Jorgenson, Dale W.Global and Regional Productivity and Economic Growth: The Fifth World KLEMS Conference.” International Productivity Monitor 36, no. Spring (2019): 1-6. Publisher's Version 19_ipm_intro_jorgenson.pdf
Jorgenson, Dale W., Mun S. Ho, and Jon D. Samuels. “Educational Attainment and the Revival of U.S. Economic Growth.” In Education, Skills, and Technical Change: Implications for Future U.S. GDP Growth, edited by Charles R. Hulten and Valerie A. Ramey, 23-60. Chicago: University of Chicago Press, 2019. Publisher's VersionAbstract

Labor quality growth captures the upgrading of the labor force through higher educational attainment and greater experience. We find that average levels of educational attainment of new entrants remain high, but will no longer continue to rise. Growing educational attainment will gradually disappear as a source of U.S. economic growth. Our second finding is that the investment boom of 1995-2000 drew many younger and less-educated workers into employment. Employment rates for these workers declined during the recovery of 2000-2007 and dropped further during the Great Recession of 2007-2009. Our third finding is employment rates for less-educated workers are unlikely to recover the peak levels that followed the investment boom of 1995-2000. In order to assess the prospects for recovery of employment rates as a potential source U.S. economic growth, we project these rates of each age-gender-education group. JEL No. E01,E24,O4,O47

Jorgenson, Dale W.Production and Welfare: Progress in Economic Measurement.” Journal of Economic Literature LVI, no. 3 (2018): 867-919. Publisher's VersionAbstract

While the GDP was intended by its originators as a measure of production, the absence of a measure of welfare in the national accounts has led to widespread misuse of the GDP to proxy welfare. Measures of welfare are needed to appraise the outcomes of changes in economic policies and evaluate the results. Concepts that describe the income distribution, such as poverty and inequality, fall within the scope of welfare rather than production. This paper reviews recent advances in the measurement of production and welfare within the national accounts, primarily in the United States and the international organizations.  Expanding the framework beyond the national accounts has led to important innovations in the measurement of both production and welfare.[1] JEL Codes: C8, D6, I3, O4.


[1] Acknowledgements: The author is grateful to his collaborators on economic measurement, many for very helpful comments on earlier versions of this paper – Barbara Fraumeni, Frank Gollop, Mun Ho, Steven Landefeld, Koji Nomura, Jon Samuels, Paul Schreyer, Daniel Slesnick, Kevin Stiroh, Marcel Timmer, and Khuong Vu. He is also grateful for comments from Bart van Ark, Diane Coyle, William Nordhaus, Nicholas Oulton, Dirk Philipsen, Rebecca Riley, Amartya Sen, and Peter van de Ven, and from the Office of National Statistics (U.K.) and the Bureau of Economic Analysis (U.S.). He would like to thank the Editor and two anonymous referees for their comments and suggestions. Financial support for this research was provided by the Donald Marron Center for Economic Data at Harvard University. None of the foregoing is responsible for any remaining deficiencies of the paper.

Jorgenson, Dale W.The Growth of the World Economy.” In Productivity Dynamics in Emerging and Industrialized Countries, edited by Deb Kusum Das, 37-57. London: Routledge, Taylor and Francis, 2018.Abstract


The World KLEMS Initiative was established at the First World KLEMS Conference, held at Harvard University in August 2010[i]. The purpose of the Initiative is to generate industry-level datasets, consisting of outputs and inputs of capital (K) and labor (L), together with inputs of energy (E), materials (M), and services (S). Productivity for each industry is defined as output per unit of all inputs. These datasets provide a new framework for analyzing the sources of economic growth at the industry and aggregate levels for countries around the world. This framework has closed a critical gap in systems of national accounts.

Growth of output, inputs, and productivity at the industry level is important for understanding changes in the structure of an economy and the contributions of different industries to economic growth. International comparisons of differences in productivity levels based on purchasing power parities of outputs and inputs at the industry level provide a second focus for industry-level productivity research. These comparisons are essential in assessing changes in comparative advantage and formulating strategies for economic growth.

The EU (European Union) KLEMS study provides industry-level datasets on the sources of growth for 25 of the 27 EU member countries[ii]. These datasets are essential for analyzing the slowdown in European economic growth that preceded the current financial and fiscal crisis. The datasets and results were presented at the Final EU KLEMS Conference in Groningen, The Netherlands, in June 2008[iii]. Marcel P. Timmer, Robert Inklaar, Mary O’Mahony, and Bart van Ark (2010) describe the datasets and analyze the sources of economic growth in Europe at the industry level.

The EU KLEMS project also included datasets for Australia, Canada, Japan, Korea, and the United States. Matilde Mas and Robert Stehrer (2012) present international comparisons within Europe and between Europe and the advanced economies in Asia and North America. As European policy-makers focus on removing barriers to the revival of economic growth, international differences in the sources of growth have become central in understanding the impacts of changes in economic policy.

The EU KLEMS project identified the failure to develop a knowledge economy as the most important source of the slowdown in European economic growth. Development of a knowledge economy will require investments in human capital, information technology, and intellectual property. An important policy implication is that extension of the single market to the services industries, which are particularly intensive in the use of information technology, will be essential for the removal of barriers to the knowledge economy.

The Second World KLEMS Conference was held at Harvard University on August 2012[iv]. The conference included reports on recent progress in the development of industry-level datasets, as well as extensions and applications.[v] Regional organizations in Asia and Latin America have now joined the European Union in supporting research on industry-level datasets. Due to the growing recognition of the importance of these datasets, an effort is underway to extend the new framework to emerging and transition economies, such as Brazil, China, India, and Russia. 

LA-KLEMS, the Latin American Chapter of the World-KLEMS Initiative, was established in December 2009 at a conference at ECLAC, the Economic Commission for Latin America and the Caribbean, in Santiago, Chile[vi]. This Chapter is coordinated by ECLAC and includes seven research organizations in four leading Latin American countries – Argentina, Brazil, Chile, and Mexico.[vii] Mario Cimoli, Andre Hofman, and Nanno Mulder (2010) have summarized the results of the initial phase of the LA-KLEMS project.

A detailed report on Mexico KLEMS was published in 2013 by INEGI, the National Institute of Statistics and Geography.[viii] This was presented at an international seminar at the Instituto Techologico Autonoma de Mexico (ITAM) in Mexico City on October 2013[ix]. Mexico KLEMS includes a complete industry-level productivity database for 1990-2011 that is integrated with the Mexican national accounts. This database will be updated annually. A very important finding is that productivity has not grown in Mexico since 1990. Periods of positive economic growth have been offset by the negative impacts of the Mexican sovereign debt crisis of 1995, the U.S. dot-com crash in 2000, and the U.S. financial and economic crisis of 2007-2009.

Asia KLEMS, the Asian Chapter of the World KLEMS Initiative, was founded in December 2010 and the first Asia KLEMS Conference was held at the Asian Development Bank Institute in Tokyo in July 2011[x]. Asia KLEMS includes the Japan Industrial Productivity database[xi], the Korean Industrial Productivity database[xii], and the China Industrial Productivity database[xiii]. Industry-level databases have been constructed for Taiwan and work is underway to develop a similar database for Malaysia. These databases were discussed at the Second Asia KLEMS Conference, held at the Bank of Korea in Seoul in August 2013[xiv].

Kyoji Fukao (2012, 2013) has employed the JIP data base in analyzing the slowdown in productivity growth in Japan after 1991, now extending into the Two Lost Decades. The initial downturn in productivity growth followed the collapse of the “bubble” in Japanese real estate prices in 1991. A brief revival of productivity growth after 2000 ended with the sharp decline in Japanese exports in 2008-2009. This followed the rapid appreciation of the Japanese yen, relative to the U.S. dollar, after the adoption of a monetary policy of quantitative easing by the Federal Reserve, the U.S. central bank. When the Bank of Japan failed to respond, Japan experienced a much more severe downturn in productivity growth and a larger decline in output than the U.S. in the aftermath of the financial and economic crisis of 2007-2009.

The Third World KLEMS Conference was held in Tokyo in May 2014[xv]. This conference, discussed industry-level datasets for more than 40 countries, including those that participate in the three regional organizations that make up the World KLEMS Initiative – EU KLEMS in Europe, LA KLEMS in Latin America, and Asia KLEMS in Asia. In addition, the conference considered research on linking datasets for the 40 countries through the World Input-Output Database (WIOD)[xvi]. Another important theme of the conference was the extension of the measurement of capital inputs to include intangibles, such as human capital and intellectual property, as well as the familiar tangible assets – plant, equipment, and inventories.

Linked data sets are especially valuable in analyzing the development of global value chains in Asia, North America, and Europe. For this purpose international trade can be decomposed by tasks performed at each link of the value chain. Trade in tasks can be compared with trade in commodities, which involves “double-counting” of intermediate goods as products pass through the value chain. A central finding is that regional value chains are now merging into global value chains involving all the major countries in the world. The World Input-Output Database is now undergoing a substantial expansion at the OECD with support from the World Trade Organization[xvii].

The Third World KLEMS Conference included reports on new industry-level data sets for India and Russia. Russia KLEMS was released in July 2013 by the Laboratory for Research in Inflation and Growth at the Higher School of Economics in Moscow[xviii]. Russia’s recovery from the sharp economic downturn that followed the dissolution of the Soviet Union and the transition to a market economy has been very impressive. Surprisingly, increases in productivity growth widely anticipated by observers inside and outside Russia have characterized only the service industries, which were underdeveloped under central planning. Mining industries have attracted large investments, but these have not been accompanied by gains in efficiency. The recent collapse in world oil prices poses an important challenge for the future growth of the Russian economy.

The India KLEMS database was released in July 2014 by the Reserve Bank of India[xix], shortly after the Third World KLEMS Conference in Tokyo. This database covers 26 industries for the period 1980-2011. Beginning in the 1980’s, liberalization of the Indian economy has resulted in a gradual and sustained acceleration in economic growth and a transfer of resources from agriculture and manufacturing to the service industries. The most surprising feature of the acceleration in Indian economic growth has been the stagnant share of manufacturing and the rapid growth in the share of services. Given the shrinking share of agriculture and the size of the Indian agricultural labor force, another surprise is that growth of capital input has been the most important source of growth in manufacturing and services, as well as more recently in agriculture.


[i] For the program and participants see:

[ii] Updated data are available for the EU countries are posted on the EU KLEMS website:

[iii] For the program and participants see:

[iv] For the program and participants see:

[v] The conference program and presentations are available at:

[vi] For the program and participants see:

[x] For the program and participants see: Asia KLEMS was preceded by International Comparison of Productivity among Asian Countries (ICPAC). The results were reported by Jorgenson, Kuroda, and Motohashi (2007).

[xi] Data are available for 108 industries covering the period


[xiv] For the program and participants see:

Jorgenson, Dale W., and Khuong M. Vu. “Total Factor Productivity and the Sources of Singapore’s Economic Growth: Measurement, Insights, and Consequences.” In Productivity Dynamics in Emerging and Industrialized Countries, edited by Deb Kusum Das, 275-312. London: Routledge, Taylor and Francis, 2018.Abstract
Singapore has been a focal point in the debate on the East Asian growth model, in which total factor productivity growth (TFPG) is unusually low relative to remarkable output growth. We use a rigorous growth accounting framework to decompose the sources of Singapore’s growth, including information technology and labor quality. Our results show that TFPG in Singapore for long periods was as low as 0.5-0.6 per cent, which verifies Singapore’s low TFPG. However, we found that Singapore’s low TFPG was caused not by a steady low TFPG pattern but by its acute vulnerability to external shocks, which causes TFPG to plummet in periods of turmoil. Singapore’s vulnerability to external shocks is due to its large export-reliant manufacturing sector and small domestic market. Our results help to further advance our understanding about Singapore’s growth model from previous studies, such as Young (1992, 1995), Kim and Lau (1994), and Hsieh (2002). We predict that, based on our base-case projection results, Singapore’s growth over the next decade will be at 2.35 per cent for labor productivity and 3.10 per cent for GDP relative to the respective rates of 2.52 per cent and 5.45 per cent, for the period of 1998-2008.
Jorgenson, Dale W.The World KLEMS Initiative: Measuring Productivity at the Industry Level.” In The Oxford Handbook of Productivity Analysis, edited by Emili Grifell-Tatje, C.A.Knox Lovell, and Robin C. Sickles, 1:663-698. New York: The Oxford University Press, 2018.Abstract

The World KLEMS Initiative was established at the First World KLEMS Conference at Harvard University in August 2010[i]. The purpose of this Initiative is to generate industry-level data on outputs, inputs, and productivity. Productivity is defined as output per unit of all inputs. The inputs consist of capital (K) and labor (L), the primary factors of production, and intermediate inputs of energy (E), materials (M), and services (S). The acronym KLEMS describes these inputs.  Industry-level data have been proved to be indispensable for analyzing the sources of economic growth for countries around the world.

International productivity comparisons are the second focus of industry-level productivity research. Productivity gaps between two countries are defined in terms of differences in productivity levels. These differences are measured by linking the productivity levels for each country by purchasing power parities for inputs and outputs. As an example, the purchasing power parity for Japan and the U.S. is defined as the price in Japan, expressed in yen, relative to the price in the U.S., expressed in dollars. Purchasing power parities can be defined in this way for commodities, industries, or aggregates like the GDP. Productivity gaps are essential for assessing competitive advantage and designing strategies for economic growth.

We review productivity measurement at the industry level in Section 2. The landmark EU (European Union) KLEMS study was initiated in 20003 and completed in 2008. This study  provided industry-level data sets for the countries of the European Union. These data have proved to be invaluable for analyzing the slowdown in European economic growth. The EU KLEMS study also included data for Australia, Canada, Japan, Korea, and the United States. These data have been widely used for international comparisons between European countries and the leading industrialized countries of Asia and North America.

Regional organizations – LA KLEMS in Latin America and Asia KLEMS in Asia – have joined the European Union in supporting industry-level research on productivity. The Latin American affiliate of the World KLEMS Initiative, LA KLEMS, was established in 2009 at the Economic Commission for Latin American and the Caribbean (ECLAC) in Santiago, Chile. The Asian affiliate, Asia KLEMS, was founded at the Asian Development Bank Institute (ADBI) in Tokyo in 2010. The regional organizations have stimulated the development of industry-level productivity measures for the emerging economies of Asia and Latin America, such as Brazil, China, and India, as well as measures for the advanced economies of Asia, Europe, and North America.

In Section 3 we present the KLEMS framework for productivity measurement for a single country. Development of this framework within the national accounts has the important advantage that official measures can be generated at regular intervals in a standardized format.[ii] The production account in current prices contains nominal outputs and incomes, while the production account in constant prices provides real outputs and inputs, as well as productivity. Paul Schreyer’s (2001) OECD Productivity Manual provided methods for productivity measurement within the national accounts.

A key feature of the KLEMS framework is a constant quality index of labor input that combines hours worked for different types of labor inputs by using labor compensation per hour as weights. Similarly, a constant quality index of capital input deals with the heterogeneity among capital services by using rental prices of these services as weights. Schreyer’s (2009) OECD Manual, Measuring Capital, presented methods for measuring capital services. Finally, inputs of energy, materials and services are generated from a time series of input-output tables in current and constant prices.

In 2008 the Advisory Committee on Measuring Innovation in the 21st Century to the U.S. Secretary of Commerce recommended that productivity data be incorporated into the U.S. national accounts. This was successfully completed by the Bureau of Economic Analysis (BEA), the agency responsible for the U.S. national accounts, and the Bureau of Labor Statistics (BLS), the agency that produces industry-level measures of productivity for the U.S. Susan Fleck, Steven Rosenthal, Matthew Russell, Erich Strassner, and Lisa Usher (2014) published an integrated BEA/BLS industry-level production account for the U.S. for 1998-2009 in Jorgenson, Landefeld, and Schreyer (2014).

In Section 4 we illustrate the KLEMS methodology for a single country by summarizing the industry-level productivity data for the United States for the period 1947-2012 compiled by Jorgenson, Ho, and Samuels (2016). We analyze the sources of U.S. economic growth for three broad periods: the Postwar Recovery of 1947-1973, the Big Slump of 1973-1995, following the energy crisis of 1973, and the period of Growth and Recession, 1995-2012. To provide more detail on the period of Growth and Recession, we analyze the sources of growth for the sub-periods 1995-2000, 2000-2007, and 2007-2012 – the Investment Boom, the Jobless Recovery, and the Great Recession.

In Section 5 we introduce the KLEMS framework for international comparisons by presenting price level indices and productivity gaps. The price level index is an indicator of international competitiveness, often expressed as over- or undervaluation of currencies. A specific example is the over- or undervaluation of the Japanese yen relative to the U.S. dollar.
The price level index for Japan and the United States compares market exchange rates with purchasing power parities for the GDP.

The productivity gaps between Japan and the U.S. are indicators of the relative efficiency of two countries in transforming inputs into outputs. To measure these productivity gaps we first construct comparable measures of productivity. We then link the U.S. and Japanese outputs and inputs at the industry level by means of purchasing power parities. As an illustration, the U.S. productivity data presented in Section 4 for 1947-2012 have been linked to comparable Japanese productivity data for 1955-2012 by Jorgenson, Nomura, and Samuels (2016).           

The international comparisons between Japan and the U.S. presented in Section 6 are based on industry-level purchasing power parities. These comparisons provide important information on the valuation of the Japanese yen relative to the U.S. dollar. The yen was under-valued from 1955 until the Plaza Accord of 1985. This enabled Japan to achieve a high level of international competitiveness, despite a large productivity gap with the United States. Since 1985 the yen has been over-valued, relative to the dollar, reaching a peak in 1995 that greatly undermined Japanese competitiveness. The yen finally achieved purchasing power parity with the dollar only in 2015, restoring Japanese international competitiveness after several years of monetary policies based on quantitative easing by the Bank of Japan.

The large productivity gap between Japan and the United States that existed in 1955 gradually closed until the end of the “bubble economy” in Japanese real estate in 1991. Since that time Japanese productivity has been stagnant, while productivity in the U.S. has continued to rise. The widening productivity gap can be traced to a relatively small number of industrial sectors in Japan, mainly in trade and services, but also including agriculture. Productivity gaps for Japanese manufacturing industries have remained relatively small. This has created opportunities for formulating a Japanese growth strategy based on stimulating productivity growth in the lagging industrial sectors. Section 7 presents our conclusions.


[i] For the program and participants see:

[ii] The World KLEMS website presents data sets in a common format for many of the participating countries. See:

Jorgenson, Dale W., ed.International Productivity Monitor: Special Issue from the Fourth World KLEMS Conference.” Fourth World KLEMS Conference. Madrid, Spain: Center for the Study of Living Standards, 2017. Publisher's Version
Jorgenson, Dale W., and Paul Schreyer. “Measuring Individual Well-Being and Social Welfare within the Framework of the System of National Accounts.” Review of Income and Wealth 63, no. Supplement 2 (2017): S460-S477. Publisher's VersionAbstract
While the agenda of “beyond GDP” encompasses measurements that lie outside boundaries of the System of National Accounts, key aspects of individual well-being and social welfare can be incorporated into an SNA framework. We bring together the relevant theoretical literature and the empirical tools needed for this purpose. We show how consumption-based measures of economic welfare can be integrated into the national accounts without changing their production or asset boundary. At the same time, explicit normative and methodological choices are required to select a social welfare function. The paper provides guidance how to make these choices transparent and how to present social welfare measures.
Jorgenson, Dale W., and Khuong M. Vu. “The Outlook for Advanced Economies.” Journal of Policy Modeling 39, no. 4 (2017): 660-672. Publisher's VersionAbstract

According to the authoritative estimates of Angus Maddison, the United States was the world’s largest economy throughout the twentieth century.[1] International economic cooperation among the world’s industrialized countries began to take its contemporary form with the formation of the G7 in 1975 and 1976. The G7 includes the U.S., the four major European countries – France, Germany, Italy, and the U.K – as well as Canada and Japan.

During most of the twentieth century a fundamental transformation of the world economy seemed a remote and unlikely prospect. However, in the twenty-first century the balance of the world economy is shifting from the industrialized economies, led by Europe, Japan, and the United States, to the emerging economies of Asia, especially China and India. The massive shift in the world economy is generating a new world order.

The World Bank’s 2005 International Comparison Program (ICP2005) showed that China had overtaken Japan in terms of purchasing power more than a decade earlier.[2] By 2012 India had overtaken Japan and has continued to grow much more rapidly. The World Bank’s 2011 International Comparison Program (ICP2011) revealed that China’s output achieved parity with the United States in terms of purchasing power in 2014.[3]  

Our first major finding is that world economic growth has accelerated during the twenty-first century. While world economic growth will continue at a rapid pace, we project that all the members of the G7 will grow more slowly that the world economy, while China and India will continue to grow more rapidly. However, Chinese economic growth has already slowed and Indian growth will follow. The Chinese and Indian economies will continue to increase in relative importance during the twenty-first century as the rate of growth of the world economy gradually declines.

In 2001 Jim O’Neill, then a Goldman-Sachs economist, originated the terminology “BRIC” economies -- Brazil, Russia, India, and China.[4] For many purposes the G7 was superseded by the G20 in 2009, including the G7 as well as the four BRIC countries, eight other countries, and the European Union. The four BRIC countries formed a group to meet before the G20 and added South Africa, becoming the “BRICS”.  The G7 countries participate actively in the G20 and have formed a similar group.  

The second major finding of this paper is that Brazil and Russia, as well as Germany, Japan, and the United States, will grow more slowly than the world economy. The leading economies in developing and implementing the Asian model of economic growth were, first, Japan, then the Asian Tigers – Hong Kong, Singapore, South Korea, and Taiwan – and finally China and India. The performance of these Asian economies has changed the course of economic development in Asia and around the world.

The Asian model of economic growth relies on globalization and investment in human and non-human capital, rather than innovation. This new growth paradigm places a high premium on skillful management by public and private authorities. Of course, investment and innovation are analytical categories for characterizing different aspects of the complex processes that generate long-term growth and structural change.

The third major finding of this paper is that replication rather than innovation is the major source of growth of the world economy. Replication takes place by adding identical production units with no change in technology. Labor input grows through the addition of new members of the labor force with the same education and experience. Capital input expands by providing new production units with the same collection of plant and equipment. Output expands in proportion with no change in productivity. By contrast, successful innovation involves the creation of new products and new processes, so that productivity increases.

Recovery of the industrialized economies from the Great Recession that began in the United States in 2007-2009 has been slow and fitful. The United States has emerged with low unemployment but reduced prospects for growth. Japan has continued to languish in the Lost Decades, awaiting the successful implementation of a new growth strategy. The fiscal and financial burden of public debt and the challenges of coping with the financial crisis in Greece pose potential threats to the restoration of growth in Europe.

The most significant impact of the Great Recession on the emerging economies of Asia was the collapse of trade in late 2008 and early 2009. This was quickly reversed and the leading Asian economies have continued to grow more rapidly than the world economy. The challenges facing these economies are different but equally daunting. Can China cope with the financial and economic pressures that followed a vast expansion of lending in response to the economic crisis? Will India succeed with fiscal consolidation and restoration of growth?

The growing significance of the Asian model is overturning long-established theories of economic growth and accelerating overdue revisions of the official economic statistics. The ruling theories of growth of the twentieth century put enormous weight on innovation, which has played a relatively modest role. This view has neglected investments in human and nonhuman capital, which are much more important for advanced economies as well as emerging economies. The new economic order will help to establish this empirically-based view of the sources of economic growth.

In this paper we set aside short-term threats to the world economy to focus on the potential for long-term growth. We show that the fundamentals of the world economy remain sound. We recognize the emergence of Asia from the underdevelopment that persisted until the middle of the twentieth century as the great economic achievement of our time. Trends established in the watershed reforms of China and India more than two decades ago have produced the dramatic changes of economic leadership in the twenty-first century.


[1] Angus Maddison (2001), The World Economy: A Millennial Perspective, Paris, Organisation for Economic Co-Operation and Development, 2001. See:

[2]  World Bank (2008), 2005 International Comparison Program, February. See:

[3] World Bank (2014) , 2011 International Comparison Program, October. See:

[4] O’Neill’s book describing the progress of the BRIC was published in 2011: Jim O’Neill (2011), The Growth Map: Economic Opportunity in the BRICs and Beyond, New York, Penguin.

Jorgenson, Dale W.Productivity and Economic Growth in the World Economy: An Introduction.” International Productivity Monitor: Special Issue from the Fourth World KLEMS Conference 33, no. Fall (2017): 1-7. Publisher's Version ipm.4th.world_.klems_.conference.pdf
Dale W, Jorgenson. “The More Global Value Chains Expand, the More the TPP Makes Sense.” Nikkei Asian Review, 2016, August 23. Publisher's Version
Jorgenson, Dale W., Mun S. Ho, and Jon D. Samuels. “The Recovery of Employment and the Revival of U.S. Economic Growth.” Vox, 2016, November 1, 2016. Publisher's Version
Jorgenson, Dale W., and Khuong Minh Vu. “The Outlook for Emerging Economies.” Journal of Policy Modeling 38, no. 4 (2016): 670-682. Publisher's Version
Jorgenson, Dale W., Koji Nomura, and Jon D. Samuels. “A Half Century of Trans-Pacific Competition: Price Level Indices and Productivity Gaps for Japanese and US Industries, 1955-2012.” In The World Economy: Growth or Stagnation? 469-507. Cambridge, UK: Cambridge University Press, 2016. Publisher's Version
Jorgenson, Dale W., Mun S. Ho, and Jon D. Samuels. “US Economic Growth -- Retrospect and Prospect: Lessons from a Prototype Industry-Level Production Account for the US, 1947-2012.” In The World Economy: Growth or Stagnation, 34-69. Cambridge, UK: Cambridge University Press, 2016. Publisher's Version
Jorgenson, Dale W.The New World Order.” In The World Economy: Growth or Stagnation? 1-33. Cambridge, UK: Cambridge University Press, 2016.
Jorgenson, Dale W.Econometric General Equilibrium Modeling.” Journal of Policy Modeling 38, no. 3 (2016): 436-447. Publisher's VersionAbstract

The point of departure for the study of the impact of energy and environmental policies is the neo-classicaltheory of economic growth formulated by Cass (1965) and Koopmans (1967). The long-run properties ofeconomic growth models are independent of energy and environmental policies. However, these policiesaffect capital accumulation and rates of productivity growth that determine the intermediate-run trends thatare important for policy evaluation.

Heterogeneity of different energy producers and consumers is critical for the implementation of energyand environmental policies. To capture this heterogeneity it is necessary to distinguish among commodities,industries, and households. Econometric methods are essential for summarizing information on differentindustries and consumer groups in a form suitable for general equilibrium modeling.

In this paper we consider the application of econometric general equilibrium modeling to the U.S., theeconomy that has been studied most intensively. The framework for our analysis is provided by the Intertem-poral General Equilibrium Model (IGEM) introduced by Jorgenson and Wilcoxen (1990). The new versionof the IGEM presented in this paper is employed for the evaluation of proposed legislation on climate policyby the U.S. Environmental Protection Agency (2011).© 2016 Published by Elsevier Inc. on behalf of The Society for Policy Modeling.

The World Economy: Growth or Stagnation?
Jorgenson, Dale W., Kyoji Fukao, and Marcel P. Timmer, ed. The World Economy: Growth or Stagnation?. Cambridge, UK: Cambridge University Press, 2016. Publisher's VersionAbstract

The balance of the world economy is shifting away from the established economies of Europe, Japan, and the USA, towards the emerging economies of Asia, especially India and China. With contributions from some of the world's leading growth theorists, this book analyses the long-term process of structural change and productivity growth across the world from a unique comparative perspective. Ongoing research from the World KLEMS Initiative is used to comparatively study new sources of growth - including the role of investment in intangible assets, human capital, technology catch-up, and trade in global value chains. This book provides comparisons of industries and economies that are key to analysing the impacts of international trade and investment. This makes it an ideal read for academics and students interested in understanding current patterns of economic growth. It will also be of value to professionals with an interest in the drivers of economic growth and crisis.

  • This is the first book that analyses the process of structural change and productivity growth in Asia, Europe, Latin America and the USA from a long-term comparative perspective
  • Relies on industry-level data for individual economies, rather than abstract conceptual models, and uses a common methodology throughout, to maximise accessibility
  • Provides state-of-the-art techniques, whilst remaining accessible for non-specialists
  • The information in the book is backed up by ongoing active research efforts
Jorgenson, Dale W., and Khuong M. Vu. “Australia and the Growth of the World Economy: 24th Colin Clark Memorial Lecture.” Economic Analysis and Policy 47, no. September (2015): 90-100.
Jorgenson, Dale W., Mun S. Ho, and Jon D. Samuels. “The Impact of Information Technology on Postwar U.S. Economic Growth.” Telecommunications Policy November (2015).