This paper introduces a new data set for the analysis of productivity in U.S. manufacturing. It consists of data on production and input levels when the plants in an industry operate at capacity. The estimates are consistent with those obtained using data on actual operations from the ASM. As an...

This paper employs recently developed non stationary panel methodologies that assume some cross-section dependence to estimate the production function for Italian regions in the industrial sector over the period 1970-1998. The analysis consists in three steps. First, unit root tests for...

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a...

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...

This paper (i) derives a number of properties of a newly specified multi-input-single-output (MISO) production function with a derived error term, and (ii) using iteratively rescaled generalized least squares, presents estimates of the cross-sectionally varying coefficients of a...

Results of assessments of total labor factor productivity TFP showed improvements where it recorded higher rate of 73.5% compared to previous periods. However, that was related with constant rate of returns as compared with variable rate of return. When technical efficiency was compared with...

Based on a large panel of Czech manufacturing firms, we estimate firm-level production functions in 2003-2007 using the Levinsohn and Petrin (2003) and Wooldridge (2009) approaches, correcting for the measurement error in capital. We show that measurement error plays a significant role in the...

Nonparametric methods have been widely used for assessing the performance of organizations in the private and public sector. The most popular ones are based on envelopment estimators, like the FDH or DEA estimators, that estimate the attainable sets and its efficient boundary by enveloping the...

We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...

We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...