Structure of interdependencies among international stock markets and contagion patterns of 2008 global financial crisis

In this study, we apply directed acyclic graphs and search algorithm designed for time series with non-Gaussian distribution to obtain causal structure of innovations from an error correction model. The structure of interdependencies among six international stock markets is investigated. The results provide positive empirical evidence that there exist long-run equilibrium and contemporaneous causal structure among these stock markets. DAG analysis results show that Hong Kong is influenced by all other open markets in contemporaneous time, whereas Shanghai is not influenced by any of the other markets in contemporaneous time. Historical decompositions indicate that New York and Shanghai stock markets are highly exogenous and Germany and Hong Kong are the least exogenous markets. Further, we find that New York is the most influential stock market with consistent impact on price movements. One implication is that diversification between US and Germany may not provide desired immunity from financial crisis contagion as much as it does diversification between US and Shanghai.VAR, cointegration, error correction, DAG, causality, financial contagion, Agricultural Finance, Financial Economics,

Mergers Simulation and Demand Analysis for the U.S. Carbonated Soft Drink Industry

Replaced with revised version of paper on 09/29/09. Former title: Mergers, Price Competition for the U.S. Carbonated Soft Drink Industrydistance metrics, demand, merger simulation, Agribusiness, Industrial Organization, Marketing, L13, C14,

On aggregation bias in structural demand models

Consumer demand analysis attracts considerable attention. It remains an open question, however, whether estimating demand with aggregate data is reliable when disaggregate store-level data is given. Demand models may produce biased results when applied to data aggregated across stores with different pricing strategies. In this study, the graphical model is used to investigate the following question: Do we find the same structure when we fit causal models on sub-groupings of stores, as we find when we fit models on aggregate data from all stores?causal analysis, aggregation bias, Demand and Price Analysis, C01,

FORECASTING AGRICULTURAL PRICES USING A BAYESIAN COMPOSITE APPROACH

Forecast users and market analysts need quality forecast information to improve their decision-making abilities. When more than one forecast is available, the analyst can improve forecast accuracy by using a composite forecast. One of several approaches to forming composite forecasts is a Bayesian approach using matrix beta priors. This paper explains the matrix beta approach and applies it to three individual forecasts of U.S. hog prices. The Bayesian composite forecast is evaluated relative to composites made from simple averages, restricted least squares, and an adaptive weighting technique.Demand and Price Analysis,

Proving causal relationships using observational data

We describe a means of rejecting a null hypothesis concerning observed, but not deliberately manipulated, variables of the form H0: A -/-> B in favor of an alternative hypothesis HA: A --> B, even given the possibility of causally related unobserved variables. Rejection of such an H0 relies on the availability of two observed and appropriately related instrumental variables. While the researcher will have limited control over the confidence level in this test, simulation results suggest that type I errors occur with a probability of less than 0.15 (often substantially less) across a wide range of circumstances. The power of the test is limited if there are but few observations available and the strength of correspondence among the variables is weak. We demonstrate the method by testing a hypothesis with critically important policy implications relating to a possible cause of childhood malnourishment.causality, Monte Carlo, observational data, hypothesis testing, Research Methods/ Statistical Methods,

Vector Autoregressions, Policy Analysis, and Directed Acyclic Graphs: An Application to the U.S. Economy

The paper considers the use of directed acyclic graphs (DAGs), and their construction from observational data with PC-algorithm TETRAD II, in providing over-identifying restrictions on the innovations from a vector autoregression. Results from Sims’ 1986 model of the US economy are replicated and compared using these data-driven techniques. The directed graph results show Sims’ six-variable VAR is not rich enough to provide an unambiguous ordering at usual levels of statistical significance. A significance level in the neighborhood of 30 % is required to find a clear structural ordering. Although the DAG results are in agreement with Sims’ theory-based model for unemployment, differences are noted for the other five variables: income, money supply, price level, interest rates, and investment. Overall the DAG results are broadly consistent with a monetarist view with adaptive expectations and no hyperinflation.vector autoregression; directed graphs; policy analysis

Generalization of the Generalized Composite Commodity Theorem: Extension based on the Theil’s Aggregation Theory

Demand and Price Analysis, Research Methods/ Statistical Methods,

The 2004 Niger Food Crisis: What Role Can Price Discovery Play in Famine Early Warning Systems?

The 2005 food crisis centered in Niger received worldwide attention and extensive media coverage. Crops suffered from poor rainfall and were plagued by locusts throughout the growing season. Malnutrition flourished with the sudden disruption in food supplies. One-fifth of Niger's children suffered from moderate to severe forms of malnutrition by the summer of 2005. In an era of increased awareness and the introduction of famine early warning systems, the development community was left wondering why they were for the most part caught off guard by the food crisis. This paper tests whether market prices and price discovery could have played an active role in detecting the food crisis. Directed acyclic graphs are used to test whether price discovery mechanisms within Niger's millet markets were ahead of the early warning systems. Results suggest that as early as October 2005 markets in Arlit and the Dosso province had price anomalies that appeared to begin signaling the upcoming food crisis. This market based discovery came about two months earlier than the warnings issued by the regional early warning networks.Food Security and Poverty,

THE CORN-EGG PRICE TRANSMISSION MECHANISM

A vector autoregression (VAR) model of corn, farm egg, and retail egg prices is estimated and shocked with a corn price increase. Impulse responses in egg prices, t-statistics for the impulse responses, and decompositions of forecast error variance are presented. Analyses of results provide insights on the corn/egg price transmission mechanism and on how corn price shocks pulsate through the egg-related economy.Demand and Price Analysis,