Higher education costs and scale and scope economies

Sav, G. Thomas

doi:10.1080/0003684042000217643

Cited by 49 publications

(26 citation statements)

References 6 publications

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“…With all the t-ratios well above two, the coefficients are highly significant in the public college sector. As experienced in other research (e.g., Cohn et al, 1989;Koshal & Koshal, 1999;Sav, 2004;Lenton, 2008), it is not surprising that the same models do not perform as well in capturing the underlying cost structure of private institutions. Also, in the for-profit sector, 96 % of the institutions did not employ nine month faculty; hence the variable is dropped from that sector.…”

Section: Empirical Estimatesmentioning

confidence: 71%

For-Profit College Entry and Cost Efficiency: Stochastic Frontier Estimates vs Two-Year Public and Non-Profit Colleges

Sav¹

2012

IBR

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This paper provides stochastic frontier cost and (in)efficiency estimates for private for-profit colleges with comparisons to public and private non-private colleges. The focus is on the two-year U.S. higher education sector where there exists the largest and fastest growing entry of for-profit colleges. Unbalanced panel data is employed for four academic years, [2005][2006][2007][2008][2009]. Translog cost frontiers are estimated with an inefficiency component that depends upon environmental factors defined by college specific characteristics. More experienced public and private non-profit colleges are found to be more cost efficient relative to the newer entrants. In addition, the newer for-profits exhibit greater efficiency variability but also show some evidence of efficiency gains over the academic years. There is some cursory evidence that for-profit entry is positively correlated, albeit weakly, with greater public college sector inefficiency.

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Section: Empirical Estimatesmentioning

confidence: 71%

For-Profit College Entry and Cost Efficiency: Stochastic Frontier Estimates vs Two-Year Public and Non-Profit Colleges

Sav¹

2012

IBR

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“…1995; Koshal et al, 2001;Laband & Lentz, 2003;Sav, 2004;Cesar, 2006;Hou et al, 2009), with only a few exceptions adopting CES (Johnes, 1997;Izadi et al, 2002) and hybrid translog cost function (de Groot et al, 1991;Glass et al, 1995;Nelson & Hevert, 1992;Stevens, 2005), while in more recent literature SFA (stochastic frontier analysis) has been adopted (Johnes, 1996;Izadi et al, 2002;Stevens, 2005;Johnes et al, 2008).…”

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confidence: 99%

Economies of scope in distance education: The case of Chinese research universities

Chen

2012

IRRODL

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<span>With the rapid development of information technologies, distance education has become “another form of product differentiation in the output mix produced by the multi-product university or college” (Cohn & Cooper, 2004, p. 607). This article aims at analyzing the economies of scope of distance education (as an educational output) in Chinese research universities. The empirical results show that a) product-specific economies of scope do exist in distance education programs offered by Chinese research universities; b) there are economies of scale in distance education; and c) there are weak cost complementarities between distance education and research output, meaning that distance education and academic research can promote each other to reduce the costs in Chinese research universities.</span><br /><input id="gwProxy" type="hidden" /><input id="jsProxy" onclick="if(typeof(jsCall)=='function'){jsCall();}else{setTimeout('jsCall()',500);}" type="hidden" />

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“…This is the measure used by other higher education cost studies that have employed IPEDS as the data source (Cohn et al, 1989;Koshal and Koshal, 1999;Sav, 2004;Lenton, 2008). The successes of past studies have also led to a general acceptance of variables that can reasonably proxy university outputs and input prices, including those listed in Table 1 for Undergraduate education output (U), Graduate education output (G), Research output (R) and the faculty Wage (W) as an input price.…”

Section: Methodsmentioning

confidence: 99%

Cost Efficiencies and Rankings of Flagship Universities

Sav¹

2011

American Journal of Economics and Business Administration

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Problem statement: Each state in the U.S. touts a premier university as the flagship of its publicly funded higher education system. With decreased government budgets and increased interest in public management reforms, these institutions are being pressured to provide evidence of and set examples for ever greater improvements in operating cost efficiencies. The problem, however, is that empirical measures of their efficiencies or inefficiencies can be sensitive and, therefore, vary widely depending upon the underlying model specification. Approach: The study used stochastic frontier analysis to estimate university cost inefficiencies over the 2005-09 academic years. Transom and Cobb-Douglas specifications were combined with two inefficiency models that treated university environmental factors as inefficiency determinants and as cost determinants. University inefficiency rankings were provided on the basis of mean scores and compared to the rankings obtained under the alternative models. Results: University mean inefficiency scores were estimated to vary between 1.19 and 1.32, indicating that costs were on average between 19 and 32% above the minimum frontier costs. At the individual university level, inefficiencies ranged from 1.015-2.43. Two specifications indicate that efficiency improvements occurred in the 2008-09 academic year. A university ranking of mean scores indicated an 87% difference between the most and least inefficient university. There was substantial sensitivity of rankings to model choice, but university rank status was found to be most unstable in the middle of the ranking distribution. Conclusion: The findings offer caution in proceeding to stochastic frontier estimates of inefficiencies without careful consideration and investigation of the sensitivities of such estimates to model choices. This study showed that advice is applicable, at least, to inefficiency estimates of U.S. flagship universities. Whether or not it is applies equally to other groups of universities is a matter of consideration for future studies.

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Higher education costs and scale and scope economies

Cited by 49 publications

References 6 publications

For-Profit College Entry and Cost Efficiency: Stochastic Frontier Estimates vs Two-Year Public and Non-Profit Colleges

For-Profit College Entry and Cost Efficiency: Stochastic Frontier Estimates vs Two-Year Public and Non-Profit Colleges

Economies of scope in distance education: The case of Chinese research universities

Cost Efficiencies and Rankings of Flagship Universities

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