Productivity growth in passenger-bus transportation: A heteroskedastic error component model with unbalanced panel data

This paper considers an econometric approach to measure total factor productivity (TFP) growth and technical change (TC) for 31 publicly-owned passenger-bus companies in India during 1983–1987. A translog variable cost function is used to represent the production technology. Firm heterogeneity is incorporated in the cost function using an error component model with firm-specific variances. TFP growth is decomposed into TC and economies of scale components. The TC component is further decomposed into pure, non-neutral, scale, and quasi-fixed factors/network components. An ownership group-wise comparison reveals that the public undertakings exhibit the highest rate of productivity growth, followed by the units operated by the state and local governments. The main source of TFP growth for the public undertakings and government-operated units is economies of scale, while the main source of falling TFP growth for corporations is technological regress.     

What determines the productivity growth? Evidence from Chinese renewable energy firms by using Bayesian stochastic frontier approach

This paper examines the determinants of the total factor productivity (TFP) growth of Chinese renewable energy firms from 2011 to 2016, using a Bayesian stochastic frontier approach. Employing the “Bauer–Kumbhakar” decomposition method, the TFP growth is decomposed into the technology part and the market part. The empirical results reveal that the TFP improvement of Chinese renewable energy firms is mainly due to technical progress, followed by technical efficiency change. With regard to the market part, the misallocation of production factors has hindered the TFP growth. Our findings also indicate that only for large firms, the TFP growth can benefit from the scale economy effect. Compared with non‐state‐owned firms, state‐owned firms suffer much lower allocative efficiency.     

Estimation of TFP growth: a semiparametric smooth coefficient approach

This article uses a semiparametric smooth coefficient model (SPSCM) to estimate TFP growth and its components (scale and technical change). The SPSCM is derived from a nonparametric specification of the production technology represented by an input distance function (IDF), using a growth formulation. The functional coefficients of the SPSCM come naturally from the model and are fully flexible in the sense that no functional form of the underlying production technology is used to derive them. Another advantage of the SPSCM is that it can estimate bias (input and scale) in technical change in a fully flexible manner. We also used a translog IDF framework to estimate TFP growth components. A panel of U.S. electricity generating plants for the period 1986?C1998 is used for this purpose. Comparing estimated TFP growth results from both parametric and semiparametric models against the Divisia TFP growth, we conclude that the SPSCM performs the best in tracking the temporal behavior of TFP growth.     

On modeling the determinants of TFP growth

We investigate the determinants of TFP growth of Italian manufacturing firms. Using stochastic frontier techniques, we consider three approaches for taking into account the influence of external factors, i.e., the determinants or drivers of growth. First, in our novel approach external factors may influence the technological progress, that is the shift of the frontier. To model this possible unexplored effect, we extend the standard time trend model to make it a function of the external factors. Then, following more standard approaches, we model external factors as either influencing the distance from the frontier, i.e., inefficiency, or the shape of the technology. Using a sample of manufacturing firms in 1998–2003, we find that technological investments and spillovers, human capital and regional banking inefficiency all have a significant effect on TFP growth.     

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.     

Technology clubs, R&D and growth patterns: Evidence from EU manufacturing

This paper investigates the forces driving output change in a panel of EU manufacturing industries. A flexible modeling strategy is adopted that accounts for: (i) inefficient use of resources and (ii) differences in the production technology across industries. With our model we are able to identify technical, efficiency, and input growth for endogenously determined technology clubs. Technology club membership is modeled as a function of R&D intensity. This framework allows us to explore the components of output growth in each club, technology spillovers and catch-up issues across industries and countries.     

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.     

我国省际技术进步及其空间扩散分析

本文区分了国有企业和非国有企业就业对经济增长的贡献,并在增强省际数据横向可比性的基础上,应用DEA方法测算了1980—2004年各省区的TFP、技术效率和技术进步指数。我们发现,我国的TFP总体上是增长的,主要是由于技术进步引起的。接着,我们应用非线性广义最小二乘法,探讨了省际技术进步的空间扩散问题,结果证实我国存在着从北京、上海、广东向其他省区的技术扩散,而且这种扩散依赖于空间距离;技术扩散地区的人力资本投资、产业结构调整和专业化不仅能够带动自身的技术进步,而且能够促进其他省区的技术进步。     

Innovation and total factor productivity in organic farming

This article measures the contribution of innovations to Total Factor Productivity (TFP) of organic olive farmers. By constructing an innovation variable instead of using a time trend, technical change is replaced by technical difference and TFP growth becomes TFP difference. Primary cross-section data on organic olive enterprises from a Greek region is used in the application of the stochastic frontier profit function. Farmers are classified into groups according to their innovative ‘profile’. TFP difference among consecutive innovation groups is decomposed into technical difference and adjustment in innovativeness effects. Results indicate that more innovative farmers perform better than less innovative ones regarding TFP scores. The rate of technical difference is always positive to the formation of TFP difference, whereas the adjustment in innovativeness effects varies among the innovation groups. Nevertheless, high-tech capital is to a different extent under-utilized, regardless of the innovation group.     

技术吸收能力对技术溢出和全要素生产率的影响——基于1995—2009年中国省区面板数据

利用1995—2009年我国28个省(自治区、直辖市)的面板数据,采用数据包络分析法,实证检验了地区的技术吸收能力对地区获得的技术溢出及其全要素生产率的影响。研究表明:省际技术溢出以及来自进出口贸易、FDI和ODI渠道的技术溢出都是影响地区TFP及其分解变量——技术进步、技术效率的重要因素;人力资本、制度因素、技术差距和吸收能力综合变量通过与技术溢出发生交互作用,对地区TFP、技术效率和技术进步产生显著影响。     

Elasticity of substitution and the stagnation of Italian productivity

The aim of this paper is to investigate the roots of the stagnation in the Italian total factor productivity (TFP). The analysis focuses on the specific pattern of technical progress in determining the dynamics of the TFP. This analysis cannot be done with Cobb-Douglas technology, but requires the employment of a constant elasticity of substitution (CES) production function that allows distinguishing between the direction and the bias of technical progress. We employ a CES specification embodying both labor- and capital-augmenting technical change, with a σ less than 1. We obtain three main results. (1) There seems to have been a structural break around the mid-1990s in the direction and bias of technological change; (2) The first half of the sample features a labor-augmenting technical change and a capital bias; and (3) In the second part of the sample, both these characteristics seem to disappear, and the evolution of factor endowments assumes a key role. This fact may be seen as one of the potential causes of the stagnation in Italian productivity.     

Technical change and total factor productivity growth for Swedish manufacturing and service industries

This article presents alternative specifications of the production functions of a large panel of Swedish firms for the period 1992 to 2000. The period can be characterized as a transition when long-run productivity growth in the Swedish economy improved from being among the weakest to one of the strongest within the Organization for Economic Co-operation and Development (OECD). In order to present a detailed exploration of this dramatic change, the time trend and general index models are applied to estimate Total Factor Productivity (TFP) growth, rate of technical change and returns to scale. The models are extended to allow for firm specific as well as time-varying technical change. The parametric TFP measures are also compared with the nonparametric Solow residual, and several hypotheses are tested to explain the growth patterns in the Swedish economy. It is found that the improved growth rate, initially starting in large exporting manufacturing firms, after a deep economic crisis at the beginning of the 1990s, spilled over to the rest of the economy, both manufacturing and services.     

1978-2007年我国畜牧业全要素生产率及其影响因素研究

本文运用扩展的索洛模型和C-D生产函数测算了1978—2007年我国畜牧业全要素生产率(TFP)及其影响因素。分析结果表明,1978—2007年我国畜牧业TFP的年均增长率为4.71%;从总体上看,我国畜牧业生产处于规模报酬递增阶段,且畜牧业政策、劳动者质量、规模化程度和科技投入量是影响我国畜牧业TFP变动的主要因素。     

我国东部地区绿色全要素生产率研究——基于DEA-Malmquist的实证分析

采用DEA-Malmquist指数分析法,选取1999—2011年东部12省市的面板数据,探究该区域绿色全要素生产率具体变动情况,结果表明:东部地区的节能减排政策是相对有效的,同时,技术进步成为导致绿色全要素生产率变化的最重要因素,技术效率虽然在逐步提升,但是增长不稳定,在东部地区已经达到规模经济的边缘之时,这种增长方式是不能持久的。基于此,东部地区以后要实现绿色全要素生产率的持续改进,在改善技术的同时,提高要素使用率和生产技术水平,使污染物排放量稳中有减。     

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.     

技术效率、全要素增长率与地区间经济增长差异——以内蒙古为例

本文以内蒙古为例,使用随机前沿模型,估算了不同地区的技术效率,并对全要素生产率(TFP)增长率进行分解。研究结果表明:(1)技术效率和TFP与一个地区的经济增长呈正向变动关系。(2)城市化率、第二产业占GDP比重、人力资本水平等提高技术效率,国有工业产值和财政支出占GDP比重降低了技术效率。(3)整体而言,各地区TFP增长主要依靠技术进步,技术效率和规模经济效率都显著不足。     

建筑业全要素生产率增长与区域经济增长的耦合效应分析

采用随机边界分析方法测算了1997—2009年省际建筑业全要素生产率(TFP)增长水平,并进行了区域差异化比较;然后借鉴物理学的耦合度理论,构建建筑业TFP增长与区域经济增长的耦合效应模型,并进行了实证检验;采用灰色关联分析方法遴选出二者耦合效应的主要影响因素,最后对建筑业经济增长方式和阶段进行了研判。研究表明:区域建筑业TFP增长存在较大差异,依据其增长率大小将31个地区划分为负增长、低增长、中增长和高增长四种类型;二者的耦合程度较高而耦合协调度较低;约束建筑业TFP增长的主要因素是地区的GDP水平,判断中国区域建筑业的经济增长仍属于粗放型增长方式和资本经济阶段。     

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.     

Remeasuring and decomposing stochastic trends in business cycles

This paper is motivated by the fact that the standard deviation of cyclical TFP derived from the standard approach under the stochastic trend is not even close to the real-world data. The main part of the paper devotes to developing a new method to apply geometric Brownian motion to characterize TFP in continuous time and converting it to an estimated process of random walk with drift. As a result, the drift estimate together with the lagged TFP in the random walk process are the stochastic trend of TFP and the stochastic error term in the random walk with drift process is the cyclical component of TFP. I then have two findings: the first one is that the standard deviation of cyclical TFP derived from the new approach is much closer to the real-world data; the second one is that stochastic trend of TFP can be decomposed into three parts: an initial value, a deterministic trend, and a term involved with Weiner process. Moreover, this paper argues that, by recalculating the business cycle statistics based on a rational expectations model, if we remeasure the stochastic trend and cyclical component of TFP using the new approach, then the ability of real business cycle model to mimic real-world economic fluctuations will be significantly improved.     

Intra-industry Trade and Innovation: An empirical study of the Colombian manufacturing industry

This paper analyses the theoretical and empirical relationship between intra-industry trade (IIT) flows in manufactures and technical change for the Colombian manufacturing industry during the 1970-95 period. A general estimating equation for the sources of change of the equilibrium number of varieties, in which TFP growth is one of its components, is derived from the basic model of trade in differentiated goods with monopolistic competition. Based on that relationship, several estimations on the determinants of IIT flows are carried out. The econometric set up follows a panel data and cross-section estimations of system of simultaneous equations. TFP and IIT indices are the endogenous variables of the system with industry characteristic, trade policy, and innovation-activity variables as the set of exogenous variables. The paper also presents a comparative analysis in the direction and trends of Colombia's IIT flows in manufactures with the Group of Seven, NAFTA, and the Latin American Free Trade area members (LAFTA) since 1974.