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NaDiMa Dialogue #11 | Economics of Climate Change: Application of Spatial Econometric Techniques with R | 9 & 11 August
Agenda
In the real world of empirical economics research, we meet violation of conventional assumptions of statistical and econometrics models. One of these assumptions which can be violated due to geographical (spatial) reasons is the independency of observations. There are many sources of spatial dependency between observations which should be dealt with. The sources of these spatial spill-overs between observations are different and includes inter-regional flows of knowledge, cluster or agglomeration of trade or production, and/or unobserved heterogeneity due to regional/ administrative differences. Some other sources for this spatial dependency are the geostatistical variables such as rainfall, temperature, hydrological, hydrogeological and other similar variables that are considered in the empirical economic models. The spatial dependency could have multi facet at the same time. Therefore, dealing with this spatial dependency is a key issue for better estimation of empirical models. In this regard, we need to relax the conventional assumption of independent observations in a cross-sectional (or panel) setting. Therefore, we need to provide a parsimonious way to specify structure for the dependence between the n observational units. Spatial econometrics helps us to deal with such empirical issues.
The course will start by providing a discussion in the modelling of spatial distribution by developing spatial weights matrix. Special attention is paid to the various approaches that are eligible to model the arrangement of spatial units in space (e.g., weights based on nearest neighbours, distances). Next, the course proceeds by providing an overview of spatial econometric models based on cross-sectional data. Several of these spatial model specifications and its corresponding estimators will be discussed, and interpretation of spatial spill-over results are provided using various empirical datasets. The R statistical software will be used to establish the simple spatial models and participants are encouraged to work with data and create simple spatial regressions and interpret the results.
Day 1 (9 August)
• Introduction
- Spatial variables
- Spatial data analysis
- The basics of spatial econometrics
• Spatial models
- Spatial weight matrix
- Test of spatial dependency
- Spatial econometric models
• Spatial econometric models with R
- Basics of R
- Spatial data in R
- Latitude, longitude and UTM
- Spatial regressions with R with examples
- Spatial plots
• Exercise distribution
Day 2 (11 August)
• Presentations and discussion of the results by participants
- Group 1- 4
- Discussion/ Q&A
• A case study with spatial data by trainer
• Schools of thoughts in spatial econometrics
• Latest developments in spatial econometrics (if time left)
• Final Discussion / Q&A (if time left)Speakers
Introduction:
Prof. Dr. Mohammad Reza Farzanegan, Philipps-Universität Marburg, CNMS & FB02Prof. Dr. Mohammad Farzanegan is Professor of Economics of the Middle East at Center for Near and Middle Eastern Studies (CNMS) & School of Business and Economics at Philipps-Universität Marburg. He is project leader of NaDiMa.
Workshop Instructor:
Tinoush Jamali Jaghdani, PhD, Research Associate at Leibniz Institute of Agricultural Development in Transition Economies (IAMO)Tinoush Jamali Jaghdani, PhD, has joined Leibniz Institute of Agricultural Development in Transition Economies (IAMO) as Research Associate in October 2016. Since then his research are mainly focused on Russian and EU food supply chains. From 2012 until 2017, he worked as Postdoc Fellow at the University of Göttingen, Germany, in the projects ULYSSES (on food price volatility) and AgriCareerNet (online teaching of trade in agriculture). In this period, he was responsible for teaching world agricultural market and trade in Göttingen University and Talca University (Chile) and food price volatility in Göttingen. Before that, he has worked as consultant for the private sector and the World Bank in Iran (2001-2004) and for FAO in Turkey (2015). He has received his PhD in agricultural economics from the University of Göttingen, Faculty of Agricultural Sciences (and minor in applied statistics from the Faculty of Mathematics) in 2012. In Göttingen, he also did his MSc. in socioeconomics of rural development in 2007. His BSc. in agricultural economics, which he received from Tehran University, Iran, in 2001. Up to now, the focus of Dr. Jamali’s research lies on water economics, food price volatility, food supply chains and food trade.
Target Audience and Prerequisites
Target Audience: Master & PhD students from the fields of Economics, Agricultural Economics, Disaster Management, Human Geography, Urban Engineering and similar fields
Prerequisites: Basic knowledge of regression methods and statistical analysis in R
Please contact us in case of any questions about the prerequisites.Registration and Technical Requirements
Time and Place: 09 August 2021, 09:00 am - 3:00 pm (CET), and 11 August 2021, 09:00 am - 3:00 pm (CET), Online via Adobe Connect
How to join: Click here to register for the event.
Please note! This is a 2-day event. Please only register if you aim to participate in both days.
Platform: We use Adobe Connect for the NaDiMa Dialogue Series. It can be accessed via browser or desktop app. Meeting Applications for Adobe Connect can be downloaded here.
Instructions and Technical Requirements for Participants:
Quick Start Guide for Participants
How to be a Participant in Adobe Connect (YouTube)Poster
Workshop Materials