Evolving splines and seasonal unit roots in weekly agricultural prices

The univariate statistical properties of agricultural price series need to be examined as a first step in the analysis of price transmission mechanisms. However, in the case of weekly price series, increasingly available, the testing procedures usually applied in this step are not suitable to deal with evolving seasonal effects. In this study, a method of testing for seasonal unit roots in weekly series of agricultural prices is described. When the deterministic seasonal component does not remain constant over time, the restricted evolving spline model (RESM) is shown to be a useful parametric formulation to capture the deterministic seasonal pattern. Therefore, the RESM model should be included as a deterministic component in auxiliary regression for unit root tests at seasonal frequencies. This proposal is applied to three weekly series of Canary Islands banana prices. From the standard seasonal unit root tests, the null hypothesis is failed to be rejected at the 5% or 10% significance level at some seasonal frequencies for each one of the series. Once critical values are obtained by simulation exercises when the RESM model is included, the hypotheses of unit root are rejected at each one of the seasonal frequencies for all of the three series.     

Information Technology Tools in New Product Development: The Impact of Complementary Resources*,†

Emergent research has examined the antecedents to using information technology (IT) in the new product development (NPD) process and the impact of IT on NPD performance. Based on the resource‐based view (RBV) of the firm, this study hypothesizes that particular resources create IT capabilities that significantly enhance NPD outcomes. More specifically, this research extends previous work by investigating whether three complementary resources, namely an executive champion for IT, global engagement, and organizational innovativeness, influence IT capabilities (IT use frequency and IT replacement frequency), which in turn affect NPD outcomes (NPD task proficiency and NPD performance). To test the conceptual model, survey data were collected from 220 NPD and IT managers in a variety of large Japanese firms. The results show that an executive champion for IT and global engagement are predictors of both IT tool use and replacement frequency while organizational innovativeness contributes only to IT tool replacement frequency. The results also indicate that both IT tool use and replacement frequency have a positive effect on NPD task proficiency, which improves NPD performance. This research contributes to the literature by adding understanding of the role of IT in NPD at the firm level in four ways. First, it examines particular organizational complementary resources and their relationship to IT capabilities. Second, it examines the RBV and IT in the context of NPD, an important business process. Third, it measures IT usage in a more granular fashion (i.e., IT tool use frequency and IT replacement frequency) rather than simply IT usage as a dichotomy. Finally, through testing the proposed model with data collected from Japanese firms, this study provides empirical evidence from an Asian country to answer the call for more NPD research to be conducted in countries other than North American and Western European contexts. The findings of the study also provide implications for managers. Importantly, they indicate that an executive level champion for IT is a key influencer in facilitating IT usage and replacement, and likely can help generate awareness of and support for greater IT investments so the firm can create IT capabilities for effective NPD.     

Quantitative Methods for Evaluating the Unilateral Effects of Mergers

We describe the quantitative modeling techniques that are used in horizontal merger review for the evaluation of unilateral effects, and discuss how the 2010 Horizontal Merger Guidelines helped legitimize these methods and motivate scholarly research. We cover markets that feature differentiated products pricing, auctions and negotiations, and homogeneous products, in turn. We also develop connections between quantitative modeling and market concentration screens that are based on the Herfindahl-Hirschman Index (HHI).

     

Prediction regions for interval-valued time series

We approximate probabilistic forecasts for interval-valued time series by offering alternative approaches. After fitting a possibly non-Gaussian bivariate vector autoregression (VAR) model to the center/log-range system, we transform prediction regions (analytical and bootstrap) for this system into regions for center/range and upper/lower bounds systems. Monte Carlo simulations show that bootstrap methods are preferred according to several new metrics. For daily S&P 500 low/high returns, we build joint conditional prediction regions of the return level and volatility. We illustrate the usefulness of obtaining bootstrap forecasts regions for low/high returns by developing a trading strategy and showing its profitability when compared to using point forecasts.