Preliminary testing of the Cobb–Douglas production function and related inferential issues

Kleyn, Judy; Arashi, Mohammad; Bekker, Andriëtte; Millard, Sollie M.

doi:10.1080/03610918.2014.968724

Cited by 27 publications

(15 citation statements)

References 41 publications

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“…The Cobb-Douglas production function is applied to the study of production functions, both in a specific business sector and in a sector of the national economy, for the study of the elasticity and substitution of productive factors, which in the classical economy are work, capital, land and production technology. It has been applied to different sectors such as agriculture, as the paper by Rebollar-Rebollar et al [ 28 ] related to milk production or manufacturing, like Smirnov and Wang studying the volume of production in US manufacturing to calculate the elasticity of labor and capital [ 33 ] or the same approach for the South African manufacturing production [ 18 ]. Likewise, it is used to calculate the cost functions of productive factors in different economic sectors [ 22 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Using flexible regression models for calculating hospital’s production functions

Reyes-Santías

Cordova-Arevalo

2020

BMC Health Serv Res

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Background The relative lack of flexibility of parametric models has led to the development of nonparametric regression techniques based on the family of generalized additive models. However, despite the potential advantages of using Generalized Additive Model (GAM) in practice many models have, until now, not been sufficiently explored in health economics problems. It could be interesting to calculate a new flexible hospital production function by means of a GAM including interactions and to compare it with the classic model Cobb-Douglas in the prediction of the behavior of productive factors. Method The flexible model considered has been the AM including the beds-facultative interaction. The covariates “Hospital”, being a categorical variable and “Year” being a continuous variable, have also been included in the model. Based on the estimation of the model penalized thin plate splines will be used to represent smoothed functions. In this configuration, the smoothed parameters will be estimated via REML. Results Cobb-douglas model fits well for the production functions of the more general clinical and surgical services, while the GAM adjusts better in the case of more specialized medical services. Conclusions Generalized Additive Models are more flexible than parametric models, providing a better fit in the presence of non-linear relationships and thus allowing more accurate prediction values. The results of this study suggest that AM is a promising technique for the areas of research and application in health economics.

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Section: Introductionmentioning

confidence: 99%

Using flexible regression models for calculating hospital’s production functions

Reyes-Santías

Cordova-Arevalo

2020

BMC Health Serv Res

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“…A is monotonically increasing with respect to U and decreasing with p. The choice of this particular acceptance-probability function is related to the Cobb-Douglas demand curves [27,28] widely used in economics. Fig.…”

Section: End-usermentioning

confidence: 99%

Tax optimization in an agent-based model of real-time spectrum secondary market

et al. 2016

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The wireless communication industry is an essential sector boosting economic progress worldwide. The structure of the legacy wireless communication market, characterised by static licensing schemes, is moving towards real-time secondary spectrum markets. While the technological body of spectrum trading has been discussed in detail, from an economic perspectives there are still a lot of gaps in understanding how these transactions affect the economy of future communication standards. A challenging aspect of the real-time spectrum market deployment is the implementation of the appropriate tax system that impacts the market structure. With regards to this, we aim to build an agentbased model of the real-time secondary spectrum market in which various taxes including value-added tax, corporate tax, consumption tax and fixed tax, are employed. The relations between selected tax type rates and the hypothetical revenue of the national regulator is established using Laffer curves. The results of the analysis confirm the existence of a tax distortion, i.e. a system deviation from the efficient system functioning affected by the tax introduction. To mea-B Peter Drotár sure the complexity of the tax strategies and the emergent tax distortion, an original approach based on Euclidean metrics defined over a vector space of the system performance indicators was proposed. This approach was later applied in parallel with the traditional Harberger's triangle methodology. We found that the constrained optimisation with the tax distortion restrictions provide satisfactory results regarding the stability of the tax distortion measure. Therefore, we propose the application of the most effective corporate tax optimisation complemented by selected additional tax types.

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“…It is also known as Cobb-Douglas functional form. It is the most worldwide functional form in both theoretical and empirical analysis of production growth (Kleyn, Arashi, Bekker, & Millard, 2017). The Cobb-Douglas function is suitable to work in term of factor prices and cost rather than factor inputs and outputs.…”

Section: Cobb-douglas Functionmentioning

confidence: 99%

Measuring Technical Efficiency of Hospitals Using Data Envelopment Analysis: A Review

Aldabahi.¹,

Am²,

Juni

2018

IJPHCS

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Background: Efficiency measurement has been of great interest as organizations attempt to improve their efficiency and productivity. Most worked were emphasised on efficiency measurement in hospitals. Focus were on hospitals to established and compared their relative productivity, considering the need to effectively utilize scarce resources available within them. DEA is one of measurement tool commonly used in hospital efficiency study. DEA requires some model specification when use to examine technical efficiency of the hospital. This manuscript aim was to identify the model specification of DEA commonly used in measuring the technical efficiency of hospital. Materials and Methods:Three databases, namely PubMed, CIHAHL and ScienceDirect were used for searching articles from 2013 to 2018. The search technique will involve the use of key words, "hospital", "hospital inputs", "technical efficiency", "hospital efficiency", "hospital outputs", together with the "data envelopment analysis or DEA. Searching and screening were based on PRISAMA procedure.Result: Twenty articles had extracted as a final result of the systematic review process. The number of DMUs was ranged between 9 and 322. Studies were varies in term on DEA model specification, and some studies were similar with other studies in regard to components of DEA model specification. Conclusion:The DEA model specification has an ability to be customized based on researcher preferences and the objective of the study in order to measure hospital technical efficiency.

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Preliminary testing of the Cobb–Douglas production function and related inferential issues

Cited by 27 publications

References 41 publications

Using flexible regression models for calculating hospital’s production functions

Using flexible regression models for calculating hospital’s production functions

Tax optimization in an agent-based model of real-time spectrum secondary market

Measuring Technical Efficiency of Hospitals Using Data Envelopment Analysis: A Review

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