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,

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,

In Search of the "Bank Lending Channel": Causality Analysis for the Transmission Mechanism of U.S. Monetary Policy

The bank lending channel states that changes in monetary policy cause changes in bank loans thus causing changes in real income. This implies the Federal Reserve can influence real income by controlling the level of intermediated loans. We apply a new method to test for an operative bank lending channel in the transmission mechanism of monetary policy. Combining an error correction model with directed acyclic graphs, we explore the existence of a bank lending channel and the effectiveness of U.S. monetary policy since 1960. This paper shows when an operative bank lending channel existed, explains its impact, and evaluates other channels of monetary policy.Financial Economics,

SAMUELSON'S FULL DUALITY AND THE USE OF DIRECTED ACYCLICAL GRAPHS: THE BIRTH OF CAUSALLY IDENTIFIED DEMAND SYSTEMS

To date, mixed demand systems have been all but ignored in empirical work. A possible reason for the scarcity of such applications is that one needs to know a priori which prices and quantities are endogenous in the mixed demand system. By using a directed acyclical graph (DAG), causal relationships among price and quantity variables are identified giving rise to a causally identified demand system (CIDS). A statistical comparison is made of the traditional Rotterdam model with a Rotterdam mixed demand system identified through the use of a DAG. In this analysis, the respective Rotterdam demand systems consist of five products: steak, ground beef, roast beef, pork, and chicken.Demand and Price Analysis,

FABRICATED CUT BEEF PRICES AS LEADING INDICATORS OF FED CATTLE PRICE

Temporal relationships are investigated among fabricated cut prices, carcass value, and fed cattle prices. Also, linkages between fed cattle and wholesale beef prices are examined using vector autoregressive (VAR) techniques. Results, using daily prices over the 1980-85 period, suggested that fabricated cut prices and cattle prices are related to the imputed carcass value, carcass quote, and fed cattle prices. In addition, three fabricated cuts dominate as leading indicators of fed cattle prices of most fabricated cut prices. They are strip loin and bottom and top round prices. VAR models outperform the univariate and random-walk models of forecasting ability.Demand and Price Analysis, Livestock Production/Industries,

Samuelson´s full duality and the use of directed acyclical graphs

To date, mixed demand systems have been all but ignored in empirical work. A possible reason for the scarcity of such applications is that one needs to know a priori which prices and quantities are endogenous in the mixed demand system. By using a directed acyclical graph (DAG), causal relationships among price and quantity variables are identified giving rise to a causally identified mixed demand system. A statistical comparison is made of the traditional Rotterdam model, a synthetic demand system, which subsumes the traditional Rotterdam model, and a Rotterdam mixed demand system identified through the use of a DAG. In this analysis, the respective demand systems consist of five products: steak, ground beef, beef roasts, pork, and chicken.directed acyclic graphs, mixed demand systems

Dynamic Relationships Among Selected U.S. Commodity-Based, Value Added Markets: Applying Directed Acyclic Graphs to a Time Series Model

This paper demonstrates the application of a recently developed methodology, the combination of directed acyclic graphs (DAGs) with Bernanke structural vector autoregression (VAR) models, to model a system of U.S. commodity-related and value-added markets. As an example, the paper applies this methodology to a quarterly system of U.S. markets: the wheat market and a set of downstream milling and bakery markets that use wheat as an input. Analyses of the model's impulse response simulations and forecast error variance decompositions provide updated estimates of market elasticity parameters that drive these markets, and updated policy-relevant information on how these quarterly markets run and dynamically interact. Results suggest that movements in commodity-based markets strongly influence each other, although most of these effects occur in the long run beyond a single crop cycle. The paper illuminates how important U.S. food prices respond to wheat farm market shocks in price and quantity.Bernanke structural VARs, directed acyclic graphs, quarterly wheat-related markets, Industrial Organization, Marketing, Research Methods/ Statistical Methods,