Executive Course: Economic Tools for Productivity Analysis

This two-day intensive course presents a coherent economic framework for analysing productivity. Unlike most courses in productivity analysis, participants will learn how to measure productivity in ways that are consistent with measurement theory. They will also learn how piecewise frontier models (PFMs), deterministic frontier models (DFMs) and stochastic frontier models (SFMs) can be used to explain variations in productivity.  Participants will obtain hands-on experience implementing various methods using R. R is a free open-­source software package that is widely used for statistical analysis in all branches of academia, government and industry.

Registration

A registration link will be available shortly. 

About the Presenter

Christopher O’Donnell is a Professor of Econometrics at the University of Queensland.  He is an Associate Editor of Empirical Economics and a former co-editor o the Journal of Productivity Analysis.  His research has been published in leading economics and econometrics journals, including the American Journal of Agricultural Economics, the Journal of Econometrics, the Journal of Applied Econometrics, and Econometric Reviews. According to Google Scholar, his research has been cited more than 24,000 times; he is the eleventh most highly-cited scholar in the field of productivity analysis. He has provided in-house training and/or been a consultant for organisations including the Organisation for Economic Co-operation and Development (OECD), the Asian Productivity Organisation (APO), the International Rice Research Institute (IRRI), the Australian Energy Regulator (AER), the New South Wales Independent Pricing and Regulatory Tribunal (IPART), the Australian Independent Hospital Pricing Authority (IHPA), the Australian Export Grains Innovation Centre (AEGIC) and the World Bank.

Who Should Attend?

The course is aimed at graduate students, researchers, economists, statisticians and consultants from private and public sector organizations, regulatory authorities, regulated firms, infrastructure industries (e.g., electricity, gas, railways), service industries (e.g., education, health), and industries with branch structures (e.g., banks, credit unions, franchises, retail chains). Participants are expected to have an understanding of microeconomics and econometrics similar to that of a second-­year undergraduate economics student at an Australian university.  Participants must bring their own laptop and have R and RStudio installed.  Familiarity with R is useful but not necessary.

Course Outline

Most of the course material is drawn from O’Donnell, C.J. (2018) Productivity and Efficiency Analysis: An Economic Approach to Measuring and Explaining Managerial Performance, Springer Nature, Singapore. Course instruction will take the form of lectures and tutorial sessions. The tutorial sessions will give participants hands-on experience using R. The course will address the following questions:

What is Productivity?

Most economists define measures of productivity to be measures of output quantity divided by measures of input quantity. Common measures of productivity include labour productivity (output quantity divided by the quantity of labour), multifactor productivity (output quantity divided by the quantity of some, but not all, inputs, usually just capital and labour) and total factor productivity (output quantity divided by the quantity of all inputs). Among other things, the course explains why a preoccupation with labour productivity often leads to poor environmental and social outcomes.

How do we Measure Changes in Productivity?

Measuring changes in productivity is an index number problem. The course focuses on indexes of output and input quantity change (and therefore productivity change) that are proper in the sense that they satisfy a set of basic axioms from index theory. One of these axioms is transitivity. If firm A produced twice as much as firm B, and firm B produced twice as much as firm C, then a transitive index would say that firm A produced four times as much as firm C. The class of proper indices includes various additive, multiplicative, primal and dual indices. Indexes that are NOT proper include the popular Fisher, Tornqvist, Malmquist, EKS and CCD indexes.

How do we Explain Changes in Productivity?

Explaining changes in productivity involves explaining changes in output and input quantities.  Economists have many models that can be used for this purpose.  The simplest models are production function models that express output quantities as time-varying functions of input quantities and characteristics of production environments. The course explains how parametric and nonparametric methods can be used to estimate such models.  It also explains how the estimated models can be used to identify the main economic drivers of productivity change: technical progress (i.e., the discovery of new techniques for transforming inputs into outputs); changes in environmental variables (i.e., variables that are physically involved in the production process but never within the control of farmers, such as temperature and rainfall); changes in technical efficiency (i.e., how well managers choose and implement production technologies); and changes in economies of scale and substitution (i.e., the productivity changes associated with changing the scale of operations, the input mix and/or the output mix).

What are the Policy Implications?

The course discusses how different government policies potentially effect, and can therefore be used to target, the different drivers of productivity change.  For example, governments can potentially increase rates of technical progress by conducting, or incentivising others to conduct, more research and development; they can maintain or improve production environments by regulating the impact of economic activities on the natural environment, and by providing public infrastructure (e.g., ports, railways); they can potentially increase levels of technical efficiency by removing barriers to the adoption of particular technologies, and through management training programs; and they can potentially increase economies of scale and substitution by changing interest rates and minimum wages, and by placing, or removing, legal restrictions on output and input choices.