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Econometrics and econometric modeling
2021The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag ...
Irina Orlova +2 more
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Econometric Model Determination
Econometrica, 1996Summary: Our general subject is model determination methods and their use in the prediction of economic time series. The methods suggested are Bayesian in spirit but they can be justified by classical as well as Bayesian arguments. The main part of the paper is concerned with model determination, forecast evaluation, and the construction of evolving ...
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Aggregation and Econometric Models
International Economic Review, 1973growing, there has been an increasing clamor from certain quarters for the reverse. The cry is for small models, not big ones, and for simple models, not complex ones. It is almost as if all that matters is prediction of current dollar and real gross national product (GNP and GNP58) and perhaps a few of their components. But surely this is blindness to
Fromm, Gary, Schink, George R
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DIRECTIONALLY DIFFERENTIABLE ECONOMETRIC MODELS
Econometric Theory, 2017The current article examines the limit distribution of the quasi-maximum likelihood estimator obtained from a directionally differentiable quasi-likelihood function and represents its limit distribution as a functional of a Gaussian stochastic process indexed by direction.
Cho, Jin Seo, White, Halbert
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VECTORIZATION AND ECONOMETRIC MODEL SIMULATION
Computer Science in Economics and Management, 1989Linear analysis of nonlinear models, stochastic simulation, evaluation of forecast errors and optimal control are examples of econometric analysis that require many datasets to be solved for the same model. In this paper, we present an algorithm which demonstrates significant gains in solution speed-up and cost reduction, using vectorization, a ...
C.E. Petersen, A. Cividini
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Spatial Econometric Interaction Modelling
2016The present book is concerned with spatial interaction modelling. In particular, it aims to illustrate, through a collection of methodological and empirical studies, how estimation approaches in this field recently developed, by including the tools typical of spatial statistics and spatial econometrics (Anselin 1988; Cressie 1993; Arbia 2006, 2014 ...
PATUELLI, ROBERTO, G. Arbia
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BOOTSTRAPPING ECONOMETRIC MODELS [PDF]
, 2007 The bootstrap is a statistical technique used more and more widely in econometrics. While it is capable of yielding very reliable inference, some precautions should be taken in order to ensure this. Two "Golden Rules" are formulated that, if observed, help to obtain the best the bootstrap can offer.
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