Seasonal Nonstationarity and Near-Nonstationarity

This paper presents a detailed discussion of the characteristics of seasonal integrated and near integrated processes, as well as the asymptotic properties of seasonal unit root tests. More specifically, the characteristics of a seasonal random walk and a more general seasonal integrated ARMA process are analysed. Also the implications of modelling nonstationary stochastic season-ality as deterministic are highlighted. A further observation made includes the asymptotic distributions and power functions of several seasonal unit root tests. Dans cet article, nous étudions les propriétés des processsus avec racines unitaires saisonnières et avec racines quasi-unitaires. Nous traitons le cas des marchés aléatoires ainsi que les processus plus généraux et analysons les distributions des estimateurs et les fonctions de puissances de plusieurs tests.Deterministic/stochastic seasonality, seasonal unit roots, Saisonnalité déterministique et stochastique, racines unitaires saisonnières

Nonstationarity in the Specification of the Environmental Kuznets Curve

Numerous studies have addressed the question of the econometric specification of the Environmental Kuznets Curve (EKC). This paper adds preliminary results on nonstationarity and its effect on functional form using a panel data set for the U.S. by state from 1929 to 1994. It is found that unit-root tests strongly support a unit root in pollutants (sulfur dioxide and nitrogen oxide) and income when testing individual states. The results from panel data unit root tests provide mixed evidence about nonstationarity in EKC data.Environmental Kuznets curve, fixed and random effects, parametric models, water pollution, watershed, nonstationarity, unit-roots, Environmental Economics and Policy,

Spurious regression under deterministic and stochastic trends

This paper analyses the asymptotic and finite sample implications of a mixed nonstationary behavior among the dependent and explanatory variables in a linear spurious regression model. We study the cases when the nonstationarity in the dependent variable is deterministic (stochastic), while the nonstationarity in the explanatory variable is stochastic (deterministic). In particular, we derive the asymptotic distribution of statistics in a spurious regression equation when one variable follows a difference stationary process (a random walk with and without drift), while the other is characterized by deterministic nonstationarity (a linear trend model with and without structural breaks in the trend function). We find that the divergence rate is sensitive to the assumed mixture of nonstationarity in the data generating process, and the phenomenon of spurious regression itself, contrary to previous findings, depends on the presence of a linear trend in the regression equation. Simulation experiments and real data confirm our asymptotic results.Unit roots, Trend stationarity, Structural breaks, Spurious regression

PRICE FORECASTING WITH TIME-SERIES METHODS AND NONSTATIONARY DATA: AN APPLICATION TO MONTHLY U.S. CATTLE PRICES

The forecasting performance of various multivariate as well as univariate ARIMA models is evaluated in the presence of nonstationarity. The results indicate the importance of identifying the characteristics of the time series by testing for types of nonstationarity. Procedures that permit model specifications consistent with the systemÂ’s dynamics provide the most accurate forecasts.Demand and Price Analysis, Livestock Production/Industries,

Mapping the results of local statistics

The application of geographically weighted regression (GWR) – a local spatial statistical technique used to test for spatial nonstationarity – has grown rapidly in the social, health and demographic sciences. GWR is a useful exploratory analytical tool that generates a set of location-specific parameter estimates which can be mapped and analysed to provide information on spatial nonstationarity in relationships between predictors and the outcome variable. A major challenge to GWR users, however, is how best to map these parameter estimates. This paper introduces a simple mapping technique that combines local parameter estimates and local t-values on one map. The resultant map can facilitate the exploration and interpretation of nonstationarity.geographically weighted regression, local statistics, mapping, nonstationarity

Rindler horizon entropy from nonstationarity

Finite entropy and energy are obtained for the horizon of a Rindler observer on the grounds of the nonstatic character of the geometry beyond the horizon. Edery - Constantineau prescription is used to find the dynamical phase space of this particular spacetime. The number of microstates rooted from the ignorance of a Rindler observer of the parameter $t$ from the nonstationary region is calculated. We suggest that the gravitational energy density constructed by means of the horizon energy and using the Holographic Principle is proportional to $g^{2}$, similar with a result recently obtained by Padmanabhan and with the energy density of the electromagnetic field.Comment: 8 pages, no figures, version published in PLB 703(5),(2011) pp. 641-644, DOI: 10.1016/j.physletb.2011.08.06

Modelling the Longitudinal Properties of Financial Ratios of European Firms

The use of financial ratios by analysts to compare the performance of firms from one accounting period to the next is of growing importance with continued European economic integration. Recent studies suggest that the individual component series of financial ratios exhibit nonstationarity which is not eliminated by the ratio transformation. In this paper, w e derive a generalised model that incorporates stochastic and deterministic trends and allows for restricted and unrestricted proportionate growth in the ratio numerator and denominator. When the individual firm series are included in a panel structure with large N and small T, we are unable to reject convincingly a joint hypothesis of nonstationarity, whilst in about one third of the individual firm panels there is no evidence of a unit root. Although the components of financial ratios are correlated variables, our estimates show that any cointegrating effects decay rapidly.financial ratios, nonstationarity, proportionate growth, cointegration, panel methods