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The primary purpose of this paper is to take an in-depth look at the question of whether liberalizing trade in agriculture can generate dynamic productivity gains comparable to those in the manufacturing sector.

In contrast to the manufacturing sector that has generated firm/plant-level trade data, there is a lack of farm-level trade data that are needed for empirical measurement of dynamic productivity gains. Therefore, the authors use thought experiments to analyze the sequence of events that would occur when trade is liberalized for agriculture; delineate the expected behaviors of the actors involved in the trade and draw inferences about whether there would be dynamic productivity gains from agricultural trade.

The central finding is that there would be little dynamic gain from agricultural trade at the farm level due to the limited role of producers in shaping their international competitiveness. Yet, agricultural trade may generate dynamic gains if states or input supply corporations respond to the freer trade environment by making more investments for research and development (R&D). Further, when intraindustry prevails, there can be productivity gains at the industry level due to the transfer of resources from less to more efficient farm producers.

The findings of the paper are expected to present insights into value for researchers working in the area of agricultural trade; for agricultural trade policymakers in developing countries and for trade negotiators engaged in reforming or designing World Trade Organization (WTO)’s trade rules for agriculture.

This study investigates the effect of renting in land on farm productivity, and the impacts of rented-in land size and transaction partner type on farm productivity.

Data from the 2015 China Household Finance Survey are analyzed using an extended regression model and the two-stage least squares method.

Farm households that rent in land are likely to achieve higher farm productivity, and ignoring endogeneity underestimates the positive effect of land renting-in. Further evidence indicates that rented-in land size has an insignificant impact on farm productivity, and that there is no difference in farm productivity between lessees renting-in land from acquaintances and those renting-in land from non-acquaintances. These results may be caused by the higher degree of marketization of land rentals between acquaintances in China. With increasing competition in agricultural factor markets, in theory, rented-in land size should not affect farm productivity.

Overall, the analysis suggests that renting in land improves farm productivity, which supports the land transfer policies that have been rolled out in recent decades in China. However, our finding that rented land size does not affect farm productivity, consistent with the results in the literature, implies that the Chinese government should no longer subsidize or prefer large farms with low productivity. More attention should be paid to small lessees and market-oriented land rentals between acquaintances. Promoting the marketization of land transfers inside acquaintance networks could realize the potential of the land market, especially if land transfers decrease.

This study identifies the effects of renting in land, rented-in land size and type of rental transaction partner on farm productivity using nationally representative data. The findings imply that the government should pay more attention to the marketization of land rentals between acquaintances. Although existing studies regard land rental between acquaintances as informal and of low efficiency, the recent evidence shows that China's land markets are changing, and policy makers should adjust their policies accordingly.

The purpose of this paper is to examine the connections of agricultural productivity, access to credit and farm size in Africa using Ghana as a case study.

The paper employs mixed methods – quantitative and qualitative strategies for data collection and analyses. The hierarchical competitive model was used for the quantitative analyses supplemented with qualitative analyses using key informant interviews, focus group discussions and household case studies.

The results show that there is significant relationship between credit from formal and informal sources and agricultural productivity. Thus access to formal and informal credit increases farm household agricultural productivity by about 0.10 (p=0.05) and 0.45 (p < 0.01), respectively. The quadratic terms of formal and informal credit as well as farm size were found to significantly influence agricultural productivity. The implication of this is that the relationships between formal credit, informal credit and farm size on one hand and agricultural productivity on the other are non-linear in nature. The interactions of formal credit with informal credit; informal credit with farm size; and formal and informal credit with farm size have significant relationships with agricultural productivity. The amount of remittance received by farm households has negative and insignificant influence on agricultural productivity. Market access is also an insignificant determinant of agricultural productivity in Ghana.

This paper provides new insights on whether the scale of production (farm size as proxy) and access to financial services (credit as a proxy) matter in promoting agricultural productivity in Africa using Ghana as a case study. Thus the paper is of relevance to policy-makers and practitioners in Africa and Ghana in particular who are seeking to make informed policy decisions on effectively incorporating credit provision into the agricultural transformation agenda of the continent.

The purpose of this study is to assess the impact of credit constraints on agricultural labour productivity as well as the impact of credit constraints and agricultural labour productivity on rural households' consumption in Ghana.

This study uses the Ghana Living Standard Survey round six (GLSS 6) as the main source of data, which happens to be one of the most comprehensive household datasets in Ghana. Quantitative estimation techniques (namely: Endogenous Switching Regression and Two Stage Least Squares) are used to address possible endogeneity and selection into credit markets.

First, large households are prone to credit constraints while age (experience) and compliance with extension advice reduce credit constraints. Second, the determinants of agricultural labour productivity for both constrained and unconstrained households are age, sex, farm equipment, herbicide and farm size. Third, household size, education and livestock rearing influence agricultural labour productivity of constrained households. Fourth, credit constraints, irrespective of how they are measured, impede agricultural labour productivity while access to credit fosters labour productivity. Lastly, credit constraints robustly reduce consumption while agricultural labour productivity strongly enhances rural households' consumption.

The first contribution is that, unlike most previous studies, we do not focus on the widely used measure of productivity – output per unit land, but on agriculture labour productivity in particular. Secondly, unlike most previous studies which examine the effect of credit constraints either on productivity alone or consumption alone, our study examines the impact of credit constraints on both. Thirdly, unlike the existing literature which uses one or two measures of credit constraints, we use a wide range of measures of credit constraints – seven different measures of credit constraints. Lastly, our empirical strategy solves at least two critical econometric problems – sample selection bias and endogeneity.

The farm size-productivity relationship has long been the subject of debate among development economists. Few studies address this issue for China, and those that do only with outdated data sets poorly representing the current situation after the past decade of rapid change, which includes the rapid development of land rental markets, village labor out-migration and use of farm machines. Meanwhile, many studies have researched this relationship for Indian, which is undergoing similar changes except for the development of active land rental markets. The purpose of this paper is to measure the farm size-productivity relationship under the situations of rapid transformation in China and India.

Based on the data of 325 Jiangxi and 400 Allahabad rice farmers in 2011, the survey covered multiple plots of each household in one/multiple growing season(s). The authors use the production function approach and the yield approach, and control for farmland quality, imperfect factor markets, and farm size measurement error, to identify the farm size-productivity relationship.

The regressions show that land yields increase with plot size both by season and over the year in China. This may be one of the reasons that farm sizes are growing in some areas. In India, however, the inverse farm size-productivity relationship is observed by the study, despite recent changes. Moreover, land yields increase with farm machine use in both China and India. This result contributes to the debate over whether mechanization improves yields or just expands the land frontier.

The paper empirically estimates the farm size-productivity relationship under rapid agrarian transformation in both China and India based on a unique data set collected by the authors in a detailed primary survey. The paper considers measurement error in the analysis, which adds values to this type of analysis.

The purpose of this paper is to examine the long-term relationship between farm size and productivity in China at the national level.

In contrast to the micro-data examination conducted by earlier literature, in this study, the authors use household aggregate panel data on 29 provinces in China for 1988–2012. Using the panel data PMG model, the authors control the factor of difference in land quality due to the fixed effect in each province, and the authors consider the difference in the long-run coefficients of farm size and land productivity rather than the difference in their short-run relationship. Thus, the authors examine the long-term relationship between farm size and productivity. Furthermore, the authors examine the robustness of this relationship in the long-term using samples of rice, wheat and corn production by region.

In contrast with the findings presented previously, the authors find that the relationship between farm size and agricultural productivity is statistically positive in the long term.

The relationship between farm size and agricultural productivity is a key research issue in agricultural and development economics. In China, many studies have provided evidence of the inverse relationship between farm size and agricultural productivity at the family farm level. However, this inverse relationship seems to reflect specific regions and specific periods in the relationship between farm size and land productivity. At the nationwide level, in the long-term, this is not an inverse but a positive relationship. It is desirable to expand farm size for the long-term development of agriculture.

Whether there exists an inverse relationship (IR) between farm size and its efficiency remains a hotly debated question among agricultural economists. In most studies to date, farm efficiency is measured by land productivity. Thus, the IR actually measures the relationship between farm size and land productivity. The purpose of this paper is to examine and understand the IR from a novel angle by using multiple definitions of farm efficiency indicators like labor productivity, profit ratio, total factor productivity (TFP) and technical efficiency (TE).

By using the farm-level panel data from Hubei province in China from 1999 to 2003, this paper employs the two-way fixed effect model of panel data and the stochastic frontier analysis of Battese and Coelli model to investigate the relationship between farm size and its production efficiency derived from the multiple definitions of production efficiency indicators including land productivity, labor productivity, profit ratio, TFP and TE.

The study confirmed the IR between land productivity and farm size, as in many formal studies. However, the relationship between farm size and other agricultural efficiency indicators may be positive, negative or uncorrelated at, depending on how the farm efficiency is defined. Therefore, the paper concluded that the relationship between farm size and its production efficiency is mixed. This paper provides economic explanations for the IR through the comprehensive study using the expansion of agricultural efficiency indicators.

Because different agricultural efficiency indicators have different policy implications for China's future agricultural and land policy, the findings have tremendous policy implications, particularly in terms of the current debate on large or small farm development strategy, the also so-called “go big or small” agricultural strategy. In this sense, the Chinese household responsibility system has played a critical role in its agriculture and will continue to play a critical role in terms of social security and social equality. Any reform to this system should proceed with caution.

While most existing studies only try to explain the IR from the perspective of land productivity, this paper attempts to propose a novel angle to examine the IR by using multiple definitions of agricultural efficiency and hopes to find some new conclusions.

The purpose of this paper is to investigate the impact of mechanization services on farm productivity in Northern China from an empirical perspective, with the aim to identify the underlying market and institutional barriers.

The authors apply the regression method with the control of village fixed effects to examining the relationship between capital–labor ratio, mechanization service ratio and farm productivity, using the panel data collected in 2013 and 2015 by CCAP.

Mechanization services improve farm productivity through substituting labor, but it may generate a less positive impact on farms who do not have self-owned capital equipment.

It is the first study to investigate how mechanization services affect farm productivity for grain producers in Northern China.

This paper aims to analyze the effects of crop specialization on agricultural productivity and commercialization for farmers who produce high-value crops in the Northern Savannah Ecological Zone of Ghana.

The study used the USAID/Ghana Feed the Future (FTF) survey, which collected data on high-value crops (i.e. maize, rice and soya). Data for the analysis consists of 2,903 farm households. The study utilized the three-stage generalized method of moment estimation technique to deal with the potential endogeneity of crop specialization within the context of productivity and commercialization and heteroscedasticity issues in the data.

The study found that crop specialization positively relates to agricultural productivity and commercialization, suggesting that increased crop specialization in the production of high-value stimulates productivity and opens market opportunities for farm households. These findings imply that crop specialization seems more beneficial to farmers as it significantly improves productivity and commercialization.

The study was conducted in the Northern Savannah Ecological Zone of Ghana and not the entire country.

To the best of the authors' knowledge, this study is the first to have jointly modeled crop specialization, agricultural productivity and commercialization. The main advantage of using this system approach is that it uses more information, thereby providing more precise parameter estimates.

This paper aims to test the impact of remittances receipt on agricultural productivity. The paper empirically assesses whether heterogeneity in economic activity of farming households affects the effects of remittances on productivity of tradable and nontradable crop farming households in Ghana.

The authors employ propensity score matching (PSM) methods to address potential endogeneity issues that could arise from the estimation due to selection bias. This paper uses the seventh round of Ghana living standard survey dataset for Ghana.

The authors find that, the involvement of farming households in other economic activities alters the impact of remittances on crop yield. This differential impact also varies according whether the crop is tradeable or not.

Policy can reduce the cost of sending remittances and include financial literacy modules in the farmer training modules to increase farmers' knowledge on investment of remittance in agricultural production.

The authors distinguish the paper from others by controlling for crop types (particularly tradeable or otherwise and gestation period), farming of a second or more crops and engagement of smallholder farmers in nonfarm economic activities.