Average Total Factor Productivity Growth Research Articles

Estimating Total Factor Productivity Growth in the Sri Lankan Coconut Sector

The stagnant nature of Sri Lankan national coconut production over many decades has been an issue in fulfilling the ever-increasing demand for domestic coconut consumption and industry. Thus, this study aims to address the question of the driving forces of total coconut production growth. This study identifies the sources of Sri Lankan coconut sector growth from 1985 to 2019 by calculating the Total Factor Productivity (TFP) growth by administering a log-transformed Cobb–Douglas production function and decomposed the results using a data set sourced from various government publications. According to the findings of the study, the average TFP growth of the coconut sector in Sri Lanka for the period 1985-to 2019 has been -1.1%, whereas it was -0.1% and -1.9% during the two sub-periods; 1985-2000 Sub-period I, 2001-2019 Sub-period II, respectively. Therefore, it is evident that the negative growth of the TFP is mostly driven by the high negative growth in the post -2000 period. These findings will help to formulate future growth policies in coconut sector of Sri Lanka.

Impact of Climate Change on Total Factor Productivity of Agriculture in District Multan

Agriculture is particularly vulnerable to climate change because it faces open weather conditions. In uncontrolled open weather circumstances, it's difficult to attain better total factor productivity (TFP), which characterizes agriculture growth in an economy. The study estimated the TFP growth of Pakistan’s agriculture in first step by employing the Tornqvist- Theil index number approach for the period 1990-2019. The time series data for thirteen crops and four livestock categories from 1990 to 2019 were collected from different sources to estimate the TFP. The average annual TFP growth of agriculture was estimated to be 2.14 percent for the study period, and it contributed about 56 percent to total agricultural output growth. The results also indicated that TFP growth in agriculture sector was highest (0.05 percent) during the 1990-2000, while lowest (-2.14 percent) during the last decade. After, TFP index that was calculated in first step was used as dependent variable in second step of analysis. Then we estimated the impact of climate change on TFP in agriculture sector in Multan district. For this first we used ARDL bound test approach for estimation of long run impact of climatic variables. The results showed that there are positive effects of both minimum and maximum temperature on TFP in the study area. The drought and floods have negative impact on TFP but in first lag their effects became positive on TFP. One of the important variables of climate is rain that had positive impact on the TFP growth, with 1% increase in rainfall there was 0.22% increase in TFP at first lag. Improving the adaptation and mitigation practices related to floods and droughts would be required for sustainable growth in TFP in agriculture sector in Multan District.

Are State-Owned Enterprises Really Ineffective? An Empirical Study Based on Stochastic Frontier Analysis

Technical efficiency (TE) and total factor productivity (TFP) are important criteria to ensure the enhancement of the quality and efficiency of state-owned enterprises (SOEs) and function as important indicators to assess the quality of their accomplishments. The purpose of this study is to explore whether the efficiency of SOEs is higher or lower than that of private enterprises. Transcendental logarithmic production function and stochastic frontier analysis (SFA) are used to assess the TE and TFP of listed central SOEs, local SOEs, and private enterprises, the data of which were taken from 2006–2020. The results show that the sampled private enterprises had the highest average TE during the study period, followed by the central and local SOEs. The private enterprises also had the highest average TFP growth rate, followed by the local and central SOEs. The TFP decompositions show that the TE change (TEC) and technical change (TC) indices of the SOEs were lower than those of the private enterprises. The TC, TEC, and scale change (SC) are limiting the TFP growth rates of the SOEs in labor-intensive industries. The SC of the SOEs has changed less than that of private enterprises in the sampled capital-intensive industries. Northern and southern China had the highest rates of TE and TFP growth. Indeed, this paper measures and decomposes TFP, and analyzes the efficiency of SOEs and private enterprises in different industries and regions in an international context.

Economic effects of climate change on agricultural production and productivity in Latin America and the Caribbean (LAC)

AbstractClimate projections indicate that temperatures in Latin America and the Caribbean (LAC) will rise by between 1.6 °C and 4 °C by the end of the century while changes in precipitation levels are expected to vary significantly across the region. This article estimates the impact of climate change on total factor productivity (TFP) and production. It combines data from the University of East Anglia's Climatic Research Unit (CRU), the Intergovernmental Panel on Climate Change (IPCC), and the Food and Agriculture Organization (FAO) on 28 LAC countries for a 54‐year period (1961–2014) in order to inform policy makers of the cost of output losses in the absence of viable climate adaptation strategies. We use estimates of a random‐parameter stochastic production frontier (SPF) model specification to capture heterogeneity in technology and partial output elasticities across countries and unobserved environmental characteristics. Results show that change in output is mainly driven by an average annual TFP growth rate of .95%. Climate change induces significant reductions (9.03–12.7%) in productivity over the 2015–2050 period. In terms of output, these losses range from USD $14.7 to $31.4 billion dollars in the LAC region, depending on the scenario and the discount rate used.

Contribution of TFP to economic growth of Dong Thap province: Current status and scenarios for the period 2021 - 2025

The study aims to analyze the contribution of Total Factor Productivity (TFP) in Dong Thap ’province’s economic growth using the Cobb-Douglas production function method, based on the data from 2000 - 2020. The study results show that the contribution of capital (ε_K) is 0.3524, the contribution of labor (ε_L) is 0.6476. Dong Thap province’s average TFP growth rate in each period of 05 years 2011 - 2015 and 2016 - 2020 is 2.31% per year and 1.93% per year, respectively, and ’TFP’s contribution to economic growth is 34.51% and 30.01%, respectively. Based on the status analysis of the period 2011 - 2015 and 2016 - 2020, the study proposes four growth scenarios associated with four productivity orientations for Dong Thap province in 2021 - 2025. This ’study’s results are the basis for organizational policies and orientations for socio-economic development, proposing provincial development guidelines and plans to 2025, oriented to 2030.

A decomposition analysis of total factor productivity growth in MENA countries: stochastic frontier analysis approach

ABSTRACT The present study aims to examine the output and total factor productivity (TFP) growth by estimating a stochastic frontier production function for a panel of Middle East and North Africa (MENA) countries, and to decompose TFP growth into technical change, technical efficiency, and scale efficiency. The empirical findings reveal that, while factor accumulation is the main driver of output growth in the MENA region, TFP growth is increasingly accounting for a respectable proportion of output growth, with improved technical efficiency playing a crucial role in productivity growth. Specifically, the average annual TFP growth is found to be 0.846%, with positive contributions from technical efficiency and scale efficiency. However, the results show that technical progress has had a negative impact on TFP growth. The positive growth in technical efficiency suggests that the countries are catching up towards the optimal production frontier. At a disaggregated level, oil-rich countries registered negative effects of technical progress, while non-oil countries registered negative effects of scale efficiency. Technical efficiency, however, accounts for the largest positive factor in TFP growth in both oil and non-oil country groups.

Productivity Dynamics: A Case of Pakistan

This study estimates the total factor productivity (TFP) for Pakistan at aggregate and sectoral level from 1982 to 2016 with a data set rebased at 2005-06. We employ actual returns to scale instead of the oversimplified assumption of constant returns to scale for measuring the TFP. Our results show that average economic growth during this period is 4.7 percent with 0.7 percent contribution from TFP. While, average TFP growth for Agriculture, Industry, and Services sector is 1.5, 4.6, and 4.3 percent, respectively. Besides, there is a noticeable decreasing trend in TFP as well as economic growth relative to 1980’s. Further, our analysis reveals that the physical and human capital contribution in productivity is quite negligible at aggregate and sectoral level. This implies that sizeable investments in human capital formation can further help the economy to attain high growth trajectory in the short to medium terms.

Productivity change and its driving forces in Chinese healthcare sector.

Since the last medical reform in 2009, China’s public hospitals have been facing the changes in the institutional environment. However, the effects of reforms have not been received enough attention to deliver evidence-based implications. In this paper, we first assess the efficiency of regional public hospitals from 2011 to 2018, employing a proposed method based on an additive indicator and an aggregate directional distance function (DDF). The method applied allows for decomposing total factor productivity (TFP) indicator into three components, including technical efficiency change (TEC), total productivity (TP) and scale efficiency change (SEC). Second, following the efficiency assessment, we carry post-efficiency analysis to identify the determinants of efficiency of the public hospitals. The results show that annual average TFP growth rate is 1.38%, which is driven mainly by TEC. Regional disparities of public hospitals’ performance are expanding. Almost 75% of the regions considered show a positive TFP growth. The regression results show that the significant determinants of efficiency of regional public hospitals include the price of and demand for health services.

Does de-capacity policy enhance the total factor productivity of China's coal companies? A Regression Discontinuity design

China's overcapacity in the coal industry has become increasingly prominent since 2013, with a severe negative impact on resource allocation and the national economy. The Chinese government has implemented a series of de-capacity policies to resolve overcapacity and improve the total factor productivity (TFP) in the coal industry. In this study, we aim to explore whether the de-capacity policy enhances the TFP growth of China's coal companies. We firstly apply the Super-SBM-Malmquist index method to measure the TFP and its decomposition items (e.g., technical change, efficiency change) of China's coal industry. We then construct the Regression Discontinuity (RD) design to examine the impact of de-capacity policy on the TFP growth of the coal companies. The main results are as follows: (1) After the implementation of the de-capacity policy in 2016, the average TFP growth and technical change of the coal companies have increased significantly. (2) The de-capacity policy can dramatically promote TFP growth and technical change of the coal companies. In contrast, it has a significant and negative effect on efficiency change. (3) The positive impact of de-capacity policy on technical change is more significant than its adverse effects on efficiency change, which is the main reason for the increase in TFP growth. Therefore, the government should give full play to the positive role of administrative means in resolving overcapacity, and promote sustainable technological innovation of the coal industry.

Productivity Growth in Chinese Medical Institutions during 2009–2018

China is the most populous nation and considerations of economic efficiency in the social sectors is important for maintaining the wellbeing of such a large population. This is especially true when gauging the performance of the healthcare sector treating the population. In this paper, we examine the total factor productivity (TFP) growth in Chinese medical institutions during the period 2009–2018, which experienced a systemic healthcare reform. In order to identify the contribution from each component of TFP indicators and from each provincial or regional medical institutions, a generalized decomposition of productivity gains is applied to analyze hospital operations based on an aggregate directional distance function (DDF). The results show that the annual average TFP growth rate in Chinese medical institutions is 1.87% that is mainly driven by technological progress (0.75%, per annum), while less contributed by technical efficiency change (0.65%, p.a.) and scale efficiency change (0.47%, p.a.). Disparities of provincial hospital performances are observed that may provide policy implications for decision makers.

Productivity growth and policy changes: A decomposition analysis of Indian metallic mining

Indian mining sector adopted the National Mineral Policy in 1993 and fully open up for foreign direct investment (FDI) in 2005. Prior to 1993, private participation in mining operation was restricted, and public sector played a dominant role in mineral exploration. Metallic minerals hold a vital position in the Indian mining sector and fulfil the input demand of industrial sector by supplying basic raw materials. This paper attempts to estimate and analyse the productive performance of the Indian metallic mining sector by decomposing the total factor productivity (TFP) growth into different components using firm‐level data for the period 1988–89 to 2014–15. Furthermore, the possibility of changes in productivity and its constituent components in different policy regimes have been unravelled. The analysis shows that the average TFP growth of the metallic mining is 0.07% during the study period, which is largely due to technological progress and technical efficiency change. However, TFP growth has declined from 0.28% in 1989–2005 to −0.33% in the period during complete allow of FDI. The decomposition of TFP growth using stochastic production frontier reveals that decline in productivity is due to change in scale efficiency and allocative efficiency components. It could be suggested that to improve the productivity growth further, metallic mining should upgrade to advance technology in operation and take the benefit of the scale factor.

Productivity Growth in Food Manufacturing Industry: Empirical Evidence from Post-reform Sri Lanka

The objective of this article is to measure productivity growth in Sri Lanka’s food manufacturing industry during the 1978–2014 period and briefly review the policy measures adopted over time aiming to improve productivity in the industry. Total Factor Productivity (TFP) growth trends were measured adopting the Cobb–Douglas production function framework using the data extracted from the Annual Surveys of Industries conducted by the Department of Census and Statistics, Sri Lanka. TFP growth was computed for the entire industry as well as for its sub-divisions with emphasis on the scale of operation, type of industry, and policy regimes. Even though the average TFP growth in Sri Lanka’s food manufacturing industries was found to be negative (−0.61%) for the entire period (1978–2014), it is noteworthy that average TFP growth improved over time from −2 per cent during the 1978–1994 sub-period to 0.7 per cent over the 1994–2014 sub-period. Furthermore, large-scale food manufacturing industries achieved higher TFP growth compared to that of their small-scale counterparts. Distilling, rectifying spirits, manufacture of grain mill products and prepared animal feeds industries showed positive and higher TFP growth while cocoa, chocolate and confectionery industries demonstrated a lower TFP growth. Food safety management systems and investments in infrastructure through Public-Private Partnerships were some policy measures that led the productivity growth in Sri Lanka’s food manufacturing industries.

Impact of Migrant Workers on Total Factor Productivity in Chinese Construction Industry

Total factor productivity (TFP) is of critical importance to the sustainable development of construction industry. This paper presents an analysis on the impact of migrant workers on TFP in Chinese construction sector. Interestingly, Solow Residual Approach is applied to conduct the analysis through comparing two scenarios, namely the scenario without considering migrant workers (Scenario A) and the scenario with including migrant workers (Scenario B). The data are collected from the China Statistical Yearbook on Construction and Chinese Annual Report on Migrant Workers for the period of 2008–2015. The results indicate that migrant workers have a significant impact on TFP, during the surveyed period they improved TFP by 10.42% in total and promoted the annual average TFP growth by 0.96%. Hence, it can be seen that the impact of migrant workers on TFP is very significant, whilst the main reason for such impact is believed to be the improvement of migrant workers’ quality obtained mainly throughout learning by doing.

The Role of Agricultural Sector Productivity in Economic Growth: The Case of Iran’s Economic Development Plan

This study provides the theoretical framework and empirical model for productivity growth evaluations in agricultural sector as one of the most important sectors in Iran’s economic development plan. We use the Solow residual model to measure the productivity growth share in the value-added growth of the agricultural sector. Our time series data includes value-added per worker, employment, and capital in this sector. The results show that the average total factor productivity growth rate in the agricultural sector is -0.72% during 1991-2010. Also, during this period, the share of total factor productivity growth in the value-added growth is -19.6%, while it has been forecasted to be 33.8% in the fourth development plan. Considering the effective role of capital in the agricultural low productivity, we suggest applying productivity management plans (especially in regards of capital productivity) to achieve future growth goals.

Does TRIPS Drive to Productivity Growth in Indian Pharmaceutical Industry

This article endeavours to analyse the inter-firm variations in total factor productivity growth (TFPG) of Indian pharmaceutical industry during the pre-Trade-Related Intellectual Property Rights (TRIPS) and post-TRIPS period by using non-parametric Malmquist productivity index (MPI). For analysis purpose, data for 30 major Indian pharmaceutical firms have been culled out from the various reports of the Centre for Monitoring Indian Economy (CMIE) during the period of 1991–2011. The empirical results reveal that the TFPG of the 30 major Indian pharmaceutical firms recorded to be 0.02 per cent and both the technological progress and efficiency change are equally contributing to the TFPG of the firms during entire study and pre-TRIPS period. It has been observed that TFPG has marginally regressed by 0.04 per cent in the post-TRIPS period and the negative growth of the average TFPG was contributed by technical inefficiency, whereas the positive technological progress helps to cover the impact of inefficiencies on TFPG. However, the growth of efficiency remains negative throughout the study period, which has been contributed both by the scale inefficiency and by the pure inefficiency, whereas the technological progress has a favourable impact on the productivity growth of the industry during the post-TRIPS period. Therefore, it can be inferred that the managerial, technical and scale inefficiencies in Indian pharmaceutical industry should be checked in order to operate at optimal scale and achieve potential productivity growth in the post-TRIPS period.

Global Trends of Productivity Growth: Evidence from the Malmquist Index

This paper examines the trend of productivity growth in OECD countries by applying the Malmquist index. Our findings indicate that total factor productivity (TFP) growth in OECD countries was much more sluggish in the 1990s than in the 1980s. The nature of productivity growth also differed between the two decades. During the 1980s, a wave of innovation in production technology is found to have improved productivity in most countries considerably, but at the same time widened the efficiency gap between a small group of technically efficient economies and other nations. However, we find that most countries managed to narrow their gap with technically efficient economies over the following decade although they experienced technological regress during that time. The trend of slow productivity growth continued well into the post-2000 period with the average TFP growth for our sample countries actually being negative over 2001-2006. We note that this deterioration in productivity was largely driven by technological regress while the trend of efficiency convergence prevalent in the 1990s all but disappeared during the period.

Productive Performance of Indian Mining Industry: A Stochastic Frontier Decomposition

This paper has estimated the Total Factor Productivity (TFP) growth of Indian mining Industry for the period 1989-2014 based on a decomposed formulation of stochastic production frontier. Productivity growth and its decomposed components have been compared over the study period. It is found that the annual average TFP growth of mining industry rose up from 3.66 % during 1989-2005 to 8.76 % during 2006-2014. Further, the result of decomposition reflects that the major source of productivity growth has changed from Technological Progress (TP) in initial years to Technical Efficiency Change (TEC) in recent years. In view of this, it could be suggested that mining industry in India requires to focus on investment in innovation and up-gradation of existing technology to further enhance productivity. Keywords: Total Factor productivity; Mining Industry; Panel data; Stochastic Frontier Analysis (SFA)Â

Assessment of the Agricultural Performance in Central and Eastern European Countries

Based on selected individual data acquired from Farm Accountancy Data Network database the output efficiency of agriculture in Central and Eastern European countries at national level is evaluated. Moreover, the output oriented constant returns to scale Data Envelopment Analysis approach is applied in order of Malmquist productivity index calculation. Analysis includes two output variables and six input variables. The data were provided on request from Farm Accountancy Data Network for ten Central and Eastern European Countries and period 2004-2012 (in case of Bulgaria and Romania 2007-2012). Based on the results, the average Total Factor Productivity growth in Central and Eastern European region over the period 2004-2012 was 1.99%. Moreover, it can be concluded that the Total Factor Productivity growth was mainly the result of Technological Change.

Measuring agricultural total factor productivity for the Association of Southeast Asian Nations region

The agricultural sector remains to be one of the key growth engines of countries in the Association of Southeast Asian Nations (ASEAN) region, underlining the importance of strong and sustained agricultural growth as well as enhanced productivity of the sector which could play an instrumental role in contributing to development of the region. In this context, this paper examines agricultural productivity across eight ASEAN countries over the period 2000-2011. The paper contributes to the growing literature on productivity measurement pertaining to agricultural sector in the ASEAN region by empirically estimating agricultural total factor productivity (TFP) through a combination of growth accounting as well as non-parametric techniques such as the Malmquist index data envelopment analysis. The empirical results reveal that ASEAN countries as a group had an average TFP growth around 1.5% over the period of consideration (2000-2011). Individually, the findings show that Malaysia outperforming other countries in terms of TFP growth, with the CLMV countries consisting of Cambodia, Laos, Myanmar and Vietnam, being laggards. The results also show a significant scope for greater collaboration among the ASEAN bloc of countries which can in turn enhance inter-region learning on agricultural technology and resource management.

Does Freer Trade Really Lead to Productivity Growth? Evidence from Africa

Summary Theory predicts that trade liberalization should raise average total factor productivity (TFP) among manufacturing firms. However, this is a generic prediction and depends on maintained assumptions about industries, factor markets, and trade patterns that may not fit well for developing countries. Using firm-level data from Ghana, Kenya, and Tanzania during the 1990s, a period of fairly rapid trade policy liberalization, we estimate productivity effects of trade. Our analysis confirms the well-known association between export intensity and higher productivity of the firm; however, the evidence for “learning by exporting,” or an increase in productivity associated with greater exports, is mixed, with several instances of negative average TFP growth among exporters. Our analysis indicates that such declines are likely attributable to the effects of lower external tariffs, because the firm-level productivity margin below which exporting is unprofitable moves down as the external tariff rate is reduced. We also find that sales to the rest of the world and sales to other African economies have differential effects on productivity growth rates, and that for country-specific reasons, these effects are not uniform. Controlling for initial productivity and the destination of exports (within or outside Africa) helps us understand why in some cases, export participation is associated with negative rates of TFP growth.