scholarly journals The Missing “Cycle” Part and Other Thoughts on the Global Financial Cycle

2020 ◽  
pp. 15-32
Author(s):  
Olga Bondarenko
Keyword(s):  
Capital Flows ◽  
Factor Model ◽  
Common Factor ◽  
Primary Role ◽  
Trade Off ◽  
Financial Cycle ◽  
Domestic Policies ◽  
Quantitative Importance ◽  
Macroeconomic Stability

The paper studies co-movement in capital flows, which gives rise to a phenomenon dubbed the global financial cycle. It first estimates a global common factor in capital flows using a factor model and draws inferences of its quantitative importance. Then the paper studies the cyclical properties of the extracted factor and concludes that, in general, its importance for capital flows is relatively limited. This may suggest that the Mundell-Fleming trilemma (as opposed to dilemma) still describes the trade-off faced by policymakers, and domestic policies play the primary role in maintaining macroeconomic stability.

From Bi-Dimensionality to Uni-Dimensionality in Self-Report Questionnaires

2020 ◽  
pp. 1-14 ◽  
Author(s):  
Bjarne Schmalbach ◽  
Markus Zenger ◽  
Michalis P. Michaelides ◽  
Karin Schermelleh-Engel ◽  
Andreas Hinz ◽  
...  
Keyword(s):  
Factor Model ◽  
Common Factor ◽  
Self Regulation ◽  
Model Fit ◽  
Self Report ◽  
External Criterion ◽  
Common Factor Model ◽  
Random Intercept ◽  
Using Data ◽  
Core Self

Abstract. The common factor model – by far the most widely used model for factor analysis – assumes equal item intercepts across respondents. Due to idiosyncratic ways of understanding and answering items of a questionnaire, this assumption is often violated, leading to an underestimation of model fit. Maydeu-Olivares and Coffman (2006) suggested the introduction of a random intercept into the model to address this concern. The present study applies this method to six established instruments (measuring depression, procrastination, optimism, self-esteem, core self-evaluations, and self-regulation) with ambiguous factor structures, using data from representative general population samples. In testing and comparing three alternative factor models (one-factor model, two-factor model, and one-factor model with a random intercept) and analyzing differential correlational patterns with an external criterion, we empirically demonstrate the random intercept model’s merit, and clarify the factor structure for the above-mentioned questionnaires. In sum, we recommend the random intercept model for cases in which acquiescence is suspected to affect response behavior.

scholarly journals A Dynamic Factor and Neural Networks Analysis of the Co-movement of Public Revenues in the EMU

2021 ◽  
Author(s):  
Cosimo Magazzino ◽  
Marco Mele
Keyword(s):  
Neural Networks ◽  
Factor Model ◽  
Common Factor ◽  
Back Propagation ◽  
Dynamic Factor ◽  
Common Component ◽  
Economic Cycles ◽  
Composite Nature ◽  
Empirical Demonstration ◽  
Public Revenues

AbstractThis paper shows that the co-movement of public revenues in the European Monetary Union (EMU) is driven by an unobserved common factor. Our empirical analysis uses yearly data covering the period 1970–2014 for 12 selected EMU member countries. We have found that this common component has a significant impact on public revenues in the majority of the countries. We highlight this common pattern in a dynamic factor model (DFM). Since this factor is unobservable, it is difficult to agree on what it represents. We argue that the latent factor that emerges from the two different empirical approaches used might have a composite nature, being the result of both the more general convergence of the economic cycles of the countries in the area and the increasingly better tuned tax structure. However, the original aspect of our paper is the use of a back-propagation neural networks (BPNN)-DF model to test the results of the time-series. At the level of computer programming, the results obtained represent the first empirical demonstration of the latent factor’s presence.

Underlying Common Factors of Adolescent Problem Behaviors

2002 ◽  
Vol 29 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Lening Zhang ◽  
John W. Welte ◽  
William F. Wieczorek
Keyword(s):  
Problem Behaviors ◽  
Latent Variable ◽  
Factor Model ◽  
Common Factor ◽  
Measurement Model ◽  
First Order ◽  
Adolescent Problem Behaviors ◽  
The Common ◽  
Order Factor ◽  
Second Order Factor Analysis

The Buffalo Longitudinal Study of Young Men was used to address the possibility of a common factor underlying adolescent problem behaviors. First, a measurement model with a single first-order factor was compared to a model with three separate correlated first-order factors. The three-factor model was better supported, making it logical to conduct a second-order factor analysis, which confirmed the logic. Second, a substantive model was estimated in each of two waves with psychopathic state as the common factor predicting drinking, drug use, and delinquency. Psychopathic state was stable across waves. The theory that a single latent variable accounts for large covariance among adolescent problem behaviors was supported.

scholarly journals Spillover Effect of Global Financial Cycle To Asset Markets in Asean-5 Countries: A Structural VAR Approach

2018 ◽  
Vol 2 (02) ◽  
pp. 1
Author(s):  
Sri Andaiyani ◽  
Telisa Aulia Falianty
Keyword(s):  
Risk Aversion ◽  
Capital Flows ◽  
Asset Prices ◽  
Emerging Market ◽  
Structural Var ◽  
Asset Markets ◽  
Equity Prices ◽  
Financial Cycle ◽  
Property Prices ◽  
The Impact

<p><em>An upsurge and volatility of capital flows to Emerging Asian Economies indicated that there is the potential effect of global financial cycle to emerging market. It provides an overview of investor risk aversion in short term investment after financial crisis 2008. Global financial cycle could have a significant impact to asset prices, including equity prices and property prices. Rey (2015) has triggered an interesting discussion about global financial cycle. She found that there was a global financial cycle in capital flows, asset prices and credit growth. This cycle was co</em><em>‐</em><em>moves with the VIX, a measure of uncertainty and risk aversion of the markets. Therefore, this study attempts to analyze empirically global financial cycle shocks, measured by the VIX, on equity prices and property prices in ASEAN-5, namely Indonesia, Malaysia, Singapore, Thailand and Philippines. We estimate quarterly frequency data from Q1 1990 to Q2 2016 with Structural Vector Autoregressive (SVAR) approach. The result of this study showed that global financial cycle has a negative significant impact on the ASEAN-5 asset markets, in spite of the response of shock differs by country and size. This result is consistent with ASEAN-5 as small open economies that remain vulnerable to the global factor. This study contributes to the literature in several ways. First, we identify not only cyclical expansions or contraction in asset markets but also the impact of global financial cycle to asset markets in ASEAN-5 countries. Second, we investigate whether there are heterogeneous responses of ASEAN-5 countries to global financial cycle shocks. Third, we also identify the pattern of cycle in ASEAN-5 countries</em>.</p><p><strong><em>J</em></strong><strong><em>EL Classification: </em></strong>F30, F37, F42</p><strong><em>Keywords: </em></strong><em>ASEAN, Asset Markets, Global Financial Cycle, SVAR</em>

Item Response Theory Analysis to Assess Dimensionality of Substance Use Disorder Abuse and Dependence Symptoms

2017 ◽  
Vol 6 (4) ◽  
Author(s):  
Levent Kirisci ◽  
Ralph Tarter ◽  
Maureen Reynolds ◽  
Michael Vanyukov
Keyword(s):  
Substance Use ◽  
Item Response Theory ◽  
Item Response ◽  
Substance Use Disorder ◽  
Factor Model ◽  
Common Factor ◽  
Latent Trait ◽  
Dominant Factor ◽  
Response Theory ◽  
Men And Women

Background. Item response theory (IRT) based studies conducted on diverse samples showed a single dominant factor for DSM-III-R and DSM-IV substance use disorder (SUD) abuse and dependence symptoms of alcohol, cannabis, sedative, cocaine, stimulants, and opiates use disorders. IRT provides the opportunity, within a person-centered framework, to accurately gauge each person’s severity of disorder that, in turn, informs required intensiveness of treatment. Objectives. The aim of this study was to determine whether the SUD symptoms indicate a unidimensional trait or instead need to be conceptualized and quantified as a multidimensional scale. Methods. The sample was composed of families of adult SUD+ men (n=349), and SUD+ women (n=173), who qualified for DSM-III-R diagnosis of substance use disorder (abuse or dependence) and families of adult men and women who did not qualify for a SUD diagnosis (SUD- men: n=190, SUD- women: n=133). An expanded version of the Structured Clinical Interview for DSM-III-R (SCID) was administered to characterize lifetime and current substance use disorders. Item response theory methodology was used to assess the dimensionality of DSM-III-R SUD abuse and dependence symptoms.Results. A bi-factor model provided the optimal representation of the factor structure of SUD symptoms in males and females. SUD symptoms are scalable as indicators of a single common factor, corresponding to general (non-drug-specific, common) liability to addiction, combined with drug-specific liabilities. Conclusions. IRT methodology used to quantify the continuous general liability to addiction (GLA) latent trait in individuals having SUD symptoms was found effective for accurately measuring SUD severity in men and women. This may be helpful for person-centered medicine approaches to effectively address intensity of treatment.

scholarly journals How Important is the Global Financial Cycle? Evidence from Capital Flows

2017 ◽  
Author(s):  
Eugenio Cerutti ◽  
Stijn Claessens ◽  
Andrew Rose
Keyword(s):  
Capital Flows ◽  
Financial Cycle

scholarly journals Generalized Mean-Reverting 4/2 Factor Model

2019 ◽  
Vol 12 (4) ◽  
pp. 159 ◽  
Author(s):  
Yuyang Cheng ◽  
Marcos Escobar-Anel ◽  
Zhenxian Gong
Keyword(s):  
Value At Risk ◽  
Implied Volatility ◽  
Factor Model ◽  
Risk Measures ◽  
Risk Measure ◽  
Common Factor ◽  
Principal Component ◽  
Characteristic Functions ◽  
Implied Volatility Surface ◽  
Volatility Surface

This paper proposes and investigates a multivariate 4/2 Factor Model. The name 4/2 comes from the superposition of a CIR term and a 3/2-model component. Our model goes multidimensional along the lines of a principal component and factor covariance decomposition. We find conditions for well-defined changes of measure and we also find two key characteristic functions in closed-form, which help with pricing and risk measure calculations. In a numerical example, we demonstrate the significant impact of the newly added 3/2 component (parameter b) and the common factor (a), both with respect to changes on the implied volatility surface (up to 100%) and on two risk measures: value at risk and expected shortfall where an increase of up to 29% was detected.

Structural Equation Modeling with Factors and Composites

2017 ◽  
Vol 13 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Factor Model ◽  
Common Factor ◽  
Equation Modeling ◽  
A Algorithm ◽  
Multivariate Statistical ◽  
Full Information Maximum Likelihood ◽  
Common Factor Model ◽  
Path Coefficients

Recent methodological developments building on partial least squares (PLS) techniques and related ideas have significantly contributed to bridging the gap between factor-based and composite-based structural equation modeling (SEM) methods. PLS-SEM is extensively used in the field of e-collaboration, as well as in many other fields where multivariate statistical analyses are employed. The author compares results obtained with four methods: covariance-based SEM with full information maximum likelihood (FIML), factor-based SEM with common factor model assumptions (FSEM1), factor-based SEM building on the PLS Regression algorithm (FSEM2), and PLS-SEM employing the Mode A algorithm (PLSA). The comparison suggests that FSEM1 yields path coefficients and loadings that are very similar to FIML's; and that FSEM2 yields path coefficients that are very similar to FIML's and loadings that are very similar to PLSA's.

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