent deflation despite the slow recovery during 2010-2017. Going forward, if strong growth performance continues well beyond 2018, hysteresis is expected to result in a structural improvement in growth and employment.

Estimates of Potential Output and the Neutral Rate for the U.S. Economy
  • Language: en
  • Pages: 31

Estimates of Potential Output and the Neutral Rate for the U.S. Economy

Estimates of potential output and the neutral short-term interest rate play important roles in policy making. However, such estimates are associated with significant uncertainty and subject to significant revisions. This paper extends the structural multivariate filter methodology by adding a monetary policy block, which allows estimating the neutral rate of interest for the U.S. economy. The addition of the monetary policy block further improves the reliability of the structural multivariate filter.

Multivariate Filter Estimation of Potential Output for the United States
  • Language: en
  • Pages: 25

Multivariate Filter Estimation of Potential Output for the United States

Estimates of potential output are an important component of a structured forecasting and policy analysis system. Using information on capacity utilization, this paper extends the multivariate filter developed by Laxton and Tetlow (1992) and modified by Benes and others (2010), Blagrave and others (2015), and Alichi and others (2015). We show that, although still fairly uncertain, the real-time estimates from this approach are more accurate than estimates constructed from naïve univariate statistical filters. The paper presents illustrative estimates for the United States and discusses how the end-of-sample estimates can be improved with additional information.

Orthogonal Series
  • Language: en
  • Pages: 468

Orthogonal Series

Introductory concepts and some general results Independent functions and their first applications The Haar system Some results on the trigonometric and Walsh systems The Hilbert transform and some function spaces The Faber-Schauder and Franklin systems Orthogonalization and factorization theorems Theorems on the convergence of general orthogonal series General theorems on the divergence of orthogonal series Some theorems on the representation of functions by orthogonal series

Advances in Continuum Mechanics
  • Language: en
  • Pages: 513

Advances in Continuum Mechanics

Recognized authors contributed to this collection of original papers from all fields of research in continuum mechanics. Special emphasis is given to time dependent and independent permanent deformations, damage and fracture. Part of the contributions is dedicated to current efforts in describing material behavior with regard to, e.g., anisotropy, thermal effects, softening, ductile and brittle fracture, porosity and granular structure. Another part deals with numerical aspects arising from the implementation of material laws in the calculations of forming processes, soil mechanics and structural mechanics. Applications of theory and numerical methods belong to the following areas: Comparison with experimental results from material testing, metal forming under thermal and dynamic conditions, failure by damage, fracture and localized deformation modes. The variety of treated topics provides a survery of the actual research in these fields; therefore, the book is addressed to those interested in special problems of continuum mechanics as well as to those interested in a general knowledge.

Programming Languages
  • Language: en
  • Pages: 634

Programming Languages

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Introduction to OOP with C++
  • Language: en
  • Pages: 335

Introduction to OOP with C++

  • Type: Book
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  • Published: 2005
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  • Publisher: Unknown

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