2016
DOI: 10.1016/j.jeoa.2016.09.002
|View full text |Cite
|
Sign up to set email alerts
|

Decomposing economic gains from population age structure transition in the Philippines

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
12
0
1

Year Published

2017
2017
2022
2022

Publication Types

Select...
3
3

Relationship

3
3

Authors

Journals

citations
Cited by 10 publications
(13 citation statements)
references
References 23 publications
0
12
0
1
Order By: Relevance
“…In this naïve simulation, we assume that the labor income age profile is directly linked to the schedule of human capital investments, such that increasing human capital spending in some class to match the higher spending in some class leads to class individuals earning labor income at the same schedule as class workers. We apply this model using recent subnational Philippines NTA estimates calculated for terciles of household income by residence location (Abrigo et al 2016). This application takes advantage of the increasing availability of subnational NTA estimates, and is in line with recent work which simulates the economic impact of counterfactual economic lifecycle schedules on specific subpopulations (Mejia-Guevara 2014; and Miller, Saad, and Martinez 2016).…”
Section: B Modelmentioning
confidence: 95%
See 1 more Smart Citation
“…In this naïve simulation, we assume that the labor income age profile is directly linked to the schedule of human capital investments, such that increasing human capital spending in some class to match the higher spending in some class leads to class individuals earning labor income at the same schedule as class workers. We apply this model using recent subnational Philippines NTA estimates calculated for terciles of household income by residence location (Abrigo et al 2016). This application takes advantage of the increasing availability of subnational NTA estimates, and is in line with recent work which simulates the economic impact of counterfactual economic lifecycle schedules on specific subpopulations (Mejia-Guevara 2014; and Miller, Saad, and Martinez 2016).…”
Section: B Modelmentioning
confidence: 95%
“…Philippines, 1991Philippines, , 1999Philippines, , and 2011 Note: The right-most estimate for each group refers to the 1991 estimate, the middle to the 1999 estimate, and the left-most to the 2011 estimate. Source: Authors' calculation based on data from Abrigo et al (2016).…”
Section: Empirical Evidence From the Philippines Case Studymentioning
confidence: 99%
“…In this naïve simulation, we assume that the labor income age profile is directly linked to the schedule of human capital investments, such that increasing human capital spending in some class to match the higher spending in some class leads to class individuals earning labor income at the same schedule as class workers. We apply this model using recent subnational Philippines NTA estimates calculated for terciles of household income by residence location (Abrigo et al 2016). This application takes advantage of the increasing availability of subnational NTA estimates, and is in line with recent work which simulates the economic impact of counterfactual economic lifecycle schedules on specific subpopulations (Mejia-Guevara 2014;and Miller, Saad, and Martinez 2016).…”
Section: B Modelmentioning
confidence: 99%
“…Although, authors' approaches to the consequences of population ageing varied, there is presumably a general agreement that the ageing of the population will affect size and structure of the labour supply (Boersch-Supan, 2001; Kurkó, 2010;Toossi, 2012;Fuch, 2014;Fields, Uppal & LaRochelle-Côté, 2017). The vast majority of the previous research analyse population age structure and/or ageing impact on economic growth in general (Fougѐre & Mѐrette, 1999;Prettner, 2013;Orlická, 2015;Abrigo, Racelis, Ian Salas & Herrin, 2016;Maestas, Mullen & Powell, 2016, Kasnauskienė & Andriuškaitė, 2017, labour productivity (Boersch-Supan, 2001;Vandenberghe & Waltenberg, 2010;Maestas et al, 2016), unemployment (Akanni & Čepar, 2015;Kasnauskienė & Andriuškaitė, 2017), wage level or labour cost (Boersch-Supan, 2001;Vandenberghe & Waltenberg, 2010), income tax revenues and social security contributions (Dolls, Doorley, Schneider & Sommer, 2014;Orlická, 2015;Prammer, 2018); changes of public expenditures (Balassone et al, 2011;Lisenkova, Mérette & Wright, 2013;Orlická, 2015;European Commission, 2018), saving (Kasnauskienė & Andriuškaitė, 2017) and consumption (Estrada, Park and Ramayandi, 2011;Stoever, 2012;Mao & Xu, 2014;Kasnauskienė & Andriuškaitė, 2017, Addessi, 2018. However, almost all these effects occur through changes in the labour market.…”
Section: Introductionmentioning
confidence: 99%