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This paper introduces an alternative environmentally sensitive productivity growth index, which is circular and free from the infeasibility problem. In doing so, we integrated the concept of the global production possibility set and the directional distance function. Like the conventional Malmquist-Luenberger productivity index, it can also be decomposed into sources of productivity growth. The suggested index is employed in analyzing 26 OECD countries for the period 1990-2003. We also employed the conventional Malmquist-Luenberger productivity index, the global Malmquist productivity index and the conventional Malmquist productivity index for comparative purposes in this empirical investigation.

We propose an extension of the Olley and Pokes (1996) productivity decomposition that accounts for the contributions of surviving, entering, and exiting firms to aggregate productivity changes. We argue that the other decompositions that break down aggregate productivity changes into similar components introduce some biases in the measurement of the contributions of entry and exit. We apply our proposed decomposition to Slovenian manufacturing data and contrast our results with those of other decompositions. We find that, over a five-year period, the measurement bias associated with entry and exit is substantial, accounting for up to 10 percentage points of aggregate productivity growth.

This paper examines some of the recent literature on the estimation of production functions. We focus on techniques suggested in two recent papers, Olley and Pakes (1996) and Levinsohn and Petrin (2003). While there are some solid and intuitive identification ideas in these papers, we argue that the techniques can suffer from functional dependence problems. We suggest an alternative approach that is based on the ideas in these papers, but does not suffer from the functional dependence problems and produces consistent estimates under alternative data generating processes for which the original procedures do not.

Secular stagnation on the supply side takes the form of a slow 1.6 percent annual growth rate of US potential real GDP, roughly half the 3.1 percent annual growth rate of actual real GDP realized from 1972 to 2004. This slowdown stems from a sharp decline in the growth rate of aggregate hours of work and of output per hour. This paper attributes the productivity growth decline to diminishing returns in the digital revolution that had its peak effect business hardware, software, and best practices in the late 1990s but has resulted in little change in those methods over the past decade.

Economists have shown that large and persistent differences in productivity levels across businesses are ubiquitous. This finding has shaped research agendas in a number of fields, including (but not limited to) macroeconomics, industrial organization, labor, and trade. This paper surveys and evaluates recent empirical work addressing the question of why businesses differ in their measured productivity levels. The causes are manifold, and differ depending on the particular setting. They include elements sourced in production practices—and therefore over which producers have some direct control, at least in theory—as well as from producers' external operating environments. After evaluating the current state of knowledge, I lay out what I see are the major questions that research in the area should address going forward.

We investigate the role of sectoral labor productivity in explaining the process of structural transformation—the secular reallocation of labor across sectors—and the time path of aggregate productivity across countries. We measure sectoral labor productivity across countries using a model of the structural transformation. Productivity differences across countries are large in agriculture and services and smaller in manufacturing. Over time, productivity gaps have been substantially reduced in agriculture and industry but not nearly as much in services. These sectoral productivity patterns generate implications in the model that are broadly consistent with the cross-country data. We find that productivity catch-up in industry explains about 50% of the gains in aggregate productivity across countries, whereas low productivity in services and the lack of catch-up explain all the experiences of slowdown, stagnation, and decline observed across countries.

The pace and scale of China's economic transformation have no historical precedent. In 1978, China was one of the poorest countries in the world. The real per capita GDP in China was only one-fortieth of the U.S. level and one-tenth the Brazilian level. Since then, China's real per capita GDP has grown at an average rate exceeding 8 percent per year. As a result, China's real per capita GDP is now almost one-fifth the U.S. level and at the same level as Brazil. This rapid and sustained improvement in average living standard has occurred in a country with more than 20 percent of the world's population so that China is now the second-largest economy in the world. I will begin by discussing briefly China's historical growth performance from 1800 to 1950. I then present growth accounting results for the period from 1952 to 1978 and the period since 1978, decomposing the sources of growth into capital deepening, labor deepening, and productivity growth. But the main focus of this paper will be to examine the sources of growth since 1978, the year when China started economic reform. Perhaps surprisingly, given China's well-documented sky-high rates of saving and investment, I will argue that China's rapid growth over the last three decades has been driven by productivity growth rather than by capital investment. I also examine the contributions of sector-level productivity growth, and of resource reallocation across sectors and across firms within a sector, to aggregate productivity growth. Overall, gradual and persistent institutional change and policy reforms that have reduced distortions and improved economic incentives are the main reasons for the productivity growth.

It is widely recognized that information technology was critical to the dramatic acceleration of U.S. labor productivity growth in the mid 1990s. This paper traces the evolution of productivity estimates to document how and when this perception emerged. Early studies concluded that information technology was relatively unimportant. Only after the massive information technology investment boom of the late 1990s did this investment and underlying productivity increases in the information technology–producing sectors come to be identified as important sources of growth. Although information technology has diminished in significance since the dot-com crash of 2000 and observed growth rates have slowed recently, we project that private sector productivity growth will average around 2.4 percent per year for the next decade, only moderately below the average of the post-1995 period.

Since the mid-1990s, labor productivity growth in Europe has significantly slowed compared to earlier decades. In contrast, labor productivity growth in the United States accelerated, so that a new productivity gap has opened up. This paper shows that this development is attributable to the slower emergence of the knowledge economy in Europe. We consider various explanations which are not mutually exclusive. These include lower growth contributions from investment in information and communication technology; the small share of information and communications technology–producing industries in Europe; and slower multifactor productivity growth, which proxies for advances in technology and innovation. Underlying these are issues related to the functioning of European labor markets and the high level of product market regulation in Europe. The paper emphasizes the key role of market service sectors in accounting for the productivity growth divergence between the two regions. We argue that improved productivity growth in Europe's market services will be needed to avoid a further widening of the productivity gap.

Productivity differences across firms are large and persistent, but the evidence for worker reallocation as an important source of aggregate productivity growth is mixed. The purpose of this paper is to estimate the structure of an equilibrium model of growth through innovation designed to identify and quantify the role of resource reallocation in the growth process. The model is a version of the Schumpeterian theory of firm evolution and growth developed by Klette and Kortum (2004) extended to allow for firm heterogeneity. The data set is a panel of Danish firms that includes information on value added, employment, and wages. The model's fit is good. The estimated model implies that more productive firms in each cohort grow faster and consequently crowd out less productive firms in steady state. This selection effect accounts for 53% of aggregate growth in the estimated version of the model.