2015
DOI: 10.1016/j.asieco.2014.12.001
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Robust determinants of growth in Asian developing economies: A Bayesian panel data model averaging approach

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Cited by 15 publications
(6 citation statements)
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“…We treat the undervaluation indexes as endogenous to the model, since the empirical literature has shown that factors such as trade openness, terms of trade, inflation, government consumption, and real interest rates may drive it. However, when dealing with endogeneity in regressions, there is no clear guidance as to the optimal number of instruments to consider (León-González and Vinayagathasan, 2015). Shedding light on the issue of instrument counts, Windmeijer (2005) notes that when instrument counts are lowered the mean bias of parameters is lowered as well.…”
Section: Data and Estimation Techniquesmentioning
confidence: 99%
“…We treat the undervaluation indexes as endogenous to the model, since the empirical literature has shown that factors such as trade openness, terms of trade, inflation, government consumption, and real interest rates may drive it. However, when dealing with endogeneity in regressions, there is no clear guidance as to the optimal number of instruments to consider (León-González and Vinayagathasan, 2015). Shedding light on the issue of instrument counts, Windmeijer (2005) notes that when instrument counts are lowered the mean bias of parameters is lowered as well.…”
Section: Data and Estimation Techniquesmentioning
confidence: 99%
“…Man [46] used 30 (mostly financial) variables for 187 countries between 1988 and 2007 to indicate determinants of economic growth. León-González and Vinayagathasan [47] used a Bayesian panel-data model averaging approach to investigate the determinants of growth in developing Asian economies. Essardi and Razzouk [48] used different approaches to investigate the relationship between human capital and economic growth in Morocco.…”
Section: Introductionmentioning
confidence: 99%
“…Đồng thời, việc áp dụng mô hình dữ liệu bảng Bayes cho phép khai thác tốt các đơn vị chéo, mô tả các tham số một cách linh hoạt và chính xác (Shrivastava et al, 2017). Đặc biệt, phân tích BMA dù không xử lý tính nội sinh hoặc hiệu ứng cố định như là các phương pháp GMM (Generalised method of moments), FEM và LSDV (Least Square Dummy Variable) nhưng BMA rất nổi bật trong việc khắc phục sự không chắc chắn của mô hình nghiên cứu (Gonzalez & Vinayagathasan, 2015).…”
Section: Dữ Liệu Và Phương Pháp Nghiên Cứuunclassified