نتایج جستجو برای: ardl method jel classification c12

تعداد نتایج: 2044390  

2015
J. Isaac Miller Xi Wang

We show how temporal aggregation affects the size and power of the DOLS residualbased KPSS test of the null of cointegration. Size is effectively controlled by setting the minimum number of leads equal to one – as opposed to zero – when selecting the lag/lead order of the DOLS regression, but at a cost to power in finite samples. If highfrequency data for one or more series are available, we sh...

2003
Yoosoon Chang

This paper presents the nonlinear IV methodology as an effective inferential basis for nonstationary panels. The nonlinear IV method resolves the inferential difficulties in testing for unit roots arising from the intrinsic heterogeneities and cross-dependencies of panel models. Individual units are allowed to be dependent through correlations among innovations, interrelatedness of short-run dy...

2017
KONRAD MENZEL

We consider a random utility model of strategic network formation, where we derive a tractable approximation to the distribution of network links using many-player asymptotics. Our framework assumes that agents have heterogeneous tastes over links, and allows for anonymous and non-anonymous interaction effects among links. The observed network is assumed to be pairwise stable, and we impose no ...

2006
Giovanni Forchini G. Forchini

Cragg and Donald (1996) have pointed out that the asymptotic size of tests for overidentifying restrictions can be much smaller than the asymptotic nominal size when the structural equation is partially identified. This may lead to misleading inference if the critical values are obtained from a chi-square distribution. To overcome this problem we derive the exact asymptotic distribution of the ...

2006
Alfred Galichon Marc Henry Shakeeb Khan Geert Ridder

We propose a methodology for constructing confidence regions with partially identified models of general form. The region is obtained by inverting a test of internal consistency of the econometric structure. We develop a dilation bootstrap methodology to deal with sampling uncertainty without reference to the hypothesized economic structure, and apply a duality principle to reduce the dimension...

2004
Cheng Hsiao M. Hashem Pesaran

Random Coefficient Panel Data Models This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coefficients models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coefficients formulation using both the sampling and Bayesian approaches. The paper also provid...

2017
Isaiah Andrews

In models with potential weak identification researchers often decide whether to report a robust confidence set based on an initial assessment of model identification. Two-step procedures of this sort can generate large coverage distortions for reported confidence sets, and existing procedures for controlling these distortions are quite limited. This paper introduces a generally-applicable appr...

2014
Luciano Gutierrez Francesco Piras

Food commodity price fluctuations have an important impact on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, while there is an urgent need for appropriate policy responses. Perhaps new approaches are needed in order to better understand international spill-overs, the feedback betwee...

Journal: :Knowledge Organization 2022

The Journal of Economic Literature codes classification system (JEL) published by the American Association (AEA) is de facto standard for research literature in economics. JEL used to classify articles, dissertations, books, book reviews, and working papers EconLit, a database maintained AEA. Over time, it has evolved extended with over 850 subclasses. This paper reviews history development sys...

2002
Nikolay Gospodinov

This paper considers the construction of median unbiased forecasts for near-integrated autoregressive processes. It derives the appropriately scaled limiting distribution of the deviation of the forecast from the true conditional mean. The dependence of the limiting distribution on nuisance parameters precludes the use of the standard asymptotic and bootstrap methods for bias correction. We pro...

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