Finn Førsund

• Finn Førsund, "Good modelling of bad outputs: Pollution and multiple-output production," International Review of Environmental and Resource Economics 3, 2009, 1-38
• Førsund FR, Kittelsen SAC and Krivonozhko VE, "Farrel revisited - Visualizing properties of DEA production frontiers," Journal of Operational Research Society 60, 2009, 1535-1545
• Podinovski VV, Førsund FR and Krivonozhko VE, "A simple derivation of scale elasticity in data envelopment analysis," European Journal of Operational Research 197, 2009, 149-153
• Edvardsen DV, Førsund FR and Kittelsen SAC, "Far out or alone in the crowd: A taxonomy of peers in DEA," Journal of productivity analysis 29(3), 2008, 201-210
• Singh B, Førsund FR, Jensen T and Larsen C, "Phasing in wind-power in Norway: network congestion and crowding-out of hydropower," Energy Policy 36(9), 2008, 3514-3520
• Finn Førsund, "Hydropower Economics,"Springer Science+Business Media LLC ,ISBN 978-0-387-73026-4. 261, 2007
• Finn Førsund, Lennart Hjalmarsson, Vladimir E. Krivonozhko, Oleg B. Utkin, "Calculation of scale elasticities in DEA models: direct and indirect approaches,"Journal of Productivity Analysis 28(1-2), 2007, 45-56
• Finn Førsund and Roberto Zanola, "The art of benchmarking: Picasso prints and auction house performance," Applied Economics 38, 2006, 1425-1434
• Finn Førsund and Roberto Zanola, "DEA meets Picasso: The impact of auction houses on the hammer price," Annals of Operations Research 145(1), 2006, 149-165
• Finn Førsund, Sverre A.C Kittelsen, Frode Lindseth and Dag Fjeld Edvardsen, "The tax man cometh-but is he efficient?," National Institute Economic Review 197(1), 2006, 106-119

• Krivonozhko, V.E.; Afanasiev, A.P.; Førsund, Finn R & Lychev, A.V. (2022). Comparison of Different Methods for Estimation of Returns to Scale in Nonradial Data Envelopment Analysis Models. Automation and remote control. ISSN 0005-1179. 83(7), s. 1136–1148. doi: 10.1134/S0005117922070098. Vis sammendrag

  The data envelopment analysis (DEA) approach has been actively developed in recent years and is used to analyze the activities of complex production units (regions, financial institutions, industrial enterprises, etc.). An important role in such an analysis is played by the calculation of various indicators of the activity of units: returns to scale, efficiency scores, marginal rates of substitution, transformations, etc. Dependences between variables in the DEA models are not explicitly specified; therefore, special optimization models are used to calculate these indicators. Much attention is given in the scientific literature to the estimation of returns to scale. This paper describes and compares some of the best known methods for calculating returns to scale. Computational experiments show that under certain conditions, the approach proposed by the authors has advantages over other methods.

• Førsund, Finn R (2021). Performance measurement and joint production of intended and unintended outputs . Journal of Productivity Analysis. ISSN 0895-562X. 55(3), s. 157–175. doi: 10.1007/s11123-021-00599-9. Fulltekst i vitenarkiv
• Podinovski, Victor V & Førsund, Finn R (2020). Scale elasticity and returns to scale. I Ray, Subhash C.; Chambers, Robert & Kumbhakar, Subal (Red.), Handbook of Production Economics (2020). Springer Nature. ISSN 978-981-10-3450-3. doi: https:/doi.org/10.1007/978-981-10-3450-3_23-1.
• Rødseth, Kenneth Løvold; Wangsness, Paal Brevik; Schøyen, Halvor & Førsund, Finn R (2019). Port efficiency and emissions from ships at berth: application to the Norwegian port sector. Maritime Economics & Logistics. ISSN 1479-2931. 22, s. 585–609. doi: 10.1057/s41278-019-00146-2. Fulltekst i vitenarkiv Vis sammendrag

  This paper explores how port efficiency affects the time that ships spend in port and therefore their atmospheric emissions whilst berthed. While the literature on port productivity and efficiency measurement largely ignores this aspect, we explore the biases in the measurement of productivity when resources spent on providing swift cargo-handling are ignored. A distinction is made between ports’ technical and scale efficiencies. Their impacts on environmental productivity (i.e., units of cargo handled per unit of ship emissions) are examined using data envelopment analysis on a unique dataset containing information about the duration of cargo-handling operations in the 25 largest ports in Norway. The results show that adopting best practices can significantly improve environmental productivities: if all ports under consideration become technically productive, the environmental productivity of the entire sample could be 80% higher. Technical efficiency alone would increase average environmental port productivity by 30%. Enhancing traditional port productivity can also substantially improve environmental productivity.

• Førsund, Finn R & Wang, Ke (2019). Measures of industry productivity change: the case of thermal electricity generation in Chinese provinces 2000–2014. Journal of Productivity Analysis. ISSN 0895-562X. 53(1), s. 37–52. doi: 10.1007/s11123-019-00556-7. Vis sammendrag

  The typical textbook production theory for a single production unit, assuming substitution possibilities both ex ante and ex post between all factors of production, may not be so well suited for understanding structural change within industries characterised by embodied technical change and a significant presence of capital equipment that represents sunk cost. In the literature an industry function is often based on just aggregating micro-level data to the industry level, or scaling up an average production function, using at times quite sophisticated econometric techniques to estimate a parametric production function. However, entry and exit of plants, and embodied technological change at the micro or plant level drive the dynamics. The requirement of plant level data has severely restricted the use of the approach. However, the paper shows that such production function concepts can be applied to coal-fired electricity generation aggregated to the Chinese province level and still get valuable structural information for policy analysis. Development in total variable factor productivity (TVFP) and bias of technical change are estimated and illuminated using figures for isoquant maps, capacity regions in input coefficient space and average- and marginal cost functions for the provinces in China.

• Førsund, Finn R (2018). Cross-Efficiency: A Critique. Data Envelopment Analysis Journal. ISSN 2161-1823. 4(1), s. 1–25. doi: 10.1561/103.00000022.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Andrey (2018). Measuring the smoothness of the DEA frontier. Optimization Letters. ISSN 1862-4472. s. 1–14. doi: 10.1007/s11590-018-1329-8.
• Førsund, Finn R (2018). Pollution Meets Efficiency: Multi-equation Modelling of Generation of Pollution and Related Efficiency Measures. I Pang, Ruizhi; Bai, Xuejie & Lovell, Knox (Red.), Energy, Environment and Transitional Green Growth in China. Springer Nature. ISSN 978-981-10-7919-1. s. 37–80. doi: 10.1007/978-981-10-7919-1_3.
• Førsund, Finn R (2018). Productivity Measurement and the Environment. I Grifell-Tatjé, Emili; Knox Lovell, C. A. & Sickles, Robin C. (Red.), The Oxford Handbook of Productivity Analysis. Oxford University Press. ISSN 9780190226718. s. 287–325. doi: 10.1093/oxfordhb/9780190226718.013.8. Fulltekst i vitenarkiv
• Førsund, Finn R (2017). Economic interpretations of DEA. Socio-Economic Planning Sciences. ISSN 0038-0121. 61(1), s. 9–15. doi: 10.1016/j.seps.2017.03.004.
• Førsund, Finn R; Banker, Rajiv & Zhang, David (2017). Use of Data Envelopment Analysis for Incentive Regulation of Electric Distribution Firms. Data Envelopment Analysis Journal. ISSN 2161-1823. 3(1), s. 1–47. doi: 10.1561/103.00000020.
• Edvardsen, Dag Fjeld; Førsund, Finn R & Kittelsen, Sverre A.C. (2017). Productivity development of Norwegian institutions of higher education 2004–2013. Journal of the Operational Research Society. ISSN 0160-5682. 68(4), s. 399–415. doi: 10.1057/s41274-017-0183-x. Vis sammendrag

  Productivity growth of institutions of higher education is of interest for two main reasons: education is an important factor for productivity growth of the economy, and in countries where higher education is funded by the public sector, accountability of resource use is of key interest. Educational services consist of teaching, research and the ‘‘third mission’’ of dissemination of knowledge to the society at large. A bootstrapped Malmquist productivity change index is used to calculate productivity development for Norwegian institutions of higher education over the 10-year period 2004–2013. The confidence intervals from bootstrapping allow part of the uncertainty of point estimates stemming from sample variation to be revealed. The main result is that the majority of institutions have had a positive productivity growth over the total period. However, when comparing with growth in labour input, the impact on productivity varies a lot.

• Krivonozhko, Vladimir E; Lychev, A.V. & Førsund, Finn R (2017). Measurement of returns to scale in radial DEA models. Computational Mathematics and Mathematical Physics. ISSN 0965-5425. 57(1), s. 83–93. doi: 10.1134/S0965542517010080.
• Førsund, Finn R (2017). Measuring effectiveness of production in the public sector. Omega. The International Journal of Management Science. ISSN 0305-0483. 73(December), s. 93–103. doi: 10.1016/j.omega.2016.12.007. Vis sammendrag

  Keyconcepts in efficiency analyses are efficiency and effectiveness. Efficiency is popularly connected to ‘doing the things right’ and effectiveness to ‘doing the right things’. The paper elaborates upon the latter concept within a setting where resources are transformed into outputs under the control of a public provider, while outcomes with outputs as inputs represent higher social goals, but this production is outside the public provider's direct control. A new measure of overall preference effectiveness is introduced and its decomposition into output-oriented efficiency and output-mix efficiency is shown. The monumental task of getting the necessary information for calculating effectiveness is highlighted

• Førsund, Finn R (2017). Multi-equation modelling of desirable and undesirable outputs satisfying the materials balance. Empirical Economics. ISSN 0377-7332. 54(1), s. 67–99. doi: 10.1007/s00181-016-1219-9.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Andrey (2017). On comparison of different sets of units used for improving the frontier in DEA models. Annals of Operations Research. ISSN 0254-5330. 250(1), s. 5–20. doi: 10.1007/s10479-015-1875-8.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Andrey (2016). Improving the Frontier in DEA Models. Doklady. Mathematics. ISSN 1064-5624. 94(3), s. 715–719. doi: 10.1134/S1064562416060181.
• Bjerkholt, Olav; Førsund, Finn R & Holmøy, Erling (2016). Commemorating Leif Johansen (1930-1982) and his pioneering computable general equilibrium model of 1960. Journal of Policy Modeling. ISSN 0161-8938. 38(3), s. 415–420. doi: 10.1016/j.jpolmod.2016.02.008.
• Førsund, Finn R & Vislie, Jon (2016). Leif Johansen on intra-industry structural change. Journal of Policy Modeling. ISSN 0161-8938. 38(3), s. 515–527. doi: 10.1016/j.jpolmod.2016.02.005.
• Førsund, Finn R; Edvardsen, Dag Fjeld & Kittelsen, Sverre A.C. (2015). Productivity of tax offices in Norway. Journal of Productivity Analysis. ISSN 0895-562X. 43(3), s. 269–279. doi: 10.1007/s11123-015-0435-1.
• Førsund, Finn R (2015). Dynamic efficiency measurement. I Ray, Subhash; Kumbhakar, Subal & Dua, Pami (Red.), Benchmarking for performance evaluation. Springer. ISSN 978-81-322-2252-1. s. 187–219. doi: 10.1007/978-81-322-2253-8_4.
• Førsund, Finn R; Krivonozhko, Vladimir E & Lychev, Andrej (2015). Terminal units in DEA: definition and determination. Journal of Productivity Analysis. ISSN 0895-562X. 43(2), s. 151–164. doi: 10.1007/s11123-013-0375-6.
• Granderson, Gerald & Førsund, Finn R (2014). Rate of return regulation and the Le Chatelier principle. Journal of Productivity Analysis. ISSN 0895-562X. 41(2), s. 263–275. doi: 10.1007/s11123-012-0300-4.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Andrey (2014). Measurement of returns to scale using non-radial DEA models. European Journal of Operational Research. ISSN 0377-2217. 232(3), s. 664–670. doi: 10.1016/j.ejor.2013.06.046.
• Førsund, Finn R & Granderson, Gerald (2013). The impacts of the Clean Air Act on production cost, and the substitution between inputs in the electric utility industry. Energy Economics. ISSN 0140-9883. 40, s. 785–794. doi: 10.1016/j.eneco.2013.08.021.
• Førsund, Finn R; Krivonozhko, Vladimir E & Lychev, Andrey (2013). Identifying suspicious efficient units in DEA models. Doklady. Mathematics. ISSN 1064-5624. 88(3), s. 655–659. doi: 10.1134/S1064562413060100.
• Førsund, Finn R (2013). Weight restrictions in DEA: misplaced emphasis? Journal of Productivity Analysis. ISSN 0895-562X. 40(3), s. 271–283. doi: 10.1007/s11123-012-0296-9.
• Førsund, Finn R (2013). Hydropower Economics: An Overview. I Shogren, Jason (Red.), Encyclopedia of Energy, Natural Resource, and Environmental Economics. Elsevier. ISSN 9780123750679. s. 200–208.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Anrey (2012). Returns-to-scale properties in DEA models: the fundamental role of interior points. Journal of Productivity Analysis. ISSN 0895-562X. 38(2), s. 121–130. doi: 10.1007/s11123-011-0253-z.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Andrey (2012). A note on imposing strong complementary slackness conditions in DEA. European Journal of Operational Research. ISSN 0377-2217. 220(3), s. 716–721. doi: 10.1016/j.ejor.2012.01.050.
• Krivonozhko, Vladimir E; Førsund, Finn R & Lychev, Andrey (2012). Methods for determination of multiple reference sets in the DEA models. Doklady. Mathematics. ISSN 1064-5624. 85(1), s. 134–138. doi: 10.1134/S1064562412010036.
• Krivonozhko, V.E.; Førsund, Finn R; Rozhnov, A.V. & Lychev, A.V. (2012). Measurement of returns to scale using a non-radial DEA model. Doklady. Mathematics. ISSN 1064-5624. 85(1), s. 144–148. doi: 10.1134/S1064562412010322.
• Førsund, Finn R & Hjalmarsson, Lennart (2011). Renewable energy expansion and the value of balance regulation power. I Johansson, Per-Olov & Kriström, Bengt (Red.), Modern Cost-benefit Analysis of Hydropower Conflicts. Edward Elgar Publishing. ISSN 978-1849808804. s. 97–126. doi: 10.4337/9781849808811.00011.
• Førsund, Finn R (2011). ENERGY IN A BATHTUB:ELECTRICITY TRADE BETWEEN COUNTRIESWITH DIFFERENT GENERATION TECHNOLOGIES. I Johansson, Per-Olov & Kriström, Bengt (Red.), Modern Cost-benefit Analysis of Hydropower Conflicts. Edward Elgar Publishing. ISSN 978-1849808804. s. 76–96. doi: 10.4337/9781849808811.00010.
• Førsund, Finn R (2011). Industrial ecology: reflections of an environmental economist. I Batabyal, Amitrajeet A. & Nijkamp, Peter (Red.), Research tools in natural resource and environmental economics. World Scientific. ISSN 978-981-4289-22-1. s. 423–455. doi: 10.1142/9789814289238_0014.
• Førsund, Finn R; Hjalmarsson, Lennart & Zheng, Jinghai (2011). A short-run production function for electricity generation in China. Journal of Chinese Economic and Business Studies. ISSN 1476-5284. 9(2), s. 205–216. doi: 10.1080/14765284.2011.568689.
• Førsund, Finn R (2010). DYNAMIC EFFICIENCY MEASUREMENT. Indian Economic Review. ISSN 0019-4670. 45(2), s. 123–157. Vis sammendrag

  A philosophical problem for studies of inefficiency of firms is how to rationalise inefficiency. Since economics do not have any theory for inefficiency, explaining the results of efficiency analyses are notoriously more difficult than carrying out the estimations. The literature points to measures of inputs and management as not including quality dimensions as a reason for measured efficiency differences, indicating that more work needs to be done on data collection. Strategic behaviour in game situations between owners and management, and between management and labour may also show up as inefficiencies. Another reason is technology differences. The frontier production function is the key to information on best-practice technology. Estimation of efficiency is usually done for units observed during the same time period, thus in this respect the measures are static. Interpretations of dynamic efficiency measurement is offered. The vintage model of substitutability between inputs including capital before investment, but no substitution possibilities after investment, and ex post production possibilities characterised by fixed input coefficients, can rationalise inefficiency due to technology differences. Key elements in understanding structural change are the entering of capacity embodying new technology and exiting of capacity no longer able to yield positive quasi-rent. Three crucial production function concepts are identified: the ex ante micro unit production function as relevant when investing in new capacity, the ex post micro production function, and the short-run industry production function giving the production possibilities at the industry level. Productivity measurement, taking these types of production functions into consideration, leads to different interpretations of productivity change than traditional approaches not being clear about which production function concept is used.

• Førsund, Finn R & Podinovski, Victor V (2010). Differential Characteristics of Efficient Frontiers in Data Envelopment Analysis. Operations Research. ISSN 0030-364X. 58(6), s. 1743–1754. doi: 10.1287/opre.1090.0794.
• Krivonozhko, Vladimir E & Førsund, Finn R (2010). The relationship between returns-to-scale properties of interior points and vertex points in DEA models. Doklady. Mathematics. ISSN 1064-5624. 81(1), s. 159–163. doi: 10.1134/S1064562410010436.
• Podinovski, Victor V; Førsund, Finn R & Krivonozhko, Vladimir E (2009). A simple derivation of scale elasticity in data envelopment analysis. European Journal of Operational Research. ISSN 0377-2217. 197(1), s. 149–153. doi: 10.1016/j.ejor.2008.06.015.
• Førsund, Finn R (2009). Good modelling of bad outputs: pollution and multiple-output production. International Review of Environmental and Resource Economics. ISSN 1932-1465. 3, s. 1–38.
• Førsund, Finn R; Kittelsen, Sverre A.C. & Krivonozhko, Vladimir E (2009). Farrell revisited-Visualizing properties of DEA production frontiers. Journal of the Operational Research Society. ISSN 0160-5682. 60(11), s. 1535–1545. doi: 10.1057/jors.2008.185.
• Edvardsen, Dag Fjeld; Førsund, Finn R & Kittelsen, Sverre A.C. (2008). Far out or alone in the crowd: a taxonomy of peers in DEA. Journal of Productivity Analysis. ISSN 0895-562X. 29(3), s. 201–210. doi: 10.1007/s11123-007-0066-2. Vis sammendrag

  A method is presented for classifying strongly efficient units in DEA as interior or exterior, and as self-evaluators or active peers. The exterior strongly efficient units are found by running the enveloping procedure “from below”. There is no firm production-function evidence of the efficiency of exterior self-evaluators. Interior self-evaluators are more likely to have active peers as neighbours in more directions and may therefore represent technology. When performing a second stage regression analysis of efficiency scores, exterior self-evaluators should be removed. The proportion of exterior active peers also provides information on whether the variable specification is supported by the data.

• Førsund, Finn R; Singh, Balbir; Jensen, Trond & Larsen, Cato (2008). Phasing in wind-power in Norway: network congestion and crowding-out of hydropower. Energy Policy. ISSN 0301-4215. 36(9), s. 3514–3520. doi: 10.1016/j.enpol.2008.06.005.
• Førsund, Finn R; Hjalmarsson, Lennart; Krivonozhko, Vladimir & Utkin, Oleg B. (2007). Calculation of scale elasticities in DEA models: direct and indirect approaches. Journal of Productivity Analysis. ISSN 0895-562X. 28, s. 45–56. doi: 10.1007/s11123-007-0047-5.
• Førsund, Finn R; Edvardsen, Dag, Fjeld; Hansen, Wiljar; Kittelsen, Sverre A.C. & Neurauter, Thor (2006). Productivity and regulatory reform of Norwegian electricity distribution utilities. I Coelli, Tim & Lawrence, Denis (Red.), Performance measurement and regulation of network utilities. Edward Elgar Publishing. ISSN 9781845423179. s. 97–131.
• Førsund, Finn R; Grosskopf, Shawna; Färe, Rolf; Hayes, Kathrin & Heshmati, Almas (2006). measurement of productivity and quality in non-marketable services: with application to schools. Quality Assurance in Education. ISSN 0968-4883. 14(1), s. 21–36.
• Førsund, Finn R; Lindseth, Frode; Kittelsen, Sverre A.C. & Edvardsen, Dag Fjeld (2006). THE TAX MAN COMETH-BUT IS HE EFFICIENT? National Institute Economic Review. ISSN 0027-9501. 197(July), s. 106–119.
• Førsund, Finn R & Zanola, Roberto (2006). DEA meets Picasso: the impact of auction houses on the hammer price. Annals of Operations Research. ISSN 0254-5330. 145, s. 149–165. Vis sammendrag

  Employing a hedonic price approach within a framework of central tendencies no conclusive results about the impact of auction houses on final prices of art objects have been found. In order to focus on auction houses as a unit we have applied a benchmarking technique, DEA, developed for efficiency studies. New performance indicators are developed and calculated giving an insight into auction house differences impossible to obtain using hedonic price approach. The performance indicators may also be regarded as quality indicators assuming perfect arbitrage leads to the same unobservable quality of art object obtaining the same price.

• Førsund, Finn R & Zanola, Roberto (2006). The art of benchmarking: Picasso prints and auction house performance. Applied Economics. ISSN 0003-6846. 38(12/12), s. 1425 –1434. Vis sammendrag

  The influence of the auction house on the price of comparable art objects is an issue in the economics of arts literature. The standard approach has been to run hedonic price regressions including the auction house as a dummy variable. The approach in this paper is to apply benchmarking tools developed in the efficiency and productivity literature directly to the auction house as a unit. New performance indices are developed based on a DEA benchmarking technique to analyse auction houses. The new indices discriminate well between auction houses by allowing one to identify both contemporaneous and inter-temporal performances. Additional best performance results are obtained for specific attributes.

• Førsund, Finn & Qin, Yan (2005). Acid rain in China: applications of the RAINS-ASIA model. I Bjerkholt, Olav & Peng, Xizhe (Red.), Frontier environmental issues. Fudan University Press. ISSN 7-309-04681-1. s. 261–306.
• Førsund, Finn & Hjalmarsson, Lennart (2005). Productivity in electricity generation in developing countries: an international comparison of East Asia power production. I Agnati, Achille; Marangoni, Giandemetrio; Montesano, Aldo & Pellanda, Anna (Red.), Dinamica economica ed istituzioni. CEDAM. ISSN 88-13-25839-9. s. 99–111.
• Førsund, Finn & Sarafoglou, Nikias (2005). The tale of two research communities: The diffusion of research on productive efficiency. International Journal of Production Economics. ISSN 0925-5273. 98(1), s. 17–40. Vis sammendrag

  The field of theoretical and applied efficiency analysis is pursued both by economists and people from operational research and management science. Each group tends to cite a different paper as the seminal one. Recent availability of extensive electronically accessible databases of journal articles makes studies of the diffusion of papers through citations possible. Research strands inspired by the seminal paper within economics are identified and followed by citation analysis during the 20 year period before the operations research paper was published. The first decade of the operations research paper is studied in a similar way and emerging differences in diffusion patterns are pointed out. Main factors influencing citations apart from the quality of the research contribution are reputation of journal, reputation of author, number of close followers; colleagues, �cadres of protégés�, Ph.D. students, and extent of network (�invisible college�). Such factors are revealed by the citing papers. In spite of increasing cross contacts between economics and operations research the last decades co-citation analysis reveals a relative constant tendency to stick to �own camp� references.

• Førsund, Finn & Hjalmarsson, Lennart (2004). Are all scales optimal in DEA? Theory and empirical evidence. Journal of Productivity Analysis. ISSN 0895-562X. 21(1), s. 25–48.
• Førsund, Finn & Hjalmarsson, Lennart (2004). Calculating scale elasticities in DEA models. Journal of the Operational Research Society. ISSN 0160-5682. 55(10), s. 1023–1038.

Se alle arbeider i Cristin

• Rødseth, Kenneth Løvold; Holmen, Rasmus Bøgh; Førsund, Finn R & Kittelsen, Sverre A.C. (2019). Effektivitet og produktivitet i norsk veibygging 2007-2016. Ex ante akademisk forlag. ISBN 978-82-93253-77-8. 103 s.
• Førsund, Finn R (2015). Hydropower economics second edition. Springer Science+Business Media B.V.. ISBN 978-1-4899-7519-5. 326 s.
• Førsund, Finn R (2007). Hydropower economics. Springer Science+Business Media B.V.. ISBN 978-0-387-73026-4. 261 s.

Se alle arbeider i Cristin

• Førsund, Finn R (2021). Framework for Optimal Production and Transmission of Electricity.
• Rødseth, Kenneth Løvold; Schøyen, Halvor; Wangsness, Paal Brevik & Førsund, Finn R (2017). Produktivitet og effektivitet i norske havner. Status 2017-Skipstrafikk∙Godstransport∙Havn. Kystverket. Vis sammendrag

  Med mål om økt bærekraft i transportsektoren har det at veksten innen godstransport skal tas på sjøen eller bane blitt et sentralt virkemiddel i den norsk samferdselspolitikken. For at det skal kunne realiseres må man styrke konkurransekraften i alle leddene i den maritime verdikjeden. Produktivitet og effektivitet ansees som bestemmende for konkurransekraften, og er følgelig relevante indikatorer når man skal vurdere overføringspotensialet. Denne artikkelen diskuterer gjennomføringen og resultatene av en produktivitets- og effektivitetsanalyse av de største havnene i Norge. Internasjonalt er det blitt gjort en rekke tilsvarende analyser, men norske havner har i liten grad blitt analysert.

• Schøyen, Halvor; Rødseth, Kenneth Løvold; Wangsness, Paal Brevik & Førsund, Finn R (2017). Samfunnsøkonomiske kostnader ved havnedrift. Status 2017-Skipstrafikk∙Godstransport∙Havn. Kystverket. Vis sammendrag

  I norsk samferdselspolitikk er et av virkemidlene for mer bærekraftig transport at vekst innen godstransport skal tas på sjø eller bane. Økt godshåndtering i havnene kan på den ene siden lede til en bedre utnyttelse av skala- og samdriftsfordeler og dermed bidra til å styrke sjøtransportens konkurranseevne. På den andre siden kan økt godshåndtering isolert sett lede til en økning i eksterne kostnader fra havnedrift. Selv om eksterne kostnader ved transport har stått sentralt i et stort antall tidligere studier er det i dag lite eller ingen kunnskap om eksterne kostnader ved havnedrift. Prosjektet «En studie av samfunnsøkonomiske kostnader ved havnedrift» (EXPORT) ønsker å studere de privatøkonomiske og miljømessige konsekvensene som godshåndtering i havnene medfører.

• Førsund, Finn R (2016). Productivity Interpretations of the Farrell Efficiency Measures and the Malmquist Index and Its Decomposition. I Aparicio, Juan; Aparicio, Juan; Lovell, Knox & Pastor, Jesus (Red.), Advances in efficiency and productivity. Springer. ISSN 978-3-319-48459-4. s. 121–147. doi: 10.1007/978-3-319-461-7.
• Kumbhakar, Subal C. & Førsund, Finn R (2015). In Memoriam: Lennart Hjalmarsson, 1944–2012. Journal of Productivity Analysis. ISSN 0895-562X. 43(3), s. 233–236. doi: 10.1007/s11123-015-0444-0.
• Førsund, Finn R (2012). Measuring effectiveness of production in the public sector.
• Førsund, Finn R (2012). Måling av effektivitet i offentlig sektor.
• Førsund, Finn R (2012). Miljø-økonomi. RØST: Radikalt økonominettverks skriftserie. ISSN 1503-9595. s. 7–14.
• Førsund, Finn R (2012). The Making of the Malmquist Productivity Index.
• Førsund, Finn R (2012). Phasing in large-scale expansion of wind power in the Nordic countries.
• Førsund, Finn R (2012). Structural change in thermal electricity generation at the province level in China 1998-2006.
• Førsund, Finn R (2012). Phasing in lage-scale expansion of wind power in the Nordic countries.
• Førsund, Finn R (2012). Dynamic structural change: Applying a plant vintage production model to the Chinese province level.
• Førsund, Finn R (2012). Phasing in large-scale expansion of intermittent power in a hydro-dominated country.
• Førsund, Finn R (2012). Lennart Hjalmarsson's contributions to Economics.
• Førsund, Finn R (2012). Pumped storage.
• Førsund, Finn R (2012). Phasing in large-scale expansion of wind power in the Nordic countries.
• Førsund, Finn R (2012). Sustainability: Definitions and Measurement.
• Førsund, Finn R (2012). Phasing in large-scale expansion of intermittent power in a hydro-dominated country.
• Førsund, Finn R; Krivonozhko, Vladimir E & lychev, andrey (2012). Measurement of returns to scale in the non-radial DEA models.
• Førsund, Finn R (2012). Measuring efficiency in the public sector.
• Førsund, Finn R (2011). Innfasing av vindkraft. Samfunnsøkonomen. ISSN 1890-5250. s. 46–54.
• Førsund, Finn R (2008). Commentary, in Special issue: The Context of Discovery: An Experiment in Modeling R&D in Agriculture, Guest Editors: Kristiaan Kerstens and Spiro E. Stefanou. Journal of Productivity Analysis. ISSN 0895-562X. 30(1), s. 63–65.
• Førsund, Finn R (2008). Evaluering av økonomisk forskning i Norge. Samfunnsøkonomen. ISSN 1890-5250. s. 16–21.
• Førsund, Finn R (2006). Hjemfall er irrelevant - la staten overta vannkraftsektoren. Økonomisk forum. ISSN 1502-6108. 60(2).
• Førsund, Finn R (2006). The anatomy of market power in electricity markets with hydropower as a dominating technology.
• Førsund, Finn R (2006). The anatomy of market power in electricity markets with hydropower as a dominating technology.
• Førsund, Finn R; Kittelsen, Sverre A.C. & Lindseth, Frode (2006). Productivity of tax offices in Norway.
• Førsund, Finn R; Kittelsen, Sverre A.C.; Lindseth, Frode & Edvardsen, Dag Fjeld (2006). The tax man cometh-but is he efficient?
• Førsund, Finn R; Kittelsen, Sverre A.C. & Lindseth, Frode (2006). EFFICIENCY AND PRODUCTIVITY OF NORWEGIAN TAX OFFICES.
• Førsund, Finn (2004). Acid Rain in China - Applications of the RAINS-ASIA Mode.
• Førsund, Finn (2004). Hjemfall til staten eller arvesølvets bortfall?
• Førsund, Finn (2004). Skriftlige innlegg fra Det Økonomiske Råds medlemmer. Dansk økonomi. ISSN 0419-9480. s. 354a–354b.
• Førsund, Finn (2004). The Malmquist Productivity Index and Circularity.
• Førsund, Finn (2004). Market Power in Hydropower Systems.
• Rødseth, Kenneth Løvold; Holmen, Rasmus Bøgh; Kittelsen, Sverre & Førsund, Finn (2022). Forbedringspotensial ved måling av effektivitet i kommunal sektor. Transportøkonomisk institutt. ISSN 978-82-480-1924-4. Vis sammendrag

  Teknisk beregningsutvalg for kommunal og fylkeskommunal økonomi (TBU) ønsket et prosjekt som vurderer mulighetene for og den praktiske anvendbarheten av effektivitetsanalyser av offentlig tjenesteyting. Denne rapporten gir en gjennomgang av beste praksis innen metodikk for effektivitetsanalyse, aktuelle data til måling av kommuneeffektivitet og empiriske sammenlikninger av metoder og modellspesifikasjoner. Rapporten gir anbefalinger om hvordan TBUs etablerte metodikk for måling av kommuneeffektivitet kan forbedres samt aktuelle temaer til videre utredning i TBUs arbeid med å etablere et solid metodisk rammeverk.

• Rødseth, Kenneth Løvold; Hansen, Wiljar; Kuosmanen, Timo & Førsund, Finn (2021). Benchmarking of outlier electricity grid companies. Transportøkonomisk institutt. ISSN 978-82-480-1901-5. Vis sammendrag

  In this report we investigate alternative methods for benchmarking of Norwegian electricity grid companies that due to their uniqueness or size are omitted from the yardstick competition in the current income cap regulation. The objective of the report is to propose a regulatory framework that to a greater extent than the current regulation, ensures the decoupling between cost norm and actual costs for the outlier electricity grid companies, and by that, provide incentives for efficient utilization and development of the electricity network grid. We investigate three alternative methodological directions: a) adjustments to the DEA-methodology, b) panel data analysis and c) local frontier estimators. Based on our analysis, we recommend local front estimators as the most likely candidate for further study and implementation in the regulation.

• Førsund, Finn R (2008). Good Modeling of Bad Outputs: Pollution and Multiple-Output Production. Økonomisk institutt. ISSN 0809-8786.
• Førsund, Finn R & Hjalmarsson, Lennart (2008). Dynamic Analysis of Structural Change and Productivity Measurement. Økonomisk institutt. ISSN 0809-8786.
• Førsund, Finn R (2006). The anatomy of market power in electricity markets with hydropower as a dominating technology. International Centre for Economic Research (ICER). Vis sammendrag

  The problem of optimal management of a water reservoir by a hydropower producer is necessarily a dynamic one since water can be transferred between periods. A hydropower producer being a monopolist cannot reduce output in the classical way without spilling water. He will follow a strategy of setting marginal revenues equal between time periods and thus shift water from relatively inelastic periods to relatively elastic ones. If the monopolist has thermal capacity the strategy is the same, but the utilization of thermal capacity is reduced. If the monopolist has control over external trade import is reduced and export increased compared with the social solution. Technical constraints of limited reservoir and interconnector capacity and a competitive fringe may reduce markedly the consequences of exercising market power.

• Førsund, Finn & Lindseth, Frode (2004). Analyse av produktivitet ved likningskontorene. Skattedirektoratet.
• Førsund, Finn & Hoel, Michael Olaf (2004). Properties of a non-competitive electricity market dominated by hydroelectric power. Økonomisk institutt. ISSN 0801-1117.

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