Sun, Kai and Henderson, Daniel J. and Kumbhakar, Subal C. (2010): Biases in approximating log production. Forthcoming in: Journal of Applied Econometrics
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Most empirical work in economic growth assumes either a Cobb-Douglas production function expressed in logs or a log-approximated constant elasticity of substitution specification. Estimates from each are likely biased due to logging the model and the latter can also suffer from approximation bias. We illustrate this with a successful replication of Masanjala and Papagerogiou (2004) and then estimate both models in levels to avoid these biases. Our estimation in levels gives results in line with conventional wisdom.
|Item Type:||MPRA Paper|
|Original Title:||Biases in approximating log production|
|Keywords:||Nonparametric, Kmenta Approximation, Levels, Logs, PPML|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General
O - Economic Development, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity
C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics
|Depositing User:||Daniel J. Henderson|
|Date Deposited:||21. Dec 2010 08:02|
|Last Modified:||12. Feb 2013 16:18|
Backus, D., Henriksen, E. and Storesletten, K. (2008), ‘Taxes and the global allocation of capital’, Journal of Monetary Economics 55, 48–61.
Byron, R. and Bera, A. (1983), ‘Least squares approximate to unknown regression functions: A comment’, International Economic Review 24, 255–260.
Cameron, A. and Trivedi, P. (2005), Microeconometrics: Methods and Applications, Cambridge University Press, New York.
Duffy, J. and Papageorgiou, C. (2000), ‘A cross-country empirical investigation of the aggregate production function specification’, Journal of Economic Growth 5, 87–120.
Duffy, J., Papageorgiou, C. and Perez-Sebastian, F. (2004), ‘Capital-skill complementarity? evidence from a panel of countries’, Review of Economics and Statistics 86, 327–344.
Durlauf, S., Johnson, P. and Temple, J. (2005), Handbook of Economic Growth, Vol. 1, Elsevier.
Gourieroux, C., Monfort, A. and Trognon, A. (1984), ‘Pseudo maximum likelihood methods: Applications to poisson models’, Econometrica 52, 701–720.
Klump, R., McAdam, P. and Willman, A. (2007), ‘Factor substitution and factor-augmenting technical progress in the United States: A normalized supply-side system approach’, Review of Economics and Statistics 89, 183–192.
Kmenta, J. (1967), ‘On estimation of the CES production function’, International Economic Review 8, 180–189.
Mankiw, G., Romer, D. and Weil, N. (1992), ‘A contribution to the empirics of economic growth’, Quarterly Journal of Economics 107, 407–437.
Manning, W. and Mullahy, J. (2001), ‘Estimating log models: To transform or not to transform?’, Journal of Health Economics 20, 461–494.
Masanjala, W. and Papagerogiou, C. (2004), ‘The Solow model with CES technology: Nonlinearities and parameter heterogeneity’, Journal of Applied Econometrics 19, 171–201.
Papke, L. and Wooldridge, J. (1996), ‘Econometric methods for fractional response variables with an application to 401(k) plan participation rates’, Journal of Applied Econometrics 11, 619– 632.
R Development Core Team (2009), ‘The R foundation for statistical computing’, http://cran.r- project.org/ .
Ramsey, J. (1969), ‘Tests for specification errors in classical linear least squares regression analysis’, Journal of the Royal Statistical Society, Series B 31, 350–371.
Santos Silva, J. and Tenreyro, S. (2006), ‘The log of gravity’, Review of Economics and Statistics 88, 641–658.
Temple, J. (2001), ‘Generalizations that aren’t? Evidence on education and growth’, European Economic Review 45, 905–918.
Thursby, J. and Lovell, C. (1978), ‘An investigation of the Kmenta approximation to the CES function’, International Economic Review 19, 363–377.