Residual variance estimation in moving average models

We consider time series models of the MA (moving average) family, and deal with the estimation of the residual variance. Results are known for maximum likelihood estimates under normality, both for known or unknown mean, in which case the asymptotic biases depend on the number of parameters (including the mean), and do not depend on the values of the parameters. For moment estimates the situation is different, because we find that the asymptotic biases depend on the values of the parameters, and become large as they approach the boundary of the region of invertibility. Our approach is to use Taylor series expansions, and the objective is to obtain asymptotic biases with error of o(l/T), where T is the sample size. Simulation results are presented, and corrections for bias suggested.     

Time-varying autoregressive conditional duration model

The main goal of this work is to generalize the autoregressive conditional duration (ACD) model applied to times between trades to the case of time-varying parameters. The use of wavelets allows that parameters vary through time and makes possible the modeling of non-stationary processes without preliminary data transformations. The time-varying ACD model estimation was done by maximum-likelihood with standard exponential distributed errors. The properties of the estimators were assessed via bootstrap. We present a simulation exercise for a non-stationary process and an empirical application to a real series, namely the TELEMAR stock. Diagnostic and goodness of fit analysis suggest that the time-varying ACD model simultaneously modeled the dependence between durations, intra-day seasonality and volatility.     

The Influence of Service Orientation on B2B e‐Service Capabilities: An Empirical Investigation

E‐Services, or the company's portfolio of service offerings available to its customers through the Internet, are an emerging area of interest to operations management. Yet little is known about the operations and capabilities needed for provision of business‐to‐business (B2B) e‐services. This paper aims to make a contribution toward closing this gap. First, we develop a new construct of B2B e‐service capability, a term that captures a generic set of five interrelated and complementary dimensions: (1) e‐service recovery, (2) e‐customization, (3) ease of navigation, (4) service portfolio comprehensiveness, and (5) information richness. These combined operational abilities are associated with B2B service delivery, including its portal design, technology architecture, and mix of product and service offerings. They are posited to be necessary for delivering effective B2B e‐services. We also argue that, both service orientation (SO) and customer receptivity to technology, influence B2B e‐service capability. We empirically test a path model using structural equation modeling on a sample of 181 businesses that have deployed B2B e‐services. We find that the influence of SO on performance is not direct but rather mediated by the e‐service capability, a finding that holds for both goods producers and service providers. We suggest that a firm's SO may mitigate industrial customers' resistance toward conducting business online.     

On the Choice of the Ridge Parameter: A Maximum Entropy Approach

In this article, a new method to estimate the ridge parameter, based on the ridge trace and an analytical method borrowed from maximum entropy, is presented. The performance of the new estimator is illustrated through a Monte Carlo simulation study and an empirical application to the well-known Portland cement data set.     

Model-Based Estimation of Unemployment Rates in Small Areas of Portugal

The high level of unemployment is a major problem in most European countries nowadays. Hence, the demand for small area labor market statistics has rapidly increased over the past few years. The Portuguese Labour Force Survey is the main source of official statistics at the macro level. However, it was not designed to produce reliable design-based statistics at the micro level due to small sample sizes. The goal of this article is to analyze the performance of model-based small area estimators to estimate the unemployment rate at micro level. Our results showed that the temporal estimator is the most suitable.     

A comparative study of multiattribute decision making methodologies

Three real life cases are considered in this paper to apply and compare the rankings obtained by the Analytic Hierarchy Process (AHP) and other Multicriteria Decision Making (MCDM) techniques such as Simple Additive Weighting (SAW), ELECTRE and Weighted Linear Assignment Method (WLAM). The results indicated that the AHP, SAW, and ELECTRE rankings do not differ significantly, however, the WLAM tends to exhibit more disagreement. However, because of the limited nature of this study, we do not suggest this as a general conclusion.     

From social capital to entrepreneurial orientation: The mediating role of dynamic capabilities

This paper analyzes how social capital and its three dimensions—structural, relational, and cognitive—affect entrepreneurial orientation through dynamic capabilities. We specifically analyzed the effect of each dimension of social capital on firms' entrepreneurial orientation and the mediating effect of dynamic capabilities to explain these relationships. This study was conducted on a sample of firms in the Spanish agri-food industry. The results of the empirical analysis show that dynamic capabilities are generated by firms' social capital. Dynamic capabilities lead relational and cognitive social capital to develop a higher entrepreneurial orientation. The negative effect of structural social capital can only be countered if firms build and develop dynamic capabilities.