This paper integrates seemingly disjoint studies on consumer behavior in micro and macro analyses via the intertemporal two-stage budgeting procedure with durable goods and liquidity constraints. The model accounts for the influences of nondurables consumption, commodity prices, and durables...

A class of demand systems based on simple parametric specification of the indirect utility functions, but allowing for the parsimonious imposition of global regularity, is proposed. Demand systems in this class are completely flexible in rank, i.e., can be potentially specified to acquire as...

In this paper, we focus on expensive multiobjective optimization problems and propose a method to predict an approximation of the Pareto optimal set using classification of sampled decision vectors as dominated or nondominated. The performance of our method, called EPIC, is demonstrated on a set...

The paper presents estimates of price elasticities of demand for twelve disaggregated alcohol beverages in Australia: premium beer, full strength beer, low alcohol beer, and mid strength beer; red bottled wine, white bottled wine, sparkling wine, cask wine, and dark and light ready-to-drink...

This paper investigates the use of bootstrap-based bias correction of semi-parametric estimators of the long memory parameter in fractionally integrated processes. The re-sampling method involves the application of the sieve boot-strap to data pre-filtered by a preliminary semi-parametric...

In this paper, we consider a model selection issue in semiparametric panel data models with fixed effects. The modelling framework under investigation can accommodate both nonlinear deterministic trends and cross-sectional dependence. And we consider the so-called "large panels" where both the...

Estimation in two classes of popular models, single-index models and partially linear single-index models, is studied in this paper. Such models feature nonstationarity. Orthogonal series expansion is used to approximate the unknown integrable link function in the models and a profile approach...

This paper investigates the accuracy of bootstrap-based bias correction of persistence measures for long memory fractionally integrated processes. The bootstrap method is based on the semi-parametric sieve approach, with the dynamics in the long memory process captured by an autoregressive...

One of the most widely used standard procedures for model evaluation in classification and regression is K-fold cross-validation (CV). However, when it comes to time series forecasting, because of the inherent serial correlation and potential non-stationarity of the data, its application is not...

A method is proposed for forecasting composite time series such as the market shares for multiple brands. Its novel feature is that it relies on multi-series adaptations of exponential smoothing combined with the log-ratio transformation for the conversion of proportions onto the real line. It...