ESS Guidelines on Seasonal Adjustment. Edición 2015

Eurostat ha publicat l’edició 2015 de les recomanacions per desestacionalització: ESS guidelines on seasonal adjustment “The revised ESS Guidelines on Seasonal Adjustment present both theoretical aspects and practical implementation issues in a friendly and easy to read framework, thereby addressing both experts and non-experts in seasonal adjustment. They meet the requirement of principle 7 (Sound […]

via ESS Guidelines on Seasonal Adjustment. Edició 2015 — Bloc d’estadística oficial

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Time Series Analysis in R Part 1: The Time Series Object

(This article was first published on R Programming – DataScience+, and kindly contributed to R-bloggers) Many of the methods used in time series analysis and forecasting have been around for quite some time but have taken a back seat to machine learning techniques in recent years. Nevertheless, time series analysis and forecasting are useful tools…

via Time Series Analysis in R Part 1: The Time Series Object — R-bloggers

Time Series Analysis in R Part 2: Time Series Transformations.

(This article was first published on R Programming – DataScience+, and kindly contributed to R-bloggers) In Part 1 of this series, we got started by looking at the ts object in R and how it represents time series data. In Part 2, I’ll discuss some of the many time series transformation functions that are available…

via Time Series Analysis in R Part 2: Time Series Transformations — R-bloggers

Handbook on Cyclical Composite indicators – 2017 edition

Eurostat i l’United Nations Statistics Division, publiquen conjuntament el manual, “Handbook on Cyclical Composite indicators – 2017 edition. For Business cycle analysis” a fi que serveixi de guia per la compilació d’indicadors compostos cíclics. “The 2007-2009 global financial and economic crises revealed severe weaknesses in the system of macroeconomic infra-annual statistics which prevent a prompt […]

via “Handbook on Cyclical Composite indicators – 2017 edition” — Bloc d’estadística oficial

Microsoft R Open 3.4.1 now available

(This article was first published on Revolutions, and kindly contributed to R-bloggers) Microsoft R Open (MRO), Microsoft’s enhanced distribution of open source R, has been upgraded to version 3.4.1 and is now available for download for Windows, Mac, and Linux. This update upgrades the R language engine to R 3.4.1 and updates the bundled packages. MRO is 100%…

via Microsoft R Open 3.4.1 now available — R-bloggers

Redes Sociales en el Consumo de los Hogares

Otra economia

Redes Sociales en el Consumo de los Hogares

Francisco Parra

1 de septiembre de 2017

Licencia de Creative Commons
Este obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional.

Abstract

El objetivo del artículo es comprobar si la teoría del consumo Keynesiana, puede ser considerada desde una perspectiva micro, alejada de las tradicional supuesto de la elección entre bienes en base a las funciones de utilidad, para ello adoptaremos un supuesto más sociológico basado en la elección siguiendo un patrón determinado, aquí supondremos que cada individuo elige imitando el comportamiento de los individuos de la inmediata clase social de mayor renta, sujeto a una restricción de gasto que es la que determina la función de consumo Keynesiana, construida en base a grupos de clases sociales (percentiles). Para realizar dicho análisis utilizaremos técnicas de regresión band spectrum, jerarquías en arboles mínimos de expansión, y técnicas de análisis de redes sociales, aplicadas a…

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Tidy Time Series Analysis, Part 4: Lags and Autocorrelation

(This article was first published on business-science.io – Articles, and kindly contributed to R-bloggers) In the fourth part in a series on Tidy Time Series Analysis, we’ll investigate lags and autocorrelation, which are useful in understanding seasonality and form the basis for autoregressive forecast models such as AR, ARMA, ARIMA, SARIMA (basically any forecast model…

via Tidy Time Series Analysis, Part 4: Lags and Autocorrelation — R-bloggers