796 research outputs found

    Metafrontier Functions for the Study of Inter-regional Productivity Differences

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    The paper uses the concept of metafrontier functions to study regional differences in production technologies. The paper has three components. The first deals with the analytical framework necessary for the definition of metafrontier functions. The second component studies the properties of the metafrontier estimated using nonparametric data envelopment analysis (DEA). The third component focuses on the estimation of metafrontiers within the parametric framework of stochastic frontier analysis (SFA). The empirical application of the models uses cross-country agricultural sector data. The DEA and SFA metafrontiers are presented and discussed.

    An Investigation of Production Risk, Risk Preferences and Technical Efficiency: Evidence From Rainfed Lowland Rice Farms in the Philippines

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    Risk plays a vital role in farmers' decisions on input allocations and, therefore, output supply. This paper provides empirical evidence on the estimation of production risk, risk preferences and technical inefficiency. An eight-year panel data set is used for 46 rice farmers from a representative rainfed lowland environment in Central Luzon, Philippines. The heteroskedastic and stochastic frontier frameworks are reconciled and extended to accommodate the risk preferences of farmers in an analysis of production risk. Results show that technical inefficiency is overstated in risky production environments where farmers are risk-averse.production risk, risk preferences, technical efficiency, Productivity Analysis, Risk and Uncertainty,

    IMPOSING REGULARITY CONDITIONS ON A SYSTEM OF COST AND FACTOR SHARE EQUATIONS

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    Systems of equations comprising cost functions and first-order derivative equations are often used to estimate characteristics of production technologies. Unfortunately, many estimated systems violate the regularity conditions implied by economic theory. Sampling theory methods can be used to impose these conditions globally, but these methods destroy the flexibility properties of most functional forms. We demonstrate how Bayesian methods can be used to maintain flexibility by imposing regularity conditions locally. The Bayesian approach is used to estimate a system of cost and share equations for the merino-woolgrowing sector. The effect of local imposition of monotonicity and concavity on the signs and magnitudes of elasticities is examined.Cost functions, Markov Chain Monte Carlo, inequality constraints, Demand and Price Analysis,

    Genome-wide association study of electrocardiographic and heart rate variability traits: the Framingham Heart Study

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    BACKGROUND: Heritable electrocardiographic (ECG) and heart rate variability (HRV) measures, reflecting pacemaking, conduction, repolarization and autonomic function in the heart have been associated with risks for cardiac arrhythmias. Whereas several rare monogenic conditions with extreme phenotypes have been noted, few common genetic factors contributing to interindividual variability in ECG and HRV measures have been identified. We report the results of a community-based genomewide association study of six ECG and HRV intermediate traits. METHODS: Genotyping using Affymetrix 100K GeneChip was conducted on 1345 related Framingham Heart Study Original and Offspring cohort participants. We analyzed 1175 Original and Offspring participants with ECG data (mean age 52 years, 52% women) and 548 Offspring participants with HRV data (mean age 48 years, 51% women), in relation to 70,987 SNPs with minor allele frequency ≄ 0.10, call rate ≄ 80%, Hardy-Weinberg p-value ≄ 0.001. We used generalized estimating equations to test association of SNP alleles with multivariable-adjusted residuals for QT, RR, and PR intervals, the ratio of low frequency to high frequency power (LF/HFP), total power (TP) and the standard deviation of normal RR intervals (SDNN). RESULTS: Associations at p < 10-3 were found for 117 (QT), 105 (RR), 111 (PR), 102 (LF/HF), 121 (TP), and 102 (SDNN) SNPs. Several common variants in NOS1AP (4 SNPs with p-values < 10-3; lowest p-value, rs6683968, p = 1 × 10-4) were associated with adjusted QT residuals, consistent with our previously reported finding for NOS1AP in an unrelated sample of FHS Offspring and other cohorts. All results are publicly available at NCBI's dbGaP at. CONCLUSION: In the community-based Framingham Heart Study none of the ECG and HRV results individually attained genomewide significance. However, the presence of bona fide QT-associated SNPs among the top 117 results for QT duration supports the importance of efforts to validate top results from the reported scans. Finding genetic variants associated with ECG and HRV quantitative traits may identify novel genes and pathways implicated in arrhythmogenesis and allow for improved recognition of individuals at high risk for arrhythmias in the general population.National Institutes of Health (K23 N01-HC25195); Doris Duke Charitable Foundation Clinical Scientist Developement Award; Pfizer; National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1

    Imposing regularity conditions on a system of cost and factor share equations

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    Systems of equations comprising cost functions and first‐order derivative equations are often used to estimate characteristics of production technologies. Unfortunately, many estimated systems violate the regularity conditions implied by economic theory. Sampling theory methods can be used to impose these conditions globally, but these methods destroy the flexibility properties of most functional forms. We demonstrate how Bayesian methods can be used to maintain flexibility by imposing regularity conditions locally. The Bayesian approach is used to estimate a system of cost and share equations for the merino wool‐growing sector. The effect of local imposition of monotonicity and concavity on the signs and magnitudes of elasticities is examined.Resource /Energy Economics and Policy,

    Testing the limits of contextual constraint: interactions with word frequency and parafoveal preview during fluent reading

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    Contextual constraint is a key factor affecting a word's fixation duration and its likelihood of being fixated during reading. Previous research has generally demonstrated additive effects of predictability and frequency in fixation times. Studies examining the role of parafoveal preview have shown that greater preview benefit is obtained from more predictable and higher frequency words versus less predictable and lower frequency words. In two experiments, we investigated effects of target word predictability, frequency, and parafoveal preview. A 3 (Predictability: low, medium, high) × 2 (Frequency: low, high) design was used with Preview (valid, invalid) manipulated between experiments. With valid previews, we found main effects of Predictability and Frequency in both fixation time and probability measures, including an interaction in early fixation measures. With invalid preview, we again found main effects of Predictability and Frequency in fixation times, but no evidence of an interaction. Fixation probability showed a weak Predictability effect and Predictability-Frequency interaction. Predictability interacted with Preview in early fixation time and probability measures. Our findings suggest that high levels of contextual constraint exert an early influence during lexical processing in reading. Results are discussed in terms of models of language processing and eye movement control

    Testing for Market Power in Multiple-Input, Multiple-Output Industries: The Australian Grains and Oilseeds Industries

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    Recent empirical studies have found significant evidence of departures from competition in the input side of the Australian bread, breakfast cereal and margarine end-product markets. For example, Griffith (2000) found that firms in some parts of the processing and marketing sector exerted market power when purchasing grains and oilseeds from farmers. As noted at the time, this result accorded well with the views of previous regulatory authorities (p.358). In the mid-1990s, the Prices Surveillence Authority (PSA 1994)determined that the markets for products contained in the Breakfast Cereals and Cooking Oils and Fats indexes were "not effectively competitive"(p.14). The PSA consequently maintained price surveillence on the major firms in this product group. The Griffith result is also consistent with the large number of legal judgements against firms in this sector over the past decade for price fixing or other types of non-competitive behaviour. For example, bread manufacturer George Weston was fined twice during 2000 for non-competitive conduct and the ACCC has also recently pursued and won cases against retailer Safeway in grains and oilseeds product lines. Griffith obtained his results using highly aggregated data and a relatively simple empirical model. In this study we focus on confirming the earlier results by formally testing for competitive behaviour in the Australian grains and oilseeds industries using a more sophisticated empirical model and a less aggregated grains and oilseeds data set. We specify a general duality model of profit maximisation that allows for imperfect competition in both the input and output markets of the grains and oilseeds industries. The model also allows for variable-proportions technologies and can be regarded as a generalisation of several models appearing in the agricultural economics and industrial organisation literatures. Aggregate Australian data taken from the 1996-97 input-output tables are used to define the structure of the relevant industries, and time series data are used implement the model for thirteen grains and oilseeds products handled by seven groups of agents. The model is estimated in a Bayesian econometrics framework. Results are reported in terms of the characteristics of estimated probability distributions for demand and supply elasticities and indexes of market power. Our results suggest that there is a positive probability that: (a) flour and cereal food product manufacturers exert market power when purchasing wheat, barley, oats and triticale; (b) beer and malt manufacturers exert market power when purchasing wheat and barley; and (c) other food product manufacturers exert market power when purchasing wheat, barley, oats and triticale. What is interesting is that each of the transaction nodes where market power is indicated is one where a farm commodity is sold to a processing sector that is, the evidence suggests oligopsonistic behaviour by grains buyers. The wheat and barley industries seem to be especially disadvantaged by this type of market conduct. A related and equally interesting result is that there was no consistent evidence of market power in the downstream nodes of the data set relating to the sales of flour and other cereal foods, or the sale of bread and other bakery products. These transaction points are where legal judgements against suppliers have been made in the recent past. We have stated our results in quite cautious language, as there is much uncertainty surrounding our estimates. This stems partly from the lack of good quality data, so we suggest that one avenue for future research should be improving the collection and integrity of relevant data (especially including the retail and distributive nodes of the various markets).Industrial Organization, Marketing,

    Imposing Observation-Varying Equality Constraints Using Generalised Restricted Least Squares

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    Linear equality restrictions derived from economic theory are frequently observation-varying. Except in special cases, Restricted Least Squares (RLS) cannot be used to impose such restrictions without either underconstraining or overconstraining the parameter space. We solve the problem by developing a new estimator that collapses to RLS in cases where the restrictions are observation-invariant. We derive some theoretical properties of our so-called Generalised Restricted Least Squares (GRLS) estimator, and conduct a simulation experiment involving the estimation of a constant returns to scale production function. We find that GRLS significantly outperforms RLS in both small and large samples
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