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Data cited at: Numbeo Methodology: The Index has been calculated twice per year by considering the latest 36 months. A). Beginning of the Year and B). Mid Year Crime Index is an estimation of the overall level of crime in a given city or a country. We consider crime levels lower than 20 as very low, crime levels between 20 and 40 as being low, crime levels between 40 and 60 as being moderate, crime levels between 60 and 80 as being high and finally crime levels higher than 80 as being very high. Safety index is, on the other way, quite the opposite of crime index. If the city has a high safety index, it is considered very safe.

Methodology Following on from previous iterations evaluating the best cities for millennials, the Best Cities for Generation Z 2019 focuses on the latest demographic whose oldest members are in the process of graduating from university and entering the workforce. This index is composed of 22 indicators ranking 110 cities worldwide based on their recognition of, and initiatives to prepare for this new, up-and-coming generation. DEFINITION OF GENERATION Z According to the Pew Research Center, those born between 1997-2012 are considered to be a member of Gen Z. Despite the lack of a definitive boundary separating Millennials and Generation Z, 1996 was selected due to the common key social, political, and technological circumstances that forms the foundation of each generation. Gen Z-ers are known to be digital natives who value security, diversity, and autonomy, and aim to achieve it through pragmatism and determination. CITY SELECTION A shortlist of prominent, international cities were selected based on their reputation as destinations to pursue work and education, as well as those who have shown initiative to act on the demands of previous generations such as Millennials and Generation X. Originally, 100 cities were chosen for the final index, however 10 additional locations that are rising in economic strength were included in order to offer a more representative overview. The final selection of 110 cities is further based on the feasibility of collecting extensive, reliable data for the factors used to assess their livability, as well inclusion at a global scale. FACTORS AND SCORING The study focuses on four broad categories with the following factors outlined below that determine the extent to which a city is attractive to live for Gen Z and embraces their values. Digital: Government Digitalisation, Connectivity/5G, Digital Payment & Banking, Digitalised Mobility/Sharing Economy, Digitalised Social Habits, Education, Privacy & Security Principles: Internationalism, Gender Equality, LGBT+ Equality, Environmental Action, Access to Mental Healthcare, Access to Healthcare, Safety, and Right to Protest Leisure: Esports, Concerts Business: Entrepreneurial Spirit & Innovation, Affordability, Social Entrepreneurship, AI Industry, Co-Working Spaces All factors as well as the overall total are measured as scores, and are valued between 1 and 100, where 1 is the lowest attainable score in the dataset and 100 is the highest. A value of 100 does not mean a city is perfect and has no need for improvement. Instead, it indicates that the city performs the best out of all locations in the index. In a similar regard, a score of 1 indicates that the city performs the weakest in comparison to the other cities in the study. Nevertheless, this does not necessarily imply that the city has no ability to attract Generation Z, nor is it uninhabitable for the demographic in a wider global context. This score for each factor is obtained directly from the raw data and implements a normalisation of the form: Score(i) = 99 * ( ( (x(i) - x(min) ) / ( (x(max) - x(min) ) ) + 1 After the collected data was normalised and determined for each factor, a weighted average to create a final score for each overall category (Digital, Principles, Leisure, Business) was calculated and normalised. The final total score for each city was then determined by calculating the sum of the weighted average score of the indicators under each category, which has been normalised in order to create a final result between 1 and 100 as follows: TOTAL SCORE = WEIGHTED AVERAGE (Digital factor scores) + WEIGHTED AVERAGE (Principles factor scores) + WEIGHTED AVERAGE (Leisure factor scores) + WEIGHTED AVERAGE (Business factor scores)

Note: Calculation based on four quarter moving average NHB RESIDEX, India’s first official housing price index, was an initiative of the National Housing Bank (NHB) undertaken at the behest of the Ministry of Finance, Government of India. The index was formulated under the guidance of a Technical Advisory Committee (TAC) comprising of stakeholders from the housing market. It was launched in July, 2007 and updated periodically till March 2015, taking 2007 as the base year. During this period, the coverage of NHB RESIDEX was expanded gradually to 26 cities Initially, NHB RESIDEX was computed using market data, which 2010 onwards, was shifted to valuation data received from banks and housing finance companies (HFCs). Thereafter, data was sourced from Central Registry of Securitisation Asset Reconstruction and Security Interest of India (CERSAI) from 2013 to 2015. With a view to make the NHB RESIDEX more current and up-to-date with the prevailing macro-economic scenario, NHB undertook a review of the processes and methodology used for computation of the index along with the base year and segmentation used.