the paper presents an analysis of both energy intensity and energy demand for the italianindustrial sector. the aim of the paper is twofold: making a decomposition of energy intensity at the aggregate level and modeling energy demand at the firm level. the decomposition of energy intensity shows different patterns for the different sub-sectors in the period of interest. in the micro approach, p...

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple inputs and multiple outputs. DEA-based Malmquist productivity index measures the productivity change over time. We propose a dynamic DEA model involving network structure in each period within the framework a DEA. We have previously published the network DEA (NDEA) and the dynamic DEA ...

This paper discusses likelihood-based estimation of panel data models with individualspecific effects and both lagged dependent variable regressors and additional predetermined explanatory variables. The resulting new estimator, labeled as sub-system LIML (ssLIML), is asymptotically equivalent to standard panel GMM as N →∞ for fixed T , but tends to present smaller biases in finite samples as i...

regarding the decentralization of credits management, this study examined the effect of fiscal policies on gross domestic product of the iranian provinces over the period 2001-2009. therefore, we used dynamic panel data and employed gmm-sys method to examine the model. the results show that the government expenditure and tax multiplier coefficients are less than one in short - run but greater t...

This paper proposes a new instrumental variables estimator for a dynamic panel model with …xed e¤ects with good bias and mean squared error properties even when identi…cation of the model becomes weak near the unit circle. We adopt a weak instrument asymptotic approximation to study the behavior of various estimators near the unit circle. We show that an estimator based on long di¤erencing the ...

This paper investigates whether firms innovate persistently or discontinuously over time using an innovation panel data set on German manufacturing and service firms for the period 1994–2002. We find that innovation behaviour is permanent at the firm–level to a very large extent. Using a dynamic random effects discrete choice model and a new estimator recently proposed by Wooldrigde (2005), we ...

This paper considers the estimation of dynamic models for panel data. It shows how to count and express the moment conditions implied by a variety of covariance restrictions. These conditions can be imposed in a GMM framework. Many of the moment conditions are nonlinear in the parameters. We derive a simple linearized estimator that is asymptotically as efficient as the nonlinear GMM estimator,...