Browsing by Author "Bhuiyan, Erfan Mahmood"
Now showing 1 - 7 of 7
Results Per Page
Sort Options
Item Can macroeconomic variables explain long term movements of stock market sector indices?: A comparison of the US and Canada(University of New Brunswick, 2018) Bhuiyan, Erfan Mahmood; Chowdhury, MurshedWhile the relationship between stock market returns and macro-economic variables has been amply examined, a gap exists in the literature regarding the relationship between different sector indices and various macroeconomic variables. This study intends to examine how certain macroeconomic variables influence different sectors of the stock market differently in the US and Canada. Using monthly data over the period 2000 – 2018, cointegration analysis is applied to model the relationship between real economic activity, money supply, long-term interest rate and different sector indices. Sectors that have been examined in this study include energy, financials, real estate, industrial, healthcare, consumer discretionary, consumer staples, materials, utilities and technology. Results suggest that there is a stable long-term relationship between the macroeconomic variables used in the study and different sector indices for the US but not for Canada. However, US money supply and interest rate can explain the Canadian Stock Market.Item Constructing profiles of low-skilled workers in New Brunswick(New Brunswick Institute for Research, Data and Training, 2021-07) Bhuiyan, Erfan Mahmood; Leonard, Philip; McDonald, TedIntroduction The objective of this report is to construct profiles of low-skilled workers in New Brunswick (NB) using different definitions of low skill and to evaluate how these profiles have evolved over time. Profiles include age group, sex, ethnicity, immigration status, employment status, industry, region of residence, and income. Data and Definitions The results of this report are based on the master data files of the 1996, 2001, 2006, and 2016 cycles of the Canadian Census and the 2011 National Household Survey (NHS) available in the Statistics Canada Research Data Centre (RDC) in Fredericton, NB. Overview and Key Findings This report constructs statistical descriptions, or profiles, of low-skilled workers in New Brunswick using three different definitions for low skill: Lack of high school certificate or its equivalent National Occupational Classification (NOC) Skill Level D Annual earnings, based on employment income, in the lowest income quintile Using these definitions for low skill, this report finds the following: 13% of working-age New Brunswickers have less than a high school certificate or equivalent This group earns an annual median income of $21,550 11% of working-age New Brunswickers are employed in NOC Skill Level D occupations This group earns an annual median income of $18,505 16% of working-age New Brunswickers earn less than the lowest income quintile cut-off. This group earns an annual median income of $6,820 Conclusion Understanding who the low-skilled workers in NB are and how the profiles of these individuals have evolved over time will help the government design more targeted programs. Once the most vulnerable groups are identified, it becomes easier to see whether they are taking advantage of existing public programs. According to this report, the groups considered most vulnerable to being low-skilled include women, part-time workers, and New Brunswickers aged 20-24. This information has the potential to help the government examine the impact of existing programs aimed at these individuals and evaluate how such programs can be improved to better serve these likely vulnerable groups.Item Mobility and retention of labour market training program participants(New Brunswick Institute for Research, Data and Training, 2022-02) Balzer, Andy; Bhuiyan, Erfan Mahmood; Leonard, Philip; McDonald, TedThis report measures the retention in New Brunswick of participants in programs designed and implemented by the Government of New Brunswick’s Department of Post-Secondary Education, Training and Labour (PETL) to help individuals prepare for, obtain, and maintain employment in New Brunswick. Information pertaining to these programs and their participants is captured in the ContactNB database, housed on the secure platform at the New Brunswick Institute for Research, Data and Training (NB-IRDT). These programs – also referred to as “interventions” – were analyzed to determine whether trained individuals remained in New Brunswick after program completion. 1-year, 3-year, and 5-year retention rates are presented for individuals who completed these interventions between 1999 and 2018, inclusive.Item Rapid response report on COVID-19 in New Brunswick: April 14, 2020(New Brunswick Institute for Research, Data and Training, 2020-04-14) Bhuiyan, Erfan Mahmood; Christensen, Eva; Daigle, Bethany; Magalhaes, Sandra; McDonald, Ted; Miah, Pablo; Somayaji, ChandyThis series of reports provides successive updates of projections that the trajectory of COVID-19 cases could follow in New Brunswick based on the experiences of other countries and regions who experienced initial COVID-19 infections earlier than NB. Specifically, these projections estimate what NB’s incident cases, hospitalizations and mortality might be if our province experienced disease trajectories similar to a range of comparison countries and regions, for both 10-day forward and peak infection scenarios. By updating our estimates in subsequent reports as more data become available, we are able to examine how NB is actually doing relative to those scenarios and use the updated data to revise our forecasts accordingly.Item Rapid response report on COVID-19 in New Brunswick: April 27, 2020(New Brunswick Institute for Research, Data and Training, 2020-04-27) Bhuiyan, Erfan Mahmood; Christensen, Eva; Daigle, Bethany; Magalhaes, Sandra; McDonald, Ted; Miah, Pablo; Somayaji, ChandyThis series of reports provides successive updates of projections that the trajectory of COVID-19 cases could follow in New Brunswick based on the experiences of other countries and regions who experienced initial COVID-19 infections earlier than NB. Specifically, these projections estimate what NB’s incident cases, hospitalizations and mortality might be if our province experienced disease trajectories similar to a range of comparison countries and regions, for both 10-day forward and peak infection scenarios. By updating our estimates in subsequent reports as more data become available, we are able to examine how NB is actually doing relative to those scenarios and use the updated data to revise our forecasts accordingly.Item Rapid response report on COVID-19 in New Brunswick: March 31, 2020(New Brunswick Institute for Research, Data and Training, 2020-03-31) Bhuiyan, Erfan Mahmood; Christensen, Eva; Daigle, Bethany; Magalhaes, Sandra; McDonald, Ted; Miah, Pablo; Somayaji, ChandyThis series of reports provides successive updates of projections that the trajectory of COVID-19 cases could follow in New Brunswick based on the experiences of other countries and regions who experienced initial COVID-19 infections earlier than NB. Specifically, these projections estimate what NB’s incident cases, hospitalizations and mortality might be if our province experienced disease trajectories similar to a range of comparison countries and regions, for both 10-day forward and peak infection scenarios. By updating our estimates in subsequent reports as more data become available, we are able to examine how NB is actually doing relative to those scenarios and use the updated data to revise our forecasts accordingly.Item Rapport d’intervention rapide concernant la COVID-19 au Nouveau-Brunswick : Le 31 mars 2020(l’Institut de recherche, de données et de formation du Nouveau-Brunswick, 2020-03-31) Bhuiyan, Erfan Mahmood; Christensen, Eva; Daigle, Bethany; Magalhaes, Sandra; McDonald, Ted; Miah, Pablo; Somayaji, Chandy