Continuing Professional Education on Data Analytics and Spatial Econometrics
Date: 22 - 25 July 2019
Time: 0830 - 1730
Venue: De La Salle University - Manila
Fee*: USD550 (Php28600 at Php52/USD) until July 15, 2019
USD650 (Php33,800 at Php52/USD)
Endorsed by the Philippine Economic Society (PES).
*inclusive of 3 meals per training day, tuition, training materials, airport pick up and drop off services in Manila
As one of the country’s top and most reputable institutions of higher learning, DLSU takes part in promoting scholarship by involving promising young researchers from frontline government agencies and various universities. The School of Economics (SOE) supports this and commits to make a significant contribution to economic science and inquiry in addressing developmental needs by bringing participants from Southeast Asia (SEA) and East Asia (EA) together. With this goal, SOE has started to organize summer training programs since 2015. For summer 2019, SOE plans to hold a series of high level lectures and focused discussions. The intensive course, to be delivered by a select group of experts, is an introduction to spatial data with spatial econometrics as a method for spatial data analysis, moving beyond traditional methods.
This course calls for young researchers, graduate students (M.S. and Ph.D) and faculty who are strongly committed to the use of statistical methods applied to spatial data and preferably have: at least completed 24 units from graduate school (Masters in Economics, Development Economics or other relevant social science field, with research or program management experience) basic knowledge in Stata or R; algebra operations; multiple regression analysis; statistical inference principles (probability distributions, random variables and hypothesis tests)
Day 1: Introduction to Spatial Data Science, Spatial Statistics and Spatial Interdependence
This introductory seminar provides an overview of the uses of spatial econometric models in the economics and social sciences, and discusses how these models get us closer to our causal models of interdependent outcomes. This will also explore strategies for determining the appropriate patterns of interconnectedness, geographic patterns of interdependence, and other means of identifying how neighboring units are socially, politically and economically interdependent.
Day 2: Specification of the spatial interdependence
There are a variety of models in the broad family of spatial econometrics, and a useful categorization divides the spatially interdependent processes based on whether the spatial interdependence occurs in the observables, unobservables and/or outcomes. Most theories provide some insight that guides this decision; a range of tests can assert whether the theory is supported or not. This lecture introduces a series of tests that will detect different patterns of spatial interdependence. Moreover, it will explore how to connect the causal relationships in one’s theory to some basic spatial econometric models including the spatial lag, spatial error and spatial-X models.
Day 3: Estimating spatial econometric models
This lecture will discuss issues of model specification that are unique to these models; this includes correctly specifying the manner in which the units (i.e., individuals, states, countries, etc) are spatially related, and whether the spatial interdependence occurs among variables, the errors, or the outcome itself. A variety of techniques used to estimate spatial econometric models including OLS, MLE and two-stage least squares will also be explored.
Day 4: Visualizing and depicting spatial interdependence
This lecture demonstrates how to calculate and provide visual depictions of substantive effects from a variety of spatial econometric models. It will introduce graphical and tabular techniques to provide meaningful quantities of interest from these models. Students are encouraged to develop their own research questions about spatial processes and to bring their own data sets. In the afternoon sessions, students will use Stata and R to apply the concepts discussed in the lectures to their own research questions.
Profile of the Lecturers:
GIANFRANCO PIRAS, PhD
Associate Professor, Economics, The Catholic University of America
Dr. Gianfranco Piras is an associate professor of economics at The Catholic University of America. Formerly, he was a research assistant professor at the Regional Research Institute at West Virginia University. He has also spent time at various institutions including the Department of City and Regional Planning at Cornell University, the Regional Economic Application Laboratory at the University of Illinois at Urbana-Champaign, and at the GeoDa center at Arizona State University. He held a position of assistant professor at the Universidad Catolica del Norte in Chile. Dr. Piras is a member of the editorial board of Letters of Spatial and Resource Sciences. He teaches in the area of applied econometrics. Dr. Piras’ research interests include spatial econometrics and statistics, urban and regional economics, computational methods and software development. He is one of the developers of the R software for statistical computing and he is currently working on two main libraries, for the estimation of spatial panel data models (splm), and for the application of GM methods in spatial econometrics (sphet). He has been involved in many research projects and he acted as a consultant for various organizations.
LAWRENCE DACUYCUY, PhD
Full Professor and Research Fellow, DLSU-School of Economics
President, Philippine Economic Society
Dr. Lawrence Dacuycuy is a Full Professor and former Dean at the School of Economics (SOE) and Research Fellow at De La Salle University - Manila. He is the current president of the Philippine Economic Society and sits as a member of the Commission on Higher Education’s Technical Committee for Economics. He finished his BS Economics in 1998 at the School of Economics, University of the Philippines and two years thereafter, he received his Master of Science in Economics degree from the same university. He obtained his doctorate in economics from Kyoto University in 2006. His research focuses on applied nonparametric and semiparametric econometrics, theoretical migration, labor economics, and macroeconomic modelling. He was part of research teams organized by the DLSU - Angelo King Institute and commissioned by the ASEAN Secretariat to study the role and functions of the banking sector, credit rating agencies and securitization markets. In 2009, he was one of the recipients of the National Academy of Science and Technology's (NAST) Outstanding Young Scientist (OYS) award. In 2012, he was a recipient of the NAST Outstanding Scientific Paper Award for his research on wage functional analysis. His current research focuses on fiscal policy and related issues using Dynamic Stochastic General Equilibrium (DSGE) models.
De La Salle University - Manila
2401 Taft Avenue
Malate, Manila, Philippines
*near Vito Cruz LRT Station