The Nature and Determinants of Volatility in Agricultural Prices

The volatility of 19 agricultural commodity prices are examined at monthly and annual frequencies. All of the price series are found to exhibit persistent volatility (periods of relatively high and low volatility). There is also strong evidence of transmission of volatilities across prices. Volatility in oil prices is found to be a significant determinant of volatilities in the majority of series and, likewise, exchange rate volatility is found to be a predictor of volatility in over half the series. There is also strong evidence that stock levels and yields are influencing price volatility. Most series exhibit significant evidence of trends in their volatility. However, these are in a downward direction for some series and in an upward direction for other series. Thus, there is no general finding of long term increases in volatility across most agricultural pricesVolatility, Agricultural Prices

The Determinants of Technology Adoption by UK Farmers using Bayesian Model Averaging. The Cases of Organic Production and Computer Usage.

We introduce and implement a reversible jump approach to Bayesian Model Averaging for the Probit model with uncertain regressors. This approach provides a direct estimate of the probability that a variable should be included in the model. Two applications are investigated. The �rst is the adoption of organic systems in UK farming, and the second is the in�uence of farm and farmer characteristics on the use of a computer on the farm. While there is a correspondence between the conclusions we would obtain with and without model averaging results, we �find important di¤erences, particularly in smaller samples.Agriculture, Adoption, Model Averaging, Organic, Computer

Bayesian inference of a smooth transition dynamic almost ideal model of food demand in the US

A dynamic ‘smooth transition’ Almost Ideal model is estimated for food consumption in the US. A Metropolis-Hastings algorithm is employed to map the posterior distributions and rejection sampling is used to evaluate and impose curvature restrictions at more than one point in the sample. The findings support the contention of structural change of a ‘smooth transition’ nature. Notably, the income food elasticity of demand becomes smaller through time, and the own price elasticities for food and non food become more elastic.Consumption Bayesian

Do Food Stamps Cause Obesity? A Generalised Bayesian Instrumental Variable Approach in the Presence of Heteroscedasticity

The impact of covariates on obesity in the US is investigated, with particular attention given to the role of the Supplemental Nutrition Assistance Program. The potential endogeneity of participation in SNAP is considered as a potential problem in investigating its causal influence on obesity using instrumental variable (IV) approaches. Due to the presence of heteroscedasticity in the errors, the approach for dealing with heteroscedastic errors in Geweke (1993) is extended to the Bayesian instrumental variable estimator outlined in Rossi et al. (2005). This approach leads to substantively different findings to a standard classical IV approach to correcting for heteroscedasticity. Although findings support the contention that the SNAP participation rate is associated with a greater prevalence of obesity, the evidence for this impact is substantially weakened when using the methods introduced in the paper.Bayesian; Food Stamps; Food Insecurity; Instrumental Variabls; Heteroscedasticity; Obesity.

Bayesian Model Averaging and Identification of Structural Breaks in Time Series

Bayesian model averaging is used for testing for multiple break points in uni- variate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over speciÖcations including: station- ary; stationary around trend; and, unit root models, each containing di§ erent types and numbers of breaks and di§ erent lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in al l of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our Öndings regarding the existence of unit roots, having al lowed for structural breaks in the data, are largely consistent with previous work.Bayesian Model Averaging, Structural Breaks, Unit Root, Macro- economic Data, Natural Resource data

Non-renewable Resource Prices: Structural Breaks and Long Term Trends

In this paper we examine the time series properties of nine non-renewable resources. In particular we are concerned with understanding the relationship between the number of structural breaks in the data and the nature of the resource price path, i.e. is it stationary or a random walk. To undertake our analysis we employ a number of relevant econometric methods including Bai and Perron's (1998) multiple structural break dating method. Our results indicate that these series are in many cases stationary and subject to a number of structural breaks. These results indicate that a deterministic model of resources prices may well be appropriate.structural change, non-renewable resources, breaks, resource depletion

Calorie and Nutrient Consumption as a Function of Income: A Cross-Country Analysis

The relationship between calorie and nutrient (fat, protein, and carbohydrates) intake as a function of income is explored using data for 171 countries over two time periods 1990-1992 and 2003-2005. Three types of analysis are employed: i) nonparametric, ii) panel regressions, and iii) quantile regressions. Engle curves for calories, fat, and protein are approximately linear in logs with carbohydrate intakes exhibiting diminishing elasticities as incomes increase, becoming negative around $US7500 and above. Other nutrient and calorie elasticity estimates are positive statistically significant. Elasticities range from 0.10 to 0.25, with fat having the highest elasticities. The estimated elasticities for the quantile regressions are similar across the 0.25, 0.50 and 0.75 quantiles, but with moderate evidence that countries in the higher quantiles have lower elasticities than those in the lower quantiles. There has been a small but significant shift in the elasticities across the two periods.Calorie and Nutrient Consumption, Food and Nutrition Policies; Income Elasticities; Nonparametric Regression; Panel Data; Quantile Regression.

Integrating spatial dependence into stochastic frontier analysis

An approach to incorporate spatial dependence into Stochastic Frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.Spatial dependence, technical efficiency, Bayesian, spatial weight matrix

Provision of an environmental output within a multi-output distance function approach

This paper redefines technical efficiency by incorporating provision of environmental goods as one of the outputs of the farm within a multi-outptut distance function framework. Permanent and rough grassland area are used as a proxy for the provision of environmental goods. The multi-output distance function approach is used to estimate technical efficiency. A Bayesian procedure involving the use of a Gibbs sampler is used to estimate the farm specific efficiency as well as the coefficients of the distance function. In addition, a number of explanatory variables for the efficiency were introduced in the analysis and posterior distributions of those were obtained. The methodology is applied to panel data on 215 dairy farms in England and Wales from the Defra Farm Business Survey. Results show that both farm efficiency rankings and determinants of inefficiency change when provision of environmental outputs by farms is incorporated in the efficiency analysis, which may have important political implications.Technical efficiency, environmental good, multi-output

Input usage, output mix and industry deregulation: an analysis of the Australian dairy manufacturing industry

In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.Bayesian, deregulation, output distance function, Agribusiness,