Forecasting replacement demand by occupation and education

Willems, E.J.T.A.; Grip, Andries de

doi:10.1016/0169-2070(93)90003-6

Cited by 23 publications

(8 citation statements)

References 7 publications

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“…The principal alternative method of calculating replacement demand has been the cohort component method. The cohort component method has been used to calculate net replacement rates in the USA (Bureau of Labor Statistics, 2006) and (Eck, 1991), The Netherlands (Willems and de Grip, 1993), Australia (Shah and Burke, 2001) and Ireland (Sexton et al , 2001). Shah and Burke state that the “detailed flow data on labour turnover that are needed to estimate net replacement demand are rarely available”.…”

Section: Estimating Replacement Demandmentioning

confidence: 99%

Estimating replacement demand: lessons from Ireland

Fox

Comerford²

2008

International Journal of Manpower

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PurposeThis paper seeks to examine the use of the cohort component method as a method of deriving replacement demand for manpower forecasting.Design/methodology/approachThe paper explains the principal concepts of replacement demand and how replacement demand has been estimated in two alternative ways: the cohort component method and using longitudinal data on individuals. The paper focuses on one of these ways, the cohort component method, and illustrates how this method can fail to capture all the relevant flows driving replacement demand. It also compares the method to the alternative approach based on individual data and discusses US and Irish results using both methods.FindingsThe cohort component method is found to underestimate replacement demand significantly in many occupations.Research limitations/implicationsResearch estimates of replacement demand should be based on individual longitudinal data rather than the cohort component method.Originality/valueMany countries undertake some form of occupational employment forecasting including, in many cases, making estimates of replacement demand. This paper should help to clarify the appropriate choice of methodology for estimating replacement demand.

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Section: Estimating Replacement Demandmentioning

confidence: 99%

Estimating replacement demand: lessons from Ireland

Fox

Comerford²

2008

International Journal of Manpower

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“…But, during the last few years, new interest in this type of manpower models seems to have gained ground. Examples of this kind of research are Willems and de Grip (1991) and Dekker et af. (1990).…”

Section: Introductionmentioning

confidence: 99%

“…(1990). These papers model sectorial demand for labour by education as a function of recent in-and out-flow of jobs with a specific education and job category (Willems and de Grip, 1991) and the share in each industry of persons with a specific occupation, education and age (Dekker et al, 1990). The crucial new thing in these models compared to old manpower models is that the input structure of labour according to education, occupation, etc.…”

Section: Introductionmentioning

confidence: 99%

A Forecast Model for Unemployment by Education

Groes¹,

Larsen²,

Tranæs

1994

Labour

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Absrracf.We present a dynamic forecast model for the labour market: demand for labour by education and the distribution of labour by education among industries are determined endogenously with overall demand by industry given exogenously. The model is derived from a simple behavioural equation based on a strong relationship between the "strength" in the struggle for jobs of an educational group, and the change in relative supply. This relationship proves to be significant in the data. Furthermore, when used to forecast employment by education on real data, the model predicts reasonably well even for educational groups, where the initial forecast year is a change point for unemployment. the jth industry (in period t), Sj(t) the supply of labour with the ith education. Dj(t) the demand for labour in the jth industry, and U,( t) = Sj( t ) -Dj( t), unemployment for the ith education. We will call the mismatch term U; unemployment, although it might take negative values. Q Fondazione Giacomo Brodolini 1994.

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“…The model is tested on real data from the EU countries. Willems and de Grip (1993) revealed that replacement demand is an important component of the future demand for manpower often neglected in manpower demand forecasts. In particular, for characterizing the prospects for newcomers on the labor market, the manpower requirements method is not adequate as it merely focuses on employment mutations.…”

Section: State-of-the-art Of Workforce Analysis: a Generic Overviewmentioning

confidence: 99%

“…Two sets of models were developed in this study. In the first set of models, the independent variable used was an estimated construction cost, and in the second set of models the estimated construction cost and project type were the 9 Willems and de Grip (1993) revealed that replacement demand is an important component of the future demand for manpower often neglected in manpower demand forecasts. In particular, for characterizing the prospects for newcomers on the labor market, the manpower requirements method is not adequate as it merely focuses on employment mutations.…”

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confidence: 99%

An Intelligent Decision Support System for Workforce Forecast

Wan¹,

Chen²,

Kuriger³

2011

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information , 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY) 05-01-2011 REPORT TYPE 7184D214 PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBERThe University of Texas at San Antonio One UTSA Circle San Antonio TX 78249 SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)Air SPONSOR/MONITOR'S REPORT NUMBER(S)AFRL-RH-WP-TR-2011-0019 DISTRIBUTION / AVAILABILITY STATEMENTDistribution A: Approved for public release; distributed is unlimited. SUPPLEMENTARY NOTES88ABW/PA cleared on 23 Feb 2011, 88ABW-2011-0727. ABSTRACTThe main objective of this project is to enhance the effectiveness of workforce forecast and deployment through innovative approaches of artificial intelligence. The research included a final document of conventional and innovative methods of workforce forecasting and a decision support software program incorporating advanced artificial intelligence techniques for workforce forecasting. SUBJECT TERMS ABSTRACTThis project studies workforce forecasting in two main aspects: (1) an extensive review of the existing methodologies and techniques and (2) an effort to develop a decision support system with models and software programming. The main objective of this project is to enhance the effectiveness of workforce forecasting and deployment through innovative approaches of artificial intelligence. The deliverables include a summary report of conventional and innovative methods of workforce forecasting (Part I) and a decision support software program using artificial intelligence techniques for workforce forecasting (Part II).Part I, provided a thorough literature review of fundamental research and practices of demand and supply forecasting techniques for workforce analysis. Over 300 relevant literatures have been identified and reviewed by the project team, and 289 of them are covered in this report.Following is a summary of the main contents and contributions of Part I:• This report provides an extensive review of the fundamental knowledge, applications, guidelines, and scope of use of various workforce forecasting methods.• A decision tree has been proposed for selecting an appropriate forecasting ...

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Forecasting replacement demand by occupation and education

Cited by 23 publications

References 7 publications

Estimating replacement demand: lessons from Ireland

Estimating replacement demand: lessons from Ireland

A Forecast Model for Unemployment by Education

An Intelligent Decision Support System for Workforce Forecast

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