The (mis)specification of discrete duration models with unobserved heterogeneity: a Monte Carlo study

Empirical researchers usually prefer statistical models that can be easily estimated using standard software packages. One such model is the sequential binary model with or without normal random effects; such models can be adopted to estimate discrete duration models with unobserved heterogeneity. But ease of estimation may come at a cost. In this paper we conduct a Monte Carlo simulation to evaluate the consequences of omitting or misspecifying the unobserved heterogeneity distribution in single-spell discrete duration models.discrete duration models, unobserved heterogeneity, Monte Carlo simulations

The number of countable models via Algebraic logic

Vaught's Conjecture states that if T is a complete First order theory in a countable language that has more than aleph_0 pairwise non isomorphic countable models, then T has 2^aleph_0 such models. Morley showed that if T has more than aleph_1 pairwise non isomorphic countable models, then it has 2^aleph_0 such models. In this paper, we First show how we can use algebraic logic, namely the representation theory of cylindric and quasi-polyadic algebras, to study Vaught's conjecture (count models), and we re-prove Morley's above mentioned theorem. Second, we show that Morley's theorem holds for the number of non isomorphic countable models omitting a countable family of types. We go further by giving examples showing that although this number can only take the values given by Morley's theorem, it can be different from the number of all non isomorphic countable models. Moreover, our examples show that the number of countable models omitting a family of types can also be either aleph_1 or 2 and therefore different from the possible values provided by Vaught's conjecture and by his well known theorem; in the case of aleph_1, however, the family is uncountable. Finally, we discuss an omitting types theorem of Shelah

Method of Correcting Wind Tunnel Data for Omitted Parts of Airplane Models

Wind tunnel models do not have complete similarity to the full scale airplane. Part of the dissimilarity is due to the difference between the stationary model in the artificial wind stream of the tunnel and the moving airplane in still air. There are a number of other reasons for departing from exact geometrical similitude. For reasons of accuracy and economy, all minor parts of the full scale airplane, such as struts, wires, fittings, control horns and other parts whose scale corrections are large are removed from wind tunnel models. By omitting the minor parts of the airplane in the wind tunnel model and adding to the forces and moments of the model those omitted parts measured full scale and properly reduced, the scale effects of such parts disappear from the model data. Scale effects due to major parts of the airplane, particularly the fuselage and wings, can be corrected by omitting the propeller and making the surface of the model as smooth as possible, two further departures from geometrical similitude between model and full scale that add considerably to the accuracy and economy of model tests

The effect of school spending on student achievement: addressing biases in value-added models

The estimation of education production models used to evaluate the effect of school inputs and past skills on test scores, often called value-added models, can be biased by three main econometric issues: unobserved child characteristics, unobserved family and school characteristics and measurement error. We propose a two-step estimation technique which exploits the availability of test scores across time, subjects, families and schools in a unique administrative data set for England to correct for these potential biases. Our empirical results suggest that omitting school characteristics biases the estimation of the effect of school expenditure, whereas omitting unobserved child endowment biases the estimation of the effect of past skills but not the effect of school expenditure

The effects of market linkages and the natural rate of discoveries on market structure

The traditional approach makes investment in innovation constrained by market structure. This paper explores the causality from innovation to market structure. Omitting this causality direction on empirical models may explain empirical problems and contradictions on these models

Allowing for Group Effects When Estimating Import Demand for Source and Product Differentiated Goods

In this study an import demand model (differential production model) is presented that is used in estimating the demand for source and product differentiated goods simultaneously. Unlike the traditional import demand models, this model can account for changes in relative group expenditures. Expenditure estimates differed when comparing the differential production model and Rotterdam model results. Results showed that if group revenue shares are relatively fixed, then the bias in expenditure estimates due to omitting group effects will be small when using traditional demand models such as the AIDS or Rotterdam models. As relative group shares significantly change and diverge the bias increases, particularly for imports representing a larger share of group expenditures.Import demand, AIDS model, Rotterdam model, product differentiation, source differentiation, Demand and Price Analysis, International Relations/Trade, F17, Q17, Q11.,

Spatial Econometrics Revisited: A Case Study of Land Values in Roanoke County

Omitting spatial characteristics such as proximity to amenities from hedonic land value models may lead to spatial autocorrelation and biased and inefficient estimators. A spatial autoregressive error model can be used to model the spatial structure of errors arising from omitted spatial effects. This paper demonstrates an alternative approach to modeling land values based on individual and joint misspecification tests using data from Roanoke County in Virginia. Spatial autocorrelation is found in land value models of Roanoke County. Defining neighborhoods based on geographic and socioeconomics characteristics produces better estimates of neighborhood effects on land values than simple distance measures. Implementing a comprehensive set of individual and joint misspecification tests results in better correction for misspecification errors compared to existing practices.Land Economics/Use,