Technology Adoption Costs and Productivity Growth: The Transition to Information Technology

Using two panels of U.S. manufacturing industries, this paper estimates capital adjustment costs from 1961 to 1996. I find that from 1974–1983 adjustment costs rose sharply—they more than doubled from about 3% of output to around 7%. Moreover, this increase is specifically associated with a shift to investment in information technology. But such large adoption costs imply that the Solow residual mismeasures productivity growth: Adoption costs are resource costs representing an unmeasured investment. I find that when this investment is included, productivity grew about 0.4% per annum faster than official measures during the 1970's and early 1980's, reducing the size of the productivity “slowdown.” Indeed, estimated productivity growth rates were roughly the same from 1974–1988 as from 1949–1973. Thus technology transitions critically affect productivity growth measurement. Journal of Economic Literature Classification Numbers: O30, O47, E22.     

Argentina's Lost Decade

Argentina suffered a depression in the 1980s that was as severe as the Great Depression experienced in the United States and Germany in the interwar period. Our paper examines this depression from the perspective of growth theory, taking total factor productivity as exogenous. The predictions of the growth model conform rather well with the observations during the “lost decade” years. Journal of Economic Literature Classification Codes: E32, O40, N46.     

Sources of Productivity Growth Dynamics: Is Japan Suffering From Baumol's Growth Disease?

This study examines the sources of labor productivity growth dynamics in Japan (1970–2010) and investigates the extent to which Japanese economic performance has been affected by Baumol's growth disease (BGD). We find that BGD silently undermines Japanese economic growth. However, the magnitude is miniscule, and consequently the aggregate labor productivity growth rate has not been decreasing monotonically. We also explore how BGD is arising and why it is small in the Japanese economy. BGD is weak because (1) the positive Baumol growth effect is also working in certain services sectors and (2) BGD is not a durable phenomenon: even if a sector begins to suffer from BGD, it is likely to recover quickly.     

The Role of Real Wages,Productivity, and Fiscal Policy in Germany's Great Depression 1928–1937

We study the behavior of output, employment, consumption, and investment in Germany during the Great Depression of 1928–1937. In this time period, real wages were countercyclical, and productivity and fiscal policy were procyclical. We use the neoclassical growth model to investigate how much these factors contribute to the depression. We find that real wages, which were significantly above their market clearing levels, were the most important factor for the economic decline in the depression. Changes in productivity and fiscal policy were also important for the decline and recovery. Even though our analysis is limited to a small number of factors, the model accounts surprisingly well for the depression in Germany. Journal of Economic Literature Classification Numbers: E13, E32, E62, N14, O47.     

Sectoral and Aggregate Technology Shocks:Is There a Relationship?

We analyze sector-specific shocks in productivity and demand in 19 manufacturing sectors of the Austrian economy. Based on a structural vector autoregressive model (SVAR) with long-run restrictions developed by Galí (1999) we extract technology and non-technology shocks from sectoral and aggregate data. We study their patterns and relationship by means of a principal components analysis and find a close association of sectoral and macroeconomic non-technology shocks but only a very weak association for technology shocks. Impulse response analysis indicates that for almost all manufacturing sectors as well as the aggregate Austrian economy productivity growth rates experience an immediate increase due to positive technology shocks while hours worked decline. Thereby we confirm Galís results on the level of Austrian manufacturing industries. From regression analysis, we find that our shocks are closely associated to employment growth and output growth but not to investment growth and that the reaction is different for the aggregate economy and manufacturing industries.JEL codes: D24, E23, E32, O30We thank Werner Müller and the participants of the 2004 conference of the Austrian Economic Association (NOeG) for helpful comments. We would like to thank an anonymous referee for many helpful comments that led to a substantial improvement of the paper. The usual disclaimer applies. This research project was supported by a research Grant (Project Nr. 9800) of the Jubiläumsfonds der Österreichische Nationalbank (OeNB).     

The Great Depression in Canada and the United States: A Neoclassical Perspective

Canada suffered a major depression from 1929 to 1939. In terms of output it was similar to the Great Depression in the United States. However, total factor productivity (TFP) in Canada did not recover relative to trend, while in the United States TFP had recovered by 1937. We find that the neoclassical growth model, with TFP treated as exogenous, can account for over half of the decline in output relative to trend in Canada. In contrast, we find that conventional explanations for the Great Depression—monetary shocks, terms of trade shocks, and labor market and competition policies—do not work for Canada. Journal of Economic Literature Classification Numbers: E30, N12, N42.     

Sources of aggregate labour productivity growth in Canada and the United States

Abstract.  In this paper we propose a decomposition technique to examine the sources of industrial contribution to aggregate labour productivity growth. We show that in terms of pure labour productivity growth, the manufacturing and service sectors contributed equally to the aggregate Canada‐U.S. labour productivity growth gap during the 1987–98 period. But, in terms of total industrial contributions, which also take into account the contributions from a change in relative size, the service sector was the largest contributor. We also find that high labour productivity growth industries did not attract resources from stagnant industries – a phenomenon consistent with Baumol's cost disease of stagnant industries. JEL Classification: O47, C43     

MACROECONOMIC POLICY REFORMS AND PRODUCTIVITY GROWTH IN AFRICAN AGRICULTURE

This article employs a two‐stage procedure to investigate the impact of macroeconomic policy reforms on the agricultural productivity growth of 33 African countries from 1981 to 2001. In the first stage, we measure agricultural productivity using a nonparametric Malmquist productivity index. In the second stage, we build a generalized method of moments (GMM) model with a measure of structural adjustment program (SAP) intensity as a key instrument for macroeconomic policy reforms. We also control for the effects of globalization, civil violence, level of development of physical and financial infrastructure, and other economic variables as well as natural resource factors that directly affect agricultural productivity. Our results indicate a strong positive correlation between the extent of SAP intensity and agricultural productivity, suggesting that the macroeconomic policy reforms improved agricultural productivity growth in the sample countries. (JEL E6, O13, O41)     

Why are initial estimates of productivity growth so unreliable?

This paper argues that initial estimates of productivity growth will tend to be much less reliable than those of most other macroeconomic aggregates, such as output or employment growth. Two distinct factors complicate productivity measurement. (1) When production increases, factor inputs typically increase as well. Productivity growth is therefore typically less variable than output growth, meaning that measurement errors will tend to be relatively more important. (2) Revisions to published estimates of production and factor inputs tend to be less highly correlated than the published estimates themselves. This further increases the impact of data revisions on published productivity estimates.To assess the extent of these problems in practice, we detail the importance of historical revisions to the most commonly-used measures of US aggregate productivity growth, expanding on previous empirical work by Aruoba (2008) and Anderson and Kliesen (2006). We find that such revisions have contributed substantially to policymakers’ forecast errors for US productivity growth.     

The productivity trend in Iran Evidence from manufacturing firms

Iran has been experiencing slow growth for the past ten years. Using plant‐level information, we show that on average firm‐specific productivity in manufacturing sectors declined at the rate of 2.6% annually, while large top decile firms experienced a modest growth in productivity between 2005 and 2011. We decompose this trend and find that within‐plant variation is its main driving force while the between firms and industries component is insignificant. We test several alternative explanations that may contribute to these negative trends. We show that the subsidy reform had a negative effect, while privatization seems to have had no effect. Private management not affected productivity growth, while firm size is associated with higher productivity growth. Also, we find that productivity growth decreases with the energy intensity of the firm. We also find that R&D expenditures significantly increase productivity growth, while the R&D sales ratio is about 0.5% in manufacturing sectors, which is about one‐fifth of the world average. A one‐percent point increase in R&D expenditures increases productivity growth by 0.5%.     

Do process innovations boost SMEs productivity growth?

In this paper, we explore in depth the effect of process innovations on total factor productivity growth for small and medium enterprises (SMEs), taking into account the potential endogeneity problem that may be caused by self-selection into these activities. First, we analyse whether the ex-ante most productive SMEs are those that start introducing process innovations; then, we test whether process innovations boost SMEs productivity growth using matching techniques to control for the possibility that selection into introducing process innovations may not be a random process. We use a sample of Spanish manufacturing SMEs for the period 1991–2002, drawn from the Encuesta sobre Estrategias Empresariales. Our results show that the introduction of process innovations yields an extra productivity growth, and that the life span of this extra productivity growth lasts for only one period.     

What Happens When the Technology Growth Trend Changes? Transition Dynamics,Capital Growth,and the “New Economy”

This paper considers transition dynamics associated with a change in the rate of technological progress, using a general equilibrium framework that incorporates stochastic technology growth trends. The model suggests that these dynamics are associated with protracted transition periods, especially when technology growth is capital-embodied. Simulations of the post-WWII U.S. economy show that the model's propagation mechanism is capable of explaining a significant portion of variation in observed growth rates, particularly for investment, capital accumulation, and employment. The simulations suggest that positive shocks to the trend rate of technology growth in the mid-1980s and early 1990s were precursors to the productivity acceleration of the late 1990s. Journal of Economic Literature Classification Numbers: E32, E22, O40.     

Technological Change and the Scale of Production

Many manufacturing industries, including the computer industry, have seen large increases in productivity growth rates and have experienced a reduction in average establishment size. A vintage capital model is introduced which can account for this fact. It is shown that a rise in the rate of technological change decreases average plant size; that is, the level of innovation affects firm size. Smaller plants are not more innovative, as has been suggested, but industries with more innovation, as measured by productivity growth, have smaller plants. Journal of Economic Literature Classification Numbers: D2, O3.     

Finance and sources of growth: evidence from the U.S. states

How does financial development affect economic growth: through its impact on accumulation of physical and human capital or by boosting total factor productivity (TFP) growth? We use a new data set on output, inputs, and total factor productivity for the US states to study this question. Unlike previous cross-country research that tries to disentangle the channels through which financial development impacts growth, we use a plausibly exogenous measure of financial development: the timing of banking deregulation across states during the period 1970–2000. At the same time our new data set allows us to go beyond what was previously done in the state banking deregulation literature and identify whether finance impacts states’ input accumulation or TFP growth. We find, in line with existing cross-country studies, that deregulation boosts growth by accelerating both TFP growth and the accumulation of physical capital without having any impact on human capital. In contrast to the cross-country studies, we also find that the effects of deregulation are largely independent of states’ initial level of development; both rich and poor states grow faster after deregulation. Additionally, since our data set breaks down aggregate output into three sectors: agriculture, manufacturing, and the remaining industries, we are able to show that deregulation accelerates the growth of productivity in manufacturing. This last finding answers an important critique of the banking deregulation studies which asserts that observed growth effects may be coming from the growth of financial industry itself and not from the beneficial effect of finance on other industries, such as manufacturing.     

Is Social Security Really Bad for Growth?

This paper develops a model of endogenous growth with overlapping generations to investigate the joint determination of social security, public investment, and growth in a small open economy. We show that a pure pay-as-you-go system with benefits indexed to wages provides taxpayers with incentives to support growth-oriented policies, which increase the future productivity of labor. We find that outcomes characterized by positive levels of intergenerational redistribution, public investment, and long-run growth can be sustained as subgame-perfect Nash equilibria of an infinitely repeated intergenerational game, if and only if the marginal productivity of public capital is large enough. Furthermore, we show that transfers comove with public investment and growth. Journal of Economic Literature Classification Numbers: E62, H55.     

FACTOR DETERMINANTS OF TOTAL FACTOR PRODUCTIVITY GROWTH FOR THE JAPANESE MANUFACTURING INDUSTRY

This study uses industrial panel data for Japanese manufacturing to estimate the sources of productivity growth by simultaneously considering embodied technical progress, spillover effects, and openness, after controlling for returns to scale, imperfect competition, and capacity utilization. Estimation results show the existence of considerable embodied technical progress and interindustry externalities of capital investments positively affecting productivity growth. Furthermore, embodied technical progress causes research and development (R&D) capital to affect productivity growth insignificantly, suggesting that the impact of R&D is realized only after being embodied into other capitals. From sector‐wise estimations, we notice differences in factors affecting productivity growth between the durable and nondurable manufacturing sectors. (JEL D24, O30)     

Trade Policy and Productivity Growth in OECD Manufacturing *

Trade liberalization may promote economic growth in a number of ways, including by accelerating the rate of technological change. Firms that face more intense import competition may be spurred to greater rates of innovation; firms which export may absorb new technologies through their contact with international markets. This paper examines evidence on trade policy and productivity growth for a sample of thirteen OECD countries and including eighteen manufacturing sectors, using data primarily from the 1980s. Within individual sectors, there are strong productivity convergence effects within the OECD. After controlling for convergence, we find a positive association between high rates of productivity growth and low tariffs, and between high productivity growth and strong export performance. We found no particular association between high productivity growth and import penetration. The results are consistent with the possibility of positive linkages between trade liberalization and accelerated productivity growth. [F1, O4]     

Productivity Dynamics with Technology Choice: An Application to Automobile Assembly

During the 1980's, all Japanese automobile producers opened assembly plants in North America. Industry analysts and previous research claim that these transplants are more productive than incumbent plants and that they produce with a substantially different production process. I compare the production processes by estimating a model that allows for heterogeneity in technology and productivity, both of which are intrinsically unobservable. The model is estimated on a panel of assembly plants, controlling for capacity utilization and price effects.
The results indicate that the more recent technology uses capital more intensively and it has a higher elasticity of substitution between labour and capital. Hicks-neutral productivity growth is estimated to be lower, while capital-biased (labour-saving) productivity growth is higher for the new technology. Using the estimation results, I decompose industry-wide productivity growth and find plant-level changes in lean plants to be the most important contributor. Plant-level productivity growth is further decomposed to reveal the importance of capital-biased productivity growth, increases in the capital–labour ratio, and returns to scale.     

Canada–US productivity gap: The role of competition intensity differential

The relative lack of competitive pressure in product markets and lower investment in both fundamental and applied innovation are among the potential factors that have been put forward to explain Canada’s weak productivity performance with respect to the US. Since competition is generally seen as the single leading catalyst for fundamental and applied innovation, this paper analyzes the role of product market competition in the Canada–US productivity level gap. We develop an empirical framework in which competition exerts both direct and indirect effects on productivity, with the indirect impact coming through fundamental and applied innovation. We find statistically significant evidence that the competition intensity differential (between Canada and the US) has contributed to the Canada–US productivity level gap directly, as well as indirectly through lower investment in both R&D activities and M&E (including ICT) investment. We also find statistically significant evidence that Canada’s relatively poor performance in both productivity and M&E (including ICT) investment have acted as a self-reinforcing mechanism, which further causes detriment to the country’s productivity.     

VERTICALLY INTEGRATED PRODUCTIVITY MEASURES: TESTS OF STANDARD ASSUMPTIONS

In this paper we use an input-output framework to examine two criticisms of standard measures of total factor productivity. These criticisms are (1) that the contribution of capital to productivity growth is underestimated, and (2) that the use of cost shares to weigh factor input contribution is questionable. Using various vertically integrated productivity measures we find that capital's productivity contribution is underestimated in the neoclassical formulation. We also find that in a Pasinetti-Rymes growth model, factor shares do not approximate output elasticities. We conclude that the argument made by Pasinetti, Rymes, and others is supported, that in long-run productivity analysis capital should not be treated as a primary input, but should be measured as an intermediate, produced input.