The investigation of the adaptation to life events and life trajectories

This study uses Machine Learning algorithms to investigate two areas of the Subjective Well-Being field - adaptation and and life trajectories. Data from the Household, Income and Labour Dynamics in Australia data set was used for analysis. When investigating adaptation and anticipation, I found tha...

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Main Author: Balakrishnan, Dilip
Other Authors: Fedor Duzhin
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166413
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1664132023-05-08T15:39:08Z The investigation of the adaptation to life events and life trajectories Balakrishnan, Dilip Fedor Duzhin Nattavudh Powdthavee School of Physical and Mathematical Sciences FDuzhin@ntu.edu.sg, nick.powdthavee@ntu.edu.sg Science::Mathematics::Statistics This study uses Machine Learning algorithms to investigate two areas of the Subjective Well-Being field - adaptation and and life trajectories. Data from the Household, Income and Labour Dynamics in Australia data set was used for analysis. When investigating adaptation and anticipation, I found that advanced supervised Machine Learning algorithms (LASSO and a combination of Fixed Effects and Random Forests) produced largely similar findings to that of Linear Regression and Fixed Effect models. My results also showed that adaptation was observed for child birth and divorce, but not for unemployment. I also discovered that men and women adapted differently to certain events. Men were not found to adapt to the death of close relatives while women were found to do so. This might have been due to psychosocial reasons. Similarly, while women were not found to adapt to marriage, men were able to adapt to marriage. Furthermore, I used several clustering algorithms, such as K-Means, and found that there were two types of life trajectories (“Calm” and “Turbulent”). The individuals who had Calm life trajectories appeared to have a higher Mean Life Satisfaction, higher Annual Trend in Life Satisfaction and lower Variability in Life Satisfaction than individuals with Turbulent life trajectories. Moreover, I uncovered that individuals with Turbulent life trajectories experienced a greater impact on Life Satisfaction than individuals with Calm life trajectories when experiencing major life events. Possible reasons were that individuals with Calm life trajectories might possess greater hedonic capital and use the flexibility mindset and flexibility sequence to deal with major life events. The implications from this study may be vital for policymakers to design appropriate interventions to help individuals cope with major life events. Bachelor of Science in Mathematical Sciences and Economics 2023-04-26T06:34:58Z 2023-04-26T06:34:58Z 2023 Final Year Project (FYP) Balakrishnan, D. (2023). The investigation of the adaptation to life events and life trajectories. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166413 https://hdl.handle.net/10356/166413 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Mathematics::Statistics
spellingShingle Science::Mathematics::Statistics
Balakrishnan, Dilip
The investigation of the adaptation to life events and life trajectories
description This study uses Machine Learning algorithms to investigate two areas of the Subjective Well-Being field - adaptation and and life trajectories. Data from the Household, Income and Labour Dynamics in Australia data set was used for analysis. When investigating adaptation and anticipation, I found that advanced supervised Machine Learning algorithms (LASSO and a combination of Fixed Effects and Random Forests) produced largely similar findings to that of Linear Regression and Fixed Effect models. My results also showed that adaptation was observed for child birth and divorce, but not for unemployment. I also discovered that men and women adapted differently to certain events. Men were not found to adapt to the death of close relatives while women were found to do so. This might have been due to psychosocial reasons. Similarly, while women were not found to adapt to marriage, men were able to adapt to marriage. Furthermore, I used several clustering algorithms, such as K-Means, and found that there were two types of life trajectories (“Calm” and “Turbulent”). The individuals who had Calm life trajectories appeared to have a higher Mean Life Satisfaction, higher Annual Trend in Life Satisfaction and lower Variability in Life Satisfaction than individuals with Turbulent life trajectories. Moreover, I uncovered that individuals with Turbulent life trajectories experienced a greater impact on Life Satisfaction than individuals with Calm life trajectories when experiencing major life events. Possible reasons were that individuals with Calm life trajectories might possess greater hedonic capital and use the flexibility mindset and flexibility sequence to deal with major life events. The implications from this study may be vital for policymakers to design appropriate interventions to help individuals cope with major life events.
author2 Fedor Duzhin
author_facet Fedor Duzhin
Balakrishnan, Dilip
format Final Year Project
author Balakrishnan, Dilip
author_sort Balakrishnan, Dilip
title The investigation of the adaptation to life events and life trajectories
title_short The investigation of the adaptation to life events and life trajectories
title_full The investigation of the adaptation to life events and life trajectories
title_fullStr The investigation of the adaptation to life events and life trajectories
title_full_unstemmed The investigation of the adaptation to life events and life trajectories
title_sort investigation of the adaptation to life events and life trajectories
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/166413
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