Session 1: Social Network
Understanding US cross-county differences in stock market participation: Networks matter
Abstract: This presentation exploits the geographic heterogeneity in stock market
participation (SMP) rates across US counties and the role
information sharing through social network plays in explaining this
|Bitcoin adoption and beliefs in Canada
Abstract: There has been a growing discussion on digital currencies in the last
few years, particularly Bitcoin. Nevertheless, research studies on
Bitcoin adoption and experimentation are limited. In this presentation, we
develop a tractable model of Bitcoin experimentation in which agents are
uncertain about the quality of the underlying technology and update
their beliefs by observing the survival of Bitcoin.
... (Read more)
The model determines how adoption decisions depend on (1) network effects, (2) own learning effects, and (3) social learning effects. We test the theoretical model's findings using unique data from the Bank of Canada's Bitcoin Omnibus Survey for the years 2017 and 2018. After accounting for the endogeneity of beliefs, we find that both network effects and own learning effects have a positive significant impact on Bitcoin adoption, while social learning effects have a negative effect. In particular, a 1-percentage-point increase in the network size increases the probability of adoption by 0.41 to 0.45 percentage points, whereas a 1-percentage-point increase in Bitcoin survival beliefs increases the probability of adoption by 0.43 to 0.55 percentage points. Our results suggest that network effects and individual experimentation were key drivers of Bitcoin adoption in 2017 and 2018.
University of Orleans
Session 2: Economic Inequality
Joint estimation of employment and unemployment hazard rates with unobserved heterogeneity using the hshaz2s command
Abstract: In this presentation, I describe hshaz2s, a new command that estimates
two-states proportional hazard rates models with unobserved
heterogeneity specific to each of the two modeled states.
|Does economic inequality breed murder? An empirical investigation of the relationship between economic inequality and homicide rates in Canadian CMAs: 1981 to 2017
Abstract: National and international research documents a relationship between
greater economic inequality and higher homicide rates. However, much of
this work uses simple cross-sections at high levels of aggregation
rather than longer time series of cities or districts and lacks
controls for a more substantial range of confounding factors.
... (Read more)
Using longitudinal Canadian provincial-level data over the period 1981 to 2017, we occasionally find a positive correlation between inequality and homicides rates. However, the relationship between income inequality and homicide rates in Canada reverses to become negative when looking at Canadian Census Metropolitan Areas (CMAs). Moreover, the province-level result between greater inequality and homicide rates also appears to break down once accounting for regional effects. We conclude that much of the literature that finds a relationship between greater economic inequality and homicide rates needs to be reexamined within a longer time and more disaggregated framework.
Livio Di Matteo
Session 3: StataCorp presentation
Custom estimation tables
Abstract: In this presentation, I build custom tables from one or more estimation
commands. I demonstrate how to add custom labels for significant
coefficients and how to make targeted style edits to cells in the table.
I conclude with a simple workflow for you to build your own custom
tables from estimation commands.
Session 4: Survey Methods
A user-friendly technique for weighting survey data using Stata
Abstract: We develop a command that implements the Imbens and Lancaster (1994) and
Hellerstein and Imbens (1999) approach to estimating population-weighted
regression models for survey data by taking advantage of auxiliary
information on moments reflecting the population from which the sample
|Survey calibration via the generalized-method-of-moments
Abstract: This presentation aims to create a standardized weighting procedure for our
ongoing survey program. We propose generalized method of moments
estimators as an alternative covariate balancing procedure to IPF.
... (Read more)
Our goal is to create weights that address three issues. First, the weights should reduce selection bias in each individual survey. Second, the weights should ensure comparability across time of each survey, even if surveys contain different "mixtures" of sample sources. Third, we would like to create separate weights that account for the panel dimension (and therefore attrition) in our April 2020 Survey, where about 1,000 respondents were from past surveys.
Bank of Canada
Bank of Canada
Session 5: Model Selection
Forward model selection using AIC or BIC format
Abstract: Often, one cannot conduct all possible subsets regression,
because there are too many models to consider. The traditional
alternative has been forward/stepwise/backward model selection.
|posw, a Neyman-orthogonal estimator after stepwise covariate selection
Abstract: This talk discusses the new posw command, which produces valid inference
for causal parameters after using a stepwise method to select which
covariates should be included in the model.
... (Read more)
The talk provides a quick introduction to using the lasso and to using the stepwise methods of covariate selection and some tradeoffs between them. It also discusses the authors recommendation to use BIC-based stepwise instead of testing-based stepwise. It also discusses some of the methodology implemented in posw, including some new results in Drukker and Liu (2021).
Sam Houston State University
Sam Houston State University
Session 6: COVID-19
Payment habits during COVID-19: Evidence from high-frequency transaction data
Abstract: We investigate how the COVID-19 pandemic has changed consumers' payment
habits in Canada. We rely on high-frequency data on cash withdrawals and
debit card transactions from Interac and Canada's ACSS clearing system.
We construct daily measures of payment habits reflecting cash usage,
average transaction values, and the share of transactions in which the
customer or card holder and the acquiring machine like ATM or POS are of
the same bank ("on-us").
|A population-based model for rationing the COVID-19 vaccine
Abstract: With the
distribution of COVID-19 vaccines, the model presented here may
with reproduction based on COVID-19 as an endpoint diagnosis serve to
assist the rationing of initially limited supplies of vaccines to those
most vulnerable to infection, potentially helping to curb
the spread of this disease.
... (Read more)
As COVID-19 vaccines develop, methods for identifying vulnerability within groups to prioritized vaccination remain unestablished. This presentation describes a novel approach based on population-based analysis of viral pneumonia vulnerability, as an example.
The analysis employed an anonymous, 16-year population dataset (n = 768,460) consisting of International Classification of Diseases (ICD-9) diagnoses, demographics, and dates identifying those with and without viral pneumonia linked to all associated diagnoses (~90 million) for calculation of independent main-class diagnoses (17) odds ratios and proportions of disorders before and after the index viral pneumonia diagnosis. A subsample of those under the age of 1 year in the first year of the dataset was analyzed prospectively with representation of the intensity of the first 50 diagnoses across all diagnoses (~1000), comparing those who did with those who did not develop viral pneumonia.
Females and males had results of differing magnitude. For those with viral pneumonia, the mean number of diagnoses was greater in both the subsample and whole sample, with associated diagnoses arising about four years on average before the viral pneumonia index diagnosis. Within the subsample, compared with those without, the temporal analysis revealed distinct overrepresentation for those with viral pneumonia at visit 1 and over the first 50 visits. Further, those with viral pneumonia had diagnoses not represented in the group without viral pneumonia.
The population-based analysis of temporal hypermorbidity may be a viable and economical approach to identifying viral pneumonia vulnerability. The approach presented here may provide an economical means of identifying vulnerability to COVID-19 in regions where comparable data are available for analysis. Rational approaches may optimize vaccination and help to limit the spread of the disease and to some extent alleviate the health service burden.
University of Calgary
Session 7: Health Science
Disparities and healthcare utilization among general surgery patients with opioid use disorders
Abstract: Introduction: Opioid use disorder is a major public health issue. We
investigated the national burden of opioid use disorders among general
surgery patients in the USA.
Chair: Anson HoOpen panel discussion with Stata developers
Anson Ho is an assistant professor in the Real Estate Management Department. His primary research interests include consumer finance, housing, and macroeconomics. Prior to joining Ryerson University in 2020, Anson was a senior economist in the Financial Stability Department at the Bank of Canada (2016–2020) and an assistant professor at Kansas State University (2011–2016). Ho received his PhD in economics from the University of Iowa in 2011.
Dr. Laura Rosella is an epidemiologist and associate professor in the Dalla Lana School of Public Health (DLSPH) at the University of Toronto, where she holds a Canada Research Chair in Population Health Analytics. She is the site director for ICES U of T and faculty affiliate at the Vector Institute. In 2020, she was made the inaugural Stephen Family Research Chair in Community Health at the Institute for Better Health, Trillium Health Partners. She leads the Population Health Analytics Lab out of DLSPH, which is focused on using population databases to inform population health and health system planning.
Murtaza Haider is a professor of Data Science and Real Estate Management at Ryerson University. He also serves as the research director of the Urban Analytics Institute. Professor Haider holds an adjunct professorship of engineering at McGill University. In addition, he is a director of Regionomics Inc., a boutique consulting firm specializing in the economics of cities and regions, and holds a masters in transport engineering and a PhD in civil engineering from the University of Toronto.