A network DEA quantity and quality-orientated production model: An application to Australian university research services

The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.

A generalized stock production model

(PDF contains 83 pages.)

Economic-demographic model: a case study of Chile and Mexico

Includes bibliography

Economic-demographic model; a case study for certain Latin American countries; preliminary version

Includes bibliography

A Dynamic Stochastic Frontier Production Model with Time-Varying Efficiency

In this paper we introduce technical efficiency via the intercept that evolve over time as a AR(1) process in a stochastic frontier (SF) framework in a panel data framework. Following are the distinguishing features of the model. First, the model is dynamic in nature. Second, it can separate technical inefficiency from fixed firm-specific effects which are not part of inefficiency. Third, the model allows one to estimate technical change separate from change in technical efficiency. We propose the ML method to estimate the parameters of the model. Finally, we derive expressions to calculate/predict technical inefficiency (efficiency).

Use of multiple regression analysis to summarize and interpret linear programming shadow prices in an economic planning model /

Issued May 1980.

Stability of the Inventory-Backorder Process in the (R; S) Inventory/Production Model

2000 Mathematics Subject Classification: 60G52, 90B30.

EPQ Model with Imperfect Quality Raw Material

MSC 2010: 26A33, 33E12, 33C60, 44A20

Magyarország hét régiójának új gazdaságföldrajzi modellje – paraméterbecslés (The new economic-geography model of Hungary's seven regions - a parameter estimate)

Az új gazdaságföldrajz – amely napjaink egy igen népszerű közgazdaságtani tudományága – modelljének majdnem minden paramétere előállítható közvetlenül külső adatok segítségével. A helyettesítési rugalmassághoz azonban más módszerre van szükség. Puga [1999] által felvázolt új gazdaságföldrajzi modellt követve, egy regressziós egyenlettel megbecsülhetővé válik a kívánt paraméter, amit Magyarország hét régiójára vonatkozó béregyenlet becsléséből nyertünk. A helyettesítési rugalmasság értéke eltér a szakirodalomhoz képest, aminek magyarázata Magyarország fejlettségi szintjével állhat összefüggésben. ____ The model of the new economic geography - very popular material for economic study these days - allows almost every parameter to be presented directly with the aid of outside data. However, another method is required for substitution flexibility. With the new economic-geography model devised by Puga [1999], a regression equation allows an estimate to be made for the desired parameter, which yielded the wage equation for the six regions of Hungary. The value for substitution flexibility differs from that of the literature, the explanation for which may lie in Hungary's level of development.