Is the STEM gender gap closing?

The Networking for Science Advancement (NSA) team's institutions consist of nine universities located in one large southwestern state. This study evaluated students enrolled from Spring 2017 to Fall 2019 in first- and second-semester general chemistry. Over 90% of the students (n = 6,694) have been exposed to a secondary school isomorphic curriculum. The population studied, Chem I (n = 4,619) and Chem II (n = 2,075), met entry-level criteria and are therefore expected to succeed (i.e., earn grades of A, B or C). This study's focus is to disaggregate data based on binary gender (M/F) in hopes of revealing patterns that might remain hidden when studying an undivided population. In Chem I, the female population was 59.6% and increased to 64.5% for Chem II. The 15-min., diagnostic Math-Up Skills Test’s (MUST) scores identified about half of all students who were unsuccessful (grades of D and F). Results from the study support that males enter Chem I and II with better automaticity skills (what can be done without using a calculator) than females. However, females outperformed males on course averages in Chem I but not Chem II. Our data provide supporting evidence that the gender gap may be closing.

Reducing emissions in London schools with photovoltaics

This paper examines the potential for PV to improve the performance of primary schools in London. Disaggregate data including energy use is compared with modelled PV generation, showing that electricity demand could theoretically be met in 59% of the schools investigated. The impact of several key factors is then considered, including architectural heritage, building age and form. The results show that the greatest PV potential exists in newer schools, as well as those that are shorter and with less dense forms.

An Empirical Evaluation of Egg Demand in the United States

We adopt an EASI model to estimate demand for omega-3, organic, cage-free, and conventional eggs in the United States. Our empirical framework accounts for demand inter-dependencies among these egg types, while allowing for unrestricted Engel curves, unobserved consumer heterogeneity, and a broader product and geographic coverage. We further address endogeneity of prices and expenditures and left-censoring induced by disaggregate data. Our results indicate that the demand for organic and cage-free eggs is price-elastic, while the demand for omega-3 and conventional eggs is price-inelastic. Additionally, we establish strong substitutability relationships between the eggs. Finally, we measure consumer welfare consequences of rising domestic egg prices brought by Japan’s egg import tariff reductions.

Using control charts to understand community variation in COVID-19

Decision-makers need signals for action as the coronavirus disease 2019 (COVID-19) pandemic progresses. Our aim was to demonstrate a novel use of statistical process control to provide timely and interpretable displays of COVID-19 data that inform local mitigation and containment strategies. Healthcare and other industries use statistical process control to study variation and disaggregate data for purposes of understanding behavior of processes and systems and intervening on them. We developed control charts at the county and city/neighborhood level within one state (California) to illustrate their potential value for decision-makers. We found that COVID-19 rates vary by region and subregion, with periods of exponential and non-exponential growth and decline. Such disaggregation provides granularity that decision-makers can use to respond to the pandemic. The annotated time series presentation connects events and policies with observed data that may help mobilize and direct the actions of residents and other stakeholders. Policy-makers and communities require access to relevant, accurate data to respond to the evolving COVID-19 pandemic. Control charts could prove valuable given their potential ease of use and interpretability in real-time decision-making and for communication about the pandemic at a meaningful level for communities.

Gender Inequality in Safety and Security Perceptions in Railway Stations

Recent studies have shown that gender is the personal aspect that mostly affects mobility patterns and travel behaviors. It has been observed, for instance, that female perception of unsafety and insecurity when traveling using public transport forces them to make unwanted travel choices, such as avoiding traveling at certain times of day and to specific destinations. In order to improve the attractiveness of public transport services, this gender gap must not be overlooked. This paper aims at contributing to research in gendered mobility by investigating differences in safety and security perceptions in railway stations, and by identifying which policies could be effective in bridging any existing gap. The methodology includes the collection of disaggregate data through a mixed Revealed Preference/Stated Preference survey, and the estimation of fixed and random parameters behavioral models. Results from a medium-sized Italian railway station show that female travelers feel safer in the presence of other people; they prefer intermodal infrastructures close to the entrance of the station and commercial activities in the internal premises. Moreover, unlike male travelers, they do not appreciate the presence of hedges and greenery outside stations.

Scalable Data Fusion with Selection Correction: An Application to Customer Base Analysis

A computationally scalable, statistically efficient aggregate-disaggregate data fusion method that corrects for selection bias is applied to model customer relationship dynamics at a subscription-based firm.

Disease and demographic development: the legacy of the plague

This paper provides an empirical investigation of the hypothesis that population shocks such as the repeated outbreaks of the plague affected the timing of the demographic transition. The empirical analysis uses disaggregate data from Germany and exploits geographic variation in the exposure to medieval plague shocks. The findings document that areas with greater exposure to plague outbreaks exhibited an earlier onset of the demographic transition. The results are consistent with the predictions of the unified growth literature and provide novel insights into the largely unexplored empirical determinants of the timing of the transition from stagnation to growth.

Urban Commute Travel Distances in Tehran, Istanbul, and Cairo: Weighted Least Square Models

A very large part of the literature on urban commute travels is related to high-income countries. The determinants of urban commute trip distances are not clear in the Middle East and North Africa (MENA); thus, this study attempts to shed light on this topic in relation to Tehran, Istanbul, and Cairo. The objective is to clarify which environmental and human factors are correlated with commuting distance in these cities. Using primary disaggregate data produced by surveys in the three cities (n = 8237) in 2017, weighted least square regressions showed that fifteen significant or highly significant variables, including individual and household characteristics, mobility decisions, residential location, and land use attributes, predict the lengths of urban commute trips in the MENA sample. Unlike western countries, age and gender are not significant predictors of commute distance in MENA large cities. The results of independent-sample Kruskal–Wallis test show that there is a significant difference between the mean one-way commute travel distances in the three cities (Tehran: 9096 m, Istanbul: 10839 m, and Cairo: 6670 m); however, there are some similarities in the determinants of commute distance in the three cities. The results can be adopted to reduce commute trip lengths by providing a more connected street network and accessible neighborhood-level facilities.

How (not) to measure democracy

Measures of democracy are regularly employed in the statistical analysis of economic, political, and social policy. This paper reviews the measures" setup, strength, and weaknesses across the three most prominent democracy datasets: PolityIV, Freedom House, and Varieties of Democracy. The measures developed by the Varieties of Democracy project outperform Polity2 and Freedom House Index with respect to the underlying definition and measurement scale, as well as the theoretical justification of the aggregation procedure. The three indices display a high level of agreement for those observations included in all three datasets. The most substantial differences between the indices lie in the indices’ coverage, i.e. in their non-missing observations (in Polity2 coding, for example, years during which a country is occupied by foreign powers constitute missing values), the availability of disaggregate data and the above mentioned key areas. This paper clarifies when to proceed with caution, but for the most part advocates the use of Varieties of Democracy in the statistical analysis of democracy.