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Mixed-data sampling

Known as: Mixed, Mixed data sampling 
Mixed-data sampling (MIDAS) is an econometric regression or filtering method developed by Ghysels et al. There is now a substantial literature on… 
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Related topics

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Distributed lagKalman filter

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
A Mixed Data Sampling Approach to Accounting Research
This paper examines a mixed data sampling (MIDAS) approach to accounting research. MIDAS regression models parsimoniously… 
2018
2018
Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data
In this paper, we examine the usefulness of Google Trends data in predicting monthly tourist arrivals and overnight stays in… 
2017
2017
The Impact of Money Supply on Nigeria Economy: A Comparison of Mixed Data Sampling (MIDAS) and ARDL Approach
The study investigates the long and short run relationships between broad money supply and real aggregate output (GDP) in Nigeria… 
2016
2016
Forecasting with Mixed Data Sampling Models (MIDAS) and Google trends data: the case of car sales in Italy
In the last few years the attention focused on the use of Internet data as an information source that could improve forecasts… 
Review
2014
Review
2014
Forecasting Short-Term Real GDP Growth in the Euro Area and Japan Using Unrestricted MIDAS Regressions
In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan… 
2013
2013
Forecasting Chinese GDP with Mixed Frequency Data Set: A Generalized Lasso Granger Method
In this paper, we introduce an effective machine learning method which can capture the temporal causal structures between… 
2013
2013
Incorporation of Social Media Data into Macroeconomic Forecast Systems: A Mixed Frequency Modelling Approach
Macroeconomic forecasts enable the policy-makers to foresee the future economic trends and take prompt measures to ensure longer… 
2010
2010
Mixed Data Sampling
MIxed DAta Sampling (MIDAS) regression models were introduced in both filtering and regression context to deal with situations… 
2005
2005
Assesing the Economic Signi cance of the Intra-daily
It is a well established empirical fact that volatility follows approximately an inverted U-shaped pattern during the day. It is… 
1998
1998
Abstract
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