Testing for Money Illusion Hypothesis in Aggregate Consumption Function: Mixed Data Sampling Approach

2015 ◽  
Author(s):  
Kaiji Motegi ◽  
Akira Sadahiro
Keyword(s):  
Mixed Data ◽  
Data Sampling ◽  
Consumption Function ◽  
Aggregate Consumption ◽  
Money Illusion ◽  
Mixed Data Sampling ◽  
Sampling Approach

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

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

2009 ◽  
Vol 41 (1) ◽  
pp. 35-55 ◽  
Author(s):  
MICHELLE T. ARMESTO ◽  
RUBÉN HERNÁNDEZ-MURILLO ◽  
MICHAEL T. OWYANG ◽  
JEREMY PIGER
Keyword(s):  
Information Content ◽  
Mixed Data ◽  
Data Sampling ◽  
Mixed Data Sampling ◽  
Sampling Approach

scholarly journals Identifying Asymmetry in the Language of the Beige Book: A Mixed Data Sampling Approach

2007 ◽  
Author(s):  
Michelle T. Armesto ◽  
Ruben Hernandez-Murillo ◽  
Michael Owyang ◽  
Jeremy M. Piger
Keyword(s):  
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.

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