Template-Type: ReDIF-Paper 1.0 Title: Jackknife methods for improved cluster–robust inference Abstract: Inferential problems have long been known to exist in finite samples when using the conventional cluster–robust variance estimator for ordinary least squares. Many improvements to inference have been suggested, including bootstrap and jackknife methods, in addition to alternative standard errors and degrees of freedom. This presentation will discuss how to use jackknife methods in Stata for improved inference. We detail the new Stata ado-command, summclust, which offers both improved inferences and diagnostic tools for assessing when conventional errors can be problematic. We also discuss jackknife methods for two different situations: linear models with multiway clustering and nonlinear models with one-way clustering. These alternative methods considerably improve upon the finite-sample overrejection problems. Author-Name: Matthew Webb Author-Workplace-Name: Carleton University Author-Person: pwe297 Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Webb.pdf File-Format: application/pdf File-Function: presentation materials Handle: RePEc:boc:csug23:01 Template-Type: ReDIF-Paper 1.0 Title: Identify latent group structures in panel data: The classifylasso command Abstract: This presentation introduces a new command, classifylasso, that implements the classifier-lasso method to simultaneously identify and estimate unobserved parameter heterogeneity in panel-data models using penalized techniques. I document the functionality of this command, including penalized least-squares estimation of group-specific coefficients and classification of unknown group membership under a certain number of groups; two lasso-type estimators with robust standard errors, namely classifier-lasso and postlasso; and determination of the number of groups based on a BIC-type information criterion. I further introduce postestimation commands to display and visualize the estimation results. Author-Name: Yiru Wang Author-Workplace-Name: University of Pittsburgh Author-Person: pwa962 Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Wang.pdf File-Format: application/pdf File-Function: presentation materials Handle: RePEc:boc:csug23:02 Template-Type: ReDIF-Paper 1.0 Title: Difference in differences with unpoolable data Abstract: In this presentation, we describe a new Stata package called unpooled-DID. This procedure is useful when data from different jurisdictions cannot be combined for analysis because of legal restrictions or confidentiality laws. Through Monte Carlo simulation studies, this procedure has been shown to be equivalent to a variation of the conventional DID model when data are poolable. The canonical DID implicitly assumes that the data for the treated group and the control group can be combined. The combined dataset is used to generate a post and treat dummy variables, which are then interacted to estimate the ATT. We also require “poolable” data to verify parallel trends, a key assumption of DID. As a result, conducting DID analysis is nearly impossible using traditional methods when datasets are not combinable. The problem is pronounced for health economists, for whom legal restrictions in sharing administrative data can constrain DID analysis to learn of health systems. This package will make it easier for researchers who work with “unpoolable” data to conduct DID analysis. Furthermore, the package will also provide researchers with a plausibility check for pretreatment trends. Author-Name: Sunny Karim Author-Workplace-Name: Carleton University Author-Name: Matthew Webb Author-Workplace-Name: Carleton University Author-Person: pwe297 Author-Name: Nicole Austin Author-Workplace-Name: Carleton University Author-Name: Erin Strumpf Author-Workplace-Name: Carleton University Author-Person: pst423 Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Karim.pdf File-Format: application/pdf File-Function: presentation materials Handle: RePEc:boc:csug23:03 Template-Type: ReDIF-Paper 1.0 Title: bivpoisson_ate: A Stata command for average treatment effects estimation with correlated count-valued outcomes Abstract: When we encounter correlated count-valued outcomes y1 in {0,1,...,M} and y2 in {0,1,...,M}, the identification and estimation of average treatment effects (ATEs) need to account for the correlation structure of the data-generating process. As illustrated by Fisher, Terza, and Zhang (2022), the Stata command bivpoisson estimates the deep parameters in count-valued seemingly unrelated regression (count SUR) models. Our model affords greater precision and accuracy in terms of deep parameter estimations in comparison with single-equation Poisson models (by Stata's poisson command). The postestimation command bivpoisson_ate supports the estimation of ATEs in our count SUR model. We provide formulas for the conditional means and the ATEs of outcomes as functions of deep parameter estimates. We show, by MC simulations, that bivpoisson_ate affords greater precision and accuracy in terms of ATEs in comparison with the ATEs estimated using poisson estimated parameters. We allow the treatment variable to be binary, and we plan to extend it to allow count-valued treatment. An example is provided to estimate the ATEs of private insurance status on the numbers of physician office visits and nonphysician health professional office visits within two-week. The user will specify: outcome y1, outcome y2, a policy variable, and a vector of control variables. Author-Name: James Fisher Author-Workplace-Name: Boston University Author-Name: Joseph Terza Author-Workplace-Name: IUPUI Author-Person: pte168 Author-Name: Abbie Zhang Author-Workplace-Name: Boston University Author-Person: pzh1122 Creation-Date: 20230820 Handle: RePEc:boc:csug23:04 Template-Type: ReDIF-Paper 1.0 Title: Fitting interval-censored Cox model with time-varying covariates in Stata Abstract: In survival analysis, interval-censored event-time data occur when the event of interest is not always observed exactly but is known to lie within some time interval. These types of data arise in many areas, including medical, epidemiological, economic, financial, and sociological studies. Ignoring interval-censoring will often lead to biased estimates. A semiparametric Cox proportional hazards regression model is used routinely to analyze uncensored and right-censored event-time data. It is also appealing for interval-censored data because it does not require any parametric assumptions about the baseline hazard function. Also, under the proportional-hazards assumption, the hazard ratios are constant over time. Semiparametric estimation of interval-censored event-time data is challenging because none of the event times are observed exactly. Thus, “semiparametric” modeling of these data often resorted to using spline methods or piecewise-exponential models for the baseline hazard function. Genuine semiparametric modeling of interval-censored event-time data was not available until recent methodological advances, which are implemented in the stintcox command. In this presentation, I will describe two basic formats for interval-censored data and will demonstrate how to fit the Cox model to these data using Stata's stintcox command. I will then demonstrate how to create time-varying covariates (TVCs) automatically using the stintcox command and how to use TVCs to test the proportional-hazards assumption. Last but not least, I will show how to incorporate TVCs in your predictions and plots of survivor and other functions. Author-Name: Xiao Yang Author-Workplace-Name: StataCorp Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Yang.pdf File-Format: application/pdf File-Function: presentation materials Handle: RePEc:boc:csug23:05 Template-Type: ReDIF-Paper 1.0 Title: New meta-analysis (MA) features in Stata 18: MA for prevalence and multilevel MA Abstract: Meta-analysis is a statistical technique for combining the results from several similar studies. Stata’s meta command offers full support for meta-analysis—from computing various effect sizes and producing a basic meta-analytic summary to performing tests for small-study effects. Stata 18 introduced support for meta-analysis of one proportion, meaning you can now use standard meta-analysis features such as forest plots and funnel plots with one-sample binary data. Stata 18 also introduced two new commands, meta meregress and meta multilevel, for performing multilevel meta-analysis. These commands allow you to analyze results from multiple studies in which the reported effect sizes are nested within higher-level groupings such as regions or schools. By properly accounting for the dependence among the effect sizes, we can produce more accurate inference. In this presentation, I will demonstrate how to perform meta-analysis of proportions and multilevel meta-analysis in Stata 18. I will provide a brief introduction to meta-analysis and discuss effect sizes and confidence intervals relevant to prevalence data. For multilevel data, we’ll see how to include random intercepts and coefficients at different levels of hierarchy, perform sensitivity analysis, and assess the variability among the effect sizes at different levels of the hierarchy. Author-Name: Gabriela Ortiz Author-Workplace-Name: StataCorp Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Ortiz.pdf File-Format: application/pdf File-Function: presentation materials Handle: RePEc:boc:csug23:06 Template-Type: ReDIF-Paper 1.0 Title: The effects of women's bargaining power on contraceptive use: Evidence from Zambia Abstract: This presentation aims to examine the relationship between women's household bargaining power and their adoption of modern contraception in Zambia, using the 2018 DHS survey data. Relying on direct measures of women's bargaining power (as indicated by the preexisting literature), which include a woman's ability to make decisions about her own healthcare, large household purchases, small household purchases, visits to her family and friends, and contraceptive use, as well as measures of her autonomous financial capability. This measure of financial capability is then interacted with a woman's ability to make healthcare decisions solely or jointly with her husband to shed additional light on the influence that bargaining power has on the uptake of modern contraceptive methods. Having both financial capability and the sole ability to make healthcare decisions for herself increases a woman's probability of adopting modern contraceptive methods by 87%, and having sole responsibility over contraceptive decisions increases it by approximately 56%. Using lasso as a robustness check, it is determined that the model is relatively well specified and has quite a large amount of explanatory power. Finally, the presentation uses a comparative analysis of spousal discord to demonstrate how spouses' often conflicting reports of intrahousehold decision making can impact key outcomes for women and finds that both spousal accord and the scenario in which the woman takes power are most effective for the adoption of modern contraception (leading to a 16.7% and 14.6% increase in the probability of using modern contraception, respectively). Overall, the study finds that several aspects of a woman's household decision making and financial freedom, as well as the degree and directionality of spousal discord within her household impact her probability of adopting modern contraceptive methods. Author-Name: Tamara Pressman Author-Workplace-Name: McGill University Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Pressman.pdf File-Format: application/pdf File-Function: presentation materials Handle: RePEc:boc:csug23:07 Template-Type: ReDIF-Paper 1.0 Title: The role of climate change adaptation in enhancing agricultural yields: Evidence from nonrandomized experiments in Africa Abstract: I examine the effects of climate change adaptation on agricultural productivity using a unique dataset from a nonrandomized experiment involving 1,811 adapted and 3,280 nonadapted farm households across four African countries. By employing 2SLS and simultaneous-equations model estimations, I find that implementing adaptation strategies significantly increases crop yields by 281.1 kilograms per hectare (23.3%). Furthermore, my analysis uncovers that the impacts vary in magnitude depending on the specific adaptation measures, crop varieties, and countries involved. Ultimately, the study highlights that farmers' capacities to adapt are primarily driven by their access to information sources and working capital. Lastly, additional climatic factors beyond rainfall and temperature play a crucial role in crop development. Author-Name: Jean Awé Author-Workplace-Name: University of Sherbrooke Creation-Date: 20230820 Handle: RePEc:boc:csug23:08 Template-Type: ReDIF-Paper 1.0 Title: Behavioral drivers of intentions to use alternatives to cash: An African survey Abstract: Seeking to identify frictions to the possible implementation of CBDCs, I explore potential behavioral drivers for people to use cash or alternative payment methods in retail transactions. I conducted an online survey targeting adults in sub-Saharan Africa, a continent characterized by lower levels of banking penetration, intensive use of cash, and popularity of mobile money accounts to overcome financial exclusion. I obtained robust evidence that the affect heuristic is the only relevant behavioral trait against the use of cash and of credit cards. This adds to criticisms of behavioral finance for frequently neglecting emotional drivers. Cognitive traits, such as mental accounting, fungibility bias, and habit do not mediate in the overall preference but in which contexts people prefer to use one payment method or another. I find no behavioral drivers against the use of electronic payments but robust evidence that higher per capita income reduces their preference. All results are robust to alternative econometric specifications: multinomial logistic, ordered logistic, and logit regressions. My research provides a clear message for policy making: authorities might better favor ensuring that a wide variety of payment alternatives are available for people to use, including cash, and let them choose. Author-Name: David Peón Author-Workplace-Name: Universidade da Coruna Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Peon.ppsx File-Format: application/x-ms-powerpoint File-Function: presentation materials Handle: RePEc:boc:csug23:09 Template-Type: ReDIF-Paper 1.0 Title: The market for Stata users: Evidence from online job postings Abstract: Using a sample of 110,284 unique online job postings during the hiring period 2010–2022 that mentioned Stata as a requisite or recommended skill, the market for Stata users is examined. Primary focus is given to what other job skills are necessary for Stata users to become hired, be they software skills, soft skills, or general skills. Analyses of these jobs’ wages, required education levels, requisite job experience, titles and industries, and geography are also presented, as are trends in all of these findings. A separate sample of 164,973 worker profiles that mention Stata as a skill is then used to compare the demand and supply sides of this labor market. Results are meant to inform Stata users as to what they can expect on the job market, and perhaps most importantly, what additional skills they should gain to maximize their labor market outcomes or stand out among others competing for the same jobs. Author-Name: Wes Routon Author-Workplace-Name: Georgia Gwinnett College Creation-Date: 20230820 File-URL: http://repec.org/csug2023/Canada23_Routon.pptx File-Format: application/x-ms-powerpoint File-Function: presentation materials Handle: RePEc:boc:csug23:10