Measuring efficiency in Australian Schools: A preliminary analysis

In this paper, we apply a public sector Data Envelopment Analysis model to estimate the efficiency of Australian primary and secondary schools. Standard microeconomic production theory showing the transformation of inputs into outputs is extended to allow nondiscretionary environmental variables characteristic of educational production. Failure to properly control for the socioeconomic environment leads to inappropriate comparisons and biased efficiency estimates. We employ a conditional estimator that does not allow a school with a better environment to serve as a benchmark for a school with a worse environment. The results suggest that Australian schools are moderately inefficient and that efficiency increases for the quintile of schools with the most favorable environment. Further, efficiency gains are realized with increasing enrollment.     

Charter school closure and student achievement: Evidence from Ohio

The closure of low-performing schools is an essential feature of the charter school model. Our regression discontinuity analysis uses an exogenous source of variation in school closure—an Ohio law that requires charter schools to close if they fail to meet a specific performance standard—to estimate the causal effect of closure on student achievement. The results indicate that closing low-performing charter schools eventually yields achievement gains of around 0.2–0.3 standard deviations in reading and math for students attending these schools at the time they were identified for closure. The study also employs mandatory closure as an instrument for estimating the impact of exiting low-quality charter schools, thus providing plausible lower-bound estimates of charter school effectiveness. These results complement the more common lottery-based estimates of charter school effects, which likely serve as upper-bound estimates due to their focus on oversubscribed schools often located in cities with high-performing charter sectors. We discuss the implications for research and policy.     

Can the theory of planned behaviour explain walking to and from school among Australian children? A social marketing formative research study

Evidence indicates that lower levels of obesity among school‐age children can be achieved through active travel to school. This research aimed to investigate the explanatory potential of constructs in the theory of planned behaviour for carers' decisions about their children's walking to and from school. The data from two online surveys of 1,076 carers in 2 Australian states showed that the theory of planned behaviour explained 35.7% of the variance in walking to and from school. The results indicate that higher perceived behavioural control, social norms, and intentions among carers are associated with higher incidence of walking to and from school by children in Australia. Limitations of the current study and future research directions are outlined.     

Foreign capital inflows,domestic savings and the price of political stability in the sudan: Weisskopf revisited

This paper reworks Weisskopf's estimates of the effect of foreign capital inflow on domestic savings for a later time period. The Sudan is presented as an example of a public sector dominated economy, dependent on one major export crop and politically unstable. While Weisskopf's savings function had an indication of a negative relationship between public sector savings and official foreign capital inflow, problems of collinearity between the independent variables cast doubt on its utility for analysis of economies dependent on limited primary exports. The negative relationship between public sector savings and official is explained in terms of the expansion of the state's bureaucracy and military.     

Quantile models and estimators for data analysis

Quantile regression is used to estimate the cross sectional relationship between high school characteristics and student achievement as measured by ACT scores. The importance of school characteristics on student achievement has been traditionally framed in terms of the effect on the expected value. With quantile regression the impact of school characteristics is allowed to be different at the mean and quantiles of the conditional distribution. Like robust estimation, the quantile approach detects relationships missed by traditional data analysis. Robust estimates detect the influence of the bulk of the data, whereas quantile estimates detect the influence of co-variates on alternate parts of the conditional distribution. Since our design consists of multiple responses (individual student ACT scores) at fixed explanatory variables (school characteristics) the quantile model can be estimated by the usual regression quantiles, but additionally by a regression on the empirical quantile at each school. This is similar to least squares where the estimate based on the entire data is identical to weighted least squares on the school averages. Unlike least squares however, the regression through the quantiles produces a different estimate than the regression quantiles.     

Mandatory summer school and student achievement

Using administrative data from a large school district, I exploit the fact that students are mandated to attend summer school based on a discontinuous function of their score on year-end exams to identify the effect of summer school attendance on achievement. I find an average effect of about .12 standard deviations for both math and reading achievement, an effect size on the low end of the range of prior estimates. These averages mask considerable heterogeneity, however, with effect size estimates ranging from just below zero to one-quarter of a standard deviation. The estimates on the upper end of the range presented here suggest that summer school may be a more cost-effective way of raising student achievement scores than class-size reductions.     

Age at immigration and school performance: A siblings analysis using swedish register data

This article analyzes the role of age at immigration for the school performance gap between native and immigrant pupils in Sweden. The analysis exploits within-family variation in a large set of register data on immigrant siblings (and native children) graduating from compulsory school (normally at age 16) between 1988 and 2003. The critical age at arrival is about nine, above which there is a strong negative impact on performance. The slopes of these age-at-immigration performance profiles are similar for boys and girls as well as for children from different family backgrounds, but they vary widely by region of origin. Moreover, the estimated profiles are flatter for Mathematics than for a range of subjects taken together. This demonstrates the importance of Sweden-specific skills. A comparison of sibling-difference and cross-sectional estimates reveals that they are strikingly similar.     

New multi-regional input–output databases for Australia – enabling timely and flexible regional analysis

ABSTRACT

Decision-making at regional scales requires timely information. Within four months of the release of official national statistics, we have produced a time-series (2008–2015) of balanced sub-national, multi-regional supply-and-use tables (MR-SUT), integrated with a set of socio-economic and environmental accounts. This was achieved using the Australian IELab, where data used in this study are available (https://ielab.info/resources/91). Four multi-regional, environmentally extended supply-use tables regionalised in different ways were produced to demonstrate the flexibility of tailoring input–output models to specific research or policy questions. Results for satellite coefficients are sensitive to the chosen regional grouping and method for regionalisation. We demonstrate the relevance of such purpose-built information to government and corporate decision-makers by analysing the indirect economic and employment consequences of a slowdown of the mining boom in Western Australia. The demonstrated innovations in flexibility and timeliness will help move past some of the limitations that have historically hindered the uptake and utility of applied input–output analysis.     

High school completion and future youth unemployment: new evidence from High School and Beyond

In this paper, I provide new evidence from High School and Beyond (HSB) on the effects of compulsory attendance on high school completion and future youth unemployment. I develop Bayesian estimation approaches to the simultaneous equation model with ordered probit and two‐limit censored regression and the bivariate duration model, accounting for the heterogeneity in returns to education and the nonlinearity in the effects of compulsory attendance. I find substantial variability in returns to education across schools and evidence of diminishing marginal effects of compulsory attendance on high school completion. The simulation results suggest that increasing the compulsory attendance age raises the probability of completing high school and reduces the proportion of time the individuals are unemployed. These effects are much more pronounced for disadvantaged students but less pronounced for advantaged students, suggesting the potential effects of compulsory attendance on reducing the inequality in education and employment. Copyright © 2005 John Wiley & Sons, Ltd.     

Localised Estimates of Dynamics of Multi‐dimensional Disadvantage: An Application of the Small Area Estimation Technique Using Australian Survey and Census Data

Deep and persistent disadvantage is an important, but statistically rare, phenomenon in the population, and sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. Survey samples are typically designed to produce estimates of population characteristics of planned areas. The sample sizes are calculated so that the survey estimator for each of the planned areas is of a desired level of precision. However, in many instances, estimators are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This has led to the development of a class of indirect estimators that make use of information from related areas through modelling. A model is used to link similar areas to enhance the estimation of unplanned areas; in other words, they borrow strength from the other areas. Doing so improves the precision of estimated characteristics in the small area, especially in areas with smaller sample sizes. Social science researchers have increasingly employed small area estimation to provide localised estimates of population characteristics from surveys. We explore how to extend this approach within the context of deep and persistent disadvantage in Australia. We find that because of the unique circumstances of the Australian population distribution, direct estimates of disadvantage have substantial variation, but by applying small area estimation, there are significant improvements in precision of estimates.     

A comparative analysis on school attainment in Turkey and Malta: application of the Tobit model

This research provides a comparative analysis on the correlates of school attainment between Turkish and Maltese people. In the analysis, school attainment is measured by years of education. Tobit model estimates are obtained in the analyses using Eurobarometer 2004.1 data set. The results of the model demonstrate that, the effect of marriage on school attainment found to be insignificant for Malta while it is significant for Turkey. Additionally, it can be seen that females are less educated than males and income has a positive effect on school attainment in both Turkey and Malta. By providing comparative analyses, this research attempts to give insights for policy makers and professionals to improve the Turkish education system.     

How can big data enhance the timeliness of official statistics?: The case of the U.S. consumer price index

The daily consumer price index (CPI) produced by the Billion Prices Project (BPP CPI) offers a glimpse of the direction taken by consumer price inflation in real time. This is in contrast to the official U.S. CPI, which is compiled monthly and released with an average of a three-week delay following the end of the reference month. A recent body of research contended that the movements of online prices are representative of those of offline retail prices, making the BPP CPI a natural candidate for accurately improving the timeliness of the official CPI. We assess the predictive content of the BPP CPI using a variety of MIDAS models that accommodate data sampled at different frequencies. These models generate estimates that remain robust to the variety of time periods considered and, by the standard of the existing literature, contribute to a significant upgrade in the forecast accuracy of official consumer price inflation figures. The paper then sketches the broad implications of BPP CPI for the consumer price statistics maintained by national statistics offices and discusses how the proposed improvement in the timeliness of the official CPI fits in this perspective.     

Productivity decline in Australian coal mining

A recent Australian Productivity Commission Staff Working Paper has estimated a 25 % decline in value added total factor productivity in Australian coal mining over the period 2000/2001–2006/2007. The decline coincides with a period of rapidly increasing global demand for, and price of, coal, which has made it economically feasible to mine coal that was previously uneconomic. This “digging deeper” hypothesis is plausible, although our initial surprise at the magnitude of the estimated decline has motivated our investigation of productivity in Australian coal mining, its financial implications and its likely causes. We begin by applying the Staff Working Paper methodology to revised data to estimate the magnitude of the decline. This exercise shrinks the estimated magnitude of the decline to 21 %. We continue by applying an alternate methodology to the revised data to re-estimate the magnitude of the decline. This exercise generates no further change to the estimated rate of decline. We then compare estimates of the decline obtained from value added and gross output frameworks, and we find a considerable shrinkage in the estimated productivity decline that highlights the importance of the Domar factor in productivity measurement. We continue by exploring the financial consequences of the productivity decline. We conclude by joining the search for sources of the productivity decline.     

Tactics of Labor Struggles

Some actions by employers have the potential to generate outrage due to perceived injustice or abuse. Employers have five main methods to inhibit such outrage: covering up the action, demonizing the workers, reinterpreting what is happening, referring the matter to official channels that give only the appearance of justice, and using intimidation and bribery. Examples from Australian labor struggles are used to illustrate these tactics and how they can be opposed.     

Hazard model estimates of the decision to reenroll in school

In a sample of males drawn from the National Longitudinal Survey of Youth, one-third of the individuals who first leave school between 1978 and 1990 are found to return to school before 1991. In light of this finding, the current study extends the analysis of schooling demand to a dynamic framework in order to consider the timing of the enrollment decision. A semiparametric, proportional hazard model for nonenrollment durations is estimated. The hazard model estimates are consistent with the view that young men reenroll in school when the costs are relatively low and/or the benefits are relatively high. For example, increases in state-wide average tuition levels and current earned wages lower the hazard rate, while increases in unemployment rates have the opposite effect.     

Maximum likelihood estimation of seemingly unrelated stochastic frontier regressions

This paper explores the changes in value added (VA) of a sample of schools for cohorts of students finishing secondary education between 2005 and 2008. VA estimates are based on distance measures obtained from DEA models. These measures are computed for each pupil in each school, and evaluate the distance between the school frontier in a given year and a pooled frontier comprising all schools analysed. The school VA is then computed by aggregating the VA scores for the cohort of pupils attending that school in a given year. The ratio between VA estimates for two consecutive cohorts, that attended the school in different years, is taken as the index of VA change. However, the evolution of school performance over time should consider not only the movements of the school frontier, but should also take into account other effects, such as the proximity of the students to the best-practices, represented by the school frontier, observed over time. For that purpose we developed an enhanced Malmquist index to evaluate the evolution of school performance over time. One of the components of the Malmquist index proposed measures VA change, and the other measures the ability of all school students to move closer to their own school best practices over time. The approach developed is applied to a sample of Portuguese secondary schools.     

A Bayesian Approach to Improve Estimate at Completion in Earned Value Management

Forecasting represents a core project management process. Estimates at completion in terms of cost and schedule provide essential data and advice to the project team in order to lead and control the project and implement suitable corrective measures. In order to improve the forecasting process, a Bayesian model has been developed within the earned value management framework aiming to calculate a confidence interval for the estimates of both cost and schedule at the completion of the project. The model is based on the integration of data records and qualitative knowledge provided by experts. The model has been tested in an oil and gas project.     

Identification and estimation of bounds on school performance measures: a nonparametric analysis of a mixture model with verification

This paper identifies and nonparametrically estimates sharp bounds on school performance measures based on test scores that may not be valid for all students. A mixture model with verification is developed to handle this problem. This is a mixture model for data that can be partitioned into two sets, one of which (the so‐called verified set) is more likely to be from the distribution of interest than the other. An administrative classification of each student as English proficient or limited English proficient determines these sets. An analysis of performance measures for some California public schools reveals how verification information and plausible monotonicity restrictions can bound the range of disagreement about school performance based on observed scores. Copyright © 2006 John Wiley & Sons, Ltd.     

The Unintended Consequences of Italy's Labour Laws: How Extensive Labour Regulation Distorts the Italian Economy

Simple solutions to complex problems often have unintended and undesirable consequences. An example is Italy's approach to combating unemployment. Rigid laws designed to protect the employed perversely discourage businesses from hiring and people from working. They also encourage precarious temporary employment among young people, informal work, and under‐the‐table deals that compromise worker benefits. The numbers of Italy's unemployed and of those outside the workforce are much higher than official estimates suggest. Italy's employment protection legislation – arguably the most restrictive in Europe – creates that which it seeks to prevent: the insecurity of unemployment.