Spatiotemporal Visualization and Analysis As a Policy Support Tool
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SPATIOTEMPORAL VISUALIZATION AND ANALYSIS AS A POLICY SUPPORT TOOL: A CASE STUDY OF THE ECONOMIC GEOGRAPHY OF TOBACCO FARMING IN THE PHILIPPINES by Steven Louis Rubinyi A Thesis Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE (GEOGRAPHIC INFORMATION SCIENCE AND TECHNOLOGY) May 2014 Copyright 2014 Steven Louis Rubinyi ii DEDICATION I dedicate this document to my mom and dad for always supporting me in my academic endeavors and encouraging me to stay curious, and explore the world. iii ACKNOWLEDGMENTS I will be forever grateful to my mentor, Professor Karen Kemp. It is safe to say that without her patient guidance and meticulous eye for details, I would not have made it this far. Thank you as well to the South East Asia Tobacco Control Alliance for helping me to acquire necessary research documents and providing feedback on my initial research idea. iv TABLE OF CONTENTS Dedication ii Acknowledgments iii List of Tables vi List of Figures vii List of Abbreviations ix Abstract x Chapter One: Introduction 1 1.1 Project Objectives and Organization 5 Chapter Two: Background 7 2.1 Country Profile 7 2.2 Tobacco in the Philippines 10 2.3. Literature Review 15 2.3.1 Policy and Spatial Analysis 15 2.3.2 Tobacco Geography 19 2.3.3 Spatiotemporal Visualization and Analysis 21 Chapter Three: Data Sources and Preparation 26 3.1 Data Sources 26 3.1.1 Administrative Boundaries 27 3.1.2 Agricultural Data 28 3.1.3 Provincial Areas Data 30 3.1.4 Limitations 30 3.2 Methodology 33 3.2.1 Construction of the Geodatabase 33 3.2.2 Stationary Visualization for Spatiotemporal Analysis 37 3.2.3 Dynamic Visualization for Spatiotemporal Analysis 38 Chapter Four: Results of Spatiotemporal Analysis 40 4.1 Percent Total Provincial Area Devoted to Growing Tobacco 40 4.1.1 Stationary Visualization of Percent Area 41 4.2 Tobacco Volume of Production 44 4.2.1 Stationary Visualization of Volume of Production 44 v 4.2.2 Dynamic Visualization of Volume of Production 47 4.3 Tobacco Farm Gate Prices 55 4.3.1 Stationary Visualization of Farm Gate Prices 56 4.3.2 Comparative Analysis, La Union Province 59 Chapter Five: Discussion 64 5.1 Potential Causes 64 5.1 Key Takeaways 66 Chapter Six: Conclusions 68 References 71 Appendices Appendix A: Percent of Provincial Area Devoted to Growing Tobacco 74 Appendix B: Total Volume of Tobacco Production, Metric Tons 82 Appendix C: Farm Gate Price of Tobacco, Pesos per Kilogram 92 vi LIST OF TABLES Table 1: Summary of Visualization-Based Techniques of Exploratory Spatiotemporal Analysis (from Andrienko et al. 2003) 24 Table 2: NTA and BAS Statistics on Total Production in the Philippines, 2007-2011 (Metric Tons) 31 Table 3: Average Yield in Metric Tons per Hectare 47 vii LIST OF FIGURES Figure 1: Philippines Regions and Provinces 8 Figure 2: Provinces Producing Tobacco at least 1 Year Since 1990 12 Figure 3: Provinces Producing Virginia and/or Native Type Tobacco at least 1 Year Since 2000 13 Figure 4: Volume of Tobacco Production in the Philippines, by Type (Metric Tons) 14 Figure 5: Statistics on Total Tobacco Production in the Philippines, 1990-2012 (Metric Tons) 32 Figure 6: Portion of Attribute Table for GADM Provincial Administrative Boundaries 35 Figure 7: Portion of Joined Excel Files from CountrySTAT with Added ID_1 Field 36 Figure 8: Percent of Total Provincial Area of Selected Provinces Devoted to Growing Tobacco, All Types 42 Figure 9: Total Volume of Tobacco Production in Metric Tons, All Types 45 Figure 10: The Philippines’ Mean Center and Focus Areas of the Mean Centers of Each Type of Tobacco 48 Figure 11: Centers of Total Production by Year for Each Tobacco Type 49 Figure 12: Center of Total Tobacco Production by Year, All Types 51 Figure 13: Center of Total Tobacco Production by Year, Native Type 52 Figure 14: Total Volume of Production for Native Type Tobacco (Metric Tons) 53 Figure 15: Center of Total Tobacco Production by Year, Virginia Type 54 viii Figure 16: Total Volume of Production for Virginia Type Tobacco (Metric Tons) 55 Figure 17: Native, Virginia, and Burley Type Farm Gate Prices for Select Provinces (Pesos per Kilogram) 58 Figure 18: Farm Gate Prices for La Union Province (Pesos per Kilogram) 60 Figure 19: Percent of La Union Province Total Area Devoted to Tobacco Farming 61 Figure 20: Total Volume of Production for La Union Province (Metric Tons) 62 Figure 21: All Tobacco Types (Appendix A) 74 Figure 22: Native Tobacco Type (Appendix A) 78 Figure 23: Virginia Tobacco Type (Appendix A) 80 Figure 24: All Tobacco Types (Appendix B) 82 Figure 25: Native Tobacco Type (Appendix B) 86 Figure 26: Virginia Tobacco Type (Appendix B) 89 Figure 27: Native Tobacco Type (Appendix C) 92 Figure 28: Virginia Tobacco Type (Appendix C) 96 Figure 29: Burley Tobacco Type (Appendix C) 100 ix LIST OF ABBREVIATIONS ASEAN Association of Southeast Asian Nations FCTC 2003 WHO Framework Convention on Tobacco Control GADM Database of Global Administrative Layers GAUL Global Administrative Unit Layers GDP Gross Domestic Product GIS Geographic Information Systems NRCCW National Resource Center for Information Technology in Child Welfare NTA National Tobacco Administration PSA Philippine Statistics Authority SEATCA Southeast Asia Tobacco Control Alliance SQL Structured Query Language UNSALB United Nations Administrative Level Boundaries Dataset USC University of Southern California USD United States Dollar VAT Value Added Tax WHO World Health Organization x ABSTRACT This study demonstrates the utility of visualization-based spatiotemporal analysis as a policy support tool in the agricultural sector through a case study analyzing changes in the spatial distribution of tobacco farming in the Philippines from 1990 through 2012. Tobacco farming remains divisive in the Philippines; although often touted by tobacco companies and supportive government agencies as integral to the Philippine economy and an effective crop for poverty alleviation, recent studies dismiss these claims altogether, suggesting that farmers would be better off diversifying or even switching crops altogether (SEATCA 2008; Espino et al. 2009; World Health Organization 2012). This study does not argue for or against tobacco farming; it simply illustrates how spatiotemporal analysis can be successfully implemented to uncover deeper, more nuanced insights that could be drawn upon to design efficient and effective tobacco farming policies. The analysis considers provincial level agricultural data from the Philippines Bureau of Agricultural Statistics for tobacco area planted, volume of production and farm gate pricing of three unique tobacco varieties: Native, Virginia, and Burley. Stationary and dynamic techniques of spatiotemporal data visualization are used, and data are analyzed for trends using outlined methods. The results holistically describe tobacco farming in the Philippines and are drawn upon to determine which tobacco growing provinces and types of tobacco are on the rise or decline, to investigate causation behind spikes and dips in production, and to outline the future direction of the industry as a whole. The spatiotemporal analysis provides empirical evidence for policy makers to better understand regional and provincial trends in tobacco farming over time. 1 CHAPTER 1: INTRODUCTION The negative health implications of tobacco use are well documented, with one in 10 adults killed by smoking worldwide according to the World Bank. Historically, the smoking epidemic primarily affected rich countries, however by 2020 it is expected that seven out of 10 smoking related deaths will be in low-income and middle-income countries (World Bank 1999). Although there is no single panacea to reducing demand for tobacco, increasing the price to consumers combined with innovative public health education campaigns and government restrictions on marketing and packaging, have recorded fair success at reducing consumption, particularly in high-income countries (SEATCA 2008). Still, as transnational tobacco companies continue to expand aggressively, both production and consumption have steadily increased in the Association of Southeast Asian Nations (ASEAN) region. The 2003 WHO Framework Convention on Tobacco Control (FCTC), developed in response to the globalization of the tobacco epidemic, asserts the importance of addressing both tobacco supply-side issues and demand reduction in an attempt to structure global regulatory policy. It is within this framework that governments in ASEAN have increasingly implemented policies and programs to combat tobacco demand, primarily through strategy dependent on a combination of price and tax measures with non-price measures. As stated in the FCTC, one of the main tools for reducing consumption while simultaneously raising funds for valuable government programs is the successful implementation of a tobacco tax, often a combination of excise tax, value added tax (VAT), import tariffs, and other inventive measures. Every country in ASEAN has some 2 form of tobacco tax burden, ranging from 16 percent of retail price in Lao PDR to 70 percent of retail price in Thailand (SEATCA 2013). The Philippines sits relatively in the middle of the pack, with a tax burden of 53 percent of retail price. A new excise tax regime was approved by the Philippines government in 2012, leading Phillip Morris, with a market share of 79.3%, to implement price increases of 30% to 75%. A 2014 study by Citi Research shows just how effective a strong excise tax can be. In 2013, after the excise tax was bolstered under Republic Act No. 10351, tobacco sales volumes declined by 15.6% in the Philippines, a notable reversal from the 3.5% compound annual growth rate experienced from 2007-2012. Although revenue from tobacco taxes in ASEAN exceeded USD 13 billion in 2011, healthcare costs remain far greater, up to 13.7 times the cumulative tax revenue in some instances.