This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples include estimation of Engel curves and equivalence scales, scale economies, semiparametric Cobb-Douglas, translog and CES cost functions, household gasoline consumption, hedonic housing prices, option prices and state price density estimation. The book should be of interest to a broad range of economists including those working in industrial organization, labor, development, urban, energy and financial economics. A variety of testing procedures are covered including simple goodness of fit tests and residual regression tests. These procedures can be used to test hypotheses such as parametric and semiparametric specifications, significance, monotonicity and additive separability. Other topics include endogeneity of parametric and nonparametric effects, as well as heteroskedasticity and autocorrelation in the residuals. Bootstrap procedures are provided.

No abstract

No abstract

No abstract

Objective: To characterize the relationships between selected socio-demographic factors and food selection among Canadian households. Design: A secondary analysis of data from the 1996 Family Food Expenditure survey was conducted (n ¼ 10 924). Household food purchases were classified into one of the five food groups from Canada's Food Guide to Healthy Eating. Parametric and nonparametric modelling techniques were employed to analyse the effects of household size, composition, income and education on the proportion of income spent on each food group and the quantity purchased from each food group. Results: Household size, composition, income and education together explained 21-29% of the variation in food purchasing. Households with older adults spent a greater share of their income on vegetables and fruit (Po0.0001), whereas households with children purchased greater quantities of milk products (Po0.0001). Higher income was associated with purchasing more of all food groups (Po0.0001), but the associations were nonlinear, with the strongest effects at lower income levels. Households where the reference person had a university degree purchased significantly more vegetables and fruit, and less meat and alternatives and 'other' foods (Po0.0001), relative to households with the lowest education level. Conclusions: Household socio-demographic characteristics have a strong influence on food purchasing, with the purchase of vegetables and fruit being particularly sensitive. Results reinforce concerns about constraints on food purchasing among lower income households. Furthermore, the differential effects of income and education on food choice need to be considered in the design of public health interventions aimed at altering dietary behaviour.