Numerical issues in threshold autoregressive modeling of time series

This paper analyses the contribution of various numerical approaches to making the estimation of threshold autoregressive time series more efficient. It relies on the computational advantages of QR factorizations and proposes Givens transformations to update these factors for sequential LS problems. By showing that the residual sum of squares is a continuous rational function over threshold intervals it develops a new fitting method based on rational interpolation and the standard necessary optimality condition. Taking as benchmark a simple grid search, the paper illustrates via Monte Carlo simulations the efficiency gains of the proposed tools.     

In Search of Theory Development in Grounded Investigations: Doctors' Experiences of Managing as an Example of Fitted and Prospective Theorizing

This article draws on a study of doctors’ experiences of clinical managing to highlight research conventions that limit the development and use of middle range theories in grounded studies. Using sensemaking and the psychological contract as example frameworks, we illustrate how customary deductive evaluations of middle range theories turn grounded researchers away from theory building. As a correction to these conventions, we offer an inductive approach to building existing theory in grounded investigations that does not depend solely on working with frameworks under different empirical conditions. We suggest that forward theorizing is most likely to progress from a synthesis of fitted explanation and prospective thinking that presses at the limits of the data's usefulness. To illustrate this approach, trialled thinking about novel theoretical juxtapositions and alternative sources was used in conjunction with our clinical director data. The value of this approach was supported in two ways. First, a number of fitted and prospective conjectures are offered about how social identity articulates with psychological contracts and sensemaking in role change situations. Second, new light is shed on the process by which particular social conditions differentially modify employees’ social categorizations, and how these inform employee responses to the evolving experience of role change. The article concludes with some tentative proposals for promoting more discussion of theory building in grounded investigations.     

A Bayesian Semiparametric Competing Risk Model with Unobserved Heterogeneity

This paper generalizes existing econometric models for censored competing risks by introducing a new flexible specification based on a piecewise linear baseline hazard, time‐varying regressors, and unobserved individual heterogeneity distributed as an infinite mixture of generalized inverse Gaussian (GIG) densities, nesting the gamma kernel as a special case. A common correlated latent time effect induces dependence among risks. Our model is based on underlying latent exit decisions in continuous time while only a time interval containing the exit time is observed, as is common in economic data. We do not make the simplifying assumption of discretizing exit decisions—our competing risk model setup allows for latent exit times of different risk types to be realized within the same time period. In this setting, we derive a tractable likelihood based on scaled GIG Laplace transforms and their higher‐order derivatives. We apply our approach to analyzing the determinants of unemployment duration with exits to jobs in the same industry or a different industry among unemployment insurance recipients on nationally representative individual‐level survey data from the US Department of Labor. Our approach allows us to conduct a counterfactual policy experiment by changing the replacement rate: we find that the impact of its change on the probability of exit from unemployment is inelastic. Copyright © 2014 John Wiley & Sons, Ltd.     

Comparative Analysis of Thresholds of Non-Revolutionary Institutional Change: China and the United States in the 1980s

Ireland has experienced a series of interlocking banking, fiscal, unemployment, and political crises since 2007. We detail the challenges involved in modeling individual moments of the crisis through the lens of balance sheets and transactions matrices among sectors of the Irish society. We conclude with a series of recommendations for models of small open economies.     

Lebesgue measure and social choice trade-offs

Summary An Arrovian social choice rule is a social welfare function satisfying independence of irrelevant alternatives and transitivity of social preference. Assume a measurable outcome spaceX with its (Lebesgue) measure normalized to unity. For any Arrovian rule and any fractiont, either some individual dictates over a subset ofX of measuret or more, or at least a fraction 1–t of the pairs of distinct alternatives have their social ordering fixed independently of individual preferences. Also, for any positive integer (less than the total number of individuals), there is some subsetH of society consisting of all but persons such that the fraction of outcome pairs (x, y) that are social ranked without consulting the preferences of anyone inH, whenever no individual is indifferent betweenx andy, is at least 1–1/4.We are grateful to Roy Mathias and Daniel Waterman for help with some technical matters, and to chairman Jim Follain and the Syracuse University Economics Department for financing the exchange that launched this project. Campbell's research was funded by National Science Foundation grants, SES 9007953 and SES 9209039.     

A Poisson mixture model of discrete choice

In this paper, we introduce a new Poisson mixture model for count panel data where the underlying Poisson process intensity is determined endogenously by consumer latent utility maximization over a set of choice alternatives. This formulation accommodates the choice and count in a single random utility framework with desirable theoretical properties. Individual heterogeneity is introduced through a random coefficient scheme with a flexible semiparametric distribution. We deal with the analytical intractability of the resulting mixture by recasting the model as an embedding of infinite sequences of scaled moments of the mixing distribution, and newly derive their cumulant representations along with bounds on their rate of numerical convergence. We further develop an efficient recursive algorithm for fast evaluation of the model likelihood within a Bayesian Gibbs sampling scheme. We apply our model to a recent household panel of supermarket visit counts. We estimate the nonparametric density of three key variables of interest-price, driving distance, and their interaction-while controlling for a range of consumer demographic characteristics. We use this econometric framework to assess the opportunity cost of time and analyze the interaction between store choice, trip frequency, search intensity, and household and store characteristics. We also conduct a counterfactual welfare experiment and compute the compensating variation for a 10%-30% increase in Walmart prices.