Stock market interdependence between Australia and its trading partners: does trade intensity matter?

We investigate the extent and manner of stock market interdependence between Australia and its trading partners and examine whether this is affected by trade intensity. Based on trade intensity, we classify Australia’s trading partners into major, medium and minor partners. We hypothesize that markets with greater (lower) trade intensity will be more (less) interdependent with Australia. We perform correlation (unconditional and conditional) analyses between Australia and its trading partners. Our results indicate that most of the markets that are highly correlated with Australia are its major trading partners. We conduct panel regression analysis to investigate whether trade intensity has any impact on the stock market correlations between Australia and its trading partners. The results show that trade intensity significantly and positively affect the correlations of Australia with its major trading partners. Thus, the results confirm our hypothesis that trade intensity drives stock market interdependence between Australia and its trading partners.     

The relationship between population growth and standard-of-living growth over 1870–2013: evidence from a bootstrapped panel Granger causality test

This paper examines the linkages between population growth and standard-of-living growth in 21 countries over the period of 1870–2013. We apply the bootstrap panel causality test proposed by Kónya (Econ Model 23:978–992, 2006), which accounts for both dependency and heterogeneity across countries. We find one-way Granger causality running from population growth to standard-of-living growth for Finland, France, Portugal, and Sweden, one-way Granger causality running from standard-of-living growth to population growth for Canada, Germany, Japan, Norway and Switzerland, two-way causality for Austria and Italy, and no causal relationship for Belgium, Brazil, Denmark, Netherlands, New Zealand, Spain, Sri Lanka, the UK, the USA, and Uruguay. Dividing the sample into two subsamples due to a structural break yields different results over the two periods of 1871–1951 and 1952–2013. Our empirical results suggest important policy implications for these 21 countries as the directions of causality differ across countries and time period.     

Forecasting US real house price returns over 1831–2013: evidence from copula models

Given the existence of nonnormality and nonlinearity in the data generating process of real house price returns over the period of 1831–2013, this article compares the ability of various univariate copula models, relative to standard benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1874–2013, based on an in-sample of 1831–1873. Overall, our results provide overwhelming evidence in favour of the copula models (Normal, Student’s t, Clayton, Frank, Gumbel, Joe and Ali-Mikhail-Huq) relative to linear benchmarks, and especially for the Student’s t-copula, which outperforms all other models both in terms of in-sample and out-of-sample predictability results. Our results highlight the importance of accounting for nonnormality and nonlinearity in the data generating process of real house price returns for the US economy for nearly two centuries of data.     

Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach

This article adopts a nonparametric quantile causality approach to examine the causal effects of the U.S. and Japan stock markets on the stock markets of the Pacific-Rim region. This approach allows us to detect not only nonlinear causalities in conditional return (mean) and conditional volatility (variance) but also the asymmetries of causalities under extreme market conditions (bullish vs. bearish states). Our results provide significant evidence of causality in return and volatility at different points of the conditional distributions of returns, with the greater effects from the U.S. than from Japan. Asymmetric quantile causality patterns are particularly pronounced in the case of Japan.     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.     

The R&D-Marketing Interface in High-Technology Firms

It has become part of the traditional wisdom that good relationships between the R&D and marketing departments are essential for effective new product development. But in so many firms it still just doesn't happen. How come? In this article, three pragmatic researchers, Professors Gupta, Raj, and Wilemon, take another look at what causes the significant barriers that exist at the interface of two of the key product innovation functions. What they discover is disagreement between marketing and R&D people about what they should do together. They also find that R&D people are the more reluctant cooperators. They draw some interesting opinions from the parties as to why the barriers exist.     

Congruence between spokesperson and product type: A matchup hypothesis perspective

This study tested the matchup hypothesis regarding choice of celebrity spokesperson by examining the fit or congruence between image type and the product advertised from an Identification and Internalization viewpoint (Kelman, 1961). Spokesperson type (celebrity versus noncelebrity) was varied, aong with congruence between spokesperson image and product (higher versus lower congruence) in a 2x2 factorial design. Results showed that increased congruence for the spokesperson/product combination resulted in the perception of higher believability and attractiveness of the spokesperson and a more favorable product attitude. The implications of these and other findings for advertising and marketing strategy are discussed. © 1994 John Wiley & Sons, Inc.