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Journal ArticleDOI

Econometric Modelling of the Aggregate Time-Series Relationship Between Consumers' Expenditure and Income in the United Kingdom

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This article is published in The Economic Journal.The article was published on 1978-12-01. It has received 1586 citations till now.

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Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation

Robert F. Engle
- 01 Jul 1982 - 
TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
Journal ArticleDOI

Pooled Mean Group Estimation of Dynamic Heterogeneous Panels

TL;DR: The pooled mean group estimator (PMG) estimator as discussed by the authors constrains long-run coefficients to be identical but allows short run coefficients and error variances to differ across groups.
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Some properties of time series data and their use in econometric model specification

TL;DR: In this paper, it was suggested that some aspects of this practice should be brought out into the open, and the type of equations to be considered are generating equations, so that a simulation of the explanatory side should produce the major properties of the variable being explained.
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Developments in the study of cointegrated economic variables

TL;DR: The idea underlying cointegration allows specification of models that capture part of such beliefs, at least for a particular type of variable that is frequently found to occur in macroeconomics.
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Testing for Common Trends

TL;DR: In this article, two tests for the number of common stochastic trends (i.e., for the order of cointegration) in a multiple time series with and without drift are developed.
References
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Journal ArticleDOI

Spurious regressions in econometrics

TL;DR: In this paper, it is pointed out that it is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the Durbin-Watson statistic.
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False Models and Post-Data Model Construction

TL;DR: This article proposed a method of discounting evidence when linear regression models are constructed after the data have been partially analyzed, which parallels a formal decision theoretic analysis of a presimplification problem in which models or model spaces are simplified before observation in order to avoid observation or processing costs.
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