Economic Crisis and Investor Behaviour

This study investigates the effects of crises on domestic and foreign investors’ behaviours by utilizing a nonlinear approach. Considering the nonlinearity inherent in many financial variables, this study proposes an appropriate econometric modelling for analysing the investors’ behaviour, particularly during turbulent times. Specifically, STAR-STGARCH family models and generalized impulse response function analysis (GIRF) are employed to understand the different reactions of foreign and domestic investors at the Malaysian Stock Exchange market during the 1997 Asian crisis. The results of the model and the GIRF analysis have shown that foreign investors exhibited a herding behavior during the crisis and responded the shock more quickly than the domestic investors. When the same analysis is applied to understand the effects of the 2008 Subprime Mortgage Crisis in the Malaysian market, the behaviors of foreign and domestic investors are found to be very similar

Cross-Country Growth Empirics and Model Uncertainty: An Overview

The aim of this paper is to provide an overview of empirical cross-country growth literature. The paper begins with describing the basic framework used in recent empirical cross-country growth research. Even though this literature was mainly inspired by endogenous growth theories, the neoclassical growth model is still the workhorse for cross-country growth empirics. The second part of the paper emphasises model uncertainty, which is indeed immense but generally neglected in the empirical cross-country growth literature. The most outstanding feature of the literature is that a large number of factors have been suggested as fundamental growth determinants. Together with the small sample property, this leads to an important problem: model uncertainty. The questions which factors are more fundamental in explaining growth dynamics and hence growth differences are still the subject of academic research. Recent attempts based on general-to-specific modeling or model averaging are promising but have their own limits. Finally, the paper highlights the implications of model uncertainty for policy evaluation