DEPARTMENT OF GEOGRAPHY GEOMATICSAND ENVIRONMENT UTM University of Toronto GGR 252HS – RETAIL GEOGRAPHY (Winter 2023 – Prof. Swales) ASSIGNMENT TWO (25%) THE GEOGRAPHY OF MARKET DEMAND This assignment addresses market demand in census tract neighbourhoods in the Toronto Census Metropolitan Area (CMA). You will first collect and present demographic data on two census tracts. Then you will compare and contrast the two census tract neighbourhoods. Finally, you will briefly identify census variables from your own neighbourhood. Before you begin, read textbook chapters seven and eight on the geography of demand. Also consult the appendices in the textbook. Appendix A gives detailed instructions on how to retrieve census data from the Statistics Canada website using your postal code. Appendix B presents many of the census variables available. Appendix C shows the kinds of goods and services purchased by households in Canada. We are using 2016 census data. Read ALL of this assignment and relevant parts of the textbook before you proceed and BEFORE you ask questions. PART A: Data collection Select a pair of census tract neighbourhoods according to the following schedule: • First letter of your surname (last name) A-H: census tracts 5350086.00 & 5350576.16 • First letter of your surname (last name) I-O: census tracts 5350413.02 & 5350265.00 • First letter of your surname (last name) P-Z: census tracts & 5350065.02 & 5350601.00 Retrieve the Statistics Canada 2016 Census Profiles for your two assigned neighbourhoods (see Appendix A in the textbook for instructions). Begin by searching for one of the Census Tracts by ‘Geographic code’ (your first census tract number above). This will generate a table for your census tract (on the left) plus a comparative benchmark such as the CMA beside it. Note there is an option to ‘Change geography’. Click on ‘Change geography’ under the benchmark data (usually the CMA) and under ‘Geographic code’ type in your second assigned census tract number. When you have retrieved the data for both your census tracts note that there are hundreds of variables. You have several options to rationalise your search. For example, at ‘Topic:’ there is a drop-down menu where you can pick the variables from various themes such as ‘All data’, ‘Population’, ‘Ethnic origin’, ‘Income’ etc. (see below). There is also an option to get ‘Rates’ rather than ‘Counts’ which will be handy for some of the data you have to retrieve. After each selection be sure to hit the ‘Submit’ button to apply your selection. You also have options to download the data and map the census tract. A further option is to get selected charts (graphs) that Statistics Canada have already created: Charts (using rates) Using these various options, study the census data for your two census tracts. Part B: Data presentation Present selected charts (graphs) and a table of data as follows. Table. Using the data from the census tables you have retrieved create your own table that shows for both census tracts the following selected variables: Population 2016; Population change 2011-2016 (%); Population density per km sq.; % Male; % Female (calculate this from counts); Population by major age groups (% 0-14 yrs., %15-64 yrs., % 65 yrs. and over); Average age of the population; Average household size; 1 person households (count & %); Average household income; Household income – $200,000 or more; Prevalence of low income (%); Average value of dwellings ($); Total visible minority population (%); No certificate, diploma or degree (%); Marital status – Not married and not living common law (count). Also from the ‘COVID-19- Relevant indicators (use the drop-down menu) identify two variables. [Note: selected variables for three of the census tracts above are already available at the end of Chapters 7 and 8 in the textbook.] Charts (graphs). From the option retrieve the following graphs and include them in your assignment: ‘Age groups – 100% data, both sexes’; ‘Ethnic origin for the population in private households – 25% sample data, both sexes’; ‘Occupied private dwellings by structural type of dwelling – 100% data’; ‘Household total income groups in 2015 for private households – 100% data’. Ensure that both census tracts are on the same graph for each variable to enable direct comparison. Examples of these graphs, using the Toronto CMA and City of Toronto rather than pairs of census tracts, are included with this assignment below. Keep these four graphs and the table to no more than two pages in your assignment. Give the table and graphs (charts) numbers and appropriate titles. You can copy the charts (graphs) from the Statistics Canada website by using Techsmith Snagit or screenshots (or some other capture software if you have it). If using screenshots, enable full screen first (right-click on the graph to get a menu). As a UofT student you can download Techsmith Snagit free from student resources. When using Snagit: use the ‘Image’ and ‘Region’ options; click ‘Capture’ and pull out a region over the graph you want to copy. Right-click the resulting image, select copy and then paste into your document. You will likely have to reduce the size of each graph to fit all four and the table on two pages – right-click the image of the graph in your document to get the ‘Size and position’ menu. Part C: Discussion Using the information you have collected, compare and contrast the two census tract neighbourhoods. Are there ways in which the variables are related? To what extent do the variables combine together to produce a distinctive market area? Identify one more variable for each neighbourhood (so, two variables in total) that you think is distinctive. Give the value for each variable and say why you think it is distinctive in each particular neighbourhood. Part D: Selected variables for your home census tract Use your postal code to find your home census tract as per the instructions in the appendix of the textbook. Identify which of the two census tracts you studied in Part A above differs most to your home census tract. Present two census variables that effectively illustrate how your home census tract differs from your selected census tract from Part A. Provide the data for both your home census tract and the selected census tract from Part A. If you do not live in Canada or your home census tract happens to be one of the census tracts you studied in Part A use the university census tract found using the postal code M5S 3G4. The written component of this assignment (exclusive of graphs and table) should be approximately 5 type-written pages (but it is possible to do a good job in less). Use 12-point font, double spaced. Do not exceed six pages. DUE DATE: Your assignment must be submitted in Quercus by 11:59 pm, March 15 (Eastern Standard Time). The file name that you upload should include your name and student number. Late penalties apply. Late penalty as per department policy: 10% per day. Academic Misconduct: Do not cheat. Read carefully the guidelines on academic misconduct: http://www.artsci.utoronto.ca/osai/The-rules/what-is-academic-misconduct. It is essential that you avoid plagiarism and consequential penalties including failing the course. Otherwise, have a productive and enjoyable experience with this assignment. ———— Selected graphs (charts) from Statistics Canada 2016 Census Profiles Note that here we are using the Toronto CMA and City of Toronto rather than the census tracts you are directed to retrieve in this assignment. These graphs may be useful benchmarks for comparative purposes. http://www.artsci.utoronto.ca/osai/The-rules/what-is-academic-misconduct Source: Statistics Canada 2016 Census Profiles (2017) Prof. Stephen Swales Skip to main content PREVIOUS NEXT Chapters Chapter Seven: The Geography of Demand — Basic Demographics — Choose Page — GO Chapter Seven: The Geography of Demand — Basic Demographics       Learning objectives Know the basic demographic components of demand (the market) and how they vary spatially. Appreciate that population (demand) is concentrated in relatively few places. Consider how basic demographics can impact the provision of private and public services. Identify the associations between market variables. Be curious about how population (market) components vary widely from place to place.       7.1 Introduction “How do we usefully describe the demographic composition and geographical distribution of a population?”   Many factors impact demand for goods and services, including: prices of goods, inflation, government policies, perception by consumers of economic prospects, and, most importantly from our perspective, the composition and expenditures of populations. All vary geographically.   Generally, higher prices of goods and services are associated with lower demand.  Higher inflation is also usually associated with lower demand. Government policies impact the amount of money available for consumption through taxes; and also impact the types of goods and services consumed through the identification of merit goods such as health services and exercise, and non-merit goods such as tobacco and alcohol (which are heavily taxed). Pessimistic perspectives on economic prospects tend to make consumers cautious and reduce demand.   Our focus initially will be on demographic composition and how it shapes consumption of goods and services.   Populations vary significantly in their demographic composition, including obvious things such as population size, sex, age, and household size, but also in ethnicity, socio-economic status, and mobility (see Figure 7.1). These characteristics also vary spatially with distinctive distribution patterns at the regional, urban, and neighbourhood scales. This is of interest academically, but also of practical utility if your objective is to reach consumers of goods and services. Demand (or the market) for goods and services varies by the composition of the population and also geographically. Where are the very old and very young populations who will be most in need of medical services? Where are the high-income populations with high expenditures who will find a new upscale retail chain appealing? Where are the recent immigrant populations that may require English as a second language (ESL) courses? How does the mode of transportation-to-work vary with proximity to downtown and how can this inform public transit provision?   Moreover, we may be interested in the combination of variables leading to more sophisticated geodemographic analysis. Where are the high-income, professional millennial populations? Where are the low-income recent immigrants with a nonofficial language mother tongue? Where are high-income Italian families? Where are high-income Chinese singles? Think about what goods and services these populations would need or find appealing.   Demographic variables are also often strongly associated with each other and in space. For example, if an area is mostly older in population composition, it will also be mostly female. Clusters of high-rise developments are often mostly female in composition. Dwellings of five stories or more are likely to be composed of smaller households. Outer-suburban single-detached dwellings are strongly associated with the automobile as a mode of transportation. If a population is highly educated, it will also have a high income.   It is important to keep in mind sources of demographic data. The census is an obvious very comprehensive data source, but others include expenditure data, occasional specific-theme surveys (such as Internet use and the digital economy), taxfiler data, and the increasing volume of data collected by private and public sector organisations such as retail chains and hospitals. The appendices of this book contain actual examples of these data.   Figure 7.1 Demographic characteristics that inform the demand for public and private goods and services     7.2 Basic demographics The most basic questions we ask about any population, regardless of the endeavour or enterprise, are how many people are they, where are they located, at what density, and what is the age and sex composition? These are the basic demographic characteristics. We could add to these family and household composition and dwelling characteristics. It is quite obvious that these are relevant regardless of the purpose of the exercise, but are particularly pertinent questions when the objective is to provide goods and services to a population.     7.2.1 How many and where? “Many people in few places.” Canada is a vast country geographically but relatively few places contain most of the population. The concentration of the population is noteworthy because it will have significant implications for the logistics of supplying goods and services in both the private and public sectors.   There are only 35 large places — Census Metropolitan Areas (CMAs) — in Canada (see Table 7.1). A CMA must have 100,000 or more people and it is evident from the table that they vary significantly in size, with Toronto easily the largest in 2016 at just under six million people. There are only six “millionaire” cities; that is, those with at least one million people: Toronto, Montreal (4.1 m), Vancouver (2.5 m), Calgary (1.4 m), and Ottawa-Gatineau and Edmonton (both approximately 1.3 m).   Although Canada is a northern country with distinctive northern characteristics, most of the population is very southern in its orientation located within a couple of hours of the U.S. border. The only large city distant from the border is Edmonton