Total Factor Productivity Estimates Research Articles

The dynamic links between product and process innovations and productivity for Colombian manufacturing

Purpose This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys. Design/methodology/approach This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models. Findings The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations. Originality/value The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.

Analysing the Total Factor Productivity Change Among Urban Cooperative Banks in India: The Malmquist Productivity Approach

This study investigates the total factor productivity (TFP) growth among urban cooperative banks in India during 2014–2020. The measurement of productivity is done using the data envelopment analysis-based Malmquist productivity index. We use two different models, viz., the intermediation approach and the production approach, to see how productivity estimates vary with the change in inputs and outputs. Our results show a large asymmetry in productivity estimates both among banks and over time. TFP estimates were consistently higher under the production approach vis-à-vis the intermediation approach. Further, the empirical results show that productivity gains were mainly determined by technological progress rather than efficiency improvements. Thus, collaborations in technological know-how can be beneficial to productivity growth. JEL Classifications: G15, G21, G34

Intelligent System of Estimation of Total Factor Productivity (TFP) and Investment Efficiency in the Economy with External Technology Gaps

This paper is the first to propose an aggregate S-trend factor production function to estimate total factor productivity (TFP) and investment efficiency in an economy. This function implements Charles R. Hulten's organizing principle: to what extent the growth of the economy is due to an increase in "productivity" (progress in technology and organization of production) and to what extent to "capital formation" (increased investment in human capital, knowledge and fixed capital). Estimation of future members of the series is usually done by a forecast model. It is a model that approximates a trend. The Verhulst's S-curve is used as the approximation function. Here A, B ,a are the parameters that change the shape of the S-curve, u, m are the parameters that change the position of the S-curve in the first quarter, t≥0. By aggregate S-trend production function we mean a two factor production function of the form z(t)= Here the function It represents the growth of the economy, which is by raw data and takes into account all influencing factors, and is certainly broader than the concept of " capital formation ", is a total factor productivity TFP. The error of approximation is quantitatively measured by the MAPE criterion.

Picking winners? Government subsidies and firm productivity in China

Are Chinese government subsidies making the targeted Chinese firms more productive? Alternatively, are efforts to promote productivity undercut by efforts to maintain or expand employment in less productive enterprises? In this paper, we attempt to shed light on these questions through the analysis of previously underutilized microdata on direct government subsidies provided to China's publicly traded firms. We estimate total-factor productivity (TFP) for Chinese listed firms and investigate the relationship between these estimates of TFP and the allocation of government subsidies. We find little evidence that the Chinese government consistently “picks winners”. Firms’ ex-ante productivity is negatively correlated with subsidies received by firms, and subsidies appear to have a negative impact on firms’ ex-post productivity growth throughout our data window, 2007 – 2018. Neither subsidies given out under the name of R&D and innovation promotion nor industrial and equipment upgrading positively affect firms’ productivity growth. On the other hand, we find a positive impact of subsidy on current year employment. These findings suggest that China's rising wave of government subsidies may have generated limited effects in promoting productivity.

Towards a better measure of productivity in India: a case of chemical and chemical products industry

PurposeA brief review of earlier studies on the productivity scenario of Indian industry shows that most of the studies analysed are confined to either parametric approach or growth accounting approach of measuring productivity. At the same time, the few studies based on the non-parametric [namely, Malmquist productivity index (MPI)] overlook the returns to scale conditions as well as the bias involved in the estimation of distance functions. Given this backdrop, this study aims to provide a robust measure of productivity, which considers the returns to scale assumptions and correct for the bias involved in the estimation of productivity.Design/methodology/approachThis study empirically tests for the returns to scale that exists in the chemical and chemical products industry in India. The test result suggests that Ray and Desli (1997) approach of MPI is the appropriate one for the present context. Initially, the conventional Ray and Desli (1997) estimation and decomposition of MPI for the period 2001 to 2017 is being used. Subsequently, to correct for the bias in the estimation of efficiency scores used for the estimation of MPI, the bootstrapping algorithm of Simar and Wilson (2007) has been extended into the context of MPI estimation.FindingsThe results from the conventional Malmquist productivity estimates testifies to an improvement of total factor productivity (TFP) in seven out of 16 years under consideration. On the contrary, TFP growth is recorded only in the four years throughout the period after the bias correction. A greater discrepancy between the two measures has been found in the case of scale change factor component of MPI.Practical implicationsThe technical change (TC) component positively influences TFP, whereas scale change factor (SCF) deteriorates the TFP condition of this industry. It will be appropriate for these firms to identify and operate under an optimal scale of operation, along with reaping the benefits of technological change. From a methodological perspective, researchers should consider the potential bias that arise in estimation of TFP and use a larger sample whenever possible.Originality/valueThis paper brings in a new perspective to the existing literature on industrial productivity. As against earlier studies, this study empirically tests the returns to scale of the sector under consideration and uses the most appropriate approach to measure productivity. The effect of sampling bias on TFP and its components is analysed.

A nonparametric analysis of climate change nexus on agricultural productivity in Africa: implications on food security

Abstract Earlier research largely ignored the effects of climate change on the growth of agricultural total factor productivity (TFP) in Africa. This study shows how climate inputs impact TFP growth in addition to other productivity growth indicators and metrics, as well as how they can impact overall input efficiency as productivity drivers. We use a panel of 42 African nations from 1999 to 2019 and a nonparametric data envelopment analysis-Malmquist technique. The non-parametric analysis revealed that the average growth rate of the non-climate-induced TFP estimates was 1.9%, while the average growth rate of the climate-induced TFP estimates was 2.4%. Accounting for temperature and precipitation separately, TFP grew by 2.3% on average. This growth rate (2.3%) is slightly less than the combined effect of temperature and precipitation (2.4%) but higher than the typical TFP growth rate (1.9%) that ignores climate variables, indicating that TFP growth in African agriculture risks being underestimated when climate inputs are ignored. We also find the distribution of the climate effects to vary across regions. In northern Africa, for example, the temperature-induced TFP growth rates were negative due to rising temperature in the region. Evidence from the decomposed TFP estimates indicates that climate variables also influence productivity determinants. However, technology improvement is fundamental to mitigating the effects of extreme weather inputs on TFP growth in Africa's agriculture. As a result, a few policy suggestions are provided to help policymakers deal with the effects of climate change on TFP growth in Africa's agriculture and ensure food security. The study advocated for a reevaluation of the climate–agriculture effect in order to fully comprehend the role of climate factors and their contributions to agricultural TFP growth in Africa.

A Contribution to the Empirics of Total Factor Productivity’s Theory Based on a CES Production Function-Case of Moroccan Economy

Some propositions related to about growth theory are not valid for all production functions. This is the case for the estimation of total factor productivity based on the growth accounting’s approach which is easily verified with a Cobb-Douglas production function, but difficult to obtain with a CES production function. In this paper, we will try to do that estimation using Moroccan data.

Ultra-fast broadband access and productivity: Evidence from Italian firms

We study the impact of ultra-fast broadband (UFB) infrastructures on the total factor productivity (TFP) and labor productivity of firms. We use unique balanced panel data for the 2013–2019 period on incorporated firms in Italy. Using the geographical location of the firms, we merge firm-level data with municipality-level information on the diffusion of UFB, which started in 2015. We derive consistent firm-level TFP estimates by adopting a version of the Ackerberg et al.’s (2015) method, which also accounts for firm fixed effects. We then assess the impact of UFB on productivity and deal with the endogeneity of UFB by exploiting the physical distance between each municipality and the closest optical packet backbone node. Our results show an overall positive impact of UFB on productivity. Services companies benefit the most from advanced broadband technologies, as do firms located in the North-West and South of Italy. We further decompose the impact of full-fiber networks from mixed copper-fiber connections and find that the former significantly contribute to enhancing firm productivity. Finally, by exploiting Labor Force Survey data, we provide suggestive evidence that productivity increases from UFB might be related to structural changes at the workforce level.

Estimation of Total Factor Productivity and its Determinants among Dairy Farms in the Eastern Region of India

The study estimated the total factor productivity (TFP) of dairy farms and its determinants in the eastern region of India. The results suggested that the overall total factor productivity of dairy farms in the region was 0.1697, and degree of variability existed which could be reduced if the farmers adopt better management practices. The frequency distribution of dairy households by TFP value was positively skewed such that 97 per cent of the farms had TFP less than 0.30. Among all the factors included in the model, herd size, composition, and C-P ratio significantly impacted TFP. Thus, TFP influenced by economies of scale, was technology, and management practices.

Dynamics of total factor productivity growth: An empirical analysis of Indian commercial banks

This paper investigates the total factor productivity (TFP) change scenario among Indian commercial banks during 1998–2017. We measure the change in the Malmquist TFP index and decompose this into technological, efficiency, and scale change components using data envelopment analysis (DEA). Further, the bootstrap-based Simar and Wilson (2007) procedure is applied to correct the bias from the conventional DEA estimates. We also explain the variations in TFP estimates using a set of bank-specific and macroeconomic variables with a system-generalised method of moments and bias-corrected fixed-effects models. Our results show an improvement in TFP among Indian commercial banks– with growth relatively higher during the pre-crisis than in the post-crisis period. The productivity gains are driven mainly by technological progress rather than efficiency improvements. Amongst different ownership categories, foreign-owned banks achieve the highest overall productivity gains, followed by the domestic privately owned and state-owned banks. Finally, our TFP regression results show that return on assets, diversification, GDP per capita, Herfindahl–Hirschman Index, and inflation are the main variables responsible for driving these total factor productivity differences.

The geographical dimension of productivity in Great Britain, 2011–18: the sources of the London productivity advantage

ABSTRACT The UK government has committed to ‘levelling up’ regional economic performance. Through deriving geographically disaggregated estimates of total factor productivity from plant-level data, we show that the productivity advantage of London is far greater than differences between other regions. Evidence is then provided on the extent to which differences in multinational ownership, trade involvement, enterprise structure, plant age, research and development, subsidization, size, and industrial structure explain the London productivity advantage. Less than half can be explained by these characteristics, which suggests that they should not be the main focus of policy to reduce spatial productivity differentials.

Are importing and exporting complements or substitutes in an emerging economy? The case of Colombia

AbstractThe aim of this paper is to investigate the impact of two trading strategies (exporting and importing) on total factor productivity (TFP) and the potential complementarity/substitutability effects of these strategies. In order to assess these effects, robust estimates of TFP are obtained using a general method of moments approach that explicitly determines the ability of a firm's trading experience to affect productivity. Data from the Annual Manufacturing Survey spanning from 2007 to 2016 is used for Colombian manufacturing firms. Our estimation results suggest that, regardless of the technological intensity of the industry in which the firm operates, active trading strategies (exporting only, importing only, both importing and exporting) pay positive rewards in terms of productivity. Nevertheless, whilst positive (complementary) synergies are found between exporting and importing for firms in med/high‐tech sectors, for firms operating in low‐tech and med/low‐tech sectors, importing and exporting appear to be substitutes.

Controlling for the effects of climate on total factor productivity: A case study of Australian farms

Estimates of agricultural Total Factor Productivity (TFP) can be highly sensitive to both short-run climate variability and long-term climate change. This is particularly true in Australia where drought impacts are responsible for most of the annual volatility in official farm TFP statistics. While climate variability can obscure short-term productivity trends, researchers have typically assumed that long run TFP trends are largely unaffected. However, in the presence of global climate change this assumption becomes problematic. For example, in Australia, shifts to higher temperatures and lower winter season rainfall over the last 20–30 years have had a significant negative impact on agricultural productivity. This study presents a framework to account for the effects of climate variability on TFP estimates. In contrast with previous work, this approach applies a reduced form machine learning based model of farm production to generate synthetic (climate-adjusted) farm-level input and output data sets. It therefore has advantages in terms of flexibility—since the synthetic datasets can be combined with any existing TFP estimation framework. In this study, the approach is applied to estimate climate-adjusted TFP indices (TFP under an assumption of constant long-run average climate conditions) for a range of Australian agricultural sectors.

Private and Social Returns to R&D: Drug Development and Demographics

Investment in intangible capital such as R&D has increased dramatically since the 1990s. However, productivity growth remains sluggish in recent years. One potential reason is that a significant share of the increase in intangible investment is geared toward consumer products such as pharmaceutical drugs with limited spillovers to productivity. We document that a significant share of R&D spending in the United States is done by pharmaceutical firms and geared to developing drugs for older patients. Increased life expectancy and quality of life for the elderly increases welfare but may not be reflected in estimates of total factor productivity.

Efficiency and Productivity of Textile Industry Sub-sector with Total Factor Productivity Approaches

The development of the manufacturing industry in Indonesia becomes a top priority because the manufacturing industry is a leading sector that can encourage other sectors and has forward and backward linkage between sectors.The difference in the use of technologythat still relatively low compared to the productivity of capital and labor will lead to differences in efficiency and productivity of each manufacturing industry sub-sector. The textile industry sub-sector contributes high amount to GDP and continues to increase every year. Total factor productivity (TFP) is considered a very comprehensive measure of productivity and efficiency.This measure explains the changes in production caused by changes in the amount of inputs used, changes in technology, capacity utilization and the quality of production factors. This study aims to analyze the effect of capital, labor, raw materials and energy to the output of the textile industry and textile products (TPT) (KBLI 14.15) with the Solow residual TFP approach. Another aim is to look at the efficiency and productivity of the textile industry sub-sector.The research used panel data regression with OLS model. The results of TFP estimation and TPT industry efficiency are different between TPT sub-sectors. TPT has integrity between downstream industries and upstream industries. Some of the obstacles in the textile industry in Indonesia include the high dependence of the Indonesian industry (TPT) on imported raw fiber materials (90%). Most of the age of the machines used by the TPT industry was old, this affects the TFP value.

Analysis of Total Factor Productivity of Pigeon Pea (Red Gram) in North-Eastern Karnataka, India

The present paper explores the growth of total factor productivity of red gram crop in North-Eastern Karnataka. The cost of cultivation data of red gram crop for the period 1990-91 to 2012-13 was used for estimation of Total Factor Productivity. It was found that TFP of red gram crop has substantially increased in North Eastern Dry Zone and the mean TFP index recorded for the entire 23 year period was 1.92. TFP of red gram during the period has registered a growth rate of 5.14 percent per annum implying that change in output growth is due to the factors such as research, extension, soil types, rainfall and infrastructure facilities, etc. In the case of North-Eastern Transitional Zone, the TFP index registered fluctuations over 23 year period and there was no substantial growth in TFP. The total factor productivity estimate of red gram crop shows that there was significant growth in TFP in North-Eastern Dry Zone compared to North-Eastern Transitional Zone.

Robots and Firms

Abstract We study the microeconomic implications of robot adoption using a rich panel data set of Spanish manufacturing firms over a 27-year period (1990–2016). We provide causal evidence on two central questions: (1) Which firm characteristics prompt firms to adopt robots? (2) What is the impact of robots on adopting firms relative to non-adopting firms? To address these questions, we look at our data through the lens of recent attempts in the literature to formalise the implications of robot technology. As for the first question, we establish robust evidence for positive selection, i.e., ex ante better performing firms (measured through output and labour productivity) are more likely to adopt robots. On the other hand, conditional on size, ex ante more skill-intensive firms are less likely to do so. As for the second question, we find that robot adoption generates substantial output gains in the vicinity of 20–25% within four years, reduces the labour cost share by 5–7% points, and leads to net job creation at a rate of 10%. These results are robust to controlling for non-random selection into robot adoption through a difference-in-differences approach combined with a propensity score reweighting estimator. To further validate these results, we also offer structural estimates of total factor productivity (TFP) where robot technology enters the (endogenous) productivity process of firms. The results demonstrate a positive causal effect of robots on productivity as well as a complementarity between robots and exporting in boosting productivity.

Productivity in the Agricultural Sector: A Global Outlook from a Latin American Perspective

Agricultural productivity has been the focus of intense scrutiny since the time of Adam Smith. In this article, we focus on agricultural productivity from two perspectives. First, we provide estimates of total factor productivity (TFP) growth for a panel of 79 countries over a period of approximately 60 years. Second, we investigated the potential determinants of productivity growth, which include infrastructure, macroeconomic variables, and variables related to climate change. We find that productivity varies greatly across countries, with leading countries showing annual agricultural productivity growth between 2% and 3%. In regards to productivity determinants, we find small within-country effects but significant between-country effects.

On modelling the determinants of total factor productivity in the MENA region: a macro-micro firm-level evidence

Using the World Bank Enterprise Surveys for Middle Eastern and North Africa (MENA) countries, the paper estimates total factor productivity (TFP) and examines its determinants. Our contribution is twofold. First, we provide TFP estimates by country and sector for the MENA region and examine how TFP varies with firm's age, size, export status, formal status and ownership. Second, we combine both micro (firm-level) and macro (nation-level) determinants of TFP to show how macroeconomic policies can affect firms' productivity levels. Our findings show that among the micro determinants, government ownership, foreign capital, female managers, owning a foreign certification, and formal registration of firms are all positively associated with TFP, with competition also exerting a positive impact on firms' productivity. All the macro determinants on the other hand, with the exception of trade openness, display the expected influence on TFP as suggested by the literature. Longer time to enforce contracts, high tax burden and high lending rates all tend to have a significantly negative impact on TFP. Higher tariffs, however, have a surprisingly positive impact on TFP which may emphasise the adverse effect trade openness can have on TFP as a result of the economy's limited ability to absorb the positive spillovers of trade.

Property rights and transaction costs – The role of ownership and organization in German public service provision

This paper provides evidence that ownership and organization matters for the efficiency of the provision of public services. The results confirm trade-offs implied by the property rights literature and provide important policy implications regarding the organization of public service provision. We find that pure private ownership is more efficient than pure public ownership, and public ownership is more efficient than mixed ownership. The delegation of management in different legal forms also has an impact, highlighting the importance of the design of the government-operator relationship. We apply a structural approach of a production function estimation, ensuring precise determination of total factor productivity for a panel of German garbage collection firms between 2000 and 2012, followed by a projection of those total factor productivity estimates on ownership and organization.