George Rapsomanikis

Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Market Integration and Uncertainty: The Impact of Domestic and International Commodity Price Variability on Rural Household Income and Welfare in Ghana and Peru

Abstract We estimate rural household income uncertainties and welfare changes due to commodity price and production variability in Ghana and Peru under different scenarios for international and domestic market shocks. Uncertainties significantly affect the variability of household income, especially for households that are specialised in the production of few commodities. Wider exposure to international markets would increase the income variability for producers of commodities that are subjected to stabilisation policies in Ghana but would reduce the variability that rural households in Peru face. In terms of welfare, rural households in both countries are expected to gain if fully exposed to international markets.

Price Transmission and Volatility Spillovers in Food Markets of Developing Countries

We use a bivariate Vector Error Correction model to assess the transmission of price signals from selected international food markets to developing countries. We introduce a Generalized Conditional Autoregressive Heteroscedasticity (GARCH) effect for the model’s innovations in order to assess volatility spillover between the world and domestic food markets of Ethiopia, India and Malawi. Our results point out that short-run adjustment to world price changes is incomplete in Ethiopia and Malawi, while volatility spillovers are significant only during periods of extreme world market volatility. The problem in these countries is one of extreme volatility due to domestic, rather than world market shocks. In India, the analysis supports relatively rapid adjustment and dampened volatility spillovers which are by large determined by domestic policies.

Stochastic biases in technical change in South African agriculture.

This paper examines biased technical change in South African agriculture using a system of share equations with unobserved components. Developing on the work of Lambert and Shonkwiler (1995), this paper generalises previous work by introducing independent unobserved components into each model using a regression-based approach. We find evidence of stochastic technical change, which is itself biased between the four factors of production: machinery, land, labour and fertiliser, and which closely reflects distinct phases of South African agricultural policy and development.

An Analysis of The Impact of Research and Development on Productivity Using Bayesian Model Averaging with a Reversible Jump Algorithm

A Bayesian model averaging approach to the estimation of lag structures is introduced and applied to assess the impact of (R&D) on agricultural productivity in the United States from 1889 to 1990. Lag and structural break coefficients are estimated using a reversible jump algorithm that traverses the model space. In addition to producing estimates and standard deviations for the coefficients, the probability that a given lag (or break) enters the model is estimated. The approach is extended to select models populated with gamma distributed lags of different frequencies. Results are consistent with the hypothesis that R&D positively drives productivity. Gamma lags are found to retain their usefulness in imposing a plausible structure on lag coefficients, and their role is enhanced through the use of model averaging. Copyright 2010, Oxford University Press.