Annual Total Factor Productivity Growth Research Articles

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.

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.

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.

Study on Production Efficiency of Flue-cured Tobacco in China Based on DEA-Malmquist Model

Based on the input-output data of flue-cured tobacco production in 18 provinces of China from 2005 to 2016, the flue-cured tobacco production efficiency was calculated and analyzed. The results show that: Firstly, the total factor productivity (TFP) of flue-cured tobacco in China shows a growth trend, the main reason of the growth is the growth of the scale efficiency. The pure technical efficiency and the technical progress play a negative role to the promotion of total factor productivity. Secondly, in the provinces where total factor productivity declines, the leading factors of total factor productivity declines are different. For the provinces where total factor productivity increases, the leading factor of total factor productivity growth is the improvement of technical efficiency. Thirdly, the change of annual total factor productivity growth rate is unstable because of the uncoordinated change of technological progress and technological efficiency. We can improve the flue-cured tobacco productivity by large-scale production, improving management level, introducing advanced production technology and strengthening technological innovation.

The productivity impacts of energy efficiency programs in developing countries: Evidence from iron and steel firms in China

We study the impact of a national energy efficiency program on total factor productivity (TFP) growth in firms in China's iron and steel industry. Using detailed firm-level survey data and multiple approaches to estimate program effects, we find participating firms experienced greater annualized TFP change. Our base specification estimates the program increased annual TFP growth by 3.1 percentage points, implying an annual private benefit of 148.7 million RMB/year per firm, with approximately equal contributions from technical change and scale efficiency change. Our results suggest that firms undervalued energy efficiency investments prior to the start of the program.

State owned enterprises and capital misallocation in Vietnam

This study uses the first comprehensive data on Vietnamese manufacturing firms and quantifies the allocative efficiency improvement due to massive entry of private firms amid a simultaneous contraction of state-owned enterprises (SOEs) in the period 2000–2008. It finds that allocative efficiency improvement contributes considerably to the sector’s annual Total Factor Productivity growth, and firm’s entry and exit exerts an increasingly important role in the second half of this period. The productivity dispersion within narrowly-defined industries remains, however, large and persistent. Such effect is attributed to the fact that SOEs disproportionately absorb credit in a period marked with unprecedented growth in domestic credit supply. This paper finds that commercial and subsidized credit per se exhibits a capital distortion reducing effect, but awarding more commercial and subsidized credit to the SOEs, in reference to the private counterparts, yields the anti-capital distortion reducing effect that intensifies with the distribution of higher quantiles.

Agricultural productivity growth and drivers: a comparative study of China and India

Purpose – China and India have made significant strides in transforming their agricultural sectors to cut hunger and poverty for the masses through improved agricultural productivity. Given limited land and shift of labor to non-agricultural sector, increasing productivity will continue to be central in agricultural growth in the twenty-first century. The purpose of this paper is to provide comparative analysis of the agricultural total factor productivity (TFP) growth in the two countries. It complements existing literature by examining the evolution and drivers of TFP at disaggregated sub-national level. Richer data allows a deeper understanding of the nature and drivers of TFP growth in the two countries. Design/methodology/approach – This paper applies different analytical framework to address different research questions using data since 1980. China study estimates a parametric output-based distance function using a translog stochastic frontier function. Productivity growth index and its multiple components are calculated using parameters derived from the parametric approach to identify the characteristics of technology such as structural bias. India study first applies data envelopment analysis to estimate the aggregate productivity growth index, technical change (TC), and efficiency change. Next productivity indexes by for traditional crops are estimated using growth accounting framework at state level. Finally, a panel regression links TFP on its determinants. Findings – Several common themes emerge from this comparative study. Faced with similar challenges of limited resources and growing demand, improving productivity is the only way to meet long-term food security. Agriculture sector has performed impressively with annual TFP growth beyond 2 percent in China and between 1 and 2 percent in India since the 1980s. The TFP growth is mainly propelled by technological advance but efficiency had been stagnant or even deteriorated. This study provides a granular picture of within country heterogeneity: fast growth in the North and Northeast part of China, South and East of India. Research limitations/implications – The study suggests some possible policy interventions to improve agricultural productivity, including investment in agricultural R & D to create advanced production technology, effective extension programs and supportive policies to increase efficiency, and diversification from staple crops for sector-wide growth. The India study suggests certain policies may not be contributing much to productivity growth in the long run due to a negative impact on environment. Further studies are needed to expand the productivity analysis to take into consideration of the negative externalities to the society. Data enhancement to account for quality-adjusted inputs could improve the estimation of productivity growth. Originality/value – Each country study reveals certain prospects of the agricultural sector and production technology. China analysis statistically confirms the existence of technical inefficiency and technology progress, suggests the translog form is appropriate to capture the production technology and satisfies conditions stipulated in theoretical models. The results indicate TC does not influence the contribution of output or input to the production process. India study pinpoints the lagging productivity growth of traditional crops, which still derives growth from input expansion. Although different states benefited from different crops, sector-wide productivity gain is primarily the result of diversification to high-value crops and livestock products.

Impacts of Financial Crisis on Regional Efficiency of Banking Industry

This paper focuses on the impact of the financial crisis on the productivity of thirty American banks. We have used CCR, BCC, and Malmquist models using data for 5 years. The models study the effects of technological improvements during the years after the financial crisis on national banks and regional banks. Total factor productivity growth rate is positive and technological efficiency is improved and has influenced more than technology to total factor productivity change over the entire sample period. The Malmquist index summary of banks’ average TFPCs shows average annual total factor productivity growth rates are 12.4%, 1.7%, and 2.1% for national banks, state banks, and Arkansas banks, respectively.

Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis

This study examines the total factor productivity (TFP) growth of the Malaysian electricity generation industry over the 1998 to 2005 period. The stochastic frontier analysis (SFA) approach is used to measure TFP change and decompose TFP growth into efficiency change and technical progress. We find that it achieved average annual TFP growth of 2.34%, with technical change contributing the most to the TFP growth over the eight year period. We hence hypothesise that the new power plants with their newer capital-embodied technologies commencing during the sample period are likely to be the main reason for this strong technical change. In addition, it is also noted that this estimate for the Malaysian electricity generation industry is larger than the estimate obtained for the electricity sector as a whole, where we obtain 1.34% per year for a comparable period.

Productivity development in Icelandic, Norwegian and Swedish fisheries

This article analyses the Total Factor Productivity (TFP) performance of fisheries in Iceland, Norway and Sweden during the period 1973 to 2003. We measure TFP growth using real gross value added as output and capital input, labour input and a stock input index based on the major fish stocks. In developed neighbouring countries, we expect rapid diffusion of fishing technology innovations contributing to productivity convergence. In addition, innovations in the public regulation and the industrial organization may also have influenced productivity growth during the period. We find that Iceland had the highest annual TFP growth. Accounting for stock changes, it amounts to 3%, while the corresponding figures for Sweden and Norway are 2.8% and 0.8%, respectively. Despite best practice fishing technologies being widely available, we find no evidence of productivity convergence among the three countries.

Analysis on DEA-Malmquist efficiency index of medical facilities in Zhejiang province

Objective To measure the changes of total factor productivity (TFP)of Zhejiang medical facilities for decision makers to promote their service efficiency.Methods Collecting the panel data of 2005-2010(four input indexes and five output indexes)from medical facilities in Zhejiang province and measuring with Malmquist index of DEA programs of DEAP2.1.Results The average annual TFP growth rate in the period is 2.0％.A further decomposition found that the average annual growth rate of technology progress is 1.8 ％,while that of technical efficiency and pure technical efficiency is only 0.2％respectively.In the meantime,no scale efficiency growth was found.Conclusion The average annual growth of total factor productivity of Zhejiang medical institutions is substantially low in the period,with technology recession found as well.To maximize productivity of the medical sector,the allocation and internal management should be strengthened to stimulate technical efficiency and scale efficiency while encouraging technology innovation. Key words: Total factor productivity; Malmquist index; Data envelopment analysis; Medical facility

The damage-control effect of pesticides on total factor productivity growth

This paper develops a framework for analysing the sources of total factor productivity (TFP) changes by explicitly taking into account the damage-control nature of pesticides. In the proposed framework, TFP changes are attributed to the conventional sources of growth (i.e. technical change, scale effect and changes in technical efficiency) and the damage-control effect which consists of three distinct components: the first one is due to changes in the initial pest infestation, the second is a spillover effect arising from neighbours' use of preventive inputs and the third is related to abatement effectiveness. The proposed model is applied to a panel of olive-growing farms in Crete, Greece, during the period 1999–2003. The empirical results indicate that the damage-control effect accounted, on average, for 5 per cent of the annual TFP growth and its main component was the improvements in abatement effectiveness. , Oxford University Press.

Foreign Direct Investment and Total Factor Productivity Growth: Does Distance from Technology Frontier Matter

In this paper we examine the effect of Foreign Direct Investment (FDI) on international variation in Total Factor Productivity (TFP) growth rates. In particular, we investigate whether a country's initial distance from technology frontier influences the degree to which a country can benefit from FDI. Adopting a logistic function of technology diffusion, this paper finds that a one standard deviation increase in distance reduces impact of FDI on annual TFP growth rate by 0.50% during the 20 year period. The results are robust to inclusion of other relevant control variables and consideration of endogeneity. Using the sample splitting technique recently developed by Hansen (2000), we also find that if the initial distance of a country exceeds a threshold level, then the follower can catch-up with the leader. On the other hand, for a country below the threshold level, there is significant negative impact of FDI that increases with distance. Consequently, the net benefit from FDI can be infinitesimal for some countries.

The Effect of Privatization on Productivity and Capital Adjustment

A JR is one of several freight and passenger railway companies created in 1987 after Japan National Railway (JNR) was privatized and separated. The authors use econometric techniques to examine total factor productivity (TFP) increases and to analyze how performance has changed among the JRs. The authors also examine whether, before privatization, capital input overcapitalization existed. Privatization raised annual TFP growth by 1.62%, bringing total annual TFP growth to 2.97% after privatization. Privatization has largely corrected the former JNR's over-capitalization.

ACCOUNTING FOR DISCREPANCIES AMONG ESTIMATES OF TFP GROWTH IN EAST ASIA

Five studies of total factor productivity (TFP) growth in eight East Asian countries are surveyed. The discrepancies among the studies are very large: the average absolute discrepancy across studies of estimated TFP growth in each country exceeds the average absolute difference across countries of the rates estimated by each study. A method for decomposing these large discrepancies among the studies is proposed and applied. The single largest source of discrepancies is the estimated elasticity of GDP with respect to capital. It is argued that the two studies that used regression estimates of this elasticity are probably less reliable than the three that derived it by assuming that factors are paid the value of their marginal product. On this basis, our preferred estimates imply that annual TFP growth in East Asia ranged from 3 per cent in Japan to a small decline in the Philippines.

Market Imperfection and Productivity Growth—Alternative Estimates for Taiwan

This study first explores why the shares of factor inputs have not been measured correctly and concludes that the earlier findings are biased due to the miscalculation of factor shares which have produced low estimated total factor productivity (TFP) growth in the East Asian countries. Second, three approaches are proposed to empirically illustrate the impact of capital and labor shares on the estimates of TFP growth. It is suggested that TFP growth in the East Asian economies will be understated if net indirect taxes and imperfect competition profit are ignored. Finally, by taking the net indirect taxes and imperfect competition profits into account, the result of this paper indicates that Taiwan's economy has enjoyed an average annual TFP growth rate of 3.6% over the period 1980–1999.

A DEA Approach to Understanding the Productivity Growth of Malaysia's Manufacturing Industries

This paper seeks to explain the productivity growth performance of Malaysia's manufacturing sector using a panel data of 28 industries from 1981–1996. Here, the data envelopment analysis technique is used to calculate and decompose the Malmquist index of total factor productivity (TFP) growth into technical change, change in technical efficiency and change in scale efficiency. This allows the identification of the sources of productivity growth which is crucial for policy formulation. It was found that the annual TFP growth of the Malaysian manufacturing sector was low at 0.8% and this was driven by small gains in both technical change and technical efficiency, with industries operating close to optimum scale.

Changes in Economic Regime and Productivity Growth: A Study of Indian Public Sector Banks

The total factor productivity (TFP) growth of Indian public sector commercial banks is examined using 23-year-long panel data. A multiple-output translog cost system, extended to accommodate both heteroskedasticity and autocorrelation, is used to measure TFP growth in the presence of quasi-fixed factors. TFP growth is further decomposed into three components, i.e., technological change, scale economies, and the effect of imperfect adjustment of quasi-fixed factors. The translog cost system is corrected for both heteroskedasticity and autocorrelation. On average, the banks achieved an annual TFP growth of 2%. During recent deregulation, the growth rate has improved to 7%.J. Comp. Econom.,October 1997,25(2), pp. 196–219. Marketing Sciences, AT&T, Basking Ridge, New Jersey 07920; Marketing Sciences, AT&T, Somerset, NJ 08873; University of Texas, Austin, Texas, 78712-1172.

Why Some R&D Organizations Are More Productive Than Others

For several years, my colleagues and I have been trying to understand how technology-intensive firms that are highly productive differ from less productive firms in the way they mane their RD namely, the costs of labor, plant, property and equipment, and materials. Economists have developed and applied such a measure to the study of technological change and productivity growth. The methodology is known as the Total Factor Productivity (TFP) approach. The TFP index is the ratio of outputs to inputs. Output is measured by real value of net sales; while input is measured by the combination of (real) production factors used to produce the output, weighted by their respective output shares (L, C and M); i.e., (Equation omitted) TFP growth over time (DeltaTFP) is measured in terms of differences in growth rates of outputs and inputs. Empirically, it has been found that in the past several decades productivity has grown faster in the United States than would be predicted from direct measurement of changes in these three factors of production (after appropriate adjustments for price changes). This in growth of measured outputs relative to measured inputs has been examined carefully and often by economists. They conclude that the excess is caused by technological change, or to be more precise, changes in the stock of technical knowledge. When R&D expenditures are used as a surrogate for the rate of technological change and added to the list of factors of production, it has been found that R&D accounts for impressive national and industry-wide gains in productivity growth after all other factors have been taken into account. Statistically valid estimates ranging from 30 percent to more than 100 percent returns to R&D expenditures are the norm. Thus, the contribution of changes in the stock of technical knowledge and gains in productivity can be understood by empirically estimating the relationship between R&D expenditures and TFP growth, holding other factors constant. This means the productivity impact of R&D can be assessed by the expression: TFP growth = a + b* (R&D intensity), where a is a constant parameter and b is the impact of R&D input on TFP measured as a marginal rate of change. R&D intensity is measured by expressing R&D expenditures as a percentage of sales. Our research goal, then, was to carefully measure all of these variables so that we could isolate the R&D variable and see if we could find a relationship between not only the level of R&D investment but between the composition of that investment and productivity growth. We began the project by selecting 15 drug firms and looking at the relationship between R&D intensity and productivity growth in these firms between 1971 and 1990. Figure 1 shows the average annual total factor productivity growth of these firms over 20 years computed from publicly available data.(Figure 1 omitted) Eli Lilly, for example, improved its productivity an average of 2.9 percent per year over that period and invested 4.5 percent of sales in R&D. Looking at the R&D-to-sales ratio in Figure 1, (i.e., R&D intensity) there is a consistent relationship with annual total factor productivity growth for this sample of companies over this period. That began to make us feel we might be looking at something worthwhile. We then plotted each of those 15 companies against some financial ratios that CEOs or security analysts might be interested in. Return-on-assets measured against total factor productivity growth looks pretty interesting. …