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Underfive mortality statistics is not only important indicators of\ndemographic situation but also social and health conditions of Myanmar and some\nneighbouring countries. The secondary data used in this study was extracted from\nADB and the World Bank Database. In this study, the underfive mortality rates over\nthe years (20032017) are modeled using time series analysis. This study designs to\npredict the future of Myanmar and some neighbouring countries by selecting the\nappropriate model among four commons models as Linear, Quadratic, Cubic, and\nExponential. In Myanmar, the values of coefficient in the Exponential model are\nstatistically significant and the value MSE (63.2685) for Exponential model is the\nsmallest on comparing with other models. Thus, the Exponential model was chosen as\nthe most appropriate and predictable future model in Myanmar. It found that the\nforecast value of U5MR in Myanmar was decreased little by little from 40.66 in 2018\nto 32.91 in 2021. In Thailand, the values of coefficient in four common models are\nstatistically significant and the value of MSE (6.9064) for the Cubic model is the\nsmallest on comparing with other models. Thus, the Cubic model was chosen as the\nmost appropriate and predictable future model in Thailand. It found that the forecast\nvalue of U5MR in Thailand was decreased little by little from 5.66 in 2018 to 14.51\nin 2021. In China, the values of coefficient in four common models are statistically\nsignificant and the value of MSE (0.4459) for the Cubic model is the smallest on\ncomparing with other models. Thus, the Cubic model was chosen as the most\nappropriate and predictable future model in China. It found that the forecast value of\nU5MR in China was decreased little by little from 7.47 in 2018 to 0.117 in 2021. In\nIndia, the values of coefficient in the Linear model are statistically significant and the\nvalue of MSE (3.4277) for the Linear model is the smallest on comparing with other\nmodels. Thus, the Linear model was chosen as the most appropriate and predictable\nfuture model in India. It found that the forecast value of U5MR in India was\ndecreased little by little from 36.13 in 2018 to 26.22 in 2021. In Bangladesh, the\nvalues of coefficient in Quadratic model are statistically significant and the value\nMSE (9.6080) for the Quadratic model is the smallest on comparing with other\nmodels. Thus, the Quadratic model was chosen as the most appropriate and\npredictable future model in Bangladesh. It found that the forecast value of U5MR in\nBangladesh was decreased little by little from 30.4 in 2018 to 26.43 in 2021. Thus, the\nforecast values of underfive mortality rates (2018 to 2021) were decreasing in\nMyanmar and neighbouring countries. Forecasting is very important in future\ndecisions making. The forecast based on the appropriate models were also validated\nin this thesis to support future decision making for planning purpose."}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "20230112"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Tin Mar Su (MAS30).pdf", "filesize": [{"value": "635 KB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_0", "mimetype": "application/pdf", "size": 635000.0, "url": {"url": "https://meral.edu.mm/record/8681/files/Tin Mar Su (MAS30).pdf"}, "version_id": "b05b920a5cf54e6ebfa599d06150be80"}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "Yangon University of Economics", "subitem_supervisor(s)": [{"subitem_supervisor": "Daw Thin Marlar Oo"}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Tin Mar Su"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Other"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "20200301"}, "item_title": "Modelling and Forecasting of the UnderFive Mortality Rates in Myanmar and Some Neighbouring Countries (Tin Mar Su, 2020)", "item_type_id": "21", "owner": "20", "path": ["1582963436320", "1582965763232"], "permalink_uri": "https://meral.edu.mm/records/8681", "pubdate": {"attribute_name": "Deposit date", "attribute_value": "20230112"}, "publish_date": "20230112", "publish_status": "0", "recid": "8681", "relation": {}, "relation_version_is_last": true, "title": ["Modelling and Forecasting of the UnderFive Mortality Rates in Myanmar and Some Neighbouring Countries (Tin Mar Su, 2020)"], "weko_shared_id": 1}
Modelling and Forecasting of the UnderFive Mortality Rates in Myanmar and Some Neighbouring Countries (Tin Mar Su, 2020)
https://meral.edu.mm/records/8681
https://meral.edu.mm/records/868137bcc55d56e6495ea59b9f6f51b1319b
d9d0c4e9e131441eb38dd1a311bf5411
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Tin Mar Su (MAS30).pdf (635 KB)

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Thesis  
Upload type  
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Title  
Title  Modelling and Forecasting of the UnderFive Mortality Rates in Myanmar and Some Neighbouring Countries (Tin Mar Su, 2020)  
Language  en  
Publication date  20200301  
Authors  
Tin Mar Su  
Description  
The underfive mortality rate is a key indicator of the state of public health of a society. Underfive mortality statistics is not only important indicators of demographic situation but also social and health conditions of Myanmar and some neighbouring countries. The secondary data used in this study was extracted from ADB and the World Bank Database. In this study, the underfive mortality rates over the years (20032017) are modeled using time series analysis. This study designs to predict the future of Myanmar and some neighbouring countries by selecting the appropriate model among four commons models as Linear, Quadratic, Cubic, and Exponential. In Myanmar, the values of coefficient in the Exponential model are statistically significant and the value MSE (63.2685) for Exponential model is the smallest on comparing with other models. Thus, the Exponential model was chosen as the most appropriate and predictable future model in Myanmar. It found that the forecast value of U5MR in Myanmar was decreased little by little from 40.66 in 2018 to 32.91 in 2021. In Thailand, the values of coefficient in four common models are statistically significant and the value of MSE (6.9064) for the Cubic model is the smallest on comparing with other models. Thus, the Cubic model was chosen as the most appropriate and predictable future model in Thailand. It found that the forecast value of U5MR in Thailand was decreased little by little from 5.66 in 2018 to 14.51 in 2021. In China, the values of coefficient in four common models are statistically significant and the value of MSE (0.4459) for the Cubic model is the smallest on comparing with other models. Thus, the Cubic model was chosen as the most appropriate and predictable future model in China. It found that the forecast value of U5MR in China was decreased little by little from 7.47 in 2018 to 0.117 in 2021. In India, the values of coefficient in the Linear model are statistically significant and the value of MSE (3.4277) for the Linear model is the smallest on comparing with other models. Thus, the Linear model was chosen as the most appropriate and predictable future model in India. It found that the forecast value of U5MR in India was decreased little by little from 36.13 in 2018 to 26.22 in 2021. In Bangladesh, the values of coefficient in Quadratic model are statistically significant and the value MSE (9.6080) for the Quadratic model is the smallest on comparing with other models. Thus, the Quadratic model was chosen as the most appropriate and predictable future model in Bangladesh. It found that the forecast value of U5MR in Bangladesh was decreased little by little from 30.4 in 2018 to 26.43 in 2021. Thus, the forecast values of underfive mortality rates (2018 to 2021) were decreasing in Myanmar and neighbouring countries. Forecasting is very important in future decisions making. The forecast based on the appropriate models were also validated in this thesis to support future decision making for planning purpose. 

Thesis/dissertations  
Yangon University of Economics  
Daw Thin Marlar Oo 