This special issue on Statistics in Econometrics contains revised and extended versions of selected papers from the Third Conference of the Econometrics Society of Thailand (Chiang Mai, Thailand, January 7-8, 2010). Papers presented in this issue cover all aspects of statistics in econometrics: a paper by D. Schoch describes how to formalize envy and loss aversion; a paper by Z. Bai, W.-K. Wong, and B. Zhang, analyzes multivariate linear and non-linear causality terms; a paper by P. Rakonczai and N. Tajvidi describes how to predict bivariate extremes; in their paper, S. Sriboonchitta, H. T. Nguyen, and V. Kreinovich analyze the relationship between two known econometric approaches to decision making under risk and uncertainty: the approach of spectral risk measures and the more traditional utilities approach; a paper by C.-L. Chang, T. Khamkaew, M. McAleer, and R. Tansuchat applies a panel threshold model of tourism specialization and economic development; a paper by E. Ogawa and T. Yoshimi analyzes the beta and sigma convergences of East Asian currencies; a paper by T. Bodnar and A. K. Gupta analyzes the impact of skewness on the performance of optimal portfolio. A paper by J. C. Xie, B. Wu, and S. Sriboonchitta goes beyond statistical techniques -- it shows how fuzzy estimation methods can be used in real estate evaluation.

The International Journal of Intelligent Technologies and Applied Statistics (IJITAS) publishes high-quality and peer-reviewed research papers in all areas of intelligent technologies and Applied Statistics. The aspects of Applied Statistics oriented towards the emerging needs for extending statistical methods to handle new types of data in technologies, including spatial data, perception-based information and causal information, and the soft computing approaches such as fuzzy logic, neural networks, evolutionary computing, multivariate analysis, statistical learning theory as well as probabilistic optimization techniques are among the topics where a connection between statistics and intelligent decision-making seems fruitful for real-world applications.