SPACE (ha!) still available:
Newly Expanded! Spatial-Econometrics Workshop, July 19-30, 10a-2p (US Eastern Time), Online/Virtual/Remote synchronous + recorded for asynchronous (re)viewing.
Please direct any & all questions about the spatial-econometrics workshop to me, Rob, at [log in to unmask] <mailto:[log in to unmask]> . And feel free, encouraged even, to recirculate the below widely throughout your networks.
While I will miss working with this year’s cohort in person, there are some upsides perhaps for scholars who may be considering it. No travel & lodging costs if they’re outside of Ann Arbor, and the online instruction will be live and also recorded for asynchronous viewing (to accommodate time-zone variation, e.g.) and therefore also accessible for later reviewing (at least for some period after the workshop ends). And, as always, participants in my workshops will retain access to all materials from the workshop—slides, notes, readings, & labs—and email access to me if I can be of future assistance, in perpetuity. My experience with online teaching of statistical methods in two ICPSR workshops last summer and with undergrads this past Fall semester here at UMich has also revealed, perhaps surprisingly, that teaching statistical methods can work extremely well in this modality. (In fact, I intend to retain most of its features when we return to in-person instruction this Fall here in Ann Arbor.)
The NEW & EXPANDED* 2021 Workshop...
Spatial Econometrics: Empirical Analysis of Geospatial Association and Cross-Unit Interdependence
Robert J. Franzese, Jr. (please direct any & all questions about the workshop to [log in to unmask] <mailto:[log in to unmask]> )
...teaches empirical methods for modeling, for estimating, and for the interpretation of spatial or cross-unit clustering or interdependence (a.k.a., contagion/diffusion/spillover/network-dependence...).
*Now with more intro to models and methods for spatial or geospatial clustering or heterogeneity (as opposed to contagion/interdependence) and distinguishing between the alternate sources of spatial association (common exposure, contagion, network selection). (This year's version extends further upon the expansions in these directions already implemented in 2020.)
Applied (computer-lab) sessions and exercises are bilingual, i.e. with lab scripts in Stata and R both available, and students are of course welcome to use other software as they prefer.
REGISTRATION: The Short Workshop course-list and registration portal is: https://myumi.ch/2DgeB.
DISCOUNTS:
1. Individuals currently affiliated with an ICPSR member institution receive a discount on their registration fees.
2. Discount for Returning ICPSR Summer Program Participants: If you participated in a previous ICPSR Summer Program, you will receive a 15% discount on your registration fee in this year's ICPSR Summer Program.
Here is the full workshop description:
Spatial Econometrics: Empirical Analysis of Geospatial Association and Cross-Unit Interdependence
19-30 July 2021, 10am-2pm Eastern, VIRTUAL (Synchronous & Recorded for Asynchronous)
PLEASE DO EMAIL ([log in to unmask] <mailto:[log in to unmask]> ) with any & all questions
Spatial (i.e., geospatial or otherwise cross-unit) association and interdependence are ubiquitous throughout the social sciences, and beyond. That is, events or outcomes in one observational unit are almost always related to similar occurrences in other observational units. This is so for such diverse phenomena as disturbances and conflicts within and between nations; crime, health, and environmental outcomes; economic and other policies in political jurisdictions; consumer, investor, and producer choices in markets; individuals’ opinions and behavior in societies; and voting by citizens in elections or by legislators in legislatures. In contexts where this omnipresent cross-unit association (or correlation) arises from interdependence (or contagion), "standard" statistical methods (which assume independent observations) are inappropriate, and design-based methods of "nonparametric causal-inference" are (at best) inadequate. This workshop introduces strategies appropriate for identifying and estimating spatial processes, distinguishing spatial association from spatial interdependence, and for proper estimation and interpretation of processes involving interdependent observations, emphasizing spatial and spatiotemporal models of interdependent (contagious) continuous and limited outcomes.
The core aim of the workshop is to demonstrate how such spatial, i.e. geo-spatial or otherwise cross-unit, interdependence can be incorporated into empirical analysis most productively. Participants will learn how to: diagnose spatial-correlation patterns; estimate spatial-regression models; distinguish between different sources of spatial correlation (common exposure, contagion, and selection); and calculate and present the spatial and spatiotemporal effects that empirical models which incorporate interdependence imply. Methods to be covered—from specification and estimation of spatial models to inference and interpretation of spatial effects—include:
• measures and tests of spatial association (Moran’s I, etc.);
• models and methods for (exogenous) spatial correlation and spatial heterogeneity (e.g., geographically weighted regression (GWR), spatial-hierarchical random-component or multi-level models (S-MLM, and spatially lagged regressor (SLX) or error models(SEM));
• instrumental-variable and maximum-likelihood estimators for models with (endogenous) spatial interdependence (spatially lagged dependent-variable models (SAR));
• multiple-source (SLX, SEM, SAR) and multiple-lag (multiple ‘W’) spatial models;
• spatial interdependence in models with limited and qualitative dependent-variables; and
• models for coevolutionary processes (i.e., processes with both spatial-cum-network interdependence and endogenous-connectivity/network-selection).
Prerequisites: None; although participants should be familiar with linear regression and models for qualitative/limited dependent variables (e.g., logit, probit, etc.), this workshop does not assume any prior knowledge of, or experience with, spatial statistics. Indeed, all necessary mathematical, statistical, geospatial-analytic, and spatial-econometric background will be reviewed as needed, albeit (obviously) very quickly.
Best regards,
And again: email any & all questions to
Rob ([log in to unmask] <mailto:[log in to unmask]> )
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Robert (Rob) J. Franzese, Jr.
Professor & Associate Chair, Department of Political Science,
College of Literature, Science, & the Arts (5755 Haven Hall)
Director, Program in International & Comparative Studies,
International Institute (333 Weiser Hall)
Research Professor, Center for Political Studies,
Institute for Social Research (4256 I.S.R.)
The University of Michigan, Ann Arbor
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Fellow & 15th (ex)President, The Society for Political Methodology
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phone: 1-734-936-1850 http://www-personal.umich.edu/~franzese
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