When considering the linkage between innovation and productivity, the relationship is often termed as the knowledge production function in the endogenous growth literature. In this article, we approach the issues involved through the aspects of the standard neoclassical production theory. The advantage is that the basic properties required of ordinary production function can be employed to infe...

In this paper we review the two main approaches to the problem of Malmquist bias which have been adopted in the cosmology literature, and show how these two formulations of the problem represent fundamentally different views of the nature of probability. We discuss the assumptions upon which both approaches are based and indicate some of their limitations. In particular we identify a basic flaw...

Recognizing the critical role of agricultural sector in the overall growth as well as development performance, this study estimates total factor productivity (TFP) in Indian agriculture at state-level. Using Index of Agricultural Production as the measure of output, changes in TFP are estimated using non-parametric Sequential Malmquist TFP index. The TFP change is decomposed into efficiency cha...

This paper proposes a nonparametric approach for jointly modelling longitudinal and survival data using functional principal components. The proposed model is data-adaptive in the sense that it does not require pre-specified functional forms for longitudinal trajectories and it automatically detects characteristic patterns. The longitudinal trajectories observed with measurement error are repre...

In this paper we derive nonparametric stochastic volatility models in discrete time. These models generalize parametric autoregressive random variance models, which have been applied quite successfully to nancial time series. For the proposed models we investigate nonparametric kernel smoothers. It is seen that so-called nonparametric deconvolution estimators could be applied in this situation ...