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      Socio-economic factors affecting high infant and child mortality rates in selected African countries: does globalisation play any role?

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          Abstract

          Background

          Despite the declining trends worldwide, infant and child mortality rates are still high in many African countries. These high rates are problematic; therefore, this study attempts to explore the contributing factors that cause high infant and child mortality rates in 14 African countries using panel data for the period of 2000–2018. In particular, the role globalisation is explored.

          Methods

          The panel corrected standard error (PCSE), the Feasible generalized least square (FGLS) models, and the pair-wise Granger causality test have been applied as methodological approaches.

          Results

          The public health expenditure, numbers of physicians, globalization, economic development, education, good governance, and HIV prevalence rate have been revealed as the determinants of infant and child mortality in these countries. All these variables except the HIV prevalence rate negatively affect the infant and child mortality rates, while the HIV prevalence rate is found to be positive. Bidirectional and unidirectional causal relationships between the variables are also attained.

          Conclusions

          Effective socio-economic policy priority with due consideration of globalization should be emphasized to reduce infant and child mortality rates in these countries.

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          Most cited references79

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          Investigating Causal Relations by Econometric Models and Cross-spectral Methods

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            On the Concept of Health Capital and the Demand for Health

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              Econometric Analysis of Cross Section and Panel Data

              This graduate text provides an intuitive but rigorous treatment of contemporary methods used in microeconometric research. The book makes clear that applied microeconometrics is about the estimation of marginal and treatment effects, and that parametric estimation is simply a means to this end. It also clarifies the distinction between causality and statistical association. The book focuses specifically on cross section and panel data methods. Population assumptions are stated separately from sampling assumptions, leading to simple statements as well as to important insights. The unified approach to linear and nonlinear models and to cross section and panel data enables straightforward coverage of more advanced methods. The numerous end-of-chapter problems are an important component of the book. Some problems contain important points not fully described in the text, and others cover new ideas that can be analyzed using tools presented in the current and previous chapters. Several problems require the use of the data sets located at the author's website.
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                Author and article information

                Contributors
                mafiz.rahman@usq.edu.au
                alam.khosrul@gmail.com
                rasheda.khanam@usq.edu.au
                Journal
                Global Health
                Global Health
                Globalization and Health
                BioMed Central (London )
                1744-8603
                7 July 2022
                7 July 2022
                2022
                : 18
                : 69
                Affiliations
                [1 ]GRID grid.1048.d, ISNI 0000 0004 0473 0844, School of Business, Centre for Health Research, , University of Southern Queensland, ; Toowoomba, Australia
                [2 ]GRID grid.449329.1, ISNI 0000 0004 4683 9733, Department of Economics, , Bangabandhu Sheikh Mujibur Rahman Science and Technology University, ; Gopalganj, 8100 Bangladesh
                Author information
                http://orcid.org/0000-0002-0025-7821
                Article
                855
                10.1186/s12992-022-00855-z
                9261177
                35799303
                39566b51-6d11-45fa-872e-651179ea7a7c
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 22 November 2021
                : 8 June 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Health & Social care
                infant mortality rate,child mortality rate,globalization,panel data,african countries

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