The authors address the issue of estimation and inference in dependent nonstationary panels of small cross-section dimensions. The main conclusion is that the best results are obtained applying bootstrap inference to single-equation estimators, such as fully modified ordinary least squares and dynamic ordinary least squares. Seemingly unrelated regression estimators perform badly, or are even u...

Information about tree biomass is important not only in the assessment of wood resources but also process preparing forest management plans, as well for estimating carbon stocks and their flow ecosystems. The study aimed to develop empirical models determining dry mass aboveground parts black locust trees components (stem, branches, leaves). research was carried out based on data collected 13 s...

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameterand height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg.) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass equations was fitted simultaneously with a constrained seemingly unrelated re...

Biomass estimation is critical for looking at ecosystem processes and as a measure of stand yield. The density-integral approach allows for coincident estimation of stem profile and biomass. The algebraic difference approach (ADA) permits the derivation of dynamic or nonstatic functions. In this study we applied the ADA to develop a self-referencing specific gravity function and biomass functio...

This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components. The approach treats the points on each nonparametric regression line as unknown parameters and uses a prior on the degree of smoothness of each line to ensure ...

selection of best demand model for explaining of consumer behaviour is one of the most important issues in microeconomic. in this paper we introduce aids[1],cbs[2], nbr[3] and rotterdam model and estimate these models by iranian urban households data for period 1973-2012.seemingly unrelated regression method is chosen for estimation of 5 groups of commodities including food, housing, clothing, ...