PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Czasopismo
2015 | nr 4 | 299--326
Tytuł artykułu

The Shape of Aggregate Production Functions: Evidence from Estimates of the World Technology Frontier

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article estimates the aggregate production function at the World Technology Frontier on the basis of annual data on inputs and output in 19 highly developed OECD countries in 1970-2004. A comparison of results based on Data Envelopment Analysis and Bayesian Stochastic Frontier Analysis uncovers a number of significant discrepancies between nonparametric estimates of the frontier and parametric (Cobb-Douglas and translog) aggregate production functions in terms of implied technical efficiency levels, partial elasticities, returns to scale, and elasticities of substitution.(original abstract)
Czasopismo
Rocznik
Numer
Strony
299--326
Opis fizyczny
Twórcy
  • National Bank of Poland; Warsaw School of Economics, Poland
autor
  • Cracow University of Economics, Poland
  • Alior Bank S.A.
  • Cracow University of Economics, Poland
Bibliografia
  • Badunenko O., Henderson D.J., Zelenyuk V. (2008), Technological change and transition: relative contributions to worldwide growth during the 1990's, Oxford Bulletin of Economics and Statistics, 70(4), 461-492.
  • Battese G., Coelli T. (1992), Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India, Journal of Productivity Analysis, 3(1-2), 153-169.
  • Battese G., Coelli T. (1995), A model for technical inefficiency effects in a stochastic frontier production function for panel data, Empirical Economics, 20, 325-332.
  • Bernanke B.S., Gürkaynak R.S. (2001), Is growth exogenous? Taking Mankiw, Romer and Weil seriously, in: B.S. Bernanke, K. Rogoff (eds.), NBER Macroeconomics Annual 2001, MIT Press, Cambridge.
  • Blackorby C., Russell R.R. (1989), Will the real elasticity of substitution please stand up? (A comparison of the Allen/Uzawa and Morishima elasticities), American Economic Review, 79(4), 882-888.
  • Bos J.W.B., Economidou C., Koetter M., Kolari J.W. (2010), Do all countries grow alike?, Journal of Development Economics, 91(1), 113-127.
  • Caselli F. (2005), Accounting for cross-country income differences, in: P. Aghion, S. Durlauf (eds.), Handbook of economic growth, Elsevier, Amsterdam.
  • Caselli F., Coleman W.J. (2006), The World Technology Frontier, American Economic Review, 96(3), 499-522.
  • Chirinko R.S. (2008), σ: the long and short of it, Journal of Macroeconomics, 30, 671-686.
  • Cohen D., Soto M. (2007), Growth and human capital: good data, good results, Journal of Economic Growth, 12(1), 51-76.
  • Duffy J., Papageorgiou C. (2000), The specification of the aggregate production function: a cross- -country empirical investigation, Journal of Economic Growth, 5, 83-116.
  • Färe R., Grosskopf S., Noriss M., Zhang Z. (1994), Productivity growth, technical progress, and efficiency change in industrialized countries, American Economic Review, 84(1), 66-83.
  • Fried H.O., Lovell C.A.K., Schmidt S.S., eds. (1993), The measurement of productive efficiency: techniques and applications, Oxford University Press, New York, Oxford.
  • de la Fuente A., Doménech R. (2006), Human capital in growth regressions: How much difference does data quality make?, Journal of the European Economic Association, 4(1), 1-36.
  • Gollin D. (2002), Getting income shares right, Journal of Political Economy, 110(2), 458-474.
  • Growiec J. (2012a), Zagregowana funkcja produkcji w ekonomii wzrostu gospodarczego i konwergencji, Oficyna Wydawnicza SGH, Warszawa.
  • Growiec J. (2012b), The World Technology Frontier: What can we learn from the US States?, Oxford Bulletin of Economics and Statistics, 74(6), 777-807.
  • Growiec J. (2013), On the measurement of technological progress across countries, Bank i Kredyt, 44(5), 467-504.
  • Growiec J., Pajor A., Pelle D., Prędki A. (2011), The shape of aggregate production functions: evidence from estimates of the World Technology Frontier, NBP Working Paper, 102, Narodowy Bank Polski, Warszawa.
  • Hall R.E., Jones C.I. (1999), Why do some countries produce so much more output per worker than others?, Quarterly Journal of Economics, 114(1), 83-116.
  • Henderson D.J. (2009), A non-parametric examination of capital-skill complementarity, Oxford Bulletin of Economics and Statistics, 71(4), 519-538.
  • Henderson D.J., Russell R.R. (2005), Human capital and convergence: a production-frontier approach, International Economic Review, 46(4), 1167-1205.
  • Heston A., Summers R., Aten B. (2006), Penn World Table version 6.2, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania.
  • Hodrick R.J., Prescott E.C. (1997), Postwar U.S. business cycles: an empirical investigation, Journal of Money, Credit and Banking, 29(1), 1-16.
  • Hoff A. (2004), The linear approximation of the CES function with n input variables, Marine Resource Economics, 19, 295-306.
  • Hsieh C.-T., Klenow P. (2009), Misallocation and manufacturing TFP in China and India, Quarterly Journal of Economics, 124, 1403-1448.
  • Jerzmanowski M. (2007), Total factor productivity differences: appropriate technology vs. efficiency, European Economic Review, 51, 2080-2110.
  • Karabarbounis L., Neiman B. (2014), The global decline of the labour share, Quarterly Journal of Economics, 129(1), 61-103.
  • Klump R., McAdam P., Willman A. (2007), Factor substitution and factor-augmenting technical progress in the US: a normalized supply-side system approach, Review of Economics and Statistics, 89, 183-192.
  • Kneip A., Simar L., Wilson P.W. (2008), Asymptotics and consistent bootstraps of DEA estimators in non-parametric frontier models, Econometric Theory, 24, 1663-1697.
  • Kneip A., Simar L., Wilson P.W. (2009), A computationally efficient, consistent bootstrap for inference with non-parametric DEA estimators, Discussion Paper, 0903, Institut de Statistique, Université catholique de Louvain.
  • Koop G., Osiewalski J., Steel M.F.J. (1999), The components of output growth: a stochastic frontier analysis, Oxford Bulletin of Economics and Statistics, 61(4), 455-487.
  • Koop G., Osiewalski J., Steel M.F.J. (2000), Measuring the sources of output growth in a panel of countries, Journal of Business and Economic Statistics, 18(3), 284-299.
  • Koop G., Steel M.F.J., Osiewalski J. (1995), Posterior analysis of stochastic frontier models using Gibbs sampling, Computational Statistics, 10, 353-373.
  • Koop G., Steel M.F.J. (2001), Bayesian analysis of stochastic frontier models, in: B. Baltagi (ed.), A companion to theoretical econometrics, Blackwell, Oxford.
  • Kumar S., Russell R.R. (2002), Technological change, technological catch-up, and capital deepening: relative contributions to growth and convergence, American Economic Review, 92(3), 527-548.
  • Kumbhakar S.C., Lovell C.A.K. (2000), Stochastic frontier analysis, Cambridge University Press, Cambridge.
  • Kumbhakar S.C., Wang H.-J. (2005), Estimation of growth convergence using a stochastic production frontier approach, Economics Letters, 88(3), 300-305.
  • Kydland F.E., Prescott E.C. (1982), Time to build and aggregate fluctuations, Econometrica, 50(6), 1345-1370.
  • León-Ledesma M., McAdam P., Willman A. (2010), Identifying the elasticity of substitution with biased technical change, American Economic Review, 100(4), 1330-1357.
  • Löthgren M., Tambour M. (1999), Testing scale efficiency in DEA models: a bootstrapping approach, Applied Economics, 31, 1231-1237.
  • McAdam P., Willman A. (2013), Medium run redux, Macroeconomic Dynamics, 17(4), 695-727.
  • Makieła K. (2009), Economic growth decomposition. An empirical analysis using Bayesian Frontier Approach, Central European Journal of Economic Modelling and Econometrics, 1, 333-369.
  • Marzec J., Osiewalski J. (2008), Bayesian inference on technology and cost efficiency of bank branches, Bank i Kredyt, 39, 29-43.
  • Park B.U., Jeong S.O., Simar L. (2009), Asymptotic distribution of Conical-Hull estimators of directional edges, Discussion Paper, 0907, Institut de Statistique, Université catholique de Louvain.
  • Simar L., Wilson P.W. (1998), Sensitivity of efficiency scores: How to bootstrap in nonparametric frontier models, Management Sciences, 44(1), 49-61.
  • Simar L., Wilson P.W. (2000a), Statistical inference in nonparametric frontier models: state of the art, Journal of Productivity Analysis, 13, 49-78.
  • Simar L., Wilson P.W. (2000b), A general methodology for bootstrapping in non-parametric frontier models, Journal of Applied Statistics, 27(6), 779-802.
  • Simar L., Wilson P.W. (2002), Non-parametric tests of returns to scale, European Journal of Operational Research, 139(1), 115-132.
  • Tierney L. (1994), Markov chains for exploring posterior distributions, Annals of Statistics, 22, 1701-1762.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171375867

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.