Results 71 to 80 of about 124,454 (198)
Using Heteroscedasticity to Estimate the Returns to Education [PDF]
We apply a new estimator to the measurement of the economic returns to education. We control for endogenous education, unobserved ability and measurement error using only the natural heteroscedasticty of wages and education attainment.
Roberto Rigobon, Vincent Hogan
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The ontogenetic allometry of body morphology and chemical composition in dairy goat wethers
Animal, 2018 We studied the ontogenetic growth of goat wethers (castrated male goats) of the Saanen and Swiss Alpine breeds based on a large range of intraspecific body mass (BM).
R.A.M. Vieira +8 more
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Public expenditure and national income - Time series evidence from Greece [PDF]
, 2000 The paper investigates the existence and nature of long-run relationships between Greek national income and four categories of public expenditure. Our results suggest that there exists a positive long-run relationship between GDP on the one hand; and ...
Arghyrou, MG
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Accounting for outliers and calendar effects in surrogate simulations of stock return sequences
, 2005 Surrogate Data Analysis (SDA) is a statistical hypothesis testing framework for the determination of weak chaos in time series dynamics. Existing SDA procedures do not account properly for the rich structures observed in stock return sequences ...
Alexandros Leontitsis +46 more
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Testing Heteroscedasticity In Nonparametric Regression
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998 Summary The importance of being able to detect heteroscedasticity in regression is widely recognized because efficient inference for the regression function requires that heteroscedasticity is taken into account. In this paper a simple consistent test for heteroscedasticity is proposed in a nonparametric regression set-up.
Dette, H., Munk, Axel
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Product Design Time Forecasting by Kernel-Based Regression with Gaussian Distribution Weights
Entropy, 2016 There exist problems of small samples and heteroscedastic noise in design time forecasts. To solve them, a kernel-based regression with Gaussian distribution weights (GDW-KR) is proposed here.
Zhi-Gen Shang, Hong-Sen Yan
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Econometrics often deals with data under, from the statistical point of view, non-standard conditions such as heteroscedasticity or measurement errors and the estimation methods need thus be either adopted to such conditions or be at least insensitive to
Pavel Cizek, Wolfgang Härdle
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Do Food Stamps Cause Obesity? A Generalised Bayesian Instrumental Variable Approach in the Presence of Heteroscedasticity [PDF]
The impact of covariates on obesity in the US is investigated, with particular attention given to the role of the Supplemental Nutrition Assistance Program.
Balcombe, Kelvin, Salois, Matthew
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Detecting Heteroscedasticity in Nonparametric Regression
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1993 SUMMARY Diagnostic tests and plots are proposed for detecting heteroscedasticity in nonparametric regression. The large and small sample power properties are studied for a class of test statistics for the hypothesis of homogeneous variances. New diagnostic plots are also developed and illustrated.
Eubank, R. L., Thomas, Will
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Density forecasting of the Dow Jones share index [PDF]
The distribution of differences in logarithms of the Dow Jones share index is compared to the normal (N), normal mixture (NM) and a weighted sum of a normal and an Assymetric Laplace distribution (NAL). It is found that the NAL fits best. We came to this
Stockhammar, P, Öller, L-E
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