Small Area Estimation of Latent Economic Well-being

© The Author(s) 2019. Small area estimation (SAE) plays a crucial role in the social sciences due to the growing need for reliable and accurate estimates for small domains. In the study of well-being, for example, policy makers need detailed information about the geographical distribution of a range of social indicators. We investigate data dimensionality reduction using factor analysis models and implement SAE on the factor scores under the empirical best linear unbiased prediction approach. We contrast this approach with the standard approach of providing a dashboard of indicators or a weighted average of indicators at the local level. We demonstrate the approach in a simulation study and a real data application based on the European Union Statistics for Income and Living Conditions for the municipalities of Tuscany

What Drives the Productive Efficiency of a Firm? The Importance of Industry, Location, R&D, and Size

This paper investigates the factors that explain the level and dynamics of manufacturing firm productive efficiency. In our empirical analysis, we use a unique sample of about 39,000 firms in 256 industries from the German Cost Structure Census over the years 1992-2005. We estimate the efficiencies of the firms and relate them to firm-specific and environmental factors. We find that (1) about half the model's explanatory power is due to industry effects, (2) firm size accounts for another 20 percent, and (3) location of headquarters explains approximately 15 percent. Interestingly, most other firm characteristics, such as R&D intensity, outsourcing activities, or the number of owners, have extremely little explanatory power. Surprisingly, our findings suggest that higher R&D intensity is associated with being less efficient, though higher R&D spending increases a firm's efficiency over time

DISTRIBUTIONS OF INDEMNITIES FOR CROP-INSURANCE PLANS: WITH APPLICATION TO GRAIN CROPS IN NEW SOUTH WALES

A review of crop-insurance schemes is followed by a discussion of a guaranteed-yield, crop-insurance plan. General formulae for the distribution function and mathematical expectation of indemnities for the insurance plan are presented in terms of the distribution of crop yields. Three special cases are considered in which the original yields, the square root of yields, and the logarithm of yields are normally distributed. The insurance plan is applied on a regional basis for wheat and sorghum production in N.S.W. Given distributional information on the crops obtained from a simulation model, expected indemnities are calculated for four different insurance plans

DISTRIBUTIONS OF INDEMNITIES FOR CROP-INSURANCE PLANS: WITH APPLICATION TO GRAIN CROPS IN NEW SOUTH WALES

A review of crop-insurance schemes is followed by a discussion of a guaranteed-yield, crop-insurance plan. General formulae for the distribution function and mathematical expectation of indemnities for the insurance plan are presented in terms of the distribution of crop yields. Three special cases are considered in which the original yields, the square root of yields, and the logarithm of yields are normally distributed. The insurance plan is applied on a regional basis for wheat and sorghum production in N.S.W. Given distributional information on the crops obtained from a simulation model, expected indemnities are calculated for four different insurance plans.Crop Production/Industries, Risk and Uncertainty,

The Relationship Between Farm Size and Technical Inefficiency of Production of Wheat Farmers in the Eastern Free State, Province of South Africa

Farm-level data for the 1988/89 agricultural year from a sample survey of wheat farmers in Eastern Free State, are analysed in this paper. Stochastic frontier production functions are estimated, in which the technical inefficiency effects are modelled in terms of the size of the farming operation and other explanatory variables. The technical inefficiency effects for the farmers involved are significant and the null hypothesis that the explanatory variables in the model for the inefficiency effects have zero coefficients is rejected. The technical inefficiency effects are negatively and significantly related to the size of the farms. Elasticities of mean outputs with respect to the different inputs, together with the technical efficiencies of the wheat farmers, are estimated for both the translog and the Cobb-Douglas stochastic frontier production functions. However, the Cobb-Douglas function is not an adequate representation of the data, given the specifications of the translog stochastic frontier production function

The Relationship Between Farm Size and Technical Inefficiency of Production of Wheat Farmers in the Eastern Free State, Province of South Africa

Farm-level data for the 1988/89 agricultural year from a sample survey of wheat farmers in Eastern Free State, are analysed in this paper. Stochastic frontier production functions are estimated, in which the technical inefficiency effects are modelled in terms of the size of the farming operation and other explanatory variables. The technical inefficiency effects for the farmers involved are significant and the null hypothesis that the explanatory variables in the model for the inefficiency effects have zero coefficients is rejected. The technical inefficiency effects are negatively and significantly related to the size of the farms. Elasticities of mean outputs with respect to the different inputs, together with the technical efficiencies of the wheat farmers, are estimated for both the translog and the Cobb-Douglas stochastic frontier production functions. However, the Cobb-Douglas function is not an adequate representation of the data, given the specifications of the translog stochastic frontier production function.Crop Production/Industries, Farm Management,

Estimation of the Distribution of Usual Intakes for Selected Dietary Components

The U.S. Department of Agriculture (USDA) has been responsible for conducting periodic surveys to estimate food consumption patterns of households and/or individuals in the United States for over 50 years. Data from these surveys have had a significant impact on the formulation of food-assistance programs, on consumer education and on food regulatory activities. In recent years, there has been interest in estimating the proportion of the population that has insufficient intake or excessive intake of certain dietary components. Different approaches have been suggested for the estimation of this proportion. In all approaches, it is necessary to analyze data on dietary intakes for a sample of individuals. Also, all approaches recognize that an individual who has a low intake of a given dietary component on one day is not necessarily deficient (or at risk of being deficient) so far as that dietary component is concerned. It is low intake over a sufficiently long period of time that produces a dietary deficiency. A dietary deficiency exists when the "usual" (i.e., normal or long-run average) intake of the dietary component is less than the appropriate dietary standard.