Reading productivity and economic trends
Dr. Koji Nomura is an Associate Professor at Keio Economic Observatory,
Keio University. He is also chief expert of the APO Productivity Databook
project, as well as project manager of the APO Productivity Database
project. He has done extensive research on productivity, particularly on
measuring capital. He has served as senior visiting research fellow at the
Economic and Social Research Institute, Cabinet Office, Government of
Japan; economist at the OECD; and fellow at the Center for Business and
Government at Harvard University JFK School of Government.
We are faced with economic decisions every day, whether as consumers, workers, entrepreneurs, or government policymakers. Generally, the better the information we have, the better are our decisions and in turn their outcomes. We may be well aware of our immediate surroundings but a panoramic view often requires some research effort. When we broaden our view, we may discover options and possibilities that we did not even know existed, relevant lessons to be learned from others’ experience of our actions or inaction, and benchmark performances to aspire to.
As a key indicator of economic performance, productivity analysis is useful in focusing on issues at hand. In particular, when a country is catching up with the world leaders in GDP per capita, significant productivity growth is an essential element in the process. A good understanding of the key drivers and dynamics of productivity growth is therefore beneficial to a country’s development efforts.
Some APO member countries may already have their own programs of productivity analysis, but such programs may not sufficiently take into account the regional and global contexts. This is a gap that the APO Productivity Databook seeks to fill to complement national programs. Through international comparisons, widespread global or regional economic trends can be distinguished from factors unique to individual economies, and benchmark performances can be identified and analyzed to focus on potential adaptations. In this manner, international comparisons highlight the ways countries are able to learn from and cooperate with each other.
In the APO Productivity Databook 2008, a new analytical framework was developed to enable cross-country comparisons for the first time in this series. Furthermore, to provide a more complete regional and global perspective, the economic performances of APO member countries were compared with those of the People’s Republic of China, USA, and EU15 for reference. Countries are ranked according to their GDP and per capita GDP. To reflect their diversity, countries covered in the publication were divided into groups based on relative per capita GDP and how fast they were catching up with the USA, the world leader. Regional economic growth was dissected into country origins. Changes in per capita GDP were traced back to the causal components, i.e., labor productivity and the labor utilization rate. To understand further the dynamics of an economy, we analyzed the industry origins of each country’s economic growth and labor productivity.
This monthly column in the APO News will present the findings from the analyses contained in the APO Productivity Databook 2008 in bite-sized form, focusing on one specific topic each month and expanding on its implications where possible. International comparisons of productivity, however, are not a precise science but fraught with measurement difficulties and issues. Although the APO Productivity Databook 2008 represents an important milestone in APO productivity research efforts, there is still room for improvement. More specifically, the work of the APO Productivity Databook project team continues in two broad directions: 1) more thorough data investigation and harmonization to improve cross-country data comparability and in turn the quality of the results; and 2) an expanded scope of the analytical framework for completeness. Admittedly, a “perfect” data set is an unattainable dream. Nevertheless, improved knowledge of the underlying statistics should enable us to judge data limitations better and in turn to interpret the results with greater confidence. The medium-term goal is to build up an APO productivity database comparable with other international databases in terms of quality, opening up the possibility for the majority of countries in the Asia-Pacific to be included in future international studies of productivity performance.