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This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world's foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the "empirical toolbox" that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to "build" the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Patients are increasingly choosing health-care institutions based on online comments; thus, we examined the influence of different forms of word-of-mouth (electronic or traditional) on patients' health-care-seeking behavior. Data were collected from 415 patients who during 2015–2016
sought medical advice at a large 3rd-grade, class-A hospital in China. Results showed that, compared to those influenced by traditional word-of-mouth, patients influenced by electronic word-of-mouth paid significantly more attention to reviews of the health-care institutions, and also spent
more time and energy choosing an appropriate health-care institution. In addition, treatment method (invasive vs. noninvasive) had a moderating influence on patients' confidence in the health-care institution. That is, those influenced by traditional word-of-mouth had greater confidence than
those influenced by electronic word-of-mouth in invasive procedures provided by the chosen health-care institution, although there was no difference in confidence for patients undergoing noninvasive procedures. Practical and theoretical implications are discussed.

This paper uses China Health and Nutrition Survey (CHNS) data to analyze the effect of foreign direct investment (FDI) on nutrient intakes across various family roles to identify the different family roles' heterogeneous nutrition intake responses to economic openness. The empirical evidence shows that FDI enhances labor forces' calorie intake significantly, especially for rural households. The government should continue facilitating more FDI inflows, especially FDI in secondary industries for rural populations. However, the larger the family, the smaller the effect of FDI on nutrient intake for some family roles. The elderly and children may be weaker responders on nutrient intake than other family members in an open economy. This implies the existence of intra-household redistribution and that the level of effectiveness will decrease with family size. The results suggest that family members in rural areas can benefit more in terms of nutrient intake. Our empirical evidence also indicates that female family members' calorie intake from the FDI effect is higher than that of male family members (except for the granddaughter/grandson). Preferential policies should be provided for the FDI, flowing to rural areas and female dominant industries.