Journal ArticleDOI
Farm Prices, Retail Prices, and Directed Graphs: Results for Pork and Beef
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TLDR
A more recent approach to dealing with the contemporaneous correlation problem is the so-called structural factorization, following the similar approaches of Bernanke and Sims as mentioned in this paper, which models data on X, Y, and Z as a vector autoregression.Abstract:
Such studies say little about contemporaneous relationships among the variables X, Y, and Z. If one models data on X, Y, and Z as a vector autoregression, some assumption about contemporaneous correlation between innovations must be made. Early work applied the Choleski factorization, which is a recursive ordering between X, Y, and Z: XYZ. A more recent approach to dealing with the contemporaneous correlation problem is the so-called structural factorization, following the similar approaches of Bernanke and Sims. A problem with the former (Choleski) is that the world might not be recursive (Cooley and LeRoy, Sims). A problem with the latter is tha correct structural information might be unknown outside of a particular deductive model.read more
Citations
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The Impact of the Oil Sector on Commodity Prices: Correlation or Causation?
TL;DR: In this article, the authors present empirical results using contemporary time-series analysis and Granger causality supplemented by a directed graph theory modeling approach to identify the links and plausible contemporaneous causal structures among energy and commodity variables.
Posted Content
Does Agriculture Really Matter for Economic Growth in Developing Countries
TL;DR: In this article, the authors re-examine the question of whether agriculture could serve as an engine of growth and find that agricultural development is a precondition to industrialization, while some strongly disagree and argue for a different path.
Journal ArticleDOI
Does agriculture really matter for economic Growth in Developing Countries
Titus O. Awokuse,Ruizhi Xie +1 more
TL;DR: In this article, the authors investigated the causal linkages between agriculture and gross domestic product growth with the aid of directed acyclic graphs, a recently developed algorithm of inductive causation.
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Causality and price discovery: an application of directed acyclic graphs
TL;DR: In this article, the authors employed directed acyclic graph (DAG) and error correction models (ECM) to analyze questions of price discovery between spatially separated commodity markets and the transportation market linking them together.
Journal ArticleDOI
Considering macroeconomic indicators in the food before fuel nexus
TL;DR: In this paper, a structural vector autoregression (SVAR) model along with a direct acyclic graph is employed to decompose how supply/demand structural shocks affect food and fuel markets.
References
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Journal ArticleDOI
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TL;DR: In this paper, a nonparametric framework for causal inference is proposed, in which diagrams are queried to determine if the assumptions available are sufficient for identifying causal effects from nonexperimental data.
Book
Graphical Models in Applied Multivariate Statistics
TL;DR: This introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition.
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Graphical Models in Applied Multivariate Statistics.
J. N. R. Jeffers,Joe Whittaker +1 more
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Atheoretical macroeconometrics: A critique
TL;DR: In this paper, the authors present a new approach called atheoretical macroeconometrics that is less dependent on prior theoretical restrictions of the sort that were central to the approach of the Cowles Commission.