Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

Enhanced Polyetherimide (PEI) Market Outlook

The global Enhanced Polyetherimide (PEI) market size is projected to grow from USD 800 million in 2023 to USD 1.7 billion by 2032, exhibiting a CAGR of 9%. This substantial growth is driven by various factors, including the increasing demand for high-performance polymers in various industries and the superior properties of PEI such as high-temperature resistance, excellent electrical insulation, and chemical resistance. PEI's adaptability in multiple forms and applications further propels its market growth.

One of the primary growth factors for the Enhanced PEI market is its extensive usage in the automotive and aerospace sectors. The need for lightweight, durable, and high-temperature resistant materials in these industries has made PEI a material of choice. The automotive industry, in particular, aims to produce fuel-efficient and lightweight vehicles, which is driving the increased usage of PEI. Similarly, the aerospace sector's stringent requirements for materials that withstand extreme conditions without compromising strength make PEI highly valuable. Furthermore, the rise in electric vehicles, which require superior electrical insulation, is expected to boost the market further.

Additionally, the expanding medical industry is significantly contributing to the market's growth. PEI's biocompatibility and resistance to sterilization processes make it suitable for various medical devices and components. With the increasing focus on healthcare and the rise in medical procedures, the demand for advanced materials like PEI is expected to rise. The growing geriatric population and an increase in chronic diseases are also factors boosting the medical devices market, thereby driving the demand for PEI.

The electronics industry also plays a pivotal role in the growth of the Enhanced PEI market. The need for miniaturization and high-performance electronic components requires materials that can perform under high stress and temperatures. PEI's excellent electrical insulation properties and its ability to be molded into intricate shapes make it ideal for electronics applications. The rapid advancement in consumer electronics, coupled with the growth of the telecommunications sector, is further propelling the market growth.

Pa Engineering Plastics play a crucial role in the development and enhancement of materials like Enhanced Polyetherimide (PEI). These engineering plastics are known for their exceptional mechanical properties, including high strength and rigidity, which make them suitable for demanding applications. The integration of Pa Engineering Plastics in the production of PEI enhances its performance characteristics, making it a preferred choice in industries such as automotive, aerospace, and electronics. The ability to withstand high temperatures and harsh environmental conditions further underscores the importance of Pa Engineering Plastics in advancing PEI's applications. As industries continue to seek materials that offer both durability and versatility, the role of Pa Engineering Plastics becomes increasingly significant in driving innovation and market growth.

Regionally, the Asia Pacific region is expected to witness the highest growth rate. This can be attributed to the rapid industrialization and urbanization in countries like China and India. The region's burgeoning automotive and electronics industries are major consumers of PEI, driving the market. Additionally, government initiatives to boost manufacturing and technological advancements are likely to further enhance the market growth in this region. North America and Europe are also significant markets for PEI, driven by strong demand in the automotive, aerospace, and medical industries.

Product Type Analysis

The Enhanced Polyetherimide market can be segmented by product type into unreinforced and reinforced PEI. Unreinforced PEI refers to the basic form of the polymer without any additional materials added to enhance its properties. This type is typically used in applications where the inherent characteristics of PEI, such as high thermal stability and excellent electrical insulation, are sufficient. The unreinforced segment is expected to grow steadily, driven by its use in medical, electronics, and consumer goods industries.

On the other hand, the reinforced PEI segment is anticipated to witness a significant growth rate. Reinforced PEI includes the polyme

Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025.

For more information, please visit HART.ubc.ca.

Housing Assessment Resource Tools (HART)

This dataset contains 18 tables which draw upon data from the 2021 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template.

17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The 18th table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension.

The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide

Custom order from Statistics Canada includes the following dimensions and data fields:

Geography:
- Country of Canada, all CDs & Country as a whole
- All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole
- All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole
*- Data on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000.

Data Quality and Suppression:
- The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released.

- Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada

- When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts greater than 10 are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero.

Universe:
Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero.

Households examined for Core Housing Need:
Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances.

Data Fields:

Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7)
1. Total - Private households by tenure including presence of mortgage payments and subsidized housing
2. Owner
3. With mortgage
4. Without mortgage
5. Renter
6. Subsidized housing
7. Not subsidized housing

Housing indicators in Core Housing Universe (12)
1. Total - Private Households by core housing need status
2. Households examined for core housing need
3. Households in core housing need
4. Below one standard only
5. Below affordability standard only
6. Below adequacy standard only
7. Below suitability standard only
8. Below 2 or more standards
9. Below affordability and suitability
10. Below affordability and adequacy
11. Below suitability and adequacy
12. Below affordability, suitability, and adequacy

Period of construction (10)
1. Total – Period of Construction
2. Before 2016
3. 1960 or before
4. 1961 to 1980
5. 1981 to 1990
6. 1991 to 2000
7. 2001 to 2005
8. 2006 to 2010
9. 2011 to 2015
10. 2016 to 2021 (Note 1)
Note 1). Includes data up to May 11, 2021.

Structural type of dwelling and Household income as proportion to AMHI (16)
1. Total - Structural type of dwelling
2. Single-detached house
3. Apartment in a building that has five or more storeys
4. Other attached dwelling
5. Apartment or flat in a duplex
6. Apartment in a building that has fewer than five storeys
7. Other single-attached house
8. Row house
9. Semi-detached house
10. Movable dwelling
11. Total – Private households by household income proportion to AMHI
12. Households with income 20% or under of area median household income (AMHI)
13. Households with income 21% to 50% of AMHI
14. Households with income 51% to 80% of AMHI
15. Households with income 81% to 120% of AMHI
16. Households with income 121% or more of AMHI

Selected characteristics (12)
1. Total – Private households by presence of activity limitation (Q18e only)
2. HH has at least one person who had an activity limitations reported for Question 18 e) only 1
3. Total – Age of primary household maintainer
4. 18 to 29 years
5. Total – Private households by military service status of the HH members
6. HH includes a person who is currently serving member and/or veteran
11. Total – Private households by shelter cost proportion to AMHI_1
12. Households with shelter cost 0.5% and under of AMHI
13. Households with shelter cost 0.6% to 1.25% of AMHI
14. Households with shelter cost 1.26% to 2% of AMHI
15. Households with shelter cost 2.1% to 3% of AMHI
16. Households with shelter cost 3.1% or more of AMHI*

Median income (2)
1. Number of households
2. Median income of household ($)
The household median income in the custom tabulation were estimates from a 25% sample-based data that have undergone weighting. These weights were applied to the sample data to produce estimates from the census long-form sample. The incomes used were drawn from the previous tax year, and therefore represent 2020 dollars.

[Only in "Census 2021 - Gender Diverse HHs" file] Genderdiversity (2)
1. Total - Gender diversity status of households
2. HH is gender diverse

File list (19 total):

Original data files (18):
1. Census 2021 - Table 1 - Median Incomes.ivt
2. Census 2021 - Table 2 - Canada.ivt
3. Census 2021 - Table 3 - Census Divisions.ivt
4. Census 2021 - Table 4 - Ontario CSDs.ivt
5. Census 2021 - Table 5 - BC CSDs.ivt
6. Census 2021 - Table 6 - Alberta CSDs.ivt
7. Census 2021 - Table 7 - Manitoba CSDs.ivt
8. Census 2021 - Table 8 - Saskatchewan CSDs.ivt
9. Census 2021 - Table 9-1 - Quebec CSDs (Part 1 of 3).ivt
10. Census 2021 - Table 9-2 - Quebec CSDs (Part 2 of 3).ivt
11. Census 2021 - Table 9-3 - Quebec CSDs (Part 3 of 3).ivt
12. Census 2021 - Table 10 - Newfoundland&Labrador CSDs.ivt
13. Census 2021 - Table 11 - PEI CSDs.ivt
14. Census 2021 - Table 12 - Nova Scotia CSDs.ivt
15. Census 2021 - Table 13 - New Brunswick CSDs.ivt
16. Census 2021 - Table 14 - Yukon CSDs.ivt
17. Census 2021 - Table 15 - NWT CSDs.ivt
18. Census 2021 - Table 16 - Nunavut CSDs.ivt
19. Census 2021 - Gender Diverse HHs.ivt

Pour de plus amples renseignements, veuillez visiter HART.ubc.ca.

Outils d'évaluation du logement ("HART")

Cet ensemble de données contient 18 tableaux qui s’appuient sur les données

The average house price in Nova Scotia in 2024 stood at approximately ******* Canadian dollars. In the next year, house prices are forecast to further increase by about five percent. Compared to other provinces, Nova Scotia ranked below the national average in terms of house prices. However, the average price of a house in Nova Scotia was twice lower than in Ontario or British Columbia. Exploding population growth in recent yearsNova Scotia is the second-smallest province after Prince Edward Island, and had a population of just under *********** in 2018. The population of this province was relatively steady between 2000 and 2015, but has taken off since then. This sudden growth may be a factor in the increasing house prices, as demand also increases due to the greater number of residents looking for homes. The future of housing affordability in Nova ScotiaHalifax, the provincial capital, had an affordable housing market as of 2018, with mortgage payments only constituting about ** percent of average household incomes. The number of housing starts in the region has increased in the past few years, which also suggests an increase in demand. Only time will tell whether this will ensure a sufficient supply of homes for the region in response to its growing population.