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,

The Use of Bootstrapped Malmquist Indices to Reassess Productivity Change Findings: An Application to a Sample of Polish Farms

The paper assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using Data Envelopment Analysis (DEA), in the first stage calculating productivity indices and in the second stage investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of the paper is to account in the second stage for the information provided by the bootstrap in the first stage. The DEA standard errors of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996-2000. The confidence interval's results suggest that contrary to what was reported by previous studies, the second half of 1990s for Polish farms was characterised not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA standard errors in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard Ordinary Least Squares, in terms of significance (fewer parameters are significant in our heteroscedastic regression) and sign (of the parameter of the share of other income in total income), they are consistent with theory and previous research. Family farms concentrating on farming experienced larger productivity progress than farms with hired labour and income diversification.productivity, Malmquist, bootstrapping, second-stage regression, Poland, Productivity Analysis,

Impact of Income on Calorie and Nutrient Intakes: A Cross-Country Analysis

The relationship between income and nutrient intake is explored. Nonparametric, panel, and quantile regressions are used. Engle curves for calories, fat, and protein are approximately linear in logs with carbohydrate intakes exhibiting diminishing elasticities as incomes increase. Elasticities range from 0.10 to 0.25, with fat having the highest elasticities. Countries in higher quantiles have lower elasticities than those in lower quantiles. Results predict significant cumulative increases in calorie consumption which are increasingly composed of fats. Though policies aimed at poverty alleviation and economic growth may assuage hunger and malnutrition, they may also exacerbate problems associated with obesity.calorie and nutrient consumption, food and nutrition policy, income elasticities, nonparametric, panel, quantile regression., Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, International Development, Research Methods/ Statistical Methods, C11, C14, C21, C23, O10, O47, Q18,

Testing for bubbles in agriculture commodity markets

A number of tests and dating algorithms have been developed and used to identify rapid increases in prices followed by a collapse, also known as explosive bubbles (Phillips, Wu and Yu, 2011; Phillips, Shi and Yu, 2012; Gilbert, 2009; Gutierrez, forthcoming). Previous analysis on agriculture commodities by Gilbert (2009) and Gutierrez (forthcoming) applied the tests developed by Phillips, Wu and Yu (2011) and focused on four agricultural commodities. In contrast, we apply the more recent generalized sup augmented Dickey-Fuller (GSADF) test for explosive bubbles (Phillips, Shi and Yu, 2012) to monthly time-series for food, beverages, agricultural raw material, cereals, dairy, meat, oils and sugar indices and a total of 28 agricultural commodities between 1980-2012. We found price bubbles occurred for some commodities within food markets

Testing for bubbles in agriculture commodity markets

A number of tests and dating algorithms have been developed and used to identify rapid increases in prices followed by a collapse, also known as explosive bubbles (Phillips, Wu and Yu, 2011; Phillips, Shi and Yu, 2012; Gilbert, 2009; Gutierrez, forthcoming). Previous analysis on agriculture commodities by Gilbert (2009) and Gutierrez (forthcoming) applied the tests developed by Phillips, Wu and Yu (2011) and focused on four agricultural commodities. In contrast, we apply the more recent generalized sup augmented Dickey-Fuller (GSADF) test for explosive bubbles (Phillips, Shi and Yu, 2012) to monthly time-series for food, beverages, agricultural raw material, cereals, dairy, meat, oils and sugar indices and a total of 28 agricultural commodities between 1980-2012. We found price bubbles occurred for some commodities within food markets

An analysis of the impact of R&D 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 US 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 coe¢ cients, 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 di¤erent 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 coe¢ cients, and their role is enhanced through the use of model averaging

An application of cointegration theory in the estimation of the Almost Ideal Demand system for food consumption in Bulgaria

The Almost Ideal Demand system is applied to consumption in Bulgaria. It is argued that the conventional estimation of the Almost Ideal model should be done within the framework of contemporary time series methodology. In this paper, the canonical cointegrating regression procedure of Park is applied. It is argued that the results of the Almost Ideal Demand system that are presented are consistent with both theory and 'casual' observation of consumer behaviour in Bulgaria

TESTING SYMMETRY AND HOMOGENEITY IN THE AIDS WITH COINTEGRATED DATA USING FULLY-MODIFIED ESTIMATION AND THE BOOTSTRAP

Convential SUR estimation of the AIDS is shown to lead to small sample bias and distortions in the size of a Wald test for symmetry and homogeneity when the data are cointegrated. A fully-modified estimator is developed in an attempt to remedy these problems. It is shown that this estimator reduces the small sample bias but fails to eliminate the size distortion. Bootstrapping is shown to be ineffective as a method of removing small sample bias in both the conventional and fully modified estimators. Bootstrapping is effective however as a method of removing the size distortion and performs equally well in this respect with both estimators

The Use of Bootstrapped Malmquist Indices to Reassess Productivity Change Findings: An Application to a Sample of Polish Farms

The paper assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using Data Envelopment Analysis (DEA), in the first stage calculating productivity indices and in the second stage investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of the paper is to account in the second stage for the information provided by the bootstrap in the first stage. The DEA standard errors of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996-2000. The confidence interval's results suggest that contrary to what was reported by previous studies, the second half of 1990s for Polish farms was characterised not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA standard errors in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard Ordinary Least Squares, in terms of significance (fewer parameters are significant in our heteroscedastic regression) and sign (of the parameter of the share of other income in total income), they are consistent with theory and previous research. Family farms concentrating on farming experienced larger productivity progress than farms with hired labour and income diversification

Productivity Change in Polish Agriculture: An Application of a Bootstrap Procedure to Malmquist Indices

This paper employs bootstrapping to correct for bias and to construct confidence intervals for Malmquist TFP indices derived with DEA. It uses these results to investigate the productivity change in Polish agriculture during a crucial period of the country's transition to a market economy, 1996-2000, when Poland was preparing for accession to the European Union. The bias corrected estimates show regress in productivity at an annual rate of 4 percent. The confidence intervals suggest that between two-thirds and four-fifths of the sample farms (250) in different years might have experienced no change in productivity. The cluster analysis based on confidence bounds reveals three paths of productivity change. Farms which recorded an increase in productivity at least in the last year of the analysed period, are larger, more capital intensive, run by younger farmers, and more integrated in factor and product markets. However, they account for only 19 percent of the sample farms. The most important for Poland now is to unlock the forces that can drive ahead structural reform and thus productivity growth