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Serge Massar was born in Zambia in 1970. [2] He obtained a degree in physics, then a PhD from the Université libre de Bruxelles (ULB) in 1991 and 1995, respectively. [2] He completed his post-doctoral research at Tel Aviv University from 1995 to 1997, and subsequently at Utrecht University from 1997 to 1998.
Parameter identification problem. In economics and econometrics, the parameter identification problem arises when the value of one or more parameters in an economic model cannot be determined from observable variables. It is closely related to non-identifiability in statistics and econometrics, which occurs when a statistical model has more ...
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. [1][2] The ...
Identifiability. In statistics, identifiability is a property which a model must satisfy for precise inference to be possible. A model is identifiable if it is theoretically possible to learn the true values of this model's underlying parameters after obtaining an infinite number of observations from it. Mathematically, this is equivalent to ...
In particular, the concept of identification can expand our vision of the realm of rhetoric as more than solely agonistic. To be sure, that is the way we have traditionally situated it: “Rhetoric,” writes Burke, “is par excellence the region of the Scramble, of insult and injury, bickering, squabbling, malice and the lie, cloaked malice and the subsidized lie. . . .
In statistics and econometrics, set identification (or partial identification) extends the concept of identifiability (or "point identification") in statistical models to environments where the model and the distribution of observable variables are not sufficient to determine a unique value for the model parameters, but instead constrain the parameters to lie in a strict subset of the ...
Vector autoregression (VAR) is a statistical model used to capture the relationship between multiple quantities as they change over time. VAR is a type of stochastic process model. VAR models generalize the single-variable (univariate) autoregressive model by allowing for multivariate time series.
Heckman correction. The Heckman correction is a statistical technique to correct bias from non-randomly selected samples or otherwise incidentally truncated dependent variables, a pervasive issue in quantitative social sciences when using observational data. [1] Conceptually, this is achieved by explicitly modelling the individual sampling ...