Of Yeast and Mushrooms: Patterns of Industry-Level Productivity Growth

Abstract. In this paper we analyse labour productivity growth in the United States, four European countries (France, Germany, the Netherlands and United Kingdom), Australia and Canada between 1987 and 2003 from an industry perspective. Rather than analysing broad industry groups, we compare the pattern of growth in all industries through Harberger diagrams. We introduce new summary measures, which indicate the pervasiveness of growth patterns. These indicators show that investment in both information and communication technology (ICT) and non-ICT capital is fairly balanced or 'yeasty', driven by overall macro-economic conditions. However, growth of total factor productivity (TFP) is much more localized or 'mushroom-like'. In particular we find a clear distinction between countries in continental Europe, in which TFP is decelerating after 1995 and becoming more localized, and Anglo-Saxon countries in which TFP growth is accelerating and becoming more broad-based, especially after 2000. The increased breadth of Anglo-Saxon TFP growth is consistent with delayed effects of intangible investments that are complementary to ICT investments.     

Information and Communications Technology as a General-Purpose Technology: Evidence from US Industry Data

Abstract. Many people point to information and communications technology (ICT) as the key for understanding the acceleration in productivity in the United States since the mid-1990s. Stories of ICT as a 'general-purpose technology' suggest that measured total factor productivity (TFP) should rise in ICT-using sectors (reflecting either unobserved accumulation of intangible organizational capital; spillovers; or both), but with a long lag. Contemporaneously, however, investments in ICT may be associated with lower TFP as resources are diverted to reorganization and learning. We find that US industry results are consistent with general-purpose technology (GPT) stories: the acceleration after the mid-1990s was broad-based – located primarily in ICT-using industries rather than ICT-producing industries. Furthermore, industry TFP accelerations in the 2000s are positively correlated with (appropriately weighted) industry ICT capital growth in the 1990s. Indeed, as GPT stories would suggest, after controlling for past ICT investment, industry TFP accelerations are negatively correlated with increases in ICT usage in the 2000s.     

Human capital, economic growth, and regional inequality in China

We show how regional growth patterns in China depend on regional differences in physical, human, and infrastructure capital as well as on differences in foreign direct investment (FDI) flows. We also evaluate the impact of market reforms, especially the reforms that followed Deng Xiaoping's “South Trip” in 1992 those that resulted from serious hardening of budget constraints of state enterprises around 1997. We find that FDI had a much larger effect on TFP growth before 1994 than after, and we attribute this to the encouragement of and increasing success of private and quasi-private enterprises. We find that human capital positively affects output and productivity growth in our cross-provincial study. Moreover, we find both direct and indirect effects of human capital on TFP growth. These impacts of education are more consistent than those found in cross-national studies. The direct effect is hypothesized to come from domestic innovation activities, while the indirect impact is a spillover effect of human capital on TFP growth. We conduct cost-benefit analysis of hypothetical investments in human capital and infrastructure. We find that, while investment in infrastructure generates higher returns in the developed, eastern regions than in the interior, investing in human capital generates slightly higher or comparable returns in the interior regions. We conclude that human capital investment in less-developed areas is justified on efficiency grounds and because it contributes to a reduction in regional inequality.     

Can total factor productivity explain value added growth in services?

This paper examines the factors responsible for generating the services led growth witnessed in the Indian economy during 1980–2005. A sectoral growth accounting exercise shows that total factor productivity (TFP) growth was the fastest for services; moreover this TFP increase was significant in accounting for service sector value added growth. A growth model with agriculture, industry and services as three principal sectors is calibrated to Indian data using sectoral TFP growth rates. The baseline model performs well in accounting for the evolution of value added shares and their growth rates, but is unable to capture sectoral employment share trends. The performance of the model with respect to value added shares improves when the post 1991 increase in service sector TFP growth following the inception of market-based liberalization reforms is accounted for. A modified version of the model with public capital can better track trends in sectoral employment shares.     

FDI and productivity growth: the role of inter‐industry linkages

Abstract There is a large literature on the effects of foreign direct investment (FDI) on productivity through inter‐industry economic linkages. This paper contributes to the literature by focusing on the developed economy of Canada. It finds that FDI generates strong effects on total factor productivity (TFP) growth through both forward and backward inter‐industry linkages, and increase in an industry's absorptive capacity raises the effects of FDI on TFP growth through forward inter‐industry linkages. For R&D intensive industries, the effects of FDI on TFP growth through inter‐industry linkages are small, but imports turn out to be an important source for TFP growth.     

Shocks,financial dependence and efficiency: Evidence from U.S. and Canadian industries

This paper investigates how changes in industries’ funding costs affect total factor productivity (TFP) growth. Based on panel regressions using data for U.S. and Canadian industries and industries’ dependence on external funding as an identification mechanism, we show that increases in the cost of funds affect TFP growth negatively. The effect is non‐monotonic depending on a sector's external finance need. This paper presents a theoretical model that produces the observed non‐monotonic effect of financial shocks on TFP growth and suggests that financial shocks distort the allocation of factors across firms even within an industry, thus reducing TFP growth.     

Productivity Growth And Market Structure In Telecommunications

This study examines sources of telecommunications sector productivity growth. Total factor productivity (TFP) growth is calculated using the Malmquist productivity index for a sample of 74 countries for the period 1991 through 1995. An econometric model is estimated which relates TFP growth to output growth, network digitisation, telecommunications development, output-mix, the business cycle and market structure. Model estimates suggest that higher digitisation rates dampen TFP growth in the short run, and cross-subsidisation of services creates inefficiency. However, developing countries can increase TFP growth through catch up, and increased privatisation and competition are conducive to productivity growth.     

Technological convergence, R&D, trade and productivity growth

This paper analyses productivity growth in a panel of 14 United Kingdom manufacturing industries since 1970. Innovation and technology transfer provide two potential sources of productivity growth for a country behind the technological frontier. We examine the roles played by research and development (R&D), international trade, and human capital in stimulating each source of productivity growth. Technology transfer is statistically significant and quantitatively important. While R&D raises rates of innovation, international trade enhances the speed of technology transfer. Human capital primarily affects output through private rates of return (captured in our index of labour quality) rather than measured TFP.     

How important are dual economy effects for aggregate productivity?

This paper brings together development accounting techniques and the dual economy model to address the role that factor markets have in creating variation in aggregate total factor productivity (TFP). Development accounting research has shown that much of the variation in income across countries can be attributed to differences in TFP. The dual economy model suggests that aggregate productivity is depressed by having too many factors allocated to low productivity work in agriculture. Data show large differences in marginal products of similar factors within many developing countries, offering prima facie evidence of this misallocation. Using a simple two-sector decomposition of the economy, this article estimates the role of these misallocations in accounting for the cross-country income distribution. A key contribution is the ability to bring sector-specific data on human and physical capital stocks to the analysis. Variation across countries in the degree of misallocation is shown to account for 30–40% of the variation in income per capita, and up to 80% of the variation in aggregate TFP.     

Creative accounting or creative destruction? Firm-level productivity growth in Chinese manufacturing

We present the first comprehensive set of firm-level total factor productivity (TFP) estimates for China's manufacturing sector that spans China's entry into the WTO. For our preferred estimate, which adjusts for a number of potential sources of measurement error and bias, the weighted average annual productivity growth for incumbents is 2.85% for a gross output production function and 7.96% for a value added production function over the period 1998-2007. This is among the highest compared to other countries. Productivity growth at the industry level is even higher, reflecting the dynamic force of creative destruction. Over the entire period, net entry accounts for over two thirds of total TFP growth. In contrast to earlier studies looking at total non-agriculture including services, we find that TFP growth dominates input accumulation as a source of output growth.     

财政科技支出对全要素生产率的影响及其机理分析

对2007—2017年我国全要素生产率的时序变化进行分析,再以省际面板数据为样本,探究财政科技支出对全要素生产率的影响及其作用机理。研究发现,财政科技支出对全要素生产率增长具有正向驱动效应,且这种正向驱动具有显著的动态效应和区域异质性、市场异质性。具体表现为:我国的东部地区最为显著,中部地区最小;市场化程度高的省(区、市)最为显著,市场化程度低的省(区、市)相对较弱。进一步检验发现,财政科技支出主要通过提升技术创新水平、抑制产业结构偏离促进全要素生产率增长。基于此,我国要进一步健全财政科技投入体系,有效加强对创新活动的支持力度,坚定不移地推进市场化改革,提升中西部地区的市场化水平,同时财政科技支出适度向非国有企业倾斜,有效提升财政科技支出的靶向性。     

What determines productivity performance of telecommunications services industry? A cross-country analysis

This article investigates the key factors that determine the productivity performance of telecommunications services industry. A simple theoretical model is used to illustrate that the Total Factor Productivity (TFP) growth is attributable to the effects of scale economies, market competition and technical change. We then examine empirically the effect of various factors on the TFP growth in the industry using panel data in 12 Organization for Economic Co-operation and Development (OECD) countries for the period 1983 through 2003. The empirical results are consistent with the theoretical prediction. A new finding in this article is that higher machinery and equipment (M&E) capital intensity and human capital contribute to higher TFP growth in the telecommunications services industry. The decomposition analysis also suggests that technical change induced by changes in M&E capital intensity and human capital are important sources of productivity performance in the industry across the OECD countries, contributing to about 20–50% and 2–7% of TFP growth, respectively. These findings highlight the importance of improving the conditions for M&E capital investment and the quality of human capital, which in turn could facilitate the adoption of new technologies and enhance the productivity in the industry.     

环境约束下地区全要素生产率增长及影响因素研究——基于马姆奎斯特生产率指数和环境库兹涅茨曲线分析

采用非参数马姆奎斯特(Malmquist)指数估算我国2000～2009年29个省、直辖市和自治区的全要素生产率(TFP),并分析了人均GDP、人口密度、教育水平、城镇化率对全要素生产率的影响。研究发现:在给定资源投入情况下,东部的生产率增加值大于中部、西部,同时污染排放还小于中部、西部;人均GDP与TFP呈倒U型曲线,即环境要素生产率与人均GDP之间存在环境库兹涅茨(EKC)曲线关系;教育水平与环境要素生产率正相关,城镇化率和人口密度与TFP负相关。     

WHY DID JAPAN'S TFP GROWTH SLOW DOWN IN THE LOST DECADE? AN EMPIRICAL ANALYSIS BASED ON FIRM‐LEVEL DATA OF MANUFACTURING FIRMS*

This study analyses the cause of the slowdown in Japan's TFP growth during the 1990s. Many preceding studies, examining the issue at the macro‐ or industry‐level, have found that the slowdown was primarily due to the stagnation in TFP growth in the manufacturing sector. Using firm level panel data covering the entire sector, we investigate the causes of the TFP slowdown and find that the reallocation of resources from less efficient to more efficient firms was very slow and limited. This “low metabolism” seems to be an important cause for the slowdown in Japan's TFP growth.     

环境规制下全要素生产率逆转拐点的空间效应*——基于省际工业面板数据的验证

工业是污染排放和能源消耗的主体,环境全要素生产率受环境规制影响,进而对工业的可持续增长有一定制约。本文采用2001-2012年中国各省份（西藏除外）工业行业的面板数据,基于Malmquist Luenberger生产率指数,在考虑环境污染的情况下测算了我国各地区工业行业的环境全要素生产率,避免了全要素生产率高估的问题;并构建空间计量模型,考虑空间相关性和异质性的影响,在控制了资本劳动投入比、地区经济发展水平、企业规模、所有制结构、外资结构等变量因素影响的基础上,实证检验了环境规制与全要素生产率的关系。实证结果表明：东部、中部和西部三大区域环境规制的强度和工业行业的环境全要素生产率之间呈现“U”型关系。随着环境规制强度不断增强,全要素生产率先降后升,而且东部地区要早于中部、西部地区达到拐点。在达到拐点以后,东部地区的全要素生产率对环境规制变动的反应要强于中、西部地区,东部地区的边际全要素生产率更高。     

TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration

This article estimates agglomeration effects via calculating EG (Elilsion & Glaeser) and TFP growth (Total Factor Production) by considering the undesired output of the industrial enterprise database and the entropy weight method. Using panel data of 207 county-level cities in China and 28 two-digit manufacturing industries from 2003 to 2013 based on SIC codes, this paper analyzes the relationship between agglomeration and TFP growth through the smooth transition model under different regions and factor-intensity. The results are as follows. (1) A negative relationship appears in manufacturing productivity. The agglomeration effect changes to the crowded effect. Environmental pollution is also generated by transportation and inadequate pollution treatment technology. (2) The excessive agglomeration phenomenon of developed areas (eastern region) is less than the less developed areas (central and western regions). (3) Resource-intensity industries present two thresholds that indicate complex regional features. For various intensive industries in different regions, the relationship between GML and agglomeration is different. High agglomeration does not always promote TFP growth. (4) At different levels of urban industrial agglomeration, the influences of efficiency change and technical change on GML are different. Overall, moderate agglomeration in all regions helps promote economic development.     

AN ATTEMPT TO EXPLAIN DIFFERENCES IN ECONOMIC GROWTH: A STOCHASTIC FRONTIER APPROACH

Total factor productivity (TFP), factor accumulation, and growth are analysed for a panel of 40 countries in 2001–11. TFP growth and technical inefficiency are estimated using a stochastic frontier model. Environmental variables are found to have an important role in explaining differences in inefficiency across countries. Over 2001–11, the general improvement in technical efficiency of countries is almost outweighed by technological regress. Results indicate that differences in factor accumulation between OECD and emerging economies are more important than differences in TFP change to explain differences in economic growth. Results also indicate negative and significant random shocks for the OECD countries.     

R&D and Absorptive Capacity: Theory and Empirical Evidence*

This paper presents a single unified framework that integrates the theoretical literature on Schumpeterian endogenous growth and major strands of the empirical literature on R&D, productivity growth and productivity convergence. Starting from a structural model of endogenous growth following Aghion and Howitt (1992, 1998) , we provide microeconomic foundations for the reduced‐form equations for total factor productivity (TFP) growth frequently estimated empirically using industry‐level data. R&D affects both innovation and the assimilation of others’ discoveries (“absorptive capacity”). Long‐run cross‐country differences in productivity emerge endogenously, and the analysis implies that many existing studies underestimate R&D's social rate of return by neglecting absorptive capacity.     

Sudden stops,sectoral reallocations,and the real exchange rate

A sudden stop of capital flows into a developing country tends to be followed by a rapid switch from trade deficits to surpluses, a depreciation of the real exchange rate, and decreases in output and total factor productivity. Substantial reallocation takes place from the nontraded sector to the traded sector. We construct a multisector growth model, calibrate it to the Mexican economy, and use it to analyze Mexico's 1994–95 crisis. When subjected to a sudden stop, the model accounts for the trade balance reversal and the real exchange rate depreciation, but it cannot account for the decreases in GDP and TFP. Extending the model to include labor frictions and variable capital utilization, we still find that it cannot quantitatively account for the dynamics of output and productivity without losing the ability to account for the movements of other variables.     

Sources of TFP growth: occupational choice and financial deepening

This paper explains and measures the sources of total factor productivity (TFP) by developing a method of growth accounting based on an integrated use of transitional growth models and micro data. We decompose TFP growth into the occupational-shift effect, financial-deepening effect, capital-heterogeneity effect, and sectoral-Solow-residuals. Applying this method to Thailand, which experienced rapid growth with enormous structural changes between 1976 and 1996, we find that 73% of TFP growth is explained by occupational shifts and financial deepening, without presuming exogenous technical progress. Expansion of credit is a major part. We also show the role of endogenous interaction between factor price dynamics and the wealth distribution for TFP. We thank Richard Rogerson for his clarifying and helpful discussion. The comments from the participants of the Minnesota Workshop in Macroeconomic Theory 2004, Stanford Institute for Theoretical Economics (SITE) Summer Workshop 2004, European Meeting and North American Summer Meeting of the Econometric Society 2004, NEUDC 2004, Iowa Conference of Economic Development, and seminars at USC Marshall School, Penn State University, UCLA, and UCSD are also appreciated. Financial support from NSF (SES-0318340) and NICHD (R01 HD27638) is gratefully acknowledged.