scholarly journals Love Thy Neighbour? Perceived Community Abidance and Private Compliance to COVID-19 Norms in India

2021 ◽  
pp. 139156142110539
Author(s):  
Upasak Das ◽  
Prasenjit Sarkhel ◽  
Sania Ashraf
Keyword(s):  
Strict Adherence ◽  
Community Institutions ◽  
Community Benefits ◽  
Omitted Variable Bias ◽  
Health Gains ◽  
Local Actors ◽  
Variable Bias ◽  
Using Data ◽  
Private Effort ◽  
Respiratory Hygiene

To arrest the spread of COVID-19 infection, strict adherence to frequent hand washing and respiratory hygiene protocols have been recommended. While these measures involve private effort, they provide health gains along with collective community benefits and hence are likely to be driven by pro-social motives like altruism and reciprocity. Using data from 934 respondents collected from April till May 2020 across India, we assess if changes in perceived community compliance can predict changes in individual compliance behaviour. We observe statistically significant and positive relationship between the two, even after accounting for observable and omitted variable bias allowing us to view the results from a plausible causal lens. Further, we find subsequent lockdowns having a detrimental effect on individual compliance though the gains from higher perceived community compliance seem to offset this loss. We also find positive perceptions about community can be particularly effective for people with pre-existing co-morbidities. Our findings underscore the need for multi-level behavioural interventions involving local actors and community institutions to sustain private compliance during the pandemic. We suggest these interventions need to be specially targeted for individuals with chronic ailments and emphasize on community behavioural practices in public messaging. JEL Codes: I12, I18, I19, I31

Orangia Highways (A)

2017 ◽  
pp. 1-5
Author(s):  
Peter Eso ◽  
Peter Klibanoff ◽  
Karl Schmedders ◽  
Graeme Hunter
Keyword(s):  
Decision Maker ◽  
Procurement Auctions ◽  
Cost Ratio ◽  
Department Of Transportation ◽  
Omitted Variable Bias ◽  
Ratio Set ◽  
Basic Facts ◽  
Variable Bias ◽  
Using Data ◽  
Set Up

The decision maker is in charge of procurement auctions at the department of transportation of Orangia (a fictitious U.S. state). Students are asked to assist him in estimating the winning bids in various auctions concerning highway repair jobs using data on past auctions. The decision maker is faced with various professional, statistical, and ethical dilemmas.To analyze highway procurement auctions from the buyer-auctioneer perspective, establish basic facts regarding the project price-to-estimated cost ratio, set up and estimate a structural regression model to predict the winning bid, and compute the probability the winning price will be below estimated cost. Difficulties include heteroskedasticity, logarithmic specification, and omitted variable bias. Also to estimate a Logit regression and predict bidder collusion probability.

scholarly journals Health and Housing Energy Expenditures: A Two-Part Model Approach

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 943
Author(s):  
Fátima Lima ◽  
Paula Ferreira ◽  
Vítor Leal
Keyword(s):  
Low Income ◽  
Health Expenditures ◽  
Household Level ◽  
Energy Expenditures ◽  
Health And Wellbeing ◽  
Health Gains ◽  
Key Factor ◽  
Using Data ◽  
Part Model ◽  
Model Approach

Interest in the interaction between energy and health within the built environment has been increasing in recent years, in the context of sustainable development. However, in order to promote health and wellbeing across all ages it is necessary to have a better understanding of the association between health and energy at household level. This study contributes to this debate by addressing the case of Portugal using data from the Household Budget Survey (HBS) microdata database. A two-part model is applied to estimate health expenditures based on energy-related expenditures, as well as socioeconomic variables. Additional statistical methods are used to enhance the perception of relevant predictors for health expenditures. Our findings suggest that given the high significance and coefficient value, energy expenditure is a relevant explanatory variable for health expenditures. This result is further validated by a dominance analysis ranking. Moreover, the results show that health gains and medical cost reductions can be a key factor to consider on the assessment of the economic viability of energy efficiency projects in buildings. This is particularly relevant for the older and low-income segments of the population.

scholarly journals Omitted Variable Bias in GLMs of Neural Spiking Activity

2018 ◽  
Vol 30 (12) ◽  
pp. 3227-3258 ◽  
Author(s):  
Ian H. Stevenson
Keyword(s):  
Neural Activity ◽  
Single Neuron ◽  
Linear Models ◽  
Theory And Practice ◽  
Parameter Estimates ◽  
Omitted Variables ◽  
History Effects ◽  
Omitted Variable Bias ◽  
Wide Range ◽  
Variable Bias

Generalized linear models (GLMs) have a wide range of applications in systems neuroscience describing the encoding of stimulus and behavioral variables, as well as the dynamics of single neurons. However, in any given experiment, many variables that have an impact on neural activity are not observed or not modeled. Here we demonstrate, in both theory and practice, how these omitted variables can result in biased parameter estimates for the effects that are included. In three case studies, we estimate tuning functions for common experiments in motor cortex, hippocampus, and visual cortex. We find that including traditionally omitted variables changes estimates of the original parameters and that modulation originally attributed to one variable is reduced after new variables are included. In GLMs describing single-neuron dynamics, we then demonstrate how postspike history effects can also be biased by omitted variables. Here we find that omitted variable bias can lead to mistaken conclusions about the stability of single-neuron firing. Omitted variable bias can appear in any model with confounders—where omitted variables modulate neural activity and the effects of the omitted variables covary with the included effects. Understanding how and to what extent omitted variable bias affects parameter estimates is likely to be important for interpreting the parameters and predictions of many neural encoding models.

scholarly journals Lock-In and Team Effects

2015 ◽  
Vol 18 (4) ◽  
pp. 376-387
Author(s):  
Trey Dronyk-Trosper ◽  
Brandli Stitzel
Keyword(s):  
Set Covering ◽  
Future Research ◽  
Prior Work ◽  
Omitted Variable Bias ◽  
Specific Effects ◽  
Heterogeneous Effects ◽  
Team Success ◽  
Variable Bias ◽  
Lock In ◽  
Least Squares Approach

How important is recruiting to a football program’s success? While prior research has attempted to answer this question, we utilize an extensive panel set covering 13 years of games along with a two-stage least squares approach to investigate the effects of recruiting on team success. This article also includes new control variables to account for omitted variable bias that prior work may have missed. We also split our sample to investigate whether recruiting displays heterogeneous effects across schools. Additionally, we find evidence that the benefits of recruiting are driven by team-specific effects, indicating that team success may be more heavily derived from the ability of teams to harness and improve their recruits than their ability to utilize each athlete’s raw abilities. This leads to important revelations regarding future research into both the value of recruits and what drives a football team’s success.

The Impact of ICT Investment on Establishment Productivity

2003 ◽  
Vol 184 ◽  
pp. 99-110 ◽  
Author(s):  
Thomas Zwick
Keyword(s):  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Data Set ◽  
Omitted Variable Bias ◽  
Lagged Effects ◽  
Variable Bias ◽  
Employee Characteristics ◽  
The Impact ◽  
Establishment Panel Data

This paper finds substantial effects of ICT investments on productivity for a large and representative German establishment panel data set. In contrast to the bulk of the literature also establishments without ICT capital are included and lagged effects of ICT investments are analysed. In addition, a broad range of establishment and employee characteristics are taken account of in order to avoid omitted variable bias. It is shown that taking into account unobserved heterogeneity of the establishments and endogeneity of ICT investments increases the estimated lagged productivity impact of ICT investments.

scholarly journals Tracking Underreported Financial Flows: China’s Development Finance and the Aid–Conflict Nexus Revisited

2015 ◽  
Vol 61 (5) ◽  
pp. 935-963 ◽  
Author(s):  
Austin M. Strange ◽  
Axel Dreher ◽  
Andreas Fuchs ◽  
Bradley Parks ◽  
Michael J. Tierney
Keyword(s):  
Open Source ◽  
Reliable Information ◽  
African Countries ◽  
Financial Flows ◽  
Development Finance ◽  
Alternative Funding ◽  
Omitted Variable Bias ◽  
Chinese Official ◽  
Variable Bias ◽  
Project Level

China’s provision of development finance to other countries is sizable but reliable information is scarce. We introduce a new open-source methodology for collecting project-level development finance information and create a database of Chinese official finance (OF) to Africa from 2000 to 2011. We find that China’s commitments amounted to approximately US$73 billion, of which US$15 billion are comparable to Official Development Assistance following Organization for Economic Cooperation and Development definitions. We provide details on 1,511 projects to fifty African countries. We use this database to extend previous research on aid and conflict, which suffers from omitted-variable bias due to the exclusion of Chinese development finance. Our results show that sudden withdrawals of “traditional” aid no longer induce conflict in the presence of sufficient alternative funding from China. Our findings highlight the importance of gathering more complete data on the development activities of “nontraditional donors” to better understand the link between aid and conflict.

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