Measuring Productivity When Technologies are Heterogeneous: A Semi-Parametric Approach for Electricity Generation

While productivity growth in electricity generation is associated with multiple positive effects from an economic and environmental perspective, measuring it is challenging. This paper proposes a framework to estimate and decompose productivity growth for a sector characterized by multiple technologies. Using a metafrontier Malmquist decomposition and frontier estimation based on stochastic non-smooth envelopment of data (StoNED) allows for productivity estimation with few microeconomic assumptions. Additionally, evaluation of productivity at representative hypothetical units permits distribution-free analysis for the whole distribution of power plant sizes. The proposed framework is used to analyze a unique and rich dataset of coal, lignite, gas, and biomass-fired generators operating in Germany from 2003 to 2010. The results indicate stagnating productivity for the sector as a whole, technical progress for biomass plants, and very high productivity for gas-fired plants

Before Stalinism: The Defence Industry of Soviet Russia in the 1920s1

Competition and profit-seeking were never strong features of the Russian defence industry before the Revolution. World War I and the Russian Civil War profoundly influenced interwar perspectives on the Soviet defence industry and accentuated this characteristic in the process. The defence industry failed to adapt to market conditions under the New Economic Policy: it produced at a loss, depended heavily on budgetary subsidies, and still failed to meet the demands of the armed forces in virtually every field of armament. The blame, at first laid on those in charge of the defence industry, was directed more and more specifically against its ‘bourgeois’ specialists. In the process, the Red Army staff became enthusiastic advocates of forced industrialisation under a command system through which they hoped to gain direct influence over defence industry personnel and allocations. Comparative Economic Studies (2005) 47, 437–455. doi:10.1057/palgrave.ces.8100100

An aggregate quantity framework for measuring and decomposing productivity change

Total factor productivity (TFP) can be defined as the ratio of an aggregate output to an aggregate input. This definition naturally leads to TFP indexes that can be expressed as the ratio of an output quantity index to an input quantity index. If the aggregator functions satisfy certain regularity properties then these TFP indexes are said to be multiplicativelycomplete. This paper formally defines what is meant by completeness and reveals that (1) the class of multiplicatively complete TFP indexes includes Laspeyres, Paasche, Fisher, Törnqvist and Hicks-Moorsteen indexes, (2) the popular Malmquist TFP index of Caves et al. (Econometrica 50(6):1393-1414, 1982a) is incomplete, implying it cannot always be interpreted as a measure of productivity change, (3) all multiplicatively complete TFP indexes can be exhaustively decomposed into measures of technical change and efficiency change, and (4) the efficiency change component can be further decomposed into measures of technical, mix and scale efficiency change. Artificial data are used to illustrate the decomposition of Hicks-Moorsteen and Fisher TFP indexes