Revealed Comparative Advantage of Textile and Clothing Industry of Bangladesh in the North American Market

2020 ◽  
Vol 7 (1) ◽  
pp. 1-12
Author(s):  
Mohammad , Ali ◽  
Qun , Wang
Keyword(s):  
Comparative Advantage ◽  
North American ◽  
Clothing Industry ◽  
Revealed Comparative Advantage ◽  
The North ◽  
North American Market

Cruising and the North American market.

2009 ◽  
pp. 74-85 ◽  
Author(s):  
A. R. Miller ◽  
W. F. Grazer
Keyword(s):  
North American ◽  
The North ◽  
North American Market

The North American market for herbal supplements

Nutrafoods ◽  
2011 ◽  
Vol 10 (2-3) ◽  
pp. 8-9
Author(s):  
Anne Wilkie
Keyword(s):  
North American ◽  
Herbal Supplements ◽  
The North ◽  
North American Market

A quantitative HPLC method for the quality assurance of Echinacea Products on the North American market

2000 ◽  
Vol 11 (4) ◽  
pp. 207-215 ◽  
Author(s):  
Chantal Bergeron ◽  
John F. Livesey ◽  
Dennis V.C. Awang ◽  
John T. Arnason ◽  
Jatinder Rana ◽  
...  
Keyword(s):  
Quality Assurance ◽  
North American ◽  
Hplc Method ◽  
The North ◽  
North American Market ◽  
Quantitative Hplc

Risk of salmonellosis from consumption of almonds in the North American market

2012 ◽  
Vol 45 (2) ◽  
pp. 1166-1174 ◽  
Author(s):  
Elisabetta Lambertini ◽  
Michelle D. Danyluk ◽  
Donald W. Schaffner ◽  
Carl K. Winter ◽  
Linda J. Harris
Keyword(s):  
North American ◽  
The North ◽  
North American Market

scholarly journals THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018

2021 ◽  
Vol 22 (4) ◽  
Author(s):  
VANDERSON A. DELAPEDRA-SILVA
Keyword(s):  
North American ◽  
Default Risk ◽  
Oil And Gas ◽  
Probability Of Default ◽  
Bankruptcy Risk ◽  
The North ◽  
North American Market ◽  
Structural Variables ◽  
Variable Distance ◽  
Distance To Default

ABSTRACT Purpose: This research aims to identify the probability of default of infrastructure companies considering the sector specificities of their activities. In addition, the work seeks to identify the application of structural variables of probability of default in a model in a reduced way in order to identify the significance of its use. For this purpose, we investigated 1,520 North American companies from six different sectors linked to infrastructure. Originality/value: The analyzes carried out to identify the probability of a company going bankrupt hardly consider its sectorial particularity. Although most models bring important inputs for risk assessment, most of them do not consider this sectoral view. Then, this work has as value and originality the contribution to fill this gap and identify the existence of sectorial differences in the analysis of default risk in infrastructure companies in the North American market in the period between 2006 and 2018. Design/methodology/approach: The study performed a logistic regression (logit model) using 11 model variables established in calculating the probability of default. It also used the variable distance to default as an explanatory variable in order to identify its ability to explain the researched phenomenon. Findings: The study identified that, in addition to the size of the companies, the distance to default variable is the only variable that can be applied with significance in all the analyzed sectors. In addition, it was identified that companies in the oil and gas sector have less sensitivity to this variable than companies in the other sectors.

scholarly journals Medindo a Influência do Mercado dos EUA sobre as Interdependências Observadas na América Latina

2005 ◽  
Vol 3 (1) ◽  
pp. 123
Author(s):  
Alba Regina Moretti ◽  
Beatriz Vaz de Melo Mendes
Keyword(s):  
Latin American ◽  
North American ◽  
Polynomial Regression ◽  
Value Theory ◽  
Extreme Value ◽  
Parametric Models ◽  
Dependence Structure ◽  
Practical Applications ◽  
The North ◽  
North American Market

The modeling of the extremal dependence structure can be made through parametric models classified in two families: Logistic and Mixed, which contain the symmetric and asymmetric models. The bivariate models are very useful in practical applications on the extreme value theory, in particular in a financial area. Considering the strong influence of the North American market on other financial markets, we investigate how does the dependence structure among the Latin American markets change after filtering the influence of the North American market. To remove that influence, we carry on a polynomial regression with GARCH (1,1) errors, and fit the bivariate extreme value models to the pairs of monthly maxima and minima of the standardized regression residuals.

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