Dynamic Efficiency in World Economy

2017

In a seminal paper, Abel et al. (1989) argue that the United States and six other major advanced economies are dynamically efficient. Updating data on mixed income and land rents, I find in contrast that the criterion for dynamic efficiency is not verified for any advanced economy, and that Japan and South Korea have unambiguously over-accumulated capital. This world “savings glut” can potentially explain otherwise hard-to-understand macroeconomic stylized facts low interest rates, cash holding by firms, financial bubbles. It is also the macroeconomic counterpart of the microeconomic observation that average firms’ return on investment is lower than their measured cost of capital. Subject to some caveats, an increase of public debt, or a generalization of pay-as-you-go systems could therefore be Pareto-improving.

1986

The issue ot dyn.aic efficiency is central to analyses of capital accueulation and economic growth. iet tne question of what operating characteristics of an econoay subject to productivity shocks should be examirieo to deteraine whether or riot it is e+iicient has not been raoi ved. This paoor do a criterion based or ooservabies tor oeteraarirg whether or not an economy is dynamically e+ficent. The criterion involves a coniparisori of the casr flows generated oy capital with the volume of investeert. Its application to the United States economy arid the ecoroci cc of other oiaor OECD nations sugqests that they are dynamically efficient.

2008

We compare economic efficiencies in Brazil, India, and China, where economic efficiency measures the gap between potential and actual output for a given input combination and technological factor. We use stochastic production frontier models to measure the contributions of factors of production and technology to growth and estimate non-positive error terms that capture production inefficiencies in each country. The results suggest that China and India had relatively inefficient production in the early 1980s but have since improved production efficiency substantially. In the same period, production efficiency in Brazil has declined somewhat from relatively high initial levels and the gap between production efficiency between these countries has narrowed substantially, supporting more rapid growth in China and India relative to Brazil.

2008

We compare economic efficiencies in Brazil, India, and China, where economic efficiency measures the gap between potential and actual output for a given input combination and technological factor. We use stochastic production frontier models to measure the contributions of factors of production and technology to growth and estimate non-positive error terms that capture production inefficiencies in each country. The results suggest that China and India had relatively inefficient production in the early 1980s but have since improved production efficiency substantially. In the same period, production efficiency in Brazil has declined somewhat from relatively high initial levels and the gap between production efficiency between these countries has narrowed substantially, supporting more rapid growth in China and India relative to Brazil.

This research analyzes economic growth from the theory of dynamic efficiency, using a global indicator of competitiveness and one of global economic freedom, starting from the hypothesis that greater economic freedom translates into greater competitiveness and economic growth. The dynamic efficiency supported by authors of the Austrian economy aims to explain how the increase in profitability and productivity in the production of goods and services depends mainly on business creativity. From the methodological point of view, the study is descriptive, correlational and prospective, using panel data from the 20 largest economies in the American continent. The study analyzes the main macroeconomic indicators, the quality of institutions, health, primary education, infrastructure and the degree of business innovation, correlated with variables that measure the level of freedom to do business, fiscal pressure, size of government, security Legal, competitiveness is measured through the factors that determine the productivity of an economy. Among the main results, it was found that the index of economic freedom and the GDP per capita show a bidirectional causal relationship in the Granger sense, thus revealing an endogenity relationship between both variables. The degree of cointegration, causality and explanation of competitiveness and economic freedom with economic growth was demonstrated.

The Journal of Developing Areas, 2004

This study compares the sources of growth in East Asia with the rest of the world, using a methodology that allows one to decompose total factor productivity (TFP) growth into technical efficiency changes (catching up) and technological progress. It applies a varying coefficients frontier production function model to aggregate data for the period 1970-1990, for a sample of 45 developed and developing countries. Our results are consistent with the view that East Asian economies were not outliers in terms of TFP growth. Of the high-performing East Asian economies, our methodology identifies South Korea as having the highest TFP growth, followed by Singapore, Taiwan and Japan. Our methodology also allows us to separately estimate technical efficiency change, which is a component of TFP growth, and we find that, in general, the estimated technical efficiency of the high-performing East Asian economies was not out of line with the rest of the world.

Economic Modelling, 2007

This paper differs from the current literature in supposing that human capital influences growth indirectly and not directly as the new growth theory assumes, through its impact on a country's efficiency performance. We also allow for the impact of openness, terms of trade, human capital and inflation on efficiency performance. This approach offers additional evidence as to why growth rates differ among countries. A DEA methodology is adopted to estimate the efficiency index of each country. The results suggest that movements towards openness increase the efficiency performance of the non-OECD countries, while the OECD countries experienced slightly faster efficiency changes relative to the formers.

Journal of Productivity Analysis, 1998

This paper presents two applications of rank statistics to evaluate efficiency performance trends using productive efficiency measures derived through various Data Envelopment Analysis (DEA) models. The paper starts with a discussion of the difficulties in obtaining consistent ranks from DEA efficiency ratings. Next, a procedure is proposed to identify intertemporal performance trends using any one of several possible efficiency measures. Another procedure is then developed to test the stability over time of the rank positions of the analyzed units. For each statistical procedure, a small numerical example involving DEA efficiency measures is provided to illustrate the proposed technique. Finally, the new procedures are applied to data reflecting the macro-economic performance of 17 OECD nations in 1979-1988. The outcomes of the application are discussed and contrasted with previous research in this area.

Procedia. Economics and finance, 2016

This paper tries to examine the relationship between the input use efficiency and economic growth for low income, upper-middle income and high income countries over the period 1991 to 2011 using data envelopment analysis (DEA). Input (labor, capital and energy) use efficiency may be defined as the ratio of input use to gross domestic product. However, this ratio or measurement is not a good indicator of input use efficiency. Improvements in input use refer to a reduction in input used for a given output or GDP, then they indicate input use efficiency. Hence, either deterministic (DEA) or non-deterministic (stochastic frontier approach) approaches within the framework of production theory have been used to measure input use efficiency. This paper also aims to make some policy implications on input use efficiency.

The Developing Economies, 2006

Financial development may lead to productivity improvement in developing countries. In this paper, based on the Data Envelopment Analysis (DEA) approach, we use the Malmquist index to measure China's total factor productivity change and its two components (i.e., efficiency change and technical progress). We find that China has recorded an increase in total factor productivity from 1993 to 2001, and that productivity growth was mostly attributed to technical progress, rather than to improvement in efficiency. Moreover, using panel data set covering 29 Chinese provinces over the period of 1993-2001 and applying the Generalized-Method-of-Moment system estimation, we investigate the impact of financial development on productivity growth in China. Empirical results show that, during this period, financial development has significantly contributed to China's productivity growth, mainly through its favourable effect on efficiency.