Aggregation of Malmquist Productivity Indexes

In this paper we extend the work of Färe and Zelenyuk (2003) to find a theoretically justified method of aggregating Malmquist Productivity Indexes over individual decision making units (firms, countries, etc.) into a group Malmquist Productivity Index. We also consider the aggregation of decomposed parts of the Malmquist Productivity Index to obtain a decomposition of the Malmquist Productivity Index for a particular group.DEA, Efficiency, Productivity, Index aggregation

Incorporating Environmental Impacts in the Measurement of Agricultural Productivity Growth

Agricultural production is known to have environmental impacts, both adverse and beneficial, and it is desirable to incorporate at least some of these impacts in an environmentally sensitive productivity index. In this paper, we construct indicators of water contamination from the use of agricultural chemicals. These environmental indicators are merged with data on marketed outputs and purchased inputs to form a state-by-year panel of relative levels of outputs and inputs, including environmental impacts. We do not have prices for these undesirable by products, since they are not marketed. Consequently, we calculate a series of Malmquist productivity indexes, which do not require price information. Our benchmark scenario is a conventional Malmquist productivity index based on marketed outputs and purchased inputs only. Our comparison scenarios consist of environmentally sensitive Malmquist productivity indexes that include indicators of risk to human health and to aquatic life from chronic exposure to pesticides. In addition, we derive a set of virtual prices of the undesirable by-products that can be used to calculate an environmentally sensitive Fisher index of productivity change.environmental impacts, productivity growth, Environmental Economics and Policy,

AGGREGATION ISSUES IN THE ESTIMATION OF MALMQUIST PRODUCTIVITY MEASURES

The paper contributes by demonstrating the sensitivity of nonparametric programming productivity measures to the choice of model –time series versus panel models of Malmquist productivity, and to various levels of commodity aggregation compared to the traditional Tornqvist-Theil index approach employing U.S. state-level data from 1960-96. To illustrate the sensitive of nonparametric programming productivity measures, we compare the implicit shadow shares recovered from the dual values of the Malmquist productivity and total factor productivity methods to the observed shares of the Tornqvist-Theil index for U.S level data from 1948-1994.Tornqvist-Theil Index, Time series, and Panel models, Malmquist productivity and Malmquist total factor productivity programming, Share-weights., Productivity Analysis, O3, C6, Q1,

New indices of labour productivity growth: Baumol’s disease revisited

We introduce two new indexes of labour productivity growth. Both indexes are intended to capture the shift in the short-run production frontier, which can be attributed to technological progress or growth in capital inputs. The two indexes adopt distinct approaches to measuring the distance between the production frontiers. One is based on the distance function and the other is based on the profit function. In the end, we show that these two theoretical measures coincide with the index number formulae that are computable from the observable prices and quantities of output and input. By applying these formulae to the U.S. industry data of the years 1970–2005, we compare newly proposed index of labour productivity growth with the growth of average labour productivity over periods and across industries. We revisit the hypothesis of Baumol’s disease throughout our observations on the trend of industry labour productivities in the service sector.Labour productivity, index numbers, Malmquist index, Törnqvist index, output distance function, input distance function, Baumol’s disease, service sector

Aggregation of Malmquist productivity indexes allowing for reallocation of resources

In this paper we consider aggregate Malmquist productivity index measures which allow inputs to be reallocated within the group (when in output orientation). This merges the single period aggregation results allowing input reallocation of Nesterenko and Zelenyuk (2007) with the aggregate Malmquist productivity index results of Zelenyuk (2006) to determine aggregate Malmquist productivity indexes that are justified by economic theory, consistent with previous aggregation results, and which maintain analogous decompositions to the original measures. Such measures are of direct relevance to firms or countries who have merged (making input reallocation possible), allowing them to measure potential productivity gains and how these have been realised (or not) over time

Alternative Measures of Total Factor Productivity Growth

The four main approaches to the measurement of total factor productivity (TFP)-growth and its decomposition are (i) Solow's residual analysis, (ii) the Index Number Approach, (iii) Input-Output Analysis (IO), and (iv) Data Envelopment Analysis (DEA).The corresponding measures of TFP growth are based on different assumptions, which we expose and interrelate.The Solow Residual serves as the benchmark for our comparisons.The interrelationships between the alternative measures permit an interpretation of the differences among them.We consolidate the four alternative measures in a common framework.TFP;Solow residual;Index numbers;Input-output;DEA

Aggregation Issues in the Estimation of Linear Programming Productivity Measures

This paper demonstrates the sensitivity of the linear programming approach in the estimation of productivity measures in the primal framework using Malmquist productivity index and Malmquist total factor productivity index models. Specifically, the sensitivity of productivity measure to the number of constraints (level of dis-aggregation) and imposition of returns to scale constraints of linear programing is evaluated. Further, the shadow or dual values are recovered from the linear program and compared to the market prices used in the ideal Fisher index approach to illustrate sensitivity. Empirical application to U.S. state-level time series data from 1960-2004 reveal productivity change decreases with increases in the number of constraints. Further, the input and output shadow or dual values are skewed, leading to the difference in the productivity measures due to aggregation.Aggregation, Share-weights, single and multiple output and input, Malmquist productivity index, Malmquist total factor productivity index, Agribusiness, Production Economics,

Multilateral productivity comparisons and homotheticity

In this paper it is shown that a well known procedure (GEKS) of transitivizing a bilateral system of productivity comparisons is implicitly a way of imposing a homothetic structure onto the data. The main implication of this result is that deviations between the bilateral and the multilateral (GEKS) indexes can be interpreted as a measure of local deviation from the homothetic assumption. This establishes an additional link between homotheticity and transitivity

A Productivity analysis of Eastern European banking taking into account risk decomposition and environmental variables

This paper develops a new Luenberger productivity which is applied to a technology where the desirable and undesirable outputs are jointly produced and are possibly negative. The components of this Luenberger productivity index - the efficiency change and the components of the technological shift - are then decomposed into factors determined by the technology, adjusted for ‘risk and environment’, ‘risk management’ and ‘environmental effects’. The method is applied to Central and Eastern European banks operating during 1998–2003 utilising three alternative input/output methodologies (intermediation, production and profit/revenue). Additionally, the comparative analysis of the sensitivity of the productivity indices in the choice of the methodologies is undertaken using statistical and kernel density tests. It is found that the main driver of productivity change in Central and Eastern European banks is technological improvement, which, in the beginning of the analysed period, hinged on the banks’ ability to capitalise on advanced technology and successfully take into account risk and environmental factors. Whereas, in the later sampled periods, we show that one of the most important factors of technological improvement/decline is risk management. Finally, the tests employed confirm previous findings, such as Pasiouras (2008) in this journal, that different input/output methodologies produce statistically different productivity results. Indeed, we also find that external factors, such as a risk in the economy and banking production, and a ‘corruption perception’ affect the productivity of banks.Luenberger productivity index; DEA; banking; undesirable outputs; negative data.

PRODUCTIVITY OF DAIRY PRODUCTION IN INDIVIDUAL STATES

In a competitive market dairy production will shift to that region which is the most productive. Thus, this paper reports the measurement of productivity of dairy production in the various states of the U.S. using recent Census data and non-parametric Malmquist index techniques. These are total factor productivity measures that do not require the assumption of cost or profit maximization behavior for aggregation. Individual state estimates of changes in efficiency, technology, and productivity from 1987 to 1992 were computed, divided by 1987 values. Over these states the average increase in productivity was 3.6 percent, or about 0.7 percent per year. Almost all of the productivity increase occurred from technological change, since the average increase in efficiency was only 0.1 percent. Technological change averaged 3.5 percent over the five year period, or about 0.7 percent each year. If there is a significant decrease in the number of farms in a state, it might be expected that the remaining farms are more efficient, under the assumption that the least efficient farms are those that exit the industry. This was tested by regressing the percent change in efficiency on the percent change in farm numbers. The results were statistically insignificant. Likewise, if the output of the average farm increased it might be expected that efficiency might fall. This was tested by regressing the percent change in efficiency on the percent change in output per farm. Again the results were statistically insignificant. It was further expected that states that increased output per farm might have done so by using new technology. This was tested by regressing percent technological change on the percent change in output per farm. These results were also statistically insignificant.Dairy Productivity, Malmquist Index, Livestock Production/Industries, Productivity Analysis,