CES production function estimation Introduction

There are different ways of estimating the parameters of a production function. For example, single-equation and system equation techniques are both possible. Another difference among methods is that estimable forms may either involve direct or indirect estimation of the parameters. For instance, rather than estimate the production function as is, one may instead estimate the derived demand functions or, say, use other relations such as factor shares. Also to be considered are the underlying economic assumptions; such possibilities being perfect competition, constant returns to scale, profit maximization, etc.

Question

Bearing the above in mind, my question is what is the standard (accepted?) method of estimating normalized CES (constant elasticity of substitution) production functions? 

For information, a normalized CES  production function can be written as

$$
Y = Y_{0} \lbrace \pi_{0} K_{0}^{\frac{1-\sigma}{\sigma}}(K_{t}\cdot e^{\gamma_{K}(t-t_{0})})^{\frac{\sigma-1}{\sigma}} + (1-\pi_{0})N_{0}^{\frac{1-\sigma}{\sigma}}(N_{t}\cdot e^{\gamma_{N}(t-t_{0})})^{\frac{\sigma-1}{\sigma}}\rbrace
$$

following the notation found in Klump, McAdam, and Willman (2011, p.22).

Importantly, what data is required to estimate the parameters of this particular production function? And, what is the exact procedure involved? Demonstrations and references are most welcome!  

Reference: 

Rainer Klump, Peter McAdam, and Alpo Willman, The normalized nested
CES production function, theory and empirics, ECB Working Paper Series,
No. 1294. (Feb., 2011), 2011.
@GraemeWalsh, another option is to use nonlinear least squares to estimate the elasticitiy of substitution, $\sigma$. This is what you want to estimate. The rest is either assumption or data. If you assume the technology is directed i.e. induced, you should use Box-Cox transformation of technology growth so that factor augmenting technological change grows at varying rates over time. 

Values of $\gamma$ depend on the average growth rate of output and how you want the technological progress to be augmented. If you think labour-augmentation was strong, then choose a value that is close to actual average rate of output growth for $\gamma_N$, something smaller for the growth rate of the capital augmenting tech growth rate $\gamma_K$.

$\pi$s are constant share parameter.I do not know much about normaisation except that it should be chosen with reference to a common time period. You could normalise all the variables and parameters using the first period, or any other. Alternatively, use non-linear methods of estimation. You could try using micEconCES package in R.