scholarly journals A Large-Dimensional Factor Analysis of the Federal Reserve's Large-Scale Asset Purchases

2015 ◽  
Author(s):  
Lasse Bork
Keyword(s):  
Factor Analysis ◽  
Large Scale ◽  
Asset Purchases

The non-linear effects of the Fed asset purchases

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alessio Anzuini
Keyword(s):  
Financial Markets ◽  
Large Scale ◽  
Balance Sheet ◽  
Monetary Economics ◽  
American Economic Review ◽  
Vector Autoregressive ◽  
Portfolio Balance ◽  
State Dependent ◽  
Linear Effects ◽  
Asset Purchases

Abstract The Federal Reserve responded to the great financial crisis deploying new monetary policy tools, the most notable of which being the expansion of its balance sheet. In a recent paper, Weale, M., and T. Wieladek. 2016. “What Are the Macroeconomic Effects of Asset Purchases?” Journal of Monetary Economics 79 (C): 81–93 show that the asset purchases were effective in stimulating economic activity as well as inflation and asset prices. Here I show that their results are state dependent: large scale asset purchase are effective only when financial markets are impaired. Financial markets are under stress when the effective risk-bearing capacity of the financial sector is drastically reduced, i.e. when the excess bond premium (EBP) of Gilchrist, S., and E. Zakrajšek. 2012. “Credit Spreads and Business Cycle Fluctuations.” The American Economic Review 102 (4): 1692–72 exceed a certain threshold. Using an estimated threshold vector autoregressive model conditional on the EBP regime, I show that an increase in the balance sheet has expansionary effects on GDP and inflation when EBP is high, but not when it is low (as its effects become mostly insignificant). I argue that the high EBP can be interpreted as a proxy of market dis-functioning so that only when this channel of transmission is on, the unconventional policy is particularly effective. This suggests that models of transmission of unconventional policies, based on asset purchases, should focus also on the market functioning channel and not only on the portfolio balance one.

scholarly journals Measuring the value of a digital supplemental resource

2021 ◽  
Vol 45 (4) ◽  
pp. 685-693
Author(s):  
Yvonne M. Baptiste ◽  
Samuel Abramovich ◽  
Cherylea J. Browne
Keyword(s):  
Factor Analysis ◽  
Science Education ◽  
Construct Validity ◽  
Student Perceptions ◽  
Large Scale ◽  
Quantitative Methods ◽  
Student Perception ◽  
Digital Learning ◽  
Internal Reliability ◽  
Traditional Component

Supplemental resources in science education are made available to students based on the belief that they will improve course-based student learning. This belief is ubiquitous, with supplemental resources being a traditional component of physiology education. In addition, the recent large-scale transition to remote learning caused by the Covid-19 pandemic suggests an increased relevance and necessity of digital versions of supplemental resources. However, the use of a supplemental resource is entirely dependent on whether students view it as beneficial. If students in a specific course do not perceive a supplemental resource as useful, there is little reason to believe the resources will be used and are worthy of investment. Consequently, measurement of student perception regarding the effectiveness of any digital learning tool is essential for educators and institutions in order to prioritize resources and make meaningful recommendations to students. In this study, a survey was used to determine student perceptions of a digital, supplemental resource. Quantitative methods, including exploratory factor analysis, were performed on data collected from the survey to examine the dimensionality and functionality of this survey. The findings from this study were used to devise an improved, standardized (i.e., reliable and valid) survey that can be used and adapted by physi3ology researchers and educators to determine student perception of a digital supplemental resource. The survey, with known construct validity and internal reliability, can provide useful information for administrators, instructors, and designers of digital supplemental resources.

Mining Spatial Patterns of Distribution of Uranium in Surface and Ground Waters in Ukraine

2017 ◽  
pp. 520-546
Author(s):  
Michael Govorov ◽  
Viktor Putrenko ◽  
Gennady Gienko
Keyword(s):  
Factor Analysis ◽  
Spatial Distribution ◽  
Spatial Patterns ◽  
Large Scale ◽  
Chemical Elements ◽  
Environmental Indicators ◽  
Local Factor ◽  
Correlation And Regression Analysis ◽  
Weighted Factor ◽  
Major Factors

A variety of geovisualization and spatial statistical methods can reveal spatial patterns in the distribution of chemical elements in surface and groundwater, and also identify major factors which define those patterns. This chapter describes a combination of modeling techniques to enhance understanding of large-scale spatial distribution of uranium in groundwater in Ukraine, by linking spatial patterns of several indicators and predictors. Factor, correlation, and regression analysis, including their spatial implementations, were used to describe the impacts of several environmental variables on spatial distribution of uranium. Local factor analysis (or Geographically Weighted Factor Analysis, GWFA) was proposed to identify major environmental factors which define the distribution of uranium, and to discover and map their spatial relationships. The study resulted in a series of maps to help visualize and explore the relationships between uranium and several environmental indicators.

Developing an Instrument for E-Public Services’ Acceptance Using Confirmatory Factor Analysis

2012 ◽  
Vol 24 (3) ◽  
pp. 18-44 ◽  
Author(s):  
Ahmed Alzahrani ◽  
Bernd Carsten Stahl ◽  
Mary Prior
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Large Scale ◽  
Public Services ◽  
Equation Modeling ◽  
Data Sampling ◽  
Potential Cost ◽  
Confirmatory Factor

Governments worldwide spend billions from their allocated IT budgets to deliver convenient electronic services to their citizens. As a result, it is important to encourage citizens to use these services to avoid potential failures. Yet, few empirical studies exist that cover the relevant issues of adoption from the perspective of citizens in developing countries. Moreover, the need for a well-validated instrument to capture citizen adoption of such services is vital, given the vast investment in technology and the potential cost-saving implications. This study integrates elements from the most popular theories, including adoption technology acceptance model (TAM), innovation diffusion theory (IDT), and theory of planned behavior (TPB), in conjunction with web trust models. It develops an instrument to measure citizens’ acceptance of electronic public services by utilizing confirmatory factor analysis (CFA) within the structural equation modeling technique. Findings of a large scale data sampling of citizens in Saudi Arabia indicate that the proposed measurement model is an acceptable fit with the data. Overall, the findings supply a rigorous instrument for measuring citizens’ acceptance of e-public services, providing further insights for researchers and offering policy makers a suitable tool with which to study proposed strategies.

The Relation Between Neurosis and Psychosis an Analysis of Symptoms and Past History of 819 Psychotics and Neurotics

1956 ◽  
Vol 102 (426) ◽  
pp. 1-21 ◽  
Author(s):  
D. S. Trouton ◽  
A. E. Maxwell
Keyword(s):  
Factor Analysis ◽  
Psychiatric Disorders ◽  
Recent Work ◽  
Large Scale ◽  
Past History ◽  
Effective Technique ◽  
Psychiatric Classification ◽  
Scientific Methods ◽  
Essential Condition ◽  
History Of

While it is usual among psychiatrists to express dissatisfaction with psychiatric classification and its problems it is by no means unusual for their psychological colleagues to advocate factor analysis as an effective technique for resolving such problems. For example, Burt (1954) describes factor analysis as “essentially a statistical device for securing the best available scheme of classification”. Yet the problems and the device tend to remain apart, the former becoming intensified, the latter undergoing continued improvements. Twenty-five years ago T. V. Moore (1930) demonstrated that the application of factor analysis to the study of psychiatric disorders was feasible, and more recent work, especially that of Eysenck (e.g. 1947) has impressively shown its fruitfulness. That some clinicians remain sceptical of the claims made for these techniques is, in part, due to the infrequency with which factorial studies bearing on psychiatry have been pursued far enough for their implications to be tested and the findings integrated with those established by other scientific methods. This deficiency may be attributable to the fact that large scale programme research (Eysenck, 1953) is an almost essential condition, if this is to be achieved.

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