Fractional integration in agricultural futures price volatilities revisited

Jin and Frechette (2004) examined the degree to which agricultural price volatilities exhibited evidence of fractional integration and concluded it was important to consider both long-run and short-run memory when modeling conditional variances. The purpose of this note is to revisit the issue using new methods and techniques which generally reaffirm the view that return volatilities are fractionally integrated and conditionally heteroskedastic, with many exhibiting significant leverage effects, a result not previously reported.     

Using a functional approach to test trending volatility in the price of Mexican and international agricultural products

In this article, we extend the traditional GARCH(1,1) model by including a functional trend term in the conditional volatility of a time series. We derive the main properties of the model and apply it to all agricultural commodities in the Mexican CPI basket, as well as to the international prices of maize, wheat, swine, poultry, and beef products for three different time periods that implied changes in price regulations and behavior: before the North American Free Trade Agreement (NAFTA; 1987–1993), post‐NAFTA (1994–2005), and commodity supercycle (2006–2014). The proposed model seems to adequately fit the volatility process and, according to heteroscedasticity tests, also outperforms the ARCH(1) and GARCH(1,1) models, some of the most popular approaches used in the literature to analyze price volatility. Our results show that, consistent with anecdotal evidence, price volatility trends increased from the period 1987–1993 to 1994–2005. From 1994–2005 to 2006–2014, trends decreased but the persistence of volatility increased for most products, especially for international commodities. In addition, we identify some agricultural products such as avocado, beans, and chicken that, due to their increasing price volatility trends in the 2006–2014 period, may present a risk for food inflation in the short run.     

Collateral‐free lending with risk‐contingent credit for agricultural development: indemnifying loans against pulse crop price risk in India

This article addresses the problem of collateral‐free lending in the context of agricultural development. We investigate a viable alternative to traditional credit products through the development of risk‐contingent credit for operating loans and farm mortgages and apply the concept to agricultural loans for pulse crops in India. Risk‐contingent credit mitigates business and financial risk by reducing debt obligations depending on the embedded commodity options whose payoffs are linked with commodity price fluctuations. We analyze daily commodity spot prices for pulse crops in India and show how risk‐contingent structured financial instruments can be priced in practice.     

Time‐series econometric analyses of biofuel‐related price volatility

Time‐series econometrics studies have analyzed volatility interactions between biofuel and food and fossil fuel markets. We review data, modeling techniques and the main findings in the literature, and present our latest contributions. We identify areas for further research.     

The effects of the Yuan‐dollar exchange rate on agricultural commodity trade between the United States,China, and their competitors

The United States claims that the undervaluation of Chinese currency, the Yuan, causes U.S. exports to China to decrease and imports from China to increase. Furthermore, because the Yuan is undervalued only against the dollar, U.S. competitors have an advantage in exporting to China and China has an advantage over its competitors in exporting to the United States. This study develops a theoretical model to analyze the effect of the Yuan undervaluation on prices, supply, demand, and trade in the United States, China, and their competitors. This study applies a cointegration/error‐correction model to empirically quantify the short‐run and long‐run effects of the devaluation of the Yuan on important agricultural commodities traded between the United States, China, and their competitors. These commodities include Chinese imports of milk, soybeans, and cotton from the United States and U.S. imports of beans, fruit juice, and fruit from China. The results show that Yuan devaluation causes Chinese imports of U.S. milk, soybeans, and cotton to decline and U.S. imports of beans, fruit juice, and fruit from China to increase in the short run and in the long run.     

Time‐varying Hedge Ratios: A Principal‐agent Approach

We use the classic agency model to derive a time‐varying optimal hedge ratio for low‐frequency time‐series data: the type of data used by crop farmers when deciding about production and about their hedging strategy. Rooted in the classic agency framework, the proposed hedge ratio reflects the context of both the crop farmer's decision and the crop farmer's contractual relationships in the marketing channel. An empirical illustration of the Dutch ware potato sector and its futures market in Amsterdam over the period 1971–2003 reveals that the time‐varying optimal hedge ratio decreased from 0.34 in 1971 to 0.24 in 2003. The hedging effectiveness, according to this ratio, is 39%. These estimates conform better with farmers’ interest in using futures contracts for hedging purposes than the much higher estimates obtained when price risk minimisation is the only objective considered.     

Animal disease outbreaks and food market price dynamics: Evidence from regime‐dependent modelling and connected scatterplots

The economic impacts of animal disease outbreaks have been widely discussed in the literature. Most authors have centred their attention on estimating the direct costs. Recent studies have shown that the indirect economic effects might lead to equal or even higher welfare losses. This study aims to contribute to this field of research by assessing the effect of an animal disease outbreak on food market price dynamics in Mexico, accounting for the potential effect of an antitrust intervention. We employ a regime‐dependent vector error correction model and a connected scatterplot analysis. The results show that both the outbreak and the antitrust intervention caused structural breaks in food market price dynamics between producers and consumers, reflected in an increase in the absolute component of the marketing margin, with serious food security implications.     

Out‐of‐sample testing price discovery in commodity markets: the case of soybeans

Price discovery, a central function of futures markets, has been usually tested in‐sample by studying the common stochastic trend between spot and futures prices. Instead, to evaluate futures as anticipatory prices, we develop a forecast approach to out‐of‐sample test price discovery in a multivariate framework. We apply it to the soybeans market. Results indicate futures prices as the best available “predictors” of future spot prices, although this finding holds only on average and for certain periods, other models show forecasting gains.     

Capturing zero‐trade values in gravity equations of trade: an analysis of protectionism in agro‐food sectors

With significant improvements in its theoretical underpinnings, the gravity model has gained renewed interest in the agro‐food trade literature. Notwithstanding, there is a dearth of literature examining the relative trade restrictiveness of tariff barriers across a broad range of agro‐food sectors. This represents an important research gap, which this study sets out to fill. Furthermore, this research reconciles the application of zero‐inflated models with a sectorally disaggregated analysis. More specifically, employing a fully specified gravity equation, a Poisson estimator and variants of the Poisson model (Negative Binomial, Zero‐Inflated Poisson, and Zero‐Inflated Negative Binomial) provide statistically significant and theoretically consistent estimates, while allowing for the inclusion of zero‐trade values. A panel data model with fixed effects is also employed to improve the estimation of the parameters of interest. Estimation results reveal that in the vast majority of sectors examined, import tariffs are found to be statistically significant, whereas export refunds exhibit a statistically smaller role due to the nonsystematic nature of their application in world food markets. Model simulations of tariff barrier eliminations reveal limited trade gains, although there is encouraging evidence of “low” and “lower middle” per capita income country trade gains in wheat, red meat, dairy, sugar, and (particularly) rice markets.     

Foot‐and‐mouth disease and the Mexican cattle industry

The objective of this article is to analyze the domestic and international effects of a hypothetical foot‐and‐mouth disease (FMD) outbreak in the Mexican cattle industry. A discrete time dynamic optimization model of the Mexican cattle sector is specified, and linked to domestic and international markets. Economic consequences of FMD outbreaks are simulated over time and under different scenarios. Specific findings and general policy recommendations are provided. The study reports a range of outbreaks from localized to large scale and suggests that changes in economic surplus due to FMD range from a positive net gain of $0.89 to $1.6 billion to a net loss of about $67 billion, depending on the specific mitigation strategy and outbreak scenario.     

Coping with systemic risk in index‐based crop insurance

The implementation of index‐based crop insurance is often impeded by the existence of systemic risk of insured losses. We assess the effectiveness of two strategies for coping with systemic risk: regional diversification and securitization with catastrophe (CAT) bonds. The analysis is conducted in an equilibrium pricing framework which allows the optimal price of the insurance and the number of traded contracts to be determined. We also explore the role of basis risk and risk aversion of market agents. The model is applied to a hypothetical area yield insurance for rice producers in northeast China. If yields in two regions are positively correlated, we find that enlarging the insured area leads to higher insurance premiums. Unless capital market investors are very risk averse, a CAT bond written on an area yield index outperforms regional diversification in terms of certainty equivalents of both farmers and insurers.     

Extreme Measures of Agricultural Financial Risk

The agricultural marketing environment is inherently risky. Having accurate measures of risk helps farmers, policy‐makers and financial institutions make better informed decisions about how to deal with this risk. This article examines three tail quantile‐based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk, Expected Shortfall and Spectral Risk Measures. We use Extreme Value Theory to model the tail returns and present results for these three different risk measures using agricultural futures market returns data. We compare estimated risk measures in terms of size and precision, and find that they are all considerably higher than Gaussian estimates. The estimated risk measures are also quite imprecise, and become more so as the risks involved become more extreme.     

Global rice trade competitiveness: a shift‐share analysis

Changes in country shares of global rice exports from 1997 to 2008 are analyzed using an econometric, shift‐share analytical framework. This framework estimates growth rates and disaggregates these rates of change into geographical structure effects and performance effects. The performance effect is further decomposed into two subeffects accounting for adaptation to changes in the geographical structure of the marketplace and a competitiveness effect. A restricted, weighted, two‐way fixed effects model is specified for estimating the geographical structure and performance effects. Results indicate a growing concentration among a few exporting countries in the global rice market, and the competitiveness effect is often significant. Government policies affecting rice trade and the competitiveness of trading partners are important factors for the shifts in rice trade patterns. In particular, Vietnam is an emerging, major player in global rice trade in competition with Thailand.     

Monetary policy shocks and the dynamics of agricultural commodity prices: evidence from structural and factor‐augmented VAR analyses

Fluctuation in commodity prices is a significant and timely issue to be studied. This study is to examine the impact of monetary policy and other macroeconomic shocks on the dynamics of agricultural commodity prices. The major contributions of this study are twofold. First, unlike other studies that use indexes, this study analyzes the commodities individually, affording the inclusion of commodity‐specific fundamentals such as the level of inventory—an important determinant of commodity price—in a structural VAR framework. Second, it exploits a rich data set of agricultural commodity prices which includes commodities that are usually overlooked in the literature, and extracts a common factor using the dynamic factor model to understand the extent of comovement of the prices and to gauge the extent to which macroeconomic shocks drive the “comovement” in a factor‐augmented VAR (FAVAR) framework. The findings show that monetary policy, global economic conditions, and the U.S. dollar exchange rates play an important role in the dynamics of agricultural commodity prices.     

Tailored to the extremes: Quantile regression for index‐based insurance contract design

A new approach for weather index‐based insurance design based on Quantile Regression (QR) to condition the yield‐index dependency is developed and compared to standard regression technique. Three conceptual different risk measures, i.e., Expected Utility, Expected Shortfall and a Spectral Risk Measure, are used to evaluate the risk reducing properties of these contracts. Our findings show that QR is much more powerful in establishing the yield‐index dependency and lead for all risk measures to a higher risk reduction than the standard technique ordinary least squares (OLS). Thus, QR leads to a more efficient contract design, which is beneficial for both, the insurer (smaller remaining risk) and the insured (higher demand and willingness to pay). Our empirical application is based on a 31 years long time series of wheat yield data from Northern Kazakhstan.     

The components of the bid‐ask spread: Evidence from the corn futures market

This article examines whether USDA announcements and commodity index fund rolling activity have an impact on liquidity costs, measured by the bid‐ask spread. Using Huang and Stoll's (1997) model of liquidity costs, we estimate whether changes to liquidity costs are driven by its adverse selection, inventory, or order processing components. Commodity index fund roll activity reduces the asymmetric information cost component of liquidity cost due to an increased proportion of noninformation‐based trading, but the inventory cost component increases as (mostly long only) commodity index funds sell their nearby positions and buy the first deferred contract—raising liquidity providers’ risk of building a position. The sum of these two effects is that liquidity costs remain low during index fund roll periods, averaging one “tick” (0.25 cents). On USDA report release days, we find that informed traders raise the asymmetric information component of liquidity costs in the first hour after release, but the inventory cost component is reduced due to the increase in volume. Similar to index fund roll activity, liquidity costs on USDA report release days remain low, averaging one “tick”. Our findings that liquidity costs are minimally changed during USDA report releases and commodity index fund roll periods is consistent with other recent research on liquidity costs, but we show that what drives liquidity costs differs substantially depending on the circumstances surrounding daily trading.     

Effects of microcredit and other loans on female empowerment in Bangladesh: the borrower's gender influences intra‐household resource allocation

This article examines microcredit's effectiveness in empowering women borrowers in rural Bangladesh. It does so by examining how gender‐specific borrowing activities influence household expenditures which are either specifically of interest to men or women, and by examining the effects of all loans rather than only those provided by microcredit organizations. The article uses a quasi‐experimental design to identify the effects of borrowing by men and women by using an original combination of panel data and instrumental variables on subsamples of the surveyed population. It finds that the borrower's gender affects how households allocate their resources to different expenditure items and assets that are valued differently by men and women. In all, the findings suggest that providing greater credit access to women may improve their household bargaining positions.