Kai Sun
;
Daniel J. Henderson
;
Subal C. Kumbhakar

biases in approximating log production (replication data)

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 (The Solow model with CES technology: nonlinearities and parameter heterogeneity, Journal of Applied Econometrics 2004; 19: 171-201) and then estimate both models in levels to avoid these biases. Our estimation in levels gives results in line with conventional wisdom.

Data and Resources

Suggested Citation

Sun, Kai; Henderson, Daniel J.; Kumbhakar, Subal C. (2011): Biases in approximating log production (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2022320.0722102276