We propose a new generic method ROPES (Regularized Optimization for Prediction and Estimation with Sparse data) for decomposing, smoothing and forecasting two-dimensional sparse data. In some ways, ROPES is similar to Ridge Regression, the LASSO, Principal Component Analysis (PCA) and...

In recent years, analysis of financial time series has focused largely on data related to market trading activity. Apart from modelling the conditional variance of returns within the GARCH family of models, presently attention has also been devoted to other market variables, especially volumes,...

Theoretical results on the properties of forecasts obtained using singular spectrum analysis are presented in this paper. The mean squared forecast error is derived under broad regularity conditions, and it is shown that the forecasts obtained in practice will converge to their population...

This paper considers a general model specification test for nonlinear multivariate cointegrating regressions where the regressor consists of a univariate integrated time series and a vector of stationary time series. The regressors and the errors are generated from the same innovations, so that...

Exponential smoothing is one of the most popular forecasting methods. We present a method for bootstrap aggregation (bagging) of exponential smoothing methods. The bagging uses a Box-Cox transformation followed by an STL decomposition to separate the time series into trend, seasonal part, and...

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...