Impact of contract farming on yield,costs and profitability in low‐value crop: evidence from a low‐income country

Lentils, a low‐value and highly nutritious crop, are Nepal's largest pulse cash crop. However, the majority of the nation's smallholders produce lentils on very small plots of land. The large gap in lentil yields between Nepal and other lentil‐producing countries underscores the importance of improving yields and income of smallholders. When it comes to the financial viability of small farms, particularly in developing countries, and globalisation, contract farming (CF) may prove useful in achieving efficiency and profitability in smallholder lentil farms in Nepal. This study employs the propensity score matching approach to examine the effects of the adoption of CF on yields, profitability and costs of smallholder lentil farms in Nepal. Findings from this study reveal that contrary to popular belief, CF adoption by lentil producers in Nepal has a positive and significant effect on per‐hectare revenues, profits and yield and a negative impact on variable and transportation costs. The study finds that only very smallholder lentil farms (0.01‐0.05 ha) benefit from CF.     

Off-Farm Labor Participation Decisions of Married Farm Couples and the Role of Government Payments

The determinants of off-farm work by married farm couples are examined using data from the 2004 Agricultural Resource Management Survey and multinomial logistic regression. Expected government payment is found important in decreasing the likelihood of off-farm work strategies involving work by the husband only or by both husband and wife relative to a strategy of no work by either husband or wife. The marginal impact of government payments on the probability of the wife working off farm alone is found positive suggesting the possibility of nonpecuniary motives for off-farm employment for 21% of farm households in the selected weighted sample.     

Land rental markets and labor productivity: Evidence from rural China

This study investigates the impact of the land rental market on labor productivity in rural China. Particular attention is given to farm and nonfarm labor productivity. Using 2012 household‐level data and a multinomial endogenous switching treatment regression technique, we find that rural households renting in farmland increased labor productivity in the farm sector by about 55%, whereas labor productivity in the nonfarm sector decreased by about 6%. We also find that rural households renting out farmland had lower labor productivity in both the farm and nonfarm sectors by 13% and 9%, respectively. More family labor transferred from the farm to the nonfarm sector after renting out land.     

A Minimax Regret Approach to Decision Making Under Uncertainty

We propose a minimax regret approach to optimal factor demand under uncertainty. Regret is the deviation of any given decision from the optimal decision based on a specified set of possible scenarios for the uncertain variables. This approach does not require the specification of instrumental variables to control for unobserved states of nature, and also does not require specification of the number of possible states in advance. Importantly, ex post production shocks can be estimated using our approach, and full statistical inferences can be obtained. Econometric techniques are based on Bayesian analysis using Markov Chain Monte Carlo techniques. A substantive empirical application is provided to illustrate the new approach.     

Share repurchases and accounting conservatism

Review of Quantitative Finance and Accounting - The prior literature indicates that financial policy (e.g., payout policy) as well as accounting policy (e.g., conservatism) can be used to address...     

Enhancing food security through diet quality: The role of nonfarm work in rural India

India has achieved food security at the macro level. However, at the micro level, the country still struggles with extensive problems of food nutrition insecurity. In this paper, we assess the impact of nonfarm income and nonfarm work status (casual and full-time nonfarm work) of operator, spouses, and couples on the diet quality of smallholder households in India. We find that nonfarm income decreases the likelihood of farming household being in the poor-diet quality group by 31% and the medium-diet quality group by 3%. Full-time nonfarm work by operators and spouses decreases the likelihood of farming households being in the poor-diet quality group by 3% and 9%, respectively. Finally, national programs like public food distribution programs increase the probability of rural farming households in the poor-diet quality group. Findings from this study underscore the importance of nonfarm income and full-time nonfarm work in improving diet quality of rural Indian households.     

A supply‐side analysis of agritourism: Evidence from farm‐level agriculture census data in Taiwan

Due to consumers’ increased demand for leisure and farmers’ need for income diversification, researchers and policymakers have significant interest in topics related to agritourism. This study provides a supply‐side analysis on agritourism using Taiwan as a case study. Utilising a sample of 720,148 family farms from the 2010 agriculture census survey in Taiwan, we quantify the effects of engaging in the agritourism business on farm income, on farm succession, and on family members’ labour supply decisions between on‐farm and off‐farm work. An analytical framework that combines the doubly robustness regression model and semiparametric estimation is proposed to address the endogeneity bias. Results indicate that participation in agritourism increases farm income and family farm succession. Farms engaging in agritourism also have more family members working on the farm, and fewer family members working off‐farm, compared to farms not engaging in agritourism. Although agritourism enterprises are developed to meet consumers’ demand for leisure, our results show that they also improve the economic welfare of farm households.     

Forecasting spot prices of agricultural commodities in India: Application of deep-learning models

Food price fluctuations can impact both producers and consumers. Forecasting the prices of the agricultural commodities is of prime concern not only to the government but also to farmers and agribusiness firms. In developing countries like India, management of food security needs competent and efficient forecasting of food prices. With the availability of data, recent innovation in deep-learning models provides a feasible solution to accurately forecast the prices. In this study, we examine the superiority of these models using the daily spot prices of five major commodities traded on the National Commodity and Derivatives Exchange: cotton seed, castor seed, rape mustard seed, soybean seed, and guar seed. The results were obtained from the application of the traditional univariate autoregressive integrated moving average model and deep-learning techniques like the time-delay neural network (TDNN) and long short-term memory (LSTM) network. The empirical results indicate that the LSTM model is indeed suitable for the financial domain and captures the directional movement of the spot price changes with high accuracy compared with the TDNN and other linear models. Accuracy of the performance of these models has been compared using out-of-sample performance measure. The overall objective of this paper is to demonstrate the utility of spot price forecasting for farmers and traders in offering them the best predictions of the price movements. Our results provide a possibility of developing pricing models that can help in fairly regulating agricultural commodity prices.     

Is an Optimum Currency Area Feasible in East and South East Asia?

Abstract

In the backdrop of the recent economic crisis in the European Union, this study attempts to assess the degree of regional integration and the suitability of a monetary union in the East and South-East Asian (ESEA) region. For this purpose, we analyse the issue in a variety of ways. First, a long-run linkage of real output of the countries is tested using the cointegration analysis. Results suggest that real output of most of the countries in the region is cointegrated and move together in the long-run. To analyse the issue in detail, we focus on the impact of three different shocks, namely global, regional and country-specific, on real output of the countries. Results of impulse response and variance decomposition analysis reveal that regional shocks do not dominate in the sample countries, which is an indication of unfavourable condition to form an optimal currency area (OCA) in the region. These results are further confirmed by the outcome of computation of the modified Bayoumi and Eichengreen's Indices. Finally, we employ the concept of Generalized Purchasing Power Parity (G-PPP), which however reveals that the bilateral real exchange rate of ESEA countries move together in the long-run and share a common stochastic trend, which in turn provides some empirical support for an OCA in the region.     

Price movement and trade size on the National Stock Exchange of India

Using data for the National Stock Exchange of India, we examine three hypotheses about which trades move prices. The Stealth Trading Hypothesis proposes that cumulative price changes (CPCs) are concentrated in particular trade sizes due to the strategic trading of informed traders. We find that depending on market conditions, from 60% to 80% of the CPC is concentrated in small trade sizes, with almost all of the remaining price change concentrated in medium trade sizes. These results support the Stealth Trading Hypothesis.