Benchmarking Efficiency of Telecommunication Industries in the US and Major European Countries - A Stochastic Possibility Frontiers Approach

Erber, Georg

doi:10.2139/ssrn.1031327

Cited by 3 publications

(4 citation statements)

References 25 publications

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“…This might be attributable to the static specification of our model which cannot properly disentangle short-run from long-run effects (see e.g. Meijers, 2007, Erber, 2005. As is well known from the literature, in general it is difficult to disentangle scale economies from the rate of Harrodneutral technical progress.…”

Section: Resultsmentioning

confidence: 98%

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Nested Stochastic Possibility Frontiers with Heterogeneous Capital Inputs

Erber¹,

Madlener

2007

SSRN Journal

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This paper studies the productivity impact of heterogeneous capital inputs of selected EU-15 member countries and of the U.S. at the macroeconomic level. The stochastic possibility frontiers approach of Battese and Coelli (1992) applied here is used to identify neutralities or nonneutralities between different heterogeneous capital and labor inputs. Owing to the introduction and estimation of two-stage nested translog possibility production frontiers, the otherwise huge parameter space for the seven input factors included in the model is reduced significantly. This gives more robust estimates of the remaining parameters. Due to the detailed data, specific types of biased technological change in heterogeneous capital inputs can be tested. Furthermore, time-varying inefficiency trajectories for each country are obtainable. Annual data from 1980 to 2004, calculated and published by the Groningen Growth and Development Centre, are used in the empirical analysis. The results obtained shed new light on how fasttechnological progress in a global economy can shift comparative advantages between countries. In particular the different factor specific impacts of ICT and non-ICT capital stocks give a more detailed picture of the structural dynamics between factor inputs than do most other empirical studies using more aggregate factor input data.

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Section: Resultsmentioning

confidence: 98%

“…From previous studies with macroeconomic multi-country panel data on an industry level (cf. Erber, 2005), we know that inefficiencies can vary considerably over time.…”

Section: Models Usedmentioning

confidence: 99%

Nested Stochastic Possibility Frontiers with Heterogeneous Capital Inputs

Erber¹,

Madlener

2007

SSRN Journal

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“…If we plot the MRT between mining and manufacturing, the result would be a chart displaying the Production Possibility Frontier (PPF) for this grossly simplified two-sector economy. The PPF curve represents the maximum possible output with the available inputs (Erber 2006). The area under the PPF represents a "production possibility set".…”

Section: Technology and Productivity Frontiersmentioning

confidence: 99%

What Drives the End User to Build a Feral Information System?

Spierings

Kerr²,

Houghton³

2014

Feral Information Systems Development

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In this chapter, the authors explore a wide mixture of economic and social concepts. At first, the reader may wonder what these diverse theories have to do with Feral Information Systems (FIS). However, the research indicates that understanding how these theoretical puzzle pieces interact with each other is important to increasing the understanding of what drives the End User to create Feral Information Systems.

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“…An increase in efficiency would signal better performance, benefiting customers in the form of improved services and lower prices (Usero & Asimakopoulos, 2013;Madden & Savage, 2001a). Crosscountry studies (e.g., Erber, 2005;Gokgoz & Demir, 2014;Torres & Bachiller, 2013) and single country studies (e.g., Lee, Park, & Oh, 2000;Moreno, Lozano, & Gutierrez, 2013;Uri, 2006) focus largely on the industry and firm level efficiency and productivity in developed countries. The few studies on emerging countries with middle incomes are country specific (e.g., Resende & Facanha, 2002;Sharma, Momaya & Manohar, 2010) or regional in focus (e.g., Cabanda, Ariff & Viverita, 2004;Moshi, Mwakatumbula & Mitomo, 2013;Torres & Bachiller, 2013).…”

Section: Introductionmentioning

confidence: 99%

Telecommunications industry efficiency: A comparative analysis of high and middle income countries

Oredegbe

Zhang

2020

Telecommunications Policy

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This study evaluates telecommunications industry efficiency in 19 countries grouped into high income countries (HICs) and middle income countries (MICs). Using data from 2001-2013 and a two-stage Data Envelopment Analysis (DEA), it finds that while HICs outperformed MICs, both of the groups exhibited improved technical efficiency, managerial effectiveness, and operational scale. Additionally, time in deregulation enhances technical and scale efficiency in HICs, however, the influence is insignificant in MICs. Labour productivity drives technical efficiency in HICs. Also, it augments managerial resourcefulness in HICs and MICs, however, its influence on scale efficiency is immaterial. Revenue per subscription enhance technical efficiency and managerial effectiveness in the two groups of countries. The relationship with scale efficiency, which is positive in HICs is irrelevant in MICs. Capital intensity has insignificant influence on managerial effectiveness in the two clusters of countries, however, it undermines technical efficiency in HICs and scale efficiency in MICs. Gross national income per capita is inconsequential to scale enhancement. However, it contributes to technical efficiency in the two categories of countries and managerial performance in HICs. Efficiency performances in HICs and MICs are insensitive to the industry's concentration level. Inflation has insignificant influence on scale efficiency in HICs and MICs. Also, it drives technical efficiency and managerial performance in MICs, but the influence in HICs is immaterial. The joint impact of labour productivity and capital intensity is irrelevant to operational scale in HICs and MICs, however, it is negatively associated with technical efficiency and managerial effectiveness in MICs. This empirical study provides additional insight that managers in the industry and policy makers will find useful during strategy formulation and policy deliberations.

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Benchmarking Efficiency of Telecommunication Industries in the US and Major European Countries - A Stochastic Possibility Frontiers Approach

Cited by 3 publications

References 25 publications

Nested Stochastic Possibility Frontiers with Heterogeneous Capital Inputs

Nested Stochastic Possibility Frontiers with Heterogeneous Capital Inputs

What Drives the End User to Build a Feral Information System?

Telecommunications industry efficiency: A comparative analysis of high and middle income countries

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