Many teaching practices implicitly assume that conceptual knowledge can be abstracted from the situations in which it is learned and used. This article argues that this assumption inevitably limits the effectiveness of such practices. Drawing on recent research into cognition as it is manifest in everyday activity, the authors argue that knowledge is situated, being in part a product of the activity, context, and culture in which it is developed and used. They discuss how this view of knowledge affects our understanding of learning, and they note that conventional schooling too often ignores the influence of school culture on what is learned in school. As an alternative to conventional practices, they propose cognitive apprenticeship (Collins, Brown, & Newman, in press), which honors the situated nature of knowledge. They examine two examples of mathematics instruction that exhibit certain key features of this approach to teaching.

/pdf/situated-cognition-and-the-culture-of-learning-3pg6ch1r4f.pdf

Situated Cognition and the Culture of Learning

https://steadystate.org/wp-content/uploads/Stern_KuznetsCurve.pdf

The Rise and Fall of the Environmental Kuznets Curve

Econometricians would like to project the image of agricultural experimenters who divide a farm into a set of smaller plots of land and who select randomly the level of fertilizer to be used on each plot. If some plots are assigned a certain amount of fertilizer while others are assigned none, then the difference between the mean yield of the fertilized plots and the mean yield of the unfertilized plots is a measure of the effect of fertilizer on agricultural yields. The econometrician's humble job is only to determine if that difference is large enough to suggest a real effect of fertilizer, or is so small that it is more likely due to random variation. This image of the applied econometrician's art is grossly misleading. I would like to suggest a more accurate one. The applied econometrician is like a farmer who notices that the yield is somewhat higher under trees where birds roost, and he uses this as evidence that bird droppings increase yields. However, when he presents this finding at the annual meeting of the American Ecological Association, another farmer in the audience objects that he used the same data but came up with the conclusion that moderate amounts of shade increase yields. A bright chap in the back of the room then observes that these two hypotheses are indistinguishable, given the available data. He mentions the phrase "identification problem," which, though no one knows quite what he means, is said with such authority that it is totally convincing. The meeting reconvenes in the halls and in the bars, with heated discussion

https://www.pc.gov.au/inquiries/completed/pig-safeguards-2008/submissions/ar103_minter_ellison/subAR103_attachment.pdf

Let's Take the Con Out of Econometrics

Data augmentation and Gibbs sampling are two closely related, sampling-based approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accuracy of the approximations to the expected value of functions of interest under the posterior. In this paper methods from spectral analysis are used to evaluate numerical accuracy formally and construct diagnostics for convergence. These methods are illustrated in the normal linear model with informative priors, and in the Tobit-censored regression model.

Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments

Marriage and household decision-making: a bargaining analysis

This is a book on demand analysis that links economic theory to empirical analysis. The first part shows how theory can be used to specify equation systems suitable for empirical analysis. The second part discusses demand systems estimation using both per capita time series data and household budget data.

Demand System Specification and Estimation

This book explores the principal issues involved in bridging the gap between the pure theory of consumer behavior and its empirical implementation. The theoretical starting point is the familiar static, one-period, utility maximizing model in which the consumer allocates a fixed budget among competing categories of goods. The authors focus upon four issues of primary importance in empirical demand analysis: the structure of preferences, the treatment of demographic variables, the treatment of dynamics, and the specification of the stochastic structure of the demand system.

In this paper we explore two issues in empirical demand analysis-the estimation of complete systems of demand equations using household budget data (Section I), and the incorporation of demographic characteristics into such systems (Section II). Although there are numerous studies which use time-series data to estimate complete demand systems, and many which estimate Engel curves from household budget data, there are virtually none which combine budget data from different periods to estimate complete systems. Since each budget study corresponds to a single price situation, one might conjecture that estimation of complete systems would not be possible unless budget studies were available from a large number of periods. This is incorrect. In Section I we argue that interesting complete demand systems can be estimated from a small number of budget studies, despite the limited price variability represented in such data. To demonstrate this, we use budget study data for two periods to estimate a pair of related demand systems: the familiar linear expenditure system (LES) and a quadratic expenditure system (QES), a generalization of LES in which the demand equations are quadratic in total expenditure.' The inclusion of demographic variables in the analysis of household consumption patterns is desirable because there are likely to be systematic differences in the consumption behavior of households with different demographic characteristics. But the effects of demographic characteristics have seldom been studied within the framework of complete demand systems. In Section II we propose "translating" as a general method for incorporating demographic variables into complete systems of demand equations. This method has not previously been discussed as a general technique for bringing demographic variables into demand systems, although it has been employed in several studies. To improve the estimates of the LES and the QES presented in Section I, we reestimate these two systems using translating to incorporate family size.

https://www.jstor.org/stable/info/1805266

Estimation of Complete Demand Systems from Household Budget Data: The Linear and Quadratic Expenditure Systems

In this paper we estimate a complete system of demand equations making full use of the restrictions implied by economic theory. Our theoretical model is based on the Klein-Rubin linear expenditure system which was first estimated by Stone. We place primary emphasis on maximum likelihood estimates obtained using annual time series observations of prices and per capita consumption for the U.S. economy in the period 1948-1965. The plan of the paper is as follows: Section 1 begins with a discussion of the problems involved in making systematic use of economic theory to estimate demand functions; this is followed by a brief description of the linear expenditure system and discussion of the specification of its dynamic and stochastic structure. In Section 2 we describe three methods of estimating the linear expenditure system, including the maximum likelihood procedure which we believe is most appropriate. We report our results in Section 3 and our conclusions in Section 4. 1 A. INTRODUCTION The pure theory of consumer behavior is concerned with individual demand functions. An individual's preferences are assumed to be representable by a well behaved utility function, U(x1, .. . , x"), where xi denotes the rate of consumption of the ith good. He is supposed to maximize U subject to the budget constraint n (1) E PkXk =I k = 1

/pdf/estimation-of-the-linear-expenditure-system-3l6x5wjl9k.pdf

Terence Wales

Papers

Demand System Specification and Estimation

Demand System Specification and Estimation

Estimation of Complete Demand Systems from Household Budget Data: The Linear and Quadratic Expenditure Systems

Estimation of the linear expenditure system

On the flexibility of flexible functional forms: An empirical approach∗