scholarly journals Value for Money from Public Education Expenditure on Elementary Education in India

10.1596/24954 ◽  
2016 ◽  
Author(s):  
Keyword(s):  
Public Education ◽  
Elementary Education ◽  
Value For Money ◽  
Education Expenditure ◽  
Education In India ◽  
Public Education Expenditure

Accounting for Growth Effects of Age Structure Transition through Public Education Expenditure: New Macroeconomic Evidence from India

2018 ◽  
Vol 7 (2) ◽  
pp. 174-211
Author(s):  
M. R. Narayana
Keyword(s):  
Human Capital ◽  
Public Education ◽  
Elementary Education ◽  
Age Structure ◽  
Labour Productivity ◽  
Capital Investments ◽  
Education Expenditure ◽  
Structure Transition ◽  
Growth Effects ◽  
Public Education Expenditure

This article quantifies the growth effects of age structure transition through current public education expenditure. Using the National Transfer Accounts’ (NTA) First Demographic Dividend (FDD) model, growth effects are accounted by the impact of current public education expenditure on economic support ratio (ESR) and labour productivity through human capital investments. The results offer new macroeconomic evidence. Age structure transition reduces the education dependency ratio (EDR) by all levels of education but the highest in the elementary education. This impacts on a long-term decline in enrolment in elementary education where the current gross enrolment ratio (GER) is close to 100 per cent and a decline in current public education expenditure. Other things being equal, the resultant potential savings, or the availability of extra budgetary resources, is a new way of financing the investment requirements for secondary and higher education with the aim of increasing national economic growth through human capital investments. In particular, growth effects are shown to be positive, higher and longer up to 2050, if the current public education spending is reallocated more for the secondary and higher education. Surprisingly, growth effects are explained less by the ESR than labour productivity. This justifies a higher human capital investment to enhance labour productivity for attainment of higher economic growth. The afore- mentioned macroeconomic framework, results and implications are of general relevance for other developing countries in South Asia and elsewhere in the world. JEL Classification: E65, H52, J11

scholarly journals Comparing COSTATIS and Generalized Procrustes Analysis with Multi-Way Public Education Expenditure Data

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1816
Author(s):  
María Concepción Vega-Hernández ◽  
Carmen Patino-Alonso
Keyword(s):  
Public Education ◽  
Procrustes Analysis ◽  
Public Expenditures ◽  
Education Expenditure ◽  
Advantages And Disadvantages ◽  
Generalized Procrustes Analysis ◽  
Expenditure Data ◽  
The Mean ◽  
Public Education Expenditure ◽  
Similarities And Differences

Governments serve a variety of purposes, and where governments spend their money has always been of concern to society. In particular, spending on public education is of great interest. However, the volume of this information can be difficult to manage. Therefore, the purpose of this work is to compare the COSTATIS method and generalized Procrustes analysis (GPA) when working with multi-way data. Despite the particular characteristics of each of them, they present similarities and differences that, when analyzed together, can provide complementary results to researchers. The COSTATIS consists of a co-inertia analysis of the compromise of two k-table analyses. The GPA method provides an optimal superimposed representation of individual configurations, and a common consensus configuration is constructed as the mean of all transformed configurations. In addition, the GPA method includes the translation, rotation and scaling of coordinates. In this study, both methods were applied, and the advantages and disadvantages of each are presented. The treated data are a sequence of tables from various countries where different public expenditures on education have been measured over time.

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