Fractional integration and cointegration in US financial time series data

This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets might be efficient) or alternatively I(d) with d < 1, which implies mean reversion. The multivariate framework exploiting recent developments in fractional cointegration allows to investigate in greater depth the relationships between financial series. We show that there exist many (fractionally) cointegrated bivariate relationships among the variables examined

Dynamic Economic Relationships Among U.S. Soy Product Markets: Using a Cointegrated Vector Autoregression Approach with Directed Acyclic Graphs

This paper applies a combined methodology of a recently developed directed acyclic graph (DAG) analysis with Johansen and Juselius' methods of the cointegrated vector autoregression (VAR) model to a monthly U.S. system of markets for soybeans, soy meal, and soy oil. Primarily a methods paper, Johansen and Juselius' procedures are applied, with a special focus on statistically addressing information inherent in well-known sources of non-normal data behavior to illustrate the effectiveness of modeling the system as a cointegrated multi-market system. Perhaps for the first time, methods of the cointegrated VAR model are combined with DAG analysis to account for contemporaneously correlated residuals, and are applied to this U.S. soy-based system. Analysis of the error correction or cointegration space illuminates the empirical nature of policy-relevant market elasticities, price transmission parameters, and effects of important policy and institutional changes/events on U.S. soy-related markets at long-run horizons beyond a single crop cycle. A statistically strong U.S. demand for soybeans emerged as the primary cointegrating relation in the error-correction space. Analysis of the DAG-adjusted cointegrated VAR model's forecast error variance decomposition illuminates how the soy-related variables and the three U.S. soy product markets dynamically interact at alternative time horizons extending up to two-years.directed acyclic graphs, cointegration, vector error correction and vector autoregression models, monthly U.S. soy-based markets., Industrial Organization, Research Methods/ Statistical Methods,

SUBSTITUTABILITY AMONG SPECIES IN THE JAPANESE TUNA MARKET: A COINTEGRATION ANALYSIS

This paper examines two sets of hypotheses concerning the existence and the cause of the long-run, inter-species price relationships in the Japanese tuna market. A shock variable is introduced into the system to determine the degree of influence on the price relationships as well as the magnitude of the power in explaining the variation in prices of tuna species. Although in most cases the coefficient estimates of the shock variable are statistically significant, overall, the variable does not have significant explanatory power in both bivariate and multivariate regressions. We also find that the degree of substitutability between bigeye and albacore is substantially lower than the degree of substitutability between bigeye and yellowfin and, yellowfin and albacore.Industrial Organization, Resource /Energy Economics and Policy,

Cointegrated Vector Autoregression Methods: An Application to Non-Normally Behaving Data on Selected U.S. Sugar-Related Markets

The methods of the cointegrated vector autoregression/error correction (VAR/VEC) model are applied to monthly U.S. markets for sugar and for sugar-using markets for confectionary, soft drink, and bakery products. Primarily a methods paper, Johansen and Juselius' methods are applied, with a special focus on addressing well-known issues that preclude statistically normal behavior, and that confront the modelled sugar-based data. In so doing, we illustrate the effectiveness and the benefits of modelling this sugar-related set of markets as a cointegrated system. Perhaps for the first time, cointegrated VEC model results are used to estimate crucial policy-relevant market parameters that drive the markets, as well as to illuminate the dynamic nature of the relationships linking these sugar-based markets.cointegration, sugar-based U.S. markets, vector autoregression, vector error correction models, Industrial Organization, Research Methods/ Statistical Methods,

MEASUREMENT OF SUBSTITUTABILITY BETWEEN U.S. DOMESTIC CATFISH AND IMPORTED FISH

This study examines p-interdependence and quantifies q-substitutability between domestic catfish and different species of imported fish in the U.S. fish market. In doing so, this study uses cointegration analyses for p-interdependence and structural analyses for q-substitutability. Cointegration analysis identifies the long run price equilibria between U.S. domestic catfish and different species of imported fish. The structural analyses show a degree of q-substitutability.cointegration, structural analyses, fish, imports, p-interdependence, and q-substitutability, International Relations/Trade,

An Empirical Investigation of Interproduct Relationships Between Domestic and Imported Seafood in the U.S.

This study seeks to identify interproduct relationships between domestic catfish and a representative selection of imported seafood. In doing so, this study uses multivariate cointegration and structural analyses. Multivariate cointegration analysis suggests that six imported seafood product groupings form a common market with domestic catfish. Structural analysis reveals that 1) domestic and imported catfish are net and gross quantity substitutes; 2) domestic catfish and imported seafood are normal goods; 3) six imported seafood products are identified as gross quantity substitutes for domestic catfish; and 4) according to the derived Allais coefficients, interaction intensities of imported seafood for domestic catfish (from greatest to least) are as follows: tuna, shrimp, salmon, tilapia, catfish, and trout.catfish, multivariate cointegration, quantity substitutability, seafood imports, structural analysis, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Demand and Price Analysis, Environmental Economics and Policy, Financial Economics, Health Economics and Policy, International Relations/Trade, Livestock Production/Industries, Marketing, Political Economy, Production Economics, Productivity Analysis, Public Economics, Research Methods/ Statistical Methods, D12, F10, F11, F13,

Museum and monument attendance and tourism flow: A time series analysis approach.

This paper takes a time series analysis approach to evaluate the directions of causality between tourism flows, on the one side, and museum and monument attendance, on the other. We consider Italy as a case study, and analyze monthly data over the period January 1996 to December 2007. All considered series are seasonally integrated, and co-integration links emerge. We focus on the error correction mechanism among co-integrated time series to detect the directional link(s) of causality. Clear-cut results emerge: generally, the causality runs from tourist flows to museum and monument attendance. The non-stationary nature of time series, their co-integration relationships, and the direction of causal links suggest specific implication for tourism and cultural policies.Tourism; Museum; Seasonal unit root; Co-integration; Causality.

DETERMINANTS OF FOOD PRICE INFLATION IN FINLAND

The agricultural commodity crisis of 2006-8 and the recent evolution of commodity markets have reignited anxieties in Finland over fast-rising food prices and food security. Although the impact of farm commodity price shocks on the final consumer is mitigated by a large degree of processing as well as the complex structure of the food chain, little is known about the strength of the linkages between food markets and input markets. Using monthly series of price indices from 1995 to 2010, we estimate a vector error-correction (VEC) model in a co-integration framework in order to investigate the short-term and long-term dynamics of food price formation. The results indicate that a statistically significant long-run equilibrium relationship exists between the prices of food and those of the main variable inputs consumed by the food chain, namely agricultural commodities, labour, and energy. When judged by the magnitude of long-run pass-through rates, farm prices represent the main determinant of food prices, followed by wages in food retail and the price of energy. However, highly volatile energy prices are also important in explaining food price variability. The parsimonious VEC model suggests that the dynamics of food price formation is dominated by a relatively quick process of adjustment to the long-run equilibrium, the half life of the transitional dynamics being six to eight months following a shock.Demand and Price Analysis,