Differences In Total Factor Productivity Research Articles

Productivity in the OECD Countries: A Critical Appraisal of the Evidence

The failure of the neoclassical growth model to account for differences in output per worker across countries has suggested that these differences should be driven by cross-country differences in total factor productivity (TFP). This paper discusses various measures of productivity and its determinants for the OECD countries from different dimensions: (i) the measurement perspective; (ii) evidence on the evolution of productivity levels across OECD countries; and (iii) a critical review of the theoretical and empirical issues regarding the determinants of cross-country productivity differentials.

Sources of Economic Growth: An Extensive Growth Accounting Exercise

A growth accounting exercise is conducted for 88 countries for 1960-94 to examine the source of cross-country differences in total factor productivity (TFP) levels. Two differences distinguish this analysis from that of the related literature. First, the critical technology parameter – the share of physical capital in output – is econometrically estimated and the usual assumption of identical technology across regions is relaxed. Second, while the few studies on the determinants of cross-country differences in TFP have focused on growth rates of real output this analysis is on levels. Recent theoretical as well as empirical arguments point to the level of TFP as the more relevant variable to explain.

Estimation of cross-country differences in industry production functions

International trade economists typically assume that there are no cross-country differences in industry total factor productivity (TFP). In contrast, this paper finds large and persistent TFP differences across a group of industrialized countries in the 1980s. The paper calculates TFP indices, and statistically examines the sources of the observed large TFP differences across countries. Two hypotheses are examined to account for TFP differences: constant returns to scale production with country-specific technological differences, and industry-level scale economies with identical technology in each country. The data support the constant returns/different technology hypothesis over the increasing returns/same technology hypothesis.

Sources of Economic Growth: An Extensive Growth Accounting Exercise

A growth accounting exercise is conducted for 88 countries for 1960-94 to examine the source of cross-country differences in total factor productivity (TFP) levels. Two differences distinguish this analysis from that of the related literature. First, the critical technology parameter—the share of physical capital in real output—is econometrically estimated and the usual assumption of identical technology across regions is relaxed. Second, while the few studies on the determinants of cross-country differences in TFP have focused on growth rates of real output this analysis is on levels. Recent theoretical as well as empirical arguments point to the level of TFP as the more relevant variable to explain.

Sources of Economic Growth: An Extensive Growth Accounting Exercise

A growth accounting exercise is conducted for 88 countries for 1960-94 to examine the source of cross-country differences in total factor productivity (TFP) levels. Two differences distinguish this analysis from that of the related literature. First, the critical technology parameter—the share of physical capital in real output—is econometrically estimated and the usual assumption of identical technology across regions is relaxed. Second, while the few studies on the determinants of cross-country differences in TFP have focused on growth rates of real output this analysis is on levels. Recent theoretical as well as empirical arguments point to the level of TFP as the more relevant variable to explain.

Firm-Level Evidence on Productivity Differentials, Turnover, and Exports in Taiwanese Manufacturing

The manufacturing sector in Taiwan has a market structure composed of large numbers of small firms, a focus on less capital-intensive industries, and a dense network of firms specializing in subcontracting and trading services. It has been argued that these features lower the start-up costs of new manufacturing firms. Recent theoretical models of market evolution show that low sunk entry and exit costs act to speed firm turnover by facilitating entry and increasing the pressure on inefficient firms to exit. As a result, low cost entry and exit may help improve aggregate productivity by allowing for the rapid transfer of resources from less to more efficient producers within an industry. Using comprehensive firm-level panel data from the Taiwanese Census of Manufactures for 1981, 1986, and 1991, we measure differences in total factor productivity among entering, exiting, and continuing firms, and quantify the contribution of firm turnover to industry productivity improvements. We find notable differences in productivity across manufacturing firms that are reflected in turnover patterns in both the domestic and export market. Cohorts of new firms have lower average productivity than incumbents but are also a heterogeneous group. The more productive members of the group survive and in many cases their productivity converges to the productivity level of incumbents. Exiting firms are less productive than survivors. Exporters, including firms that recently left the export market, are more productive than nonexporters. These patterns are consistent with the view that both the domestic and export market sort out high productivity from low productivity firms and that the export market is a tougher screen.

Lawrence R. Klein Lecture 1997: Needed: A Theory of Total Factor Productivity

This paper evaluates the argument that differences in physical and intangible capital can account for the large international income differences that characterize the world economy today. The finding is that they cannot. Savings rate differences are of minor importance. What is all-important is total factor productivity (TFP). In addition, the paper presents industry evidence that TFPs differ across countries and time for reasons other than differences in the publicly available stock of technical knowledge. These findings lead the author to conclude a theory of TFP is needed. This theory must account for differences in TFP that arise for reasons other than growth in the stock of technical knowledge. Copyright 1998 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Estimation of Cross-Country Differences in Industry Production Functions

International trade economists typically assume that there are no cross-country differences in industry total factor productivity (TFP). In contrast, this paper finds large and persistent TFP differences across a group of industrialized countries in the 1980s. The paper calculates TFP indices, and statistically examines the sources of the observed large TFP differences across countries. Two hypotheses are examined to account for TFP differences: constant returns to scale production with country-specific technological differences, and industry-level scale economies with identical technology in each country. The data support the constant returns/different technology hypothesis over the increasing returns/same technology hypothesis.

Costs and Productivity in Automobile Production: The Challenge of Japanese Efficiency

Preface 1. Introduction 2. International differences in output, productivity and wages in the automobile industry: the 1950s to the mid-1980s 3. The cost-function approach to the analysis of cost and total factor productivity differences 4. Data base sources and method of construction 5. Empirical results: estimation of the cost function 6. Productivity growth in the automobile industry, 1970-84: a comparison of the United States, Japan, Germany and Canada 7. International comparisons of automobile industry cost and productivity levels: Japan, Germany and the United States 8. International comparisons of automobile industry cost and productivity levels: Canadian with US, Japanese and German production 9. Summary and conclusions References Index.

Analysis of Productivity at the Firm Level: An Application to Life Insurers

Analysis of at the Firm Level: An Application to Life Insurers: Comment The non-parametric measurement of total factor productivity (TFP) has become widely accepted and applied to many industries [2], and more recently to life insurers. A limitation of this approach is that differences in TFP may arise due to factors other than production efficiency. Denny, Fuss and Waverman [5], for example, identify two additional attributes to differences in TFP across time: exploitation of economies of scale, and changes in deviation from marginal cost pricing. To help overcome these limitations, various researchers employed the parametric technique of neoclassical cost estimation [10]. The parametric approach is a more general and detailed specification of the production structure of an industry or a company than the TFP approach. Further, in most recent studies of this type, researchers have utilized flexible functional forms in order to avoid imposing unnecessary restrictions on the production technology (see for example Berndt and Khaled [1] among many others). This approach is appealing but is often expensive to undertake and requires substantial time series observations. For practitioners, however, TFP analysis has various advantages. TFP is a relative measure showing how the ratio of total output to total input changes from one period to the other. It is relatively inexpensive to perform and since the data are displayed in an index number form, it is easy to identify anomalies in the data. In addition, TFP and the variables used in its construction may reveal valuable information on trends and changes in an industry. Moreover, Diewert and Morrison [7] have added another factor, the terms of trade effect, in explaining productivity. This Comment extends the study of Weiss [13] in which new techniques for measuring output of life insurers are developed and used in computing divisia and exact indexes of TFP for one stock and one mutual insurer over a five-year interval. Weiss [13] maintains that because the rate of technological change calculated using the Tornqvist approximation (TFP) equals the exact measure of the shift of the variable cost function due to technological change ( t) (see Diewert [6]), the nature of returns to scale is constant. In her words, Productivity theory suggests that superlative indexes such as the exact index and the Tornqvist-Theil approximation to the divisia index yield similar results if the production function reflects constant returns to scale, regardless of whether the insurer is acting competitively... [13, p. 74]. Given the result obtained by Weiss, which indicates that the divisia and exact indexes vary directly with each other, it was concluded that ...the sample insurers' production functions exhibited constant returns to scale over the sample periods [13, p. 74]. While this is true if all inputs are variable, if some of the inputs are fixed (e.g. number of square feet of home office building and constant dollar capital input in Weiss), the statement is in error, primarily because the shift in the variable cost function due to technological change ( t) is greater than the negative value of the overall production relationship's rate of technological change ( t). that is, t at t where at is the mean share of variable relative to total costs (at The latter can be proven with the aid of two equations: t = 1/2 (at + at - 1) t + R ( ) where t is the shift in total cost function due to technological change and R ( ) is a remainder term of first differences which are at least of second order. t = - t + R* ( ) where t is the rate of technological change corresponding to the joint production function (of all inputs), and R* ( ) is a remainder term of finite differences which are at least of second order.(1) Now suppose there is a constant mark-up, over marginal cost pricing structure. …

Regional difference in total factor productivity and spatial features: Empirical Analysis on the Basis of a Sectoral Translog Production Function

This paper applies a sectoral production function of translog type to Japanese regional data, introducing the variables of spatial attributes as the determinants of the technological level in the region, and thereby analyses the regional difference in total factor productivity.