Searching for the Causal Structure of a Vector Autoregression

By Selva Demiralp, Kevin D. Hoover. 2003

277 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/08829336b96fb4caad7be410ac168e5c5a115426

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Citations in the corpus

Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity (2008, background): “Such a model is called the structural vector autoregressive (SVAR) model in econometric theory, in which numerous attempts have been made for its estimation, see e.g. (Swanson & Granger, 1997; Demiralp & Hoover, 2003; Moneta & Spirtes, 2006).”
Causal Inference by Independent Component Analysis: Theory and Applications* (2013, unknown): “As Demiralp and Hoover (2003) pointed out, this is quite ironic, because the main idea of the VAR approach was to let the data speak and to eschew incredible a priori restrictions (Sims, 1980), but if the SVAR method relies on preconceived stories about simultaneous causal relationships it is at…”
Model selection when there are multiple breaks (2012, background): “There are also many possible contenders for (D), including, but not restricted to, Phillips (1994, 1995, 1996), Tibshirani (1996), Hoover and Perez (1999, 2004), Hendry and Krolzig (1999, 2001), White (2000), Krolzig (2003), Kurcewicz and Mycielski (2003), Demiralp and Hoover (2003), and Perez-Amara”
Granger causality and path diagrams for multivariate time series (2007, background): “Swanson and Granger (1997) and Demiralp and Hoover (2003) have applied these concepts to macroeconomic problems to determine the contemporaneous causal order of a structural vector autoregression.”
Causality : Objectives and Assessment (2010, background): “…et al., 2000; Kononenko, 2009), epidemiology (Aickin, 2002), climatology (Chu and Glymour, 2008), social and economic sciences (Kaplan, 2000; Demiralp and Hoover, 2003; Moneta, 2005), marketing (CFMDCY, 2006), neuroscience (Ding et al., 2006; Neves et al., 2008), psychology, law…”
Estimating brain functional connectivity with sparse multivariate autoregression (2005, methodology): “These techniques have been proposed for use in graphical time-series models by Demiralp & Hoover (2003).”
Graphical causal models and VARs: an empirical assessment of the real business cycles hypothesis (2008, methodology): “The most used algorithm in the DAG case is the PC algorithm (Spirtes et al. 2000), which has been applied to the VAR identiﬁcation by Demiralp and Hoover (2003) and Bessler and Lee (2002).”
Washing Away Your Sins? Corporate Social Responsibility, Corporate Social Irresponsibility, and Firm Performance (2016, methodology): “In light of the time series data that we employ (e.g., Demiralp and Hoover 2003), we take the following steps: We ensure that our data are stationary; we simultaneously model CSR, CSI, and firm performance to ensure there is no omitted simultaneity; and, in line with the literature, we include…”
DYNOTEARS: Structure Learning from Time-Series Data (2020, methodology): “In econometrics, they are also known as structural vector autoregressive (SVAR) models (Demiralp and Hoover, 2003; Swanson and Granger, 1997).”
Does agriculture really matter for economic Growth in Developing Countries (2015, background): “However, the PC algorithm has its limitations, as simulations studies have shown that it is prone to errors in direction of edges, especially in small sample sizes (Demiralp and Hoover 2003).”
Learning Causal Structure from Undersampled Time Series (2013, methodology): “In particular, the “proper” experimental strategy is often to provide some exogenous shock to the dynamical system, measure its evolution, and then apply a causal learning algorithm to the resulting time series data, such as Demiralp and Hoover (2003); Moneta et al.”
The New Palgrave Dictionary of Economics Online Causality in Economics and Econometrics (unknown): “Graph-theoretic approaches to causality were first developed outside of economics by computer scientists (for example, Pearl, 2000) and philosophers (for example, Spirtes, Glymour and Scheines, 2000), but have recently been applied within economics (Swanson and Granger, 1997; Akleman, Bessler and Bu”
Search for Additive Nonlinear Time Series Causal Models (2008, methodology): “The chain-like contemporaneous causal structure is chosen to evaluate the ability of our algorithm to identify the direction of those contemporaneous causal relations that could not be detected using previous algorithms (Bessler et al., 2002; Demiralp and Hoover, 2003; Moneta, 2003; Hoover, 2005).”