Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia*

This article empirically examines the impact of R&D and climate change on the Western Australian Agricultural sector using standard time series econometrics. Based on historical data for the period of 1977–2005, the empirical results show that both R&D and climate change matter for long‐run productivity growth. The long‐run elasticity of total factor productivity (TFP) with respect to R&D expenditure is 0.497, while that of climate change is 0.506. There is a unidirectional causality running from R&D expenditure to TFP growth in both the short run and long run. Further, the variance decomposition and impulse response function confirm that a significant portion of output and productivity growth beyond the sample period is explained by R&D expenditure. These results justify the increase in R&D investment in the deteriorating climatic condition in the agricultural sector to improve the long‐run prospects of productivity growth.     

The relationship between woody biomass consumption and economic growth: Nonlinear ARDL and causality

In this paper, the structure of the relationship between woody biomass energy consumption and real per Capita GDP was analyzed in the period of 1980–2012 for the selected African countries by ARDL (Autoregressive Distributed Lag), nonlinear ARDL, Granger causality and forecast error variance decomposition methods. After a symmetric relationship between woody biomass energy consumption and economic growth was determined by the nonlinear ARDL (NARDL) model, ARDL and Granger Causality methods were applied. According to results of the Granger Causality method, there is a unidirectional causality running from economic growth to woody biomass energy consumption for Botswana, Cameroon, Uganda, and Zambia and from woody biomass energy consumption to economic growth for Burkina Faso, Malawi, Central African Republic, Namibia, Côte d’Ivoire, Djibouti, Gabon and Zimbabwe. The bidirectional causality was supported for Kenya, Lesotho, Madagascar and Togo. Lastly, forecast error variance decomposition method was applied to support the results obtained from Granger Causality method. The forecast error variance decomposition results of real per Capita GDP and woody biomass energy consumption showed that woody biomass energy and real per Capita GDP made the important contribution to the forecast error variance of itself and each other.     

Is agriculture the engine of growth?

We seek to address formally the question raised by Gardner (2003) in his Elmhirst lecture as to the direction of causality between agricultural value added per worker and Gross Domestic Product (GDP) per capita. Using the Granger causality test in the panel data analyzed by Gardner for 85 countries, we find overwhelming evidence that supports the conclusion that agricultural value added is the causal variable in developing countries, while the direction of causality in developed countries is unclear. We also examine further the use of the Granger causality test in integrated data and provide evidence that the performance of the test can be increased in small samples through the use of the bootstrap.     

The public R&D and productivity growth in Australia's broadacre agriculture: is there a link?

This paper investigates the dynamic relationships between research and development (R&D) expenditure and productivity growth in Australian broadacre agriculture using aggregate time series data for the period 1953 to 2009. The results show a cointegrating relationship between R&D and productivity growth and a unidirectional causality from R&D to TFP (total factor productivity) growth in Australian broadacre agriculture. Using the dynamic properties of the model, data from beyond the sample period are analysed by employing the variance decomposition and the impulse response function. The findings reveal that R&D can be readily linked to the variation in productivity growth beyond the sample period. Furthermore, the forecasting results indicate that a significant out‐of‐sample relationship exists between public R&D and productivity in broadacre agriculture.     

The Impact of FDI on CO2 Emissions in Latin America

This paper uses panel Granger causality tests to study the relationship between sector-specific foreign direct investment (FDI) and CO₂ emissions. Using a sample of 18 Latin American countries for the period 1980–2007, we find causality running from FDI in pollution-intensive industries (“the dirty sector”) to CO₂ emissions per capita. This result is robust to controlling for other factors associated with CO₂ emissions and using the ratio of CO₂ emissions to GDP. For other sectors, we find no robust evidence that FDI causes CO₂ emissions.     

CAUSALITY BETWEEN PRODUCTIVITY AND EXPORTS IN AGRICULTURE: EVIDENCE FROM ASIA AND LATIN AMERICA

This paper examines the causal relationship between agricultural productivity and exports for selected Asian and Latin American countries. Alternative views about the causal relationship between these variables of economic interest exist. Economic theory provides no firm basis to judge whether productivity causes exports or exports cause productivity (export-led growth). Since this issue is empirical, econometric tests are utilised to investigate the nature of this causality. Test results are mixed although the export-led growth hypothesis is validated in a few cases.     

Assessing Total Factor Productivity Growth in Sub‐Saharan African Agriculture

The importance of the agricultural sector in the economic development process is well known. Improvements in agricultural productivity are often found to spill into other areas of a developing economy, potentially improving the standards of living of urban and rural workers alike. Given the importance of this sector, accurate measures of total factor productivity (TFP) across countries can be helpful in identifying conditions, institutions or policies that promote agricultural development. In this article, we estimate TFP growth in agriculture for a panel of 39 sub‐Saharan African countries from 1961 to 2007. We also develop a set of development outcome measures theoretically consistent with strong agricultural performance to serve as external validation of our results. We find that three estimation methods (stochastic frontier, generalised maximum entropy, and Bayesian efficiency) generate relative rankings that are consistent with the development outcome measures, providing external validation of the methods. However, the data envelopment analysis approach performs poorly in this regard.     

Livestock in China: Commodity-Specific Total Factor Productivity Decomposition Using New Panel Data

Studies of total factor productivity (TFP) in livestock production are rare, but when available provide useful information especially in the context of developing countries such as China where livestock is becoming more important in the domestic agricultural economy. We estimate TFP for four major livestock products in China employing the stochastic frontier approach, and decompose productivity growth into its technical efficiency (TE) and technical progress components. Efforts are made to adjust and augment the available livestock statistics. The results show that growth in TFP and its components varied between the 1980s and the 1990s as well as over production structures. While there is evidence of considerable technical innovation in China's livestock sector, TE improvement has been relatively slow.     

Research and productivity in Thai agriculture

This paper examines the impact that publicly funded agricultural research has on productivity in crop production within Thailand. It tests empirically the two hypotheses that, first, publicly funded research and development (R&D) in crop production is a significant determinant of total factor productivity (TFP) in the crop sector and, second, that its social rate of return is high. The statistical analysis applies error correction methods to national level time series data for Thailand, covering the period 1970–2006. Emphasis is given to public research in crop production, where most publicly funded agricultural R&D has occurred. The role of international research spillovers and other possible determinants of TFP are also taken into account. The results demonstrate that public investment in research has a positive and significant impact on TFP. International research spillovers have also contributed to TFP. The results support the finding of earlier studies that returns on public research investment have been high. This result holds even after controlling for possible sources of upward biases present in most such studies, due to the omission of alternative determinants of measured TFP. The findings raise a concern over declining public expenditure on crop research, in Thailand and many other developing countries.     

Government Expenditures,Health Outcomes and Marginal Productivity of Agricultural Inputs: The Case of Tanzania

This paper examines the impact of health expenditures on agricultural labour productivity in order to inform the necessary policy decisions about targeting scarce public resources towards their most effective uses. We link health sector expenditures in rural Tanzania to health outcomes and agricultural labour productivity using data from the 2008 Household Budget Survey (10,975 households) and the 2007/08 Agricultural Census (52,594 households) across 113 districts in Tanzania. The results indicate that the marginal productivity of labour as well as land and fertilisers respond significantly to health expenditures. However, the magnitude of the response varies across types of disease, categories of expenditures and agricultural inputs. These findings suggest both the need and scope for targeting public expenditures in the health sector to achieve better agricultural growth outcomes.     

基于参数和非参数方法的玉米生产效率研究——以吉林省为例

本文以中国玉米主产区吉林省为例,基于非参数HMB指数方法和参数K-L随机前沿生产函数方法,采用1991-2005年投入产出的面板数据(Panel Data),对玉米生产的全要素生产率进行实证分析.结果表明,主产区的玉米全要素生产率(TFP)变动具有周期性的变化特点,每一周期技术进步、技术效率、规模效率和混合效率对玉米全要素生产率变动的作用不同;分区综合结果显示,黄金边缘区玉米生产率的增长幅度最高,黄金玉米主产区玉米生产率的增长幅度次之,非主产区玉米生产率的增长幅度最低.今后为促进主产区玉米全要素生产率增长应采取促进技术进步、挖掘主产区潜力等措施.     

Publicly-funded UK agricultural R&D and 'social' total factor productivity

Most studies concerned with measuring the rate of return to publicly‐funded agricultural R&D investment have found high returns, suggesting under‐investment, and calls for increased expenditure have been common. However, the evaluation of returns tends to measure the effect of research expenditure against growth in total factor productivity (TFP), based on market inputs and outputs. When compared against growing public unease over the environmental effects of pursuing agricultural productivity growth, TFP indices become a misleading measure of growth. This paper integrates some non‐market components into the TFP index. The costs of two specific externalities of agricultural production, namely fertiliser and pesticide pollution, are integrated in a TFP index constructed for the period 1948–1995. This adjusted, or ‘social’, TFP index is measured against UK public R&D expenditures. The rates of return to agricultural R&D are reduced by using the ‘social’ as opposed to the traditional TFP index. Whilst both remain at justifiable levels, previous studies appear to have over‐estimated the effect of agricultural R&D expenditures. Furthermore, with changes in policy towards more socially acceptable but non‐productivity enhancing outcomes, such as animal welfare, rural diversification and organic farming, the future framework for analysing returns to agricultural R&D should not be so dependent on productivity growth as an indicator of research effectiveness.     

AGRICULTURAL RESEARCH EXPENDITURES AND AGRICULTURAL PRODUCTIVITY CHANGE

This note comments on the econometric analysis of the dynamic relationship between agricultural research expenditures and agricultural productivity change. The validity of the Almon restrictions, particularly endpoint restrictions, commonly imposed on the distributed lag is questioned. It is suggested that models incorporating such restrictions may lead to biased estimates of the effects of research spending. More fundamentally, doubts are raised as to whether any meaningful relationship between research spending and productivity change can be established from the available data.     

Urbanization and food imports in sub-Saharan Africa

The Granger statistical test of causality was used to examine the relationship between total food imports and urbanization and between food aid and urbanization. Urbanization appears to have caused total food imports to increase in 13 of the 24 countries. Food imports appear to be a cause of urbanization in three countries. Food aid, however, apparently was a cause of urbanization in 16 of the 24 countries used in the analysis.     

Explaining agricultural productivity growth: an international perspective

This article presents multi-output, multi-input total factor productivity (TFP) growth rates in agriculture for 88 countries over the 1970–2001 period, estimated with both stochastic frontier analysis (SFA) and the more commonly employed data envelopment analysis (DEA). We find results with SFA to be more plausible than with DEA, and use them to analyze trends across countries and the determinants of TFP growth in developing countries. The central finding is that policy and institutional variables, including public agricultural expenditure and proagricultural price policy reforms, are significant correlates of TFP growth. The most significant geographic correlate of TFP growth is distance to the nearest OECD country.     

Total factor productivity change in China's grain production sector: 1980–2018

This study analyses changes in total factor productivity (TFP) of grains as an aggregate commodity and major grain crops including rice, wheat, and corn, using pooled provincial and time-series data from 1980 to 2018 for China. Results show that the growth of TFP in the grain sector was driven by technical improvements. Moreover, the grain output and wheat production benefited more from TFP growth, whereas the growth in the usage of inputs drove the growth in rice and corn production. Findings also indicate that the laissez-faire market-oriented policy led to a dramatic fall in output while the intervention-led policy resulted in a substantial rise in output, but neither of them fostered the growth of productivity. Conversely, the incentive-led policy in a market-oriented environment that raised the comparative profitability in grain production promoted the growth in both output and productivity in the grain sector. As the comparative advantage shifts away from agriculture in China, an appropriate support is thus necessary to stimulate farmers' incentive in growing grain crops.     

Technology catch-up in agriculture among advanced economies

We examine whether countries with low initial levels of agricultural total factor productivity (TFP) tend to ‘catch up’ with the technology leaders. We first compare relative levels of agricultural TFP, capital services and labour input levels in agriculture for 17 OECD countries between 1973 and 2011. Then we apply (conditional) convergence analysis to the panel data to examine the speed of convergence and test whether the convergence is transitory or permanent by analysing TFP changes over the business cycle. Capital intensities, quality improvement of capital, factors such as human capital spillovers, and certain agricultural policies are conditioning variables. We examine how differences in relative capital intensities affect agricultural productivity convergence over the business cycle. We find evidence that the speed of convergence increases during periods of contraction in economic activity.     

大连市房地产开发资金来源与价格波动关系研究

基于大连市当前快速上涨的房价问题,根据大连市2004-2012年房地产开发资金来源与房地产价格数据,在利用ADF法对各个时间序列数据进行检验的基础上,运用Granger因果关系检验模型对大连市房地产开发资金来源变动与房价变动之间的因果关系进行分析,并运用灰色关联度方法对与房价有显著Granger因果关系的资金来源之间的关联度进行实证研究。研究结果显示:利用外资与房价的变化并没有直接的因果关系,大连市房地产是以其他资金来源为主,国内贷款和自筹资金对总的资金开发来源的影响处于同一水平。     

Explaining the Decline in UK Agricultural Productivity Growth

This paper reports the results of a study of total factor productivity (TFP) growth in UK agriculture, from 1953‐2000. It shows that prior to 1984 TFP grew at 1.68% per annum and after that date at only 0.26%. International comparisons show that the UK has fallen far behind the leading EU countries. Yield growth declined even more and only labour productivity continues to grow rapidly. In part, the result is due to better data that incorporates more quality adjustment, but the real decline can be explained mainly by cuts in R&D, less patents, less growth in farm size and the demise of public extension. There are other negative factors, which have not been quantified, including asset fixity, convergence and ozone pollution, and a background argument that recent growth rates cannot be sustained.     

Asian Agricultural Productivity and Convergence

This paper measures agricultural total factor productivity (TFP), for eighteen Asian countries, from 1965 to 1996. TFP is measured by calculating the Malmquist index with respect to the sequential frontier, which is appropriate when the cross section is relatively small. The results show that half the countries have experienced negative productivity growth, due to losses in technical efficiency combined with stagnation in technological progress. Both cross‐section and time series tests show that there is no evidence of convergence in agricultural productivity for these countries. The less productive countries are falling further behind, rather than catching up. Finally, comparisons with Africa show that although Asia has had faster TFP growth than Africa, three of the five African regions (East, Central and Southern) have grown faster than any of the Asian regions.