Publications on Total factor productivity (TFP)
There are 3 publications for Total factor productivity (TFP).
Working Paper No. 998 | January 2022
A Critique of Aggregate IndicatorsEconomic analysts have used trends in total factor productivity (TFP) to evaluate the effectiveness with which economies are utilizing advances in technology. However, this measure is problematic on several different dimensions. First, the idea that it is possible to separate out the relative contribution to economic output of labor, capital, and technology requires ignoring their complex interdependence in actual production. Second, since TFP growth has declined in recent decades in all of the developed market societies, there is good reason to believe that the decline is an artifact of the slower rates of economic growth that are linked to austerity policies. Third, reliance on TFP assumes that measures of gross domestic product are accurately capturing changes in economic output, even as the portion of the labor force producing tangible goods has declined substantially. Finally, there are other indicators that suggest that current rates of technological progress might be as strong or stronger than in earlier decades.Download:Associated Program:Author(s):Fred Block
Working Paper No. 994 | October 2021
Biased Coefficients and Endogenous Regressors, or a Case of Collective Amnesia?The possible endogeneity of labor and capital in production functions, and the consequent bias of the estimated elasticities, has been discussed and addressed in the literature in different ways since the 1940s. This paper revisits an argument first outlined in the 1950s, which questioned production function estimations. This argument is that output, capital, and employment are linked through a distribution accounting identity, a key point that the recent literature has overlooked. This identity can be rewritten as a form that resembles a production function (Cobb-Douglas, CES, translog). We show that this happens because the data used in empirical exercises are value (monetary) data, not physical quantities. The argument has clear predictions about the size of the factor elasticities and about what is commonly interpreted as the bias of the estimated elasticities. To test these predictions, we estimate a typical Cobb-Douglas function using five estimators and show that: (i) the identity is responsible for the fact that the elasticities must be the factor shares; (ii) the bias of the estimated elasticities (i.e., departure from the factor shares) is, in reality, caused by the omission of a term in the identity. However, unlike in the standard omitted-variable bias problem, here the omitted term is known; and (iii) the estimation method is a second-order issue. Estimation methods that theoretically deal with endogeneity, including the most recent ones, cannot solve this problem. We conclude that the use of monetary values rather than physical data poses an insoluble problem for the estimation of production functions. This is, consequently, far more serious than any supposed endogeneity problems.Download:Associated Program:Author(s):Jesus Felipe John McCombie Aashish Mehta Donna Faye Bajaro
Working Paper No. 946 | February 2020
A Comment on Autor and SalomonsWe show that Autor and Salomons’ (2017, 2018) analysis of the impact of technical progress on employment growth is problematic. When they use labor productivity growth as a proxy for technical progress, their regressions are quasi-accounting identities that omit one variable of the identity. Consequently, the coefficient of labor productivity growth suffers from omitted-variable bias, where the omitted variable is known. The use of total factor productivity (TFP) growth as a proxy for technical progress does not solve the problem. Contrary to what the profession has argued for decades, we show that this variable is not a measure of technical progress. This is because TFP growth derived residually from a production function, together with the conditions for producer equilibrium, can also be derived from an accounting identity without any assumption. We interpret TFP growth as a measure of distributional changes. This identity also indicates that Autor and Salomons’ estimates of TFP growth’s impact on employment growth are biased due to the omission of the other variables in the identity. Overall, we conclude that their work does not shed light on the question they address.Download:Associated Programs:Author(s):Jesus Felipe Donna Faye Bajaro Gemma Estrada John McCombie