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Children and their Families: Function of the Community
Hogg Foundation for Mental Healt
A Reinterpretation of Interactions in Regressions
Regression specifications in applied econometrics frequently employ regressors that are defined as the product of two other regressors to form an interaction. Unfortunately, the interpretation of the results of these models is not as straight forward as in the linear case. In this paper, we present a method for drawing inferences for interaction models by defining the partial influence function. We present an example that demonstrates how one may draw new inferences by constructing the confidence intervals for the partial influence functions based on the traditional published findings for regressions with interaction terms.Interaction effects; dummy variables; linear transformation; Fieller method
Interactions in Regressions
Regression specifications frequently employ regressors that are defined as the product of two other regressors to form an interaction. Unfortunately, these models have a number of potential difficulties when it comes to interpretation. In this paper, we discuss two common aspects of these specifications that can lead to difficulties. The first is the change in parameter estimates and tstatistics when different definitions of dummy variables are used. The second involves an application of Fieller’s theorem to draw appropriate inferences from a regression with interaction variables.Interaction effects; dummy variables; linear transformation; Fieller method
Alcohol Consumption, Smoking and Wages.
The good health of an individual is a combination of uncontrollable factors that includes genetics and random events and controllable factors through the regulation of activities such as smoking and drinking. Since the work of Grossman (1972) a significant relationship between health and earnings is predicted. In this paper, the 1995 Australian National Health Survey is used to simultaneously examine the effects of drinking and smoking on wages. To model the interaction of smoking with alcohol consumption separate models are fit for smokers and nonsmokers. These models account for potential selectivity bias resulting from the decision to smoke and endogeneity arising from a potential casual relationship between earnings and alcohol consumption.WAGES ; ALCOHOL ; CONSUMPTION ; MODELS
Alernative Forms for Restricted Regressions
We study the relationship between group size and the extent of risk sharing in an insurance game played over a number of periods with random idiosyncratic and aggregate shocks to income in each period. Risk sharing is attained via agents that receive a high endowment in one period making unilateral transfers to agents that receive a low endowment in that period. The complete risk sharing allocation is for all agents to place their endowments in a common pool, which is then shared equally among members of the group in every period. Theoretically, the larger the group size, the smaller the per capita dispersion in consumption and greater is the potential value of insurance. Field evidence however suggests that smaller groups do better than larger groups as far as risk sharing is concerned. Results from our experiments show that the extent of mutual insurance is significantly higher in smaller groups, though contributions to the pool are never close to what complete risk sharing requires.Reciprocity Risk Sharing Group Size Experiments
Self-organizing search lists using probabilistic back-pointers
A class of algorithms is given for maintaining self-organizing sequential search lists, where the only permutation applied is to move the accessed record of each search some distance towards the front of the list. During searches, these algorithms retain a back-pointer to a previously probed record in order to determine the destination of the accessed record's eventual move. The back-pointer does not traverse the list, but rather it is advanced occationally to point to the record just probed by the search algorithm. This avoids the cost of a second traversal through a significant portion of the list, which may be a significant savings when each record access may require a new page to be brought into primary memory. Probabilistic functions for deciding when to advance the pointer are presented and analyzed. These functions demonstrate average case complexities of measures such as asymptotic cost and convergence similar to some of the more common list update algorithms in the literature. In cases where the accessed record is moved forward a distance proportional to the distance to the front of the list, the use of these functions may save up to 50% of the time required for permuting the list
Providing Intuition to the Fieller Method with Two Geometric Representations using STATA and Eviews
The Fieller Method for the construction of confidence intervals for ratios of the expected value of two normally distributed random variables has been shown by a number of authors to be a superior method to the delta approximation. However, it is not widely used due in part, to the tendency to present the intervals only in a formula context. In addition, potential users have been deterred by the potential difficulty in interpreting non-finite confidence intervals when the confidence level is less than 100%. In this paper we present two graphical methods which can be easily constructed using two widely used statistical software packages (Eviews and Stata) for the representation of the Fieller intervals. An application is presented to assess the results of a model of the non-accelerating inflation rate of unemployment (NAIRU).Fieller method, ratios of parameters, confidence interval, confidence ellipsoid,1st derivative function, NAIRU, EViews, STATA
Confidence Intervals for Estimates of Elasticities
Elasticities are often estimated from the results of demand analysis however, drawing inferences from them may involve assumptions that could influence the outcome. In this paper we investigate one of the most common forms of elasticity which is defined as a ratio of estimated relationships and demonstrate how the Fieller method for the construction of confidence intervals can be used to draw inferences. We estimate the elasticities of expenditure from Engel curves using a variety of estimation models. Parametric Engel curves are modelled using OLS, MM robust regression, and Tobit. Semiparametric Engel curves are estimated using a penalized spline regression. We demonstrate the construction of confidence intervals of the expenditure elasticities for a series of expenditure levels as well as the estimated cumulative density function for the elasticity evaluated for a particular household.Engel curves, Fieller method, Tobit, robust regression, semiparametric
Maintenance of Strongly Connected Component in Shared-memory Graph
In this paper, we present an on-line fully dynamic algorithm for maintaining
strongly connected component of a directed graph in a shared memory
architecture. The edges and vertices are added or deleted concurrently by fixed
number of threads. To the best of our knowledge, this is the first work to
propose using linearizable concurrent directed graph and is build using both
ordered and unordered list-based set. We provide an empirical comparison
against sequential and coarse-grained. The results show our algorithm's
throughput is increased between 3 to 6x depending on different workload
distributions and applications. We believe that there are huge applications in
the on-line graph. Finally, we show how the algorithm can be extended to
community detection in on-line graph.Comment: 29 pages, 4 figures, Accepted in the Conference NETYS-201
Systematic Influences on Teaching Evaluations : The Case for Caution
The evaluation of teaching and learning has become an important activity in tertiary education institutions. Student surveys provide information about student perceptions and judgments of a particular subject. However, as is widely recognised, the appropriate interpretation of this data is problematic. There is a large literature, mainly for the US, on the use and usefulness of student subject evaluations. This literature has highlighted a number of ‘mitigating factors’ such as subject difficulty, discipline area, etc., that should be taken into account in interpreting the results of these questionnaires. In this paper we examine 8 years of QOT responses from an Economics Department in an Australian University which accounted for more than 79,000 student subject enrolments in 565 subjects. The purpose of this analysis is to establish how the information contained in these data can be used to interpret the responses. In particular, we determine to what extent other factors besides the instructor in charge of the subject have an impact on the raw average student evaluation scores. We find that the following characteristics of the students in these classes had an influence on the average QOT score: year level, enrolment size, the quantitative nature of the subject, the country of origin of the students, the proportion that are female, Honours status of the student, the differential in their mark from previous marks, quality of workbook, quality of textbook and the relative QOT score versus other subjects taught at the same time. However, a number of other factors proposed in the literature to be important influences were found not to be. These include the student’s fee paying status, whether they attended a public, private or catholic secondary school, which other faculty within the University they came from, and if the subject was taught in multiple sessions.
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