scholarly journals On the Relationship between Oil and Exchange Rates of Oil-Exporting and Oil-Importing Countries: From the Great Recession Period to the COVID-19 Era

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8046
Author(s):  
Vincenzo Candila ◽  
Denis Maximov ◽  
Alexey Mikhaylov ◽  
Nikita Moiseev ◽  
Tomonobu Senjyu ◽  
...  
Keyword(s):  
United States ◽  
South Korea ◽  
United Arab Emirates ◽  
Great Recession ◽  
Mixed Data ◽  
Data Sampling ◽  
The Great Recession ◽  
Long Run ◽  
Mixed Data Sampling ◽  
Recession Period

This paper is dedicated to studying and modeling the interdependence between the oil returns and exchange-rate movements of oil-exporting and oil-importing countries. Globally, twelve countries/regions are investigated, representing more than 60% and 67% of all oil exports and imports. The sample period encompasses economic and natural events like the Great Recession period (2007–2009) and the COVID-19 pandemic. We use the dynamic conditional correlation mixed-data sampling (DCC-MIDAS) model, with the aim of investigating the interdependencies expressed by the long-run correlation, which is a smoother (but always daily observed) version of the (daily) time-varying correlation. Focusing on the advent of the COVID-19 pandemic in 2020, the long-run correlations of the oil-exporting countries (Saudia Arabia, Russia, Iraq, Canada, United States, United Arab Emirates, and Nigeria) and (lagged) WTI crude oil returns strongly increase. For a subset of these countries (that is, Saudia Arabia, Iraq, United States, United Arab Emirates, and Nigeria), the (lagged) correlations turn out to be positive, while for Canada and Russia they remain negative as before the advent of the pandemic. In addition, the oil-importing countries and regions under investigation (Europe, China, India, Japan, and South Korea) experience a similar pattern: before the COVID-19 pandemic, the (lagged) correlations were negative for China, India, and South Korea. After the COVID-19 pandemic, the correlations of these latter countries increased.

Determinants of Homeownership among Immigrants: Changes during the Great Recession and Beyond

2018 ◽  
Vol 52 (3) ◽  
pp. 648-694 ◽  
Author(s):  
Kusum Mundra ◽  
Ruth Uwaifo Oyelere
Keyword(s):  
United States ◽  
Length Of Stay ◽  
Great Recession ◽  
Household Income ◽  
The United States ◽  
Citizenship Status ◽  
The Great Recession ◽  
Before And After ◽  
The Impact ◽  
Recession Period

In this paper, we explore factors correlated with immigrant homeownership before and after the Great Recession. We focus solely on immigrants because of recent evidence that suggests homeownership rates declined less for immigrants than natives in the United States during the recession and onward. Specifically, we examine to what extent an immigrant's income, savings, length of stay in the destination country, citizenship status, and birthplace networks affected the probability of homeownership before the recession, and how these impacts on homeownership changed since the recession. We examine these questions using microdata for the years 2000–2012. Our results suggest that citizenship status, birthplace network, family size, savings, household income, and length of stay are significant for an immigrant's homeownership. In comparing the pre‐recession period to the period afterward, we find that the impact of birthplace networks on homeownership probabilities doubled while the impact of savings slightly declined.

Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach

2008 ◽  
Author(s):  
Michelle T. Armesto ◽  
Ruben Hernandez-Murillo ◽  
Michael Owyang ◽  
Jeremy M. Piger
Keyword(s):  
Information Content ◽  
Mixed Data ◽  
Data Sampling ◽  
Mixed Data Sampling ◽  
Sampling Approach

scholarly journals COVID-19 Outbreak and CO2 Emissions: Macro-Financial Linkages

2020 ◽  
Vol 14 (1) ◽  
pp. 12
Author(s):  
Julien Chevallier
Keyword(s):  
Co2 Emissions ◽  
Fossil Fuels ◽  
Mixed Data ◽  
Energy Information Administration ◽  
Time Varying ◽  
Data Sampling ◽  
Quantitative Finance ◽  
Financial Variables ◽  
Mixed Data Sampling ◽  
The One

In the Dynamic Conditional Correlation with Mixed Data Sampling (DCC-MIDAS) framework, we scrutinize the correlations between the macro-financial environment and CO2 emissions in the aftermath of the COVID-19 diffusion. The main original idea is that the economy’s lock-down will alleviate part of the greenhouse gases’ burden that human activity induces on the environment. We capture the time-varying correlations between U.S. COVID-19 confirmed cases, deaths, and recovered cases that were recorded by the Johns Hopkins Coronavirus Center, on the one hand; U.S. Total Industrial Production Index and Total Fossil Fuels CO2 emissions from the U.S. Energy Information Administration on the other hand. High-frequency data for U.S. stock markets are included with five-minute realized volatility from the Oxford-Man Institute of Quantitative Finance. The DCC-MIDAS approach indicates that COVID-19 confirmed cases and deaths negatively influence the macro-financial variables and CO2 emissions. We quantify the time-varying correlations of CO2 emissions with either COVID-19 confirmed cases or COVID-19 deaths to sharply decrease by −15% to −30%. The main takeaway is that we track correlations and reveal a recessionary outlook against the background of the pandemic.

An Analysis of Big 4 Pricing and Firm Size: The Differential Impact of Demand and Supply Shocks on Large and Small Clients

2017 ◽  
Vol 34 (2) ◽  
pp. 204-230 ◽  
Author(s):  
Fatima Alali ◽  
Randal Elder ◽  
Jian Zhou
Keyword(s):  
Small Firm ◽  
Great Recession ◽  
Small Firms ◽  
Unique Contribution ◽  
Demand And Supply ◽  
The Great Recession ◽  
Audit Market ◽  
Sarbanes Oxley ◽  
Big 4 ◽  
Recession Period

We investigate Big 4 pricing over the period of 2000 to 2010. We classify the data into five periods: 2000-2001 as the pre-Sarbanes–Oxley Act (SOX) period, 2002-2003 as the SOX period, 2004-2006 as the Auditing Standard 2 (AS2) period, 2007 as the AS5 period, and 2008-2010 as the Great Recession period. The shocks to the audit market associated with these changes in auditing regulations and the economic environment have differential impacts on large clients and small clients. The percentage of small clients using Big 4 auditors dropped significantly over these shocks, whereas the percentage of large clients using Big 4 auditors experienced a large drop only from the SOX period to the AS2 period. We find that Big 4 pricing increased significantly from the pre-SOX period to the SOX period and continued to increase significantly in the AS2 period. Big 4 pricing experienced a significant decline in the AS5 period and declined insignificantly in the Great Recession period. Big 4 small firm pricing decreased significantly in the AS2 period compared with the SOX period and in the Great Recession period compared with the AS5 period. We find that the Big 4 pricing for small clients is contingent on the nature of competition. The Big 4 charged small firms higher prices in the SOX period, AS5 period, and Great Recession period when competition was lower. Our paper provides a unique contribution as a comprehensive analysis of Big 4 pricing and Big 4 small firm pricing.

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