Bayesian estimation of labor demand by age: theoretical consistency and an application to an input–output model

Kim, Kijin; Hewings, Geoffrey J. D.

doi:10.1080/09535314.2018.1427050

Cited by 11 publications

(11 citation statements)

References 25 publications

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“…Based on prior studies, the elasticity of labour demand can vary according to various factors, including industries heterogeneity, type of skills, type of occupational groups, wages rate and age cohort. Past studies found that elasticity of labour demand differs by age cohorts (Kim & Hewings, 2018;Manuel & Julian, 2018), industry-levels (Adam & Moutos, 2014), and differences in wage (Devesh, 2019). A study by Luis et al (2019) reveals that heterogeneity in labour demand elasticity is found among industries across regions, sectors, and plant sizes (depending on workers' skills).…”

Section: Autoregressive Distributed Lag (Ardl) -A Dynamic Labour Demand Modelmentioning

confidence: 99%

Skilled Labour Demand in the Malaysian Construction Sector

Sulaiman¹,

Ismail²,

Saukani³

et al. 2021

JSSM

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Acquiring a skilled workforce is one of the major challenges the Malaysian construction sector is facing. As the construction industry in Malaysia relies on labour, shortage of labour will hamper the industry's sustainability. By focusing on demand for high-skilled labour, i.e. professional and technical workers, this study analyses the construction sector's demand for labour according to skills in the short and long runs, and specifically the labour demand of the construction subsectors, particularly the residential building, non-residential building, civil engineering and specialised construction activities subsectors. Furthermore, using the elasticity of labour-output, labour workforce for these two categories are estimated for the years 2015 and 2020. This study uses the Malaysia Construction Industry Survey data from 1990 to 2012 of four subsectors, namely residential buildings, non-residential buildings, civil engineering and specialised construction activities. The findings show that both categories of labour demand have a relationship with its determinant in the short and long runs. However, the supply for professional workers is still lacking, and this shortage is addressed by substitution with technical workers. The need for manpower is higher for technical workers. In addition, the manpower required in 2015 and 2020 are the largest for specialised construction activities due to its larger initial stock and higher output growth.

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Section: Autoregressive Distributed Lag (Ardl) -A Dynamic Labour Demand Modelmentioning

confidence: 99%

Skilled Labour Demand in the Malaysian Construction Sector

Sulaiman¹,

Ismail²,

Saukani³

et al. 2021

JSSM

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“… Source : Kim and Hewings (2019). Note : 1) The [i,j]th entry represents a direct increase of $1 in income to group j leads to k cents in income payments to group i; 2) It is assumed that technology and relative prices of goods and labor groups do not change from 2009 on. …”

Section: Addressing Heterogeneitymentioning

confidence: 99%

“…Income multipliers for income quintiles. Source : Unpublished estimates from Kim and Hewings (2019) available by request.…”

Section: Addressing Heterogeneitymentioning

confidence: 99%

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Demo-economic Modeling: Review and Prospects

Batey

Hewings

2021

International Regional Science Review

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This paper focuses on progress in achieving greater integration between demographic and economic components in system-wide modeling. It underlines the importance of Czamanski’s Baltimore model as well as other influential research based on the two-sector economic base model, before proceeding to review more complex, spatially-disaggregated economy-wide models. The subsequent work of Ledent, Schinnar and others is presented as the foundation for some important initiatives that centered on the Batey-Madden model and its derivatives. Attention is directed to some recent advances in the Batey-Madden model and subsequent work addressing household heterogeneity in the context of income formation and distribution associated with contributions by Miyazawa. The paper explores some avenues for integration of activity analysis and household disaggregation based on income, age or skill endowments to enhance the understanding of the role that households play in the economy.

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“…This leads to "type 2" IO models where household behavior is assumed to be endogenously determined to capture these effects. By now there is a substantial literature on these issues, see Sonis and Hewings (1999), Miller and Blair (2009) and Kim and Hewings (2019). For comprehensive discussions of extended IO models, see Batey and Rose (1990) or Batey (2018).…”

Section: Introductionmentioning

confidence: 99%