Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
13,190
result(s) for
"Time Periods"
Sort by:
Benjamin Franklin you've got mail
\"Ike Saturday travels back to 1776 to help Benjamin Franklin keep history on track\"-- Provided by publisher.
Book
Three strategies to track configurations over time with Qualitative Comparative Analysis
Qualitative Comparative Analysis (QCA) – a configurational research approach – has become often-used in political science. In its original form, QCA is relatively static and does not analyze configurations over time. Since many key questions in political science – and other social sciences – have a temporal dimension, this is a major drawback of QCA. Therefore, we discuss and compare three QCA-related strategies that enable researchers to track configurations over time: (1) Multiple Time Periods, Single QCA; (2) Multiple QCAs, Different Time Periods; and (3) Fuzzy-Set Ideal Type Analysis. We use existing datasets to empirically demonstrate and visualize the strategies. By comparing the strategies, we also contribute to existing overviews on how to address time in QCA. We conclude by formulating an agenda for the further development of the three strategies in applied research, in political science and beyond.
Journal Article
Comparing NGO Resilience and 'Structures of Opportunity' in South Africa and Zimbabwe (2010-2013)
African non-governmental organisations undergo various shifts in order to cope with diverse challenges. This article takes a longitudinal case study approach to analyse the identities and resilience of a small sample of NGOs in South Africa and Zimbabwe between 2009 and 2013. This article will rely on time period and the nature of the state in each site as independent variables. The nuances brought on by the different time periods and each organisation's profile, and the two countries where the NGOs are set, are significant for contributing to the literature on the fluid and adaptive nature of African NGOs in their bid for survival. Through exploring these four diverse NGOs in the two states and time period where new challenges and opportunities are presented, the article will also highlight the variety of challenges and strategies each NGO engaged with when confronting crises specific to their settings and the identities each NGO adopted when developing and shifting their agendas.
Journal Article
Limitations of Fixed-Effects Models for Panel Data
Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical discussion of 12 limitations, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions vis-à-vis previous work. Instead of discouraging the use of fixed-effects models, we encourage more critical applications of this rigorous and promising methodology. The most important deficiencies—Type II errors, biased coefficients and imprecise standard errors, misleading p values, misguided causal claims, and various theoretical concerns—should be weighed against the likely presence of unobserved heterogeneity in other regression models. Ultimately, we must do a better job of communicating the pitfalls of fixed-effects models to our colleagues and students.
Journal Article
Time-Aware Language Models as Temporal Knowledge Bases
Many facts come with an expiration date, from the name of the President to the basketball team Lebron James plays for. However, most language models (LMs) are trained on snapshots of data collected at a specific moment in time. This can limit their utility, especially in the closed-book setting where the pretraining corpus must contain the facts the model should memorize. We introduce a diagnostic dataset aimed at probing LMs for factual knowledge that changes over time and highlight problems with LMs at either end of the spectrum—those trained on specific slices of temporal data, as well as those trained on a wide range of temporal data. To mitigate these problems, we propose a simple technique for jointly modeling text with its timestamp. This improves memorization of seen facts from the training time period, as well as calibration on predictions about unseen facts from future time periods. We also show that models trained with temporal context can be efficiently “refreshed” as new data arrives, without the need for retraining from scratch.
Journal Article
On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data
The two-way linear fixed effects regression (2FE) has become a default method for estimating causal effects from panel data. Many applied researchers use the 2FE estimator to adjust for unobserved unit-specific and time-specific confounders at the same time. Unfortunately, we demonstrate that the ability of the 2FE model to simultaneously adjust for these two types of unobserved confounders critically relies upon the assumption of linear additive effects. Another common justification for the use of the 2FE estimator is based on its equivalence to the difference-in-differences estimator under the simplest setting with two groups and two time periods. We show that this equivalence does not hold under more general settings commonly encountered in applied research. Instead, we prove that the multi-period difference-in-differences estimator is equivalent to the weighted 2FE estimator with some observations having negative weights. These analytical results imply that in contrast to the popular belief, the 2FE estimator does not represent a design-based, nonparametric estimation strategy for causal inference. Instead, its validity fundamentally rests on the modeling assumptions.
Journal Article
A first look at online reputation on Airbnb, where every stay is above average
Judging by the millions of reviews left by guests on the Airbnb platform, this trusted community marketplace for accommodations is fulfilling its mission of matching travelers with hosts having room to spare remarkably well. Based on our analysis of ratings, we collected for millions of properties listed on Airbnb worldwide, we find that nearly 95% of Airbnb properties boast an average star-rating of either 4.5 or 5 stars (the maximum); virtually none have less than a 3.5 star-rating. We contrast this with the ratings of roughly 700,000 hotels, B&Bs, and vacation rentals worldwide that we collected from TripAdvisor. We find that hotel and B&B average ratings are much lower—3.8 and 4.1 stars, respectively—with much more variance across reviews. TripAdvisor vacation rental ratings are more similar to Airbnb ratings, but only about 85% of properties have an average rating of 4.5 or 5 stars. We then consider properties cross-listed on both platforms. For these properties, we find that even though the average ratings on Airbnb and TripAdvisor are more similar than hotels and B&Bs, proportionally more properties receive the highest ratings (4.5 stars and above) on Airbnb than on TripAdvisor. Moreover, there is only a weak correlation in the ratings of individual cross-listed properties across the two platforms. Finally, we show that these differences are consistent when considering data from two different time periods: 2015 and 2018.
Journal Article
Skewed Wealth Distributions
Invariably, across a cross-section of countries and time periods, wealth distributions are skewed to the right displaying thick upper tails, that is, large and slowly declining top wealth shares. In this survey, we categorize the theoretical studies on the distribution of wealth in terms of the underlying economic mechanisms generating skewness and thick tails. Further, we show how these mechanisms can be micro-founded by the consumption–savings decisions of rational agents in specific economic and demographic environments. Finally we map the large empirical work on the wealth distribution to its theoretical underpinnings.
Journal Article
Inspired to perform
Emerging research evidence across multiple industries suggests that thriving at work is critically important for creating sustainable organizational performance. However, we possess little understanding of how factors across different organizational levels stimulate thriving at work. To address this gap, the current study proposes a multilevel model that simultaneously examines contextual and individual factors that facilitate thriving at work and how thriving relates to positive health and overall unit performance. Analysis of data collected from 275 employees, at multiple time periods, and their immediate supervisors, representing 94 work units, revealed that servant leadership and core self-evaluations are 2 important contextual and individual factors that significantly relate to thriving at work. The results further indicated that thriving positively relates to positive health at the individual level, with this relationship partially mediated by affective commitment. Our results also showed that collective thriving at work positively relates to collective affective commitment, which in turn, positively relates to overall unit performance. Taken together, these findings suggest that work context and individual characteristics play significant roles in facilitating thriving at work and that thriving is an important means by which managers and their organizations can improve employees' positive health and unit performance.
Journal Article
Elevated Blood Lead Levels in Children Associated With the Flint Drinking Water Crisis: A Spatial Analysis of Risk and Public Health Response
Objectives. We analyzed differences in pediatric elevated blood lead level incidence before and after Flint, Michigan, introduced a more corrosive water source into an aging water system without adequate corrosion control.
Methods. We reviewed blood lead levels for children younger than 5 years before (2013) and after (2015) water source change in Greater Flint, Michigan. We assessed the percentage of elevated blood lead levels in both time periods, and identified geographical locations through spatial analysis.
Results. Incidence of elevated blood lead levels increased from 2.4% to 4.9% (P < .05) after water source change, and neighborhoods with the highest water lead levels experienced a 6.6% increase. No significant change was seen outside the city. Geospatial analysis identified disadvantaged neighborhoods as having the greatest elevated blood lead level increases and informed response prioritization during the now-declared public health emergency.
Conclusions. The percentage of children with elevated blood lead levels increased after water source change, particularly in socioeconomically disadvantaged neighborhoods. Water is a growing source of childhood lead exposure because of aging infrastructure.
Journal Article