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Regression models with mixed sampling frequencies

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TLDR
In this paper, the asymptotic properties of the NLS estimators of such regression models were derived and compared with the traditional model that involves aggregating or equally weighting data to estimate a model at the same sampling frequency.
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This article is published in Journal of Econometrics.The article was published on 2010-10-01 and is currently open access. It has received 264 citations till now. The article focuses on the topics: Regression diagnostic & Regression analysis.

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Forecasting, Structural Time Series Models and the Kalman Filter

TL;DR: In this paper, the authors provide a unified and comprehensive theory of structural time series models, including a detailed treatment of the Kalman filter for modeling economic and social time series, and address the special problems which the treatment of such series poses.
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Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach

TL;DR: The twelve month forecasts reveal that Google Trends information offers significant benefits to forecasters, particularly in tourism, and policymakers and business practitioners especially in the Caribbean can take advantage of the forecasting capability of Google search data for their planning purposes.
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Midas Versus Mixed-Frequency VAR: Nowcasting GDP in the Euro Area

TL;DR: In this article, the authors compare the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model specification in the presence of mixed frequency data, e.g., monthly and quarterly series.
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News—Good or Bad—and Its Impact on Volatility Predictions over Multiple Horizons

TL;DR: In this paper, the authors revisited the concept of news impact curves introduced by Engle and Ng (1993) and examined whether the sign and magnitude of intra-daily returns have impact on expected volatility the next day or over longer future horizons.
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Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials

TL;DR: In this paper, unrestricted mixed data sampling (U-MIDAS) regressions are derived from linear high frequency models, and their parameters can be estimated by ordinary least squares, and compared with functional distributed lags estimated by non-linear least squares.
References
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Journal ArticleDOI

A Contribution to the Empirics of Economic Growth

TL;DR: The authors examined whether the Solow growth model is consistent with the international variation in the standard of living, and they showed that an augmented Solow model that includes accumulation of human as well as physical capital provides an excellent description of the cross-country data.
Journal ArticleDOI

Time Series Analysis.

Journal ArticleDOI

Time series analysis

James D. Hamilton
- 01 Feb 1997 - 
TL;DR: A ordered sequence of events or observations having a time component is called as a time series, and some good examples are daily opening and closing stock prices, daily humidity, temperature, pressure, annual gross domestic product of a country and so on.
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Forecasting, Structural Time Series Models and the Kalman Filter

TL;DR: In this article, the Kalman filter and state space models were used for univariate structural time series models to estimate, predict, and smoothen the univariate time series model.
Posted Content

Forecasting, Structural Time Series Models and the Kalman Filter

TL;DR: In this paper, the authors provide a unified and comprehensive theory of structural time series models, including a detailed treatment of the Kalman filter for modeling economic and social time series, and address the special problems which the treatment of such series poses.
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Q1. What are the contributions in "Department of economics university of cyprus ethnic minority immigrants and their children in britain" ?

This paper investigates educational attainment and economic behaviour of ethnic minority immigrants and their children in Britain. The authors examine possible explanations for these gaps. Further, British born ethnic minorities have lower employment propensities for the same wages than native born whites. 

The authors then explore some possible explanations for these differences. A better understanding of such mechanisms and how they relate to labour market outcomes for Britain ’ s ethnic minorities is an important agenda for future research. This suggests that inactivity is partly due to lower readiness to participate in the labour market. One important reason for observed differences, in particular in employment outcomes, may be related to particular views and attitudes about and specific engagement with the labour market. 

This suggests that the lower labour force participation rates for some ethnic groups (e.g. for Pakistani and Bangladeshi women) is largely due to their lower readiness to participate in the labour market, and less so because individuals do not find jobs or are being discriminated against. 

the lower labour market participation rate for some British born ethnic minority groups may be partly explained by their lower readiness to participate in the labour market. 

One reason for the lower employment probabilities of ethnic minorities in general, and somegroups in particular may be that individuals are discouraged and do not participate in the labour market. 

While the percentage of first generation ethnic minority immigrants that fall into the “High” educational category is 3.6 percentage points higher than that of white British born, the percentage that falls into the “No qualification” category is likewise 7.7 percentage points higher.