Occupational Differences in the Return on Human Capital in the Spanish Travel Agency and Hospitality Industries

2011 ◽  
Vol 17 (6) ◽  
pp. 1325-1345 ◽  
Author(s):  
Alejandro García Pozo ◽  
Andrés J. Marchante Mera ◽  
José Luis Sánchez Ollero
Keyword(s):  
Human Capital ◽  
Relative Weight ◽  
Travel Agency ◽  
Rates Of Return ◽  
Services Sector ◽  
Occupational Differences ◽  
Rate Of Returns

This study analyses the returns on human capital in the Spanish hospitality and travel agency industries across seven occupational categories by gender. It is motivated by evidence that there is great variation between jobs in this sector and that estimations of the rate of returns for each component of human capital for the entire sector may not be accurate. The main results indicate that the rates of return on human capital are lower in these industries for most occupations than in the private services sector. Given that differences in the returns on human capital components across occupational categories are statistically significant and large, then the relative weight of each segment within the aggregate may explain the results obtained in previous studies.

scholarly journals Kuznets meets Lucas: structural change and human capital

2018 ◽  
Vol 71 (4) ◽  
pp. 848-873
Author(s):  
Edgar Cruz
Keyword(s):  
Human Capital ◽  
Structural Change ◽  
Capital Accumulation ◽  
Human Capital Accumulation ◽  
Relative Prices ◽  
Services Sector ◽  
Us Economy ◽  
The Us ◽  
Balanced Growth Path ◽  
Cross Country

Abstract This paper develops a multi-sector growth model with human capital accumulation. In this model, human capital induces structural change through two channels: changes in relative prices and changes in the investment rate of physical and human capital. We show that the specifications of the model give rise to a generalized balanced growth path (GBGP). Furthermore, We show that the model is consistent with (i) the decline in agriculture, (ii) the hump-shaped of manufacturing, (iii) the rise of the services sector, and (iv) the path of human capital accumulation in the US economy during the 20th century. Given the findings, We outline that imbalances between physical and human capital contribute to explain cross-country differences in the pace of structural change.

scholarly journals DETERMINANT RETURN TO EDUCATION IN INDONESIA

2018 ◽  
Vol 17 (1) ◽  
pp. 52 ◽  
Author(s):  
Mukhamad Azhar ◽  
S. Suwatno ◽  
Amir Mahmud
Keyword(s):  
Human Capital ◽  
Human Resources ◽  
School Enrollment ◽  
Return To Education ◽  
Learning Session ◽  
Rates Of Return ◽  
Developed Country ◽  
Returns To Schooling ◽  
Return To Schooling ◽  
Less Developed Country

Badan Pusat Statistik. (2016). Penduduk Berumur 15 Tahun ke Atas yang Bekerja Selama Seminggu yang Lalu Menurut Lapangan Pekerjaan Utama dan Pendidikan Tertinggi yang Ditamatkan. Jakarta: Badan Pusat Statistik.Badan Pusat Statistik.(2016). Keadan Angkatan Kerja Provinsi Banten Agustus 2016. BPS Banten.Becker, Gary S. (1975). Human Capital, A Theoretical and Empirical Analysis with Special Reference to Education, 2nd Edition. Diakses dari http://www.nber.org/Deolalikar, Anil. (1993). Gender Differences in the Returns to Schooling and in School Enrollment Rates in Indonesia. Journal of Human Resources. 28 (4), 899-932[Friedman, Howard S., Schustack, Miriam W. (2008). Kepzribadian Teori Klasik dan Riset Modern. Jakarta: Penerbit Erlangga.Heckman, James J., Lochner, Lance J., dan Todd, Petra E. (2003) Fifty Years of Mincer Earnings aKrueger, Alan B., and Lindahl, Mikael. (2000). Education for Growth: Why and For Whom?. Working Paper No. 7591.Megasari,  Diah Nurulia, (2014). Analisis Tingkat Pengembalian Investasi Pendidikan Antara Laki-Laki Dan Perempuan Di Provinsi Jawa Barat Tahun 2014. Universitas Negeri YogyakartaOECD Stat. Extract. Dzaiakses dari: http://stats.oecd.org, pada 1 April 2015.OECD. (2000). Estimating Economic and Social Returns to Learning: Session 3 Issues for Discussion.Perkins, D.H, Radelet, S, Snograss, R.R, Gillis, M, and Roemer, M. 2001. Economics of Development.WW. Norton & Company, Inc. United States of America.Psacharopoulos, G. 1985. “Returns to education: A further international update andimplication”. The Journal of Human Resources, 20 (4), 583-597.Psacharopoulos, George 1994 “Returns to Investment in Education: A Global Update”.World development vol. 22 no. 9 pp 1325-43.Psacharopoulos, George. (1993). Return to Investment in Education: A Global    Update.               Diaksesdari:             http://www- wds.worldbank.org/servlet, pada 10 Agustus 2015.Psacharopoulos, George. (2006). The Value of Investment in Education: Theory, Evidence, and Policy. Journal of Education Finance. 32(2), 113-136.Purnastuti, L., dkk. (2011). Economic Return to Schooling in a Less Developed Country: Evidence for Indonesia. Diakses dari: http://kastoria.teikoz.gr/icoae2/, pada 20 Desember 2014.Purnastuti, L., dkk. (2015). Analisis Tingkat Pengembalian Investasi Pendidikan di Daerah Istimewa Yogyakarta. Prosiding Seminar Nasional 9 Mei 2015. Hlm. 797-806Purnastuti, L., Miller, P., dan Salim, R. (2013). Decilining Rates of Return to evidence for Indonesia. Bulletin of Indonesia Economic Studies.49(2), 213-236.Purnastuti, Losina., Miller, Paul., and Salim, Ruhul (2012). Economic Returns to Schooling in A Less Developed Country: Evidence for Indonesia. Journal of European Economy. Vol. 11. Sepecial Issue.Purnastuti, Losina., Miller, Paul., and Salim, Ruhul (2013). Declining rates of return to education: evidence for Indonesia, Bulletin of Indonesian Economic Studies.Schultz, Theodore, W (1961). Investment in Human Capital. Diakses dari: www.ssc.wisc.edu, pada 23 Februari 2015.

Paginas Amarelas

2017 ◽  
pp. 1-26
Author(s):  
Robert F. Bruner ◽  
Mario Wanderley
Keyword(s):  
Risk Premium ◽  
Cash Flows ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Rates Of Return ◽  
Asset Pricing Model ◽  
Telephone Directory ◽  
Rate Of Returns ◽  
Student Discussion

This case serves as a foundation for student discussion of the estimation of required rates of return (ROR) on investments in emerging markets. An associate in J.P. Morgan's Latin America M&A department (mergers and acquisitions) is assigned the task of valuing the telephone directory operations (“paginas amarelas” means “yellow pages”) of a large Brazilian conglomerate. All cash flows have been converted to U.S. dollars, and present values computed for various discount rates. The remaining step is to determine the appropriate target rate of returns for dollar flows originating in Argentina, Brazil, and Chile. The capital asset pricing model (CAPM) is used along with a political risk premium and country beta. The necessary figure work is comparatively light, leaving the student time to reflect on the need for various adjustments in estimating crossborder rates of return.

SERVICES SECTOR ROLE IN THE DEVELOPMENT OF HUMAN CAPITAL IN RURAL AREAS

2019 ◽  
Vol 3 (62) ◽  
pp. 132-138
Author(s):  
Serik M. Kusmagambetov ◽  
◽  
Elena S. Kusmagambetova ◽  
Keyword(s):  
Human Capital ◽  
Rural Areas ◽  
Services Sector

scholarly journals Associations of Linear Growth and Relative Weight Gain in Early Life with Human Capital at 30 Years of Age

2017 ◽  
Vol 182 ◽  
pp. 85-91.e3 ◽  
Author(s):  
Bernardo Lessa Horta ◽  
Cesar G. Victora ◽  
Christian Loret de Mola ◽  
Luciana Quevedo ◽  
Ricardo Tavares Pinheiro ◽  
...  
Keyword(s):  
Human Capital ◽  
Weight Gain ◽  
Early Life ◽  
Linear Growth ◽  
Relative Weight

scholarly journals Human Capital and the Wealth of Nations

2014 ◽  
Vol 104 (9) ◽  
pp. 2736-2762 ◽  
Author(s):  
Rodolfo E. Manuelli ◽  
Ananth Seshadri
Keyword(s):  
Human Capital ◽  
Demographic Variables ◽  
Factor Productivity ◽  
Rates Of Return ◽  
Capital Theory ◽  
Country Differences ◽  
Cross Country ◽  
Wealth Of Nations

We reevaluate the role of human capital in determining the wealth of nations. We use standard human capital theory to estimate stocks of human capital and allow the quality of human capital to vary across countries. Our model can explain differences in schooling and earnings profiles and, consequently, estimates of Mincerian rates of return across countries. We find that effective human capital per worker varies substantially across countries. Cross-country differences in Total Factor Productivity (TFP) are significantly smaller than found in previous studies. Our model implies that output per worker is highly responsive to changes in TFP and demographic variables. (JEL E23, I25, J24, J31, O47)

scholarly journals Patterns of growth in childhood in relation to adult schooling attainment and IQ in 6 birth cohorts in low and middle-income countries: evidence from COHORTS

2020 ◽  
Author(s):  
Natalia E Poveda ◽  
Fernando P Hartwig ◽  
Cesar G Victora ◽  
Linda S Adair ◽  
Fernando C Barros ◽  
...  
Keyword(s):  
Human Capital ◽  
Early Childhood ◽  
Early Life ◽  
Linear Growth ◽  
Relative Weight ◽  
Childhood And Adolescence ◽  
Birth Cohorts ◽  
Middle Income ◽  
Middle Income Countries ◽  
School Attainment

SummaryBackgroundGrowth faltering has been associated with poor intellectual performance. The relative strengths of associations between growth in early and in later childhood remain underexplored. We examined the association between growth in childhood and adolescence and adult human capital in five low- or middle-income countries (LMICs).MethodsWe analyzed data from six prospective birth cohorts of five LMICs (Brazil, Guatemala, India, the Philippines, and South Africa). We assessed the associations of measures of height and relative weight at four ages (birth, at around age 2 years, mid-childhood (MC), adulthood), with two dimension of adult human capital (schooling attainment and IQ).FindingsIn site- and sex-pooled analyses, size at birth and linear growth from birth to around 2 years of age were positively associated with schooling attainment and adult IQ. Linear growth from age 2 years to MC and from MC to adulthood was not associated with higher school attainment or IQ. Change in relative weight in early childhood was not associated with either outcome. Relative weight in MC and in adulthood were inversely associated with schooling attainment but were not associated with adult IQ.InterpretationLinear growth in the first 1,000 days is a predictor of schooling attainment and IQ in adulthood in LMICs. Linear growth in later periods was not associated with either of these outcomes. Changes in relative weight had inconsistent association with schooling and IQ in adulthood.FundingBill and Melinda Gates Foundation (OPP1164115)Research in contextEvidence before this studyEarly life growth faltering has been associated with poor cognitive and intellectual performance in childhood and poorer schooling outcomes in children and adults. There is a paucity of data about how growth in specific age intervals over the course of childhood and adolescence relates to attained schooling and adult cognitive performance.We conducted a literature search using the terms (growth [Title/Abstract]) AND ((school [Title/Abstract] OR schooling [Title/Abstract]) AND (intelligence [Title/Abstract] OR IQ [Title/Abstract]) OR (human capital [Title/Abstract]) in Pubmed. The search yielded 536 publications from 1965 to 2020. We screened titles and selected 31 publications that included linear growth and our outcomes of interest, namely school attainment and intelligence quotient (IQ). Additionally, we checked reference lists of selected articles and identified eleven papers that were not displayed in the initial electronic query. We therefore reviewed 42 abstracts and identified 24 unique studies conducted in low and middle-income countries (LMICs). Fourteen of them investigated the association of birth size and/or early-life size with schooling or IQ, or with both outcomes during childhood. Three studies investigated the association between linear growth in early childhood and schooling and intelligence in adults, one studied the association between early-life undernutrition and IQ in early adulthood and another six publications investigated the association between growth and school attainment in adults. Economists have also studied the relationship between stunting or linear growth and schooling in LMICs, but to our knowledge not the relative importance of growth during specific age intervals.Added value of this studyThis is an analysis of the associations between child and adolescent growth and two dimensions of human capital (schooling attainment and IQ) in adulthood in six birth cohorts from five LMICs. The evidence of long-term associations of linear growth with adult IQ is scarce and the few published studies have analyzed data from a single country. In the present study, we found that size at birth and linear growth from birth to around 2 years of age were positively associated with both schooling and IQ in adulthood. Linear growth between early and mid-childhood (MC)was not associated with higher school attainment or IQ in adjusted models. Linear growth from MC to adulthood was not associated with IQ in men or women, and was inversely associated with schooling attainment in women only. Change in relative weight in early childhood was positively associated with schooling attainment only in minimally adjusted models. Relative weight measures in MC and adulthood were inversely associated with schooling attainment. Change in relative weight between MC and adulthood was not associated with adult IQ.Implications of all the available evidenceWe confirmed in multiple cohorts that birth size and linear growth from birth to age 2 years are predictors of schooling attainment and adult IQ. Linear growth in early life was the strongest predictor of these two human capital dimensions in adulthood among individuals in LMICs. We did not find evidence that supports the notion that linear growth in adolescence contributes to a better cognitive performance in adulthood. Thus, our results inform the more effective timing of nutritional and other interventions to improve linear growth and human capital in the long-term.

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