Agricultural Total Factor Productivity Growth Research Articles

New evidence of the driving forces behind Brazil's agricultural TFP growth—A stochastic frontier analysis with climatic variables and land suitability index

AbstractUsing panel data from 510 Brazilian micro‐regions in three census years (1995, 2006 and 2017), this study presents a productivity decomposition for the Brazilian agricultural sector using stochastic production frontier methods that account for the effects of rainfall, temperature and the land suitability index. We also calculated the total factor productivity (TFP) index and decomposed it into technical efficiency, technological change, scale efficiency and environmental efficiency. This article thus provides a new and more realistic assessment of recent Brazilian agricultural productivity growth. In recent decades, Brazilian agriculture has become widely known for presenting fast productivity growth; however, our results suggest that a lower TFP growth rate than previous estimates (1.96% per annum) and the overall effects of climate change could potentially compromise Brazilian agricultural TFP growth in the long run. Our findings might thus generate insights for agricultural and regional policies to increase efficiency in the sector and promote sustainable agricultural development in Brazil, which will contribute to the sector's competitiveness in international markets, the country's social and economic welfare, and environmental conservancy.

The nexus of foreign direct investment and agricultural productivity: does absorptive capacity matter?

PurposeThis study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.Design/methodology/approachEmploying provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.FindingsThe results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).Originality/valueThis study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.

Analysis of Spatial Unbalance and Convergence of Agricultural Total Factor Productivity Growth in China—Based on Provincial Spatial Panel Data from 1978 to 2020

Using the provincial panel data from 1978 to 2020 as the research object, this study employs the fixed effect SFA-Malmquist model to measure the agricultural total factor productivity of each province and city, and the spatial correlation of China’s agricultural total factor productivity is determined by Moran’s I. On this basis, three weights (adjacency, economy, geography) are included as spatial factors in three spatial β-convergence models (SAR, SEM and SDM), and the spatial convergence characteristics of China’s agricultural total factor productivity are analyzed in different time periods and different regions. The study found that: First, China’s agricultural total factor productivity shows a growing trend, but as time goes on, its growth rate gradually slows down, and the growth rate in the eastern region is higher than that in the central and western regions. Second, China’s agricultural total factor productivity has significant spatial correlation and spatial convergence characteristics. The differences in agricultural total factor productivity in various regions are shrinking over time, and the spatial spillover effect significantly shortens the convergence process. Due to spatial convergence, while carrying out agricultural production, all regions should thoroughly consider the advantages of agricultural resources in neighboring regions and strengthen cooperation and exchanges between regions.

Comparative performance of agricultural productivity in 44 SSA countries for a period of 59 years (1961-2019): A Malmquist productivity index approach.

We investigate the extent and nature of productivity growth in Sub-Saharan African countries using non-parametric frontier techniques. In this work, we examine agricultural total factor productivity (TFP) change in 44 countries in Sub-Saharan Africa (SSA), covering a period of fifty-nine (59) years (1961-2019). We make use of data drawn from the Food and Agriculture Organization of the United Nations. Due to the non-availability of reliable input price data, the study uses data envelopment analysis (DEA) to derive Malmquist productivity indices. The results demonstrate a decline in agricultural TFP growth in the region from 1961 to 2019. This notwithstanding, a general average growth was seen in some of the conventional inputs measured (land, labour, capital, and fertilizer) which are the main drivers of growth in the region. This finding implies that the increase in agricultural output over the past five decades in SSA is mainly due to an increased use of conventional inputs over time, including land, and not due to an increase in the ratio of output over inputs. As a generally acceptable and preferred indicator of technical and efficiency changes, we use TFP to calculate the Malmquist productivity index (MPI).

Productivity in Indonesian agriculture: Impacts of domestic and international research

AbstractTotal factor productivity growth contributed 38% of Indonesia's agricultural output growth from the mid‐1970s to the mid‐2000s. This study uses time series data analysed with an error correction mechanism to examine the contribution that Indonesian publicly funded agricultural research made to this outcome, allowing for other possible determinants of productivity growth, including international agricultural research, extension, government price policy and weather. The results imply a 27% real annual rate of return from a marginal increase in Indonesian agricultural research expenditure. Indonesia's public agricultural research explains virtually all of its agricultural total factor productivity growth between 1975 and 2006.

Can agricultural trade improve total factor productivity? Empirical evidence from G20 countries

Improving agricultural total factor productivity is essential to achieving the high-quality and sustainable development of agriculture. As major global agricultural producers, the G20 countries play an important role in agricultural product trade and development. As such, it is well-positioned to play a positive role in improving agricultural total factor productivity. This paper uses the DEA-Malmquist index method to measure agricultural total factor productivity (TFP) in G20 countries from 2010 to 2019, and analyzes the impact of agricultural trade on TFP using the two-way fixed effects model. It finds that (1) the main source of agricultural TFP growth in G20 countries is technical progress, while the effect of technical efficiency on agricultural TFP is not obvious. (2) Agricultural trade can significantly improve agricultural TFP growth in G20 countries, and the effect is more obvious in developed countries. From the perspective of trade flow, the positive effect of export trade on agricultural TFP is stronger. (3) The institutional environment strengthens the improvement effect of agricultural trade on agricultural TFP. Thus, this study not only provides valuable insight into the relationship between agricultural trade and agricultural productivity, but also offers a strong argument in favor of the formulation of relevant policies to improve agricultural productivity and promote a more sustainable agricultural sector.

Policy Impacts of High-Standard Farmland Construction on Agricultural Sustainability: Total Factor Productivity-Based Analysis

High-standard farmland construction is an important initiative in China that promotes sustainable agricultural development and ensures food security through land consolidation. This study measures the growth of agricultural total factor productivity (ATFP) in China, which is used to characterize the sustainable development of agriculture. Using provincial panel data from China and a continuous difference-in-difference (DID) model, the study examines the impact of high-standard farmland construction policy on ATFP growth. Results show that ATFP in China has an increasing trend with an average annual growth rate of 3.6%. The average enhancement effect of high-standard farmland construction policy on ATFP is 1.0%, which remains significant after various robustness tests. The positive effect of the policy on ATFP becomes apparent in the third year of implementation and shows a gradually increasing trend. The study also finds that the impact of high-standard farmland construction on ATFP is more pronounced in the central regions of China, the main grain-producing regions, and the regions with higher ATFP. High-standard farmland construction policy enhances ATFP by promoting agricultural technology change and technical efficiency. To promote the growth of ATFP and achieve sustainable agricultural development, China should continue to promote the construction of high-standard farmland and explore suitable construction models for different regions.

Agricultural expenditure and agricultural total factor productivity growth in South Africa

<abstract> <p>The study investigates the impact of government agricultural expenditure on agricultural total factor productivity (TFP) growth in South Africa. South Africa subscribes to the African Union-inspired Comprehensive Africa Agriculture Development Programme (CAADP), established in 2003 to exterminate hunger and lessen absolute poverty. CAADP requires governments to allot at least 10% of government expenditure to agriculture and achieve an average 6% annual growth in agricultural GDP through doubling agricultural productivity. Despite launching CAADP in 2011, South Africa is off-track. Our analysis follows a two-step procedure using data for the period 1986 to 2018. Firstly, using input and output data, we estimate agricultural TFP indices using the growth accounting (GA) and the Malmquist-Data Envelopment Analysis (DEA) methods. Secondly, we use the Autoregressive Distributed Lag econometric technique to estimate the agricultural TFP impact of government expenditure. Estimates from the GA approach proved more reliable. We find that government agricultural expenditure has a significant positive effect on agricultural TFP growth of 4% and 18.5% in the short-run and long-run, suggesting high and increasing marginal gains. Estimations on weather variables reveal that a 1% increase in average temperatures and rainfall would increase TFP by 2.7% and 1.4% respectively. We recommend that South Africa fully implements the CAADP. Also, given significantly positive estimates of imports and exports, we call for increased agricultural trade liberalization biased towards export promotion and more intra-Africa agricultural trade within the AfCFTA framework.</p> </abstract>

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.

Impacts of Climatic Variability on Agricultural Total Factor Productivity Growth in the Southern United States

This study investigates the impact of climatic variability on both agricultural production and total factor productivity (TFP) in the Southern United States (US). It also aims at identifying the drivers of productivity in this region. The analysis is tailored to inform decision makers about effective policy options to increase and sustain productivity in this important agricultural region. We use data from the US Department of Agriculture, National Climatic Data Center, and US Geological Survey to estimate alternative stochastic production frontier models. The estimated parameters are then analyzed and used to compute and decompose TFP into several measures of efficiency. The results show that agricultural production in the Southern US is more responsive to labor and has been increasing at a 1.13 percent rate annually. The findings also suggest that while precipitation, on average, has a positive and significant impact on productivity, intra-annual variation in both temperature and precipitation, which can be considered as anomalies, has a negative and significant impact on production. The impact of climatic effects on productivity across states is mixed and technological progress has been the main driver of TFP growth. Findings indicate that climatic variability is having a negative impact on agricultural productivity in the Southern US, similar in magnitude to the positive impact of irrigation.

Agricultural Trade Liberalisation and Agricultural Total Factor Productivity Growth Convergence in Africa

Reducing income inequality in Africa rests on agricultural total factor productivity (TFP) growth and convergence. Liberalizing agricultural trade has emerged as a force of agricultural TFP growth convergence. Notwithstanding increasing agricultural trade, TFP in Africa is falling while the differences in TFP growth rates remain wide. We provide evidence on the impact of agricultural trade liberalization on agricultural TFP growth convergence. We examine trade by origin, disaggregated into intra-Africa, and rest-of-the-world trade. Also, we recognize the uniqueness of agricultural trade liberalization and analyze the effect of the removal of trade-distorting agriculture support. Using maize and rice data for the period 2005-2016, we apply a Feasible-Generalized- Least-Squares estimation of panel data models derived from Barro and Sala-i-Martin (1990). We find evidence for both absolute and conditional convergence, which is stronger for maize. Moreover, agricultural trade openness speeds up TFP growth convergence for both crops. Convergence speed is higher for intra-Africa trade. Estimations on domestic agriculture support suggest that reduction of support beyond distortion-free levels enhances TFP growth convergence. Our findings call for more agricultural trade liberalization. We appeal that the recently launched Africa Continental Free Trade Area prioritizes intra-Africa agricultural trade liberalization and further elimination of trade-distorting domestic agriculture support.
 Vol. 9, No. 2, August 2022: 71-88

Exploring the Growth of Agricultural Productivity in AFRICA: A Färe-Primont Index Approach

The effort to increase agricultural productivity continues to receive interest in Africa as low productivity levels, poverty and food insecurity remain or even increase. This study used the Färe-Primont Index to estimate agricultural total factor productivity growth for 49 African countries. Panel data consisting of 833 observations for the period 2000 to 2016 were obtained from the United State Department of Agriculture Economic Research Service database. The results show that the average growth rate for agriculture in Africa is 0.73% per annum. The sector experienced increased growth after the Maputo Declaration, which was sustained during the global financial crisis. West Africa experienced the largest growth while Southern Africa suffered a substantial decline. The study also discovered that growth differed between countries indicating that customization of the Comprehensive Africa Agriculture Development Programme into regional and country-specific policy interventions is important to boost agricultural productivity. Finally, the growth was achieved through technical change, while efficiency change constrained growth. Policy-makers should increase investment in agricultural extension services, education and training to enhance managerial capacity (efficiency change) because improved managerial capacity could increase agricultural growth and thereby increase food security and alleviate poverty in Africa.

Does agricultural mechanisation promote agricultural TFPG? Evidence from spatial panel data in China

ABSTRACT Does the promotion of agricultural mechanization level have spatial driving effects on the agricultural total factor productivity growth (TFPG)? Based on spatial panel data from 2000 to 2019, we begin by measuring agricultural TFPG, then incorporating spatial econometric models as well as carrying out spatial regression to first explore the influence agricultural mechanization level has on the agricultural TFPG. Meanwhile, we also perform decomposition of the spatial regression results to further study the spatial spillover effects performed by agricultural mechanization. The study suggests that the promotion of agricultural mechanization level has exerted significant spatial spillover effects on the agricultural TFPG, especially in the eastern and northeast regions of China, demonstrating obvious radiation effects, whereas the central and western regions may not produce such intense spatial spillovers due to the pattern of agricultural development. The results could not only enhance the understanding of agricultural mechanization on the agricultural TFPG but also produce constructive implications for optimizing the spatial layout of agricultural mechanization development, promoting agricultural development according to local conditions and formulating reasonable agricultural economic development policies.

Assessing Africa’s Agricultural TFP for Food Security and Effects on Human Development: Evidence from 35 Countries

Population growth, food shortages, and low levels of human development have been longstanding issues confronting many African countries. Agricultural productivity remains a critical goal for mitigating these challenges and ensuring overall economic development. Total factor productivity (TFP) is a crucial metric for determining a sector’s overall growth. However, due to a lack of comprehensive assessments of the trends and determinants of TFP growth in African agriculture, there are disagreements. Within the context of inclusive human development, the impact of agricultural productivity is frequently misrepresented in the current literature. This paper estimated TFP growth and assessed its impact on human development in Africa. Due to technological improvement, TFP increased moderately at a 5.4% growth rate across African countries over the period (2001–2019). Empirical evidence indicates that TFP growth enhances human development in the long run, but the effect varies according to levels of human development (HDI) and the nature of growth over time. For instance, higher levels of human development tend to mitigate the impact of TFP. Further analysis revealed that technical efficiency improvement is critical for enhancing food safety and human development. Policy recommendations for improving TFP for food security and human development in Africa are provided. Further investigation into agricultural TFP’s impact beyond the poverty measure in Africa is encouraged.

Agricultural trade liberalisation, agricultural total factor productivity growth and food security in Africa

ABSTRACT The study draws inference on the impact of agricultural trade openness, total factor productivity (TFP) growth, and domestic agriculture support on food security in Africa. To retain estimates efficiency and consistency in the presence of complex error terms, we employed the Panel-Corrected-Standard-Error (PCSE) estimator on panel data spanning 2005–2016 for 13 African countries. Results suggest that agricultural trade liberalisation and TFP have significant and favourable effects. Moreover, we find that reducing agricultural support beyond distortion-free levels enhances food security. Further to trade openness, we call for export growth-oriented domestic support anchored on agricultural human-capital development, innovation, and research and development.

Decomposition of climate-induced productivity growth in Indian agriculture

This paper adopts a stochastic frontier approach to investigate the trend and determinants of total factor productivity (TFP) growth in the agriculture sector of India, using extensive district-level data. The assessment of the production frontier highlights the efficiency aspect of Indian agriculture and contributes to an analysis of those factors that might be directly engaged in the production process. After controlling for the district-specific climatic effect in the production of eighteen major crops, TFP growth is deconstructed into technical progress, technical efficiency change and scale effects. Four weather parameters, average temperature, rainfall, evapotranspiration and windspeed, are defined as exogenous determinants of the technical inefficiency term to analyze the influence of changing climate. Based on the true fixed effect model and maximum likelihood method, the estimated TFP growth averaged 0.688% per year between 1990 and 2015. The relative performance of Indian states apparently differs according to estimated productivity scores. The findings show that changes in technical efficiency account for most TFP growth, whereas differences in scale components account for annual and cross-state productivity growth disparities. The study suggests that region-specific policies are required to enhance agricultural productivity and add to the understanding of the arguments over TFP growth in Indian agriculture.

Using malmquist TFP index for evaluating agricultural productivity: Agriculture of Türkiye NUTS2 regions

Agriculture is one of the main economic sectors in Türkiye. Therefore, a performance evaluation is essential for an improvement in agricultural sector. In this study, the productivity of Turkish agricultural sector was analyzed for the years between 2006-2015. A non-parametric technique, Data Envelopment Analysis (DEA) based Malmquist index method, was applied to calculate the Total Factor Productivity (TFP) indices for agriculture in 26 NUTS2 (The Nomenclature of Territorial Units for Statistics) regions of Türkiye for the selected 10-year period. Total agricultural production value is used as the output variable and six input variables are selected as: land, labor, machine, livestock and government investment. The analysis was conducted via the computer program DEAP2.1. The result reveals that agricultural TFP of regions has decreased by 2% annually on average. The maximum TFP growth in agriculture occurred between 2007 and 2008 with a mean increase of 12% in overall TFP of regions. On the other hand, the greatest regression in the overall TFP was observed in 2010-2011 period by a decrease of 13%.

Has mobile phone technology aided the growth of agricultural productivity in sub-Saharan Africa?

Background: A recent increase in the adoption of mobile phone technology generated a great deal of interest and optimism regarding its effect on economic development in sub-Saharan Africa (SSA), particularly on the enhancement of agricultural development.Aim: In this study the impact of mobile phone technology on agricultural productivity in SSA is examined.Setting: The empirical assessment uses a panel data set covering 41 countries over a period of 25 years.Methods: We employed an econometric approach and panel data covering 41 countries and a 25 year-period (1990–2014) to investigate the effect of the adoption of mobile phone technology and other socio-economic variables on agricultural total factor productivity (TFP). The use of regression analyses allowed us to estimate and measure the contribution of certain variables to agricultural TFP growth in SSA.Results: The results show that the uptake of mobile phone technology had a positive effect on agricultural TFP growth in SSA.Conclusion: Mobile phone technology has been established to be one of the drivers of agricultural productivity in SSA.Implication: The implications of this study are that governments, NGOs, and businesses working on improving agricultural productivity and food security in SSA need to continue endorsing mobile technology as a means to improve agricultural productivity.

Research of Total Factor Productivity and Agricultural Management Based on Malmquist-DEA Modeling

Based on the Malmquist-DEA Modeling and drawing on the data from 12 cities in Hubei, a central province of China, this paper measures the total factor productivity (TFP) of agricultural management as well as technological change (TC) and technical efficiency change (EC). The Cobb–Douglas (C-D) production function is adopted to empirically estimate the impacts of TFP and its constituent elements on the agricultural management and economic growth comprehensively and further study the effects on different regions in Hubei. The results demonstrate that TC grows at an annual average rate of 6.7% and drives agricultural TFP growth in Hubei. The decline in scale efficiency accounts for the drop of 1.1% of EC. The agricultural TFP growth rates among different regions vary remarkably but overall have a positive and significant effect on agricultural output. The research sheds light on the analysis of agricultural development of Hubei according to the findings based on Malmquist-DEA Modeling and provides practical implications for the future management.

Farmland transfer and agricultural economic growth nexus in China: agricultural TFP intermediary effect perspective

PurposeThe multidimensional effects of farmland transfer in China have been profoundly unstudied. The purpose of this paper is to provide insights on the effects of the intermediary role of agricultural total factor productivity (TFP) of farmland transfer on agricultural economic growth in China.Design/methodology/approachBased on the agricultural data of 30 provinces in China over the period 2005–2018, this paper uses the intermediary effect model to test the relationship between farmland transfer, agricultural TFP and agricultural economic growth. This paper employed an intermediary effect test model to investigate the intermediary role of agricultural TFP in the influence of farmland transfer on agricultural economic growth.FindingsThe findings indicated that farmland transfer has a significant effect on promoting agricultural economic growth. There is a significant “inverted U-shaped” relationship between farmland transfer and agricultural TFP. The sample value of 84.3% of farmland transfers in China is still within the TFP promoting effect range. In addition, farmland transfer has an indirect impact on agricultural economic growth through the channel of agricultural TFP. Agricultural TFP plays a significant intermediary role, but the effect is relatively lowOriginality/valueThis paper is the first to provide fundamental evidence on the impact of farmland transfers on agricultural economic growth in China, driven by agricultural TFP as an intermediary factor. Agricultural TFP can reduce the involution effect of farmland transfer and promote an indirect effect on agricultural economic growth.