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Population Projections for Newfoundland & Labrador Document Transcript

  • 1. The Effect of Migration on Population Projections for Newfoundland and Labrador December 14, 2004 Ryan MacNeil Masters Candidate Local Economic Development University of Waterloo In fulfillment of the requirements for LED 619: Regional Economic and Investment Analysis Dr. Clarence Woudsma
  • 2. Population in NL 2 Executive Summary In 2001, Newfoundland and Labrador’s population stood at 521,987 (Statistics Canada, 2004a) and its unemployment rate at 16.7% (Newfoundland and Labrador, 2004a). In theory, unemployment and underemployment should push “economically rational” people away from depressed provinces. Newfoundland and Labrador’s population should be declining precipitously as a result of its economic malaise. But the province has the lowest rates of out-migration in the country (House et al, 1990). It also has the lowest rates of in-migration and a remarkably high level of return migration (Ibid.). These trends can have a profound impact on the province's labour supply and therefore its economic growth. This paper explores the effect of interprovincial migration on the growth prospects of Newfoundland and Labrador. There are two population projection techniques common to regional analysis. The most common and basic projections are made using linear regression. More detailed projections that include age and gender breakdowns are made using the cohort survival method. Neither method explicitly considers the effects of migration, but the cohort survival technique can be modified into a migration-adjusted cohort survival method. For the purposes of this paper, basic regression and cohort survival projections are used along side a migration-adjusted cohort projection to demonstrate the effect of migration on population trends. The results confirm that these techniques are limited by their ability to account for fluctuating migration rates. By 2041 the province would have seen a disastrous population decline of 45.5% if 2001 migration rates had continued over time. Luckily migration rates have improved considerably over the past 3 years, and 2003 figures place the decline at 21.4% over 40 years. If no migration were to take place the decline would be 17.9%. The obvious conclusion is that Newfoundland and Labrador’s long term growth is sensitive to fluctuating migration rates. There is evidence that these migration rates are partly determined by changing economic conditions in Newfoundland and Labrador and economic conditions outside the province over which it has less control. There is also some academic evidence that Newfoundlanders and Labradoreans do not make migration decisions that are entirely economically rational. That is, they do not base migration decisions solely on the location of employment opportunities and wages. While migration trends have recently improved at the provincial level there is no indication as to whether or not this improvement has been consistent across communities. Nor is there any indication as to whether or not these new rates will hold over time. Indeed, it is likely that provincial and local migration rates are constantly fluctuating. It is important that migration trends be monitored; given the profound role migration could play in the province’s long-term growth. An evolving set of recruitment, retention and repatriation interventions can help economic developers harness migration and affect positive growth.
  • 3. Population in NL 3 Table of Contents Executive Summary........................................................................................................................ 2 Table of Contents............................................................................................................................ 3 1.0 Introduction......................................................................................................................... 4 2.0 Research Methodology ....................................................................................................... 5 2.1 Regression....................................................................................................................... 6 Appropriateness ...................................................................................................................... 6 Technique................................................................................................................................ 6 Data ......................................................................................................................................... 6 Assumptions and Limitations ................................................................................................. 6 2.2 Cohort Survival............................................................................................................... 7 Appropriateness ...................................................................................................................... 7 Technique................................................................................................................................ 7 Data ......................................................................................................................................... 7 Assumptions and Limitations ................................................................................................. 8 2.3 Migration-adjusted Cohort Survival ............................................................................... 8 Appropriateness ...................................................................................................................... 8 Technique................................................................................................................................ 9 Data ......................................................................................................................................... 9 Assumptions and Limitations ................................................................................................. 9 3.0 Results Analysis................................................................................................................ 10 3.1 Regression..................................................................................................................... 10 3.2 Basic Cohort Survival ................................................................................................... 12 3.3 Migration-adjusted Cohort Survival ............................................................................. 13 3.4 2003 Migration Rates.................................................................................................... 16 3.5 Comparing the Four Models ......................................................................................... 18 4.0 Conclusions....................................................................................................................... 19 Works Cited .................................................................................................................................. 21 Appendices Cohort Survival Tables and Charts .................................................................................................A Migration Adjusted Cohort Survival Tables and Charts ................................................................B Linear Regression Tables and Charts ............................................................................................C Data Tables ....................................................................................................................................D Recruitment, Retention and Repatriation Strategies for Local Economic Development ...............E Cover photo: A Newfoundland Lighthouse, http://www.gov.nl.ca/tourism/topmenu/gallery/pages/light.htm
  • 4. Population in NL 4 1.0 Introduction Over the past 20 years, Newfoundland and Labrador’s population has hovered around 550,000 people. In 2001 it stood at 521,987 (Statistics Canada, 2004a). It is common knowledge that the province has the highest unemployment rate in the country -- 16.7% in 2001 (Newfoundland and Labrador, 2003). In theory, unemployment and underemployment should push “economically rational” people away from depressed provinces. Newfoundland and Labrador’s population should be declining precipitously as a result of its economic malaise. However, many researchers are now critical of labour market theories of migration. House, White and Ripley (1990) studied two small coastal communities on the Great Northern Peninsula of Newfoundland: Anchor Point and Bird Cove. Their findings do not completely fit with the theory of an economically rational migrant. It is argued that, to Newfoundlanders, economic self-interest includes non-cash wealth and benefits from the informal economy. Also, rational migration decisions extend beyond immediate economic considerations to include past experience and present personality. The authors explain, “In real life, people respond to situations in terms of their personal biographies, which vary according to where they were born and raised, their family relationships and a host of other influences” (House, White and Ripley, 1990, 3). It is surprising to some that out-migration rates are relatively high in the Western Provinces and low in the Atlantic Provinces. Newfoundland and Labrador has the lowest rates of gross out- migration in the country (Looker, 2001 and House, White and Ripley, 1990). Gross out- migration is not the source of the province’s net out-migration. What distinguishes Newfoundland is not that Newfoundlanders choose to leave their home province at a greater rate than people in other provinces, but rather that other Canadians choose to move to Newfoundland at a lower rate than they do any other province (House, White and Ripley, 1990, 12). Despite a depressingly low level of in-migration, Newfoundland and Labrador has a remarkably high level of return migration – the highest rates in the country. Over half of the migrants into Newfoundland and Labrador are former residents. This trend has been consistent for at least the past 20 years (Ibid.).
  • 5. Population in NL 5 Gmelch and Richling (1988) tell the story of return migration to outport Newfoundland not in terms of the return migrants’ failure in the urban economy, but rather their desire to rediscover intimate social relations, community spirit and a rural household economy (including the self- sufficient nature of hunting, fishing, and barter). As veterans of urban-industrial Canada, having tasted the ‘modern life’, their voluntary return to the province’s rural villages offers an unambiguous message that outport society and culture are still vibrant and appealing (Gmelch and Richling, 1988, 14). House, White and Ripley agree that return migration to Newfoundland is not a result of labour market failure, rather the result of a new awareness of Newfoundland’s advantages. The grass is no longer greener on the other side. Both research teams also agree that social considerations are integral to the migration decisions of rural Newfoundlanders. Social capital is one of the key incentives to return migration. The researchers further suggest that this observation likely applies in varying degrees to other Atlantic Canadian communities and beyond. This paper provides context for a master’s thesis on socially motivated migration in Atlantic Canada. Titled “Community, Social Capital and Return Migration in Atlantic Canada,” the thesis will attempt to extend theories about migration in Newfoundland and Labrador to the rest of Atlantic Canada. It will attempt to demonstrate that communities with stronger bonding social capital have higher rates of return migration. The findings will support efforts to return talent into diminished labour markets. To this end, this paper will reveal the importance of interprovincial migration to Newfoundland and Labrador’s labour market. It will demonstrate the need for further migration research and interventions by economic development professionals in the province. 2.0 Research Methodology There are two population projection techniques common to regional analysis. The most common and basic projections are made using linear regression. More detailed projections that include age and gender breakdowns are made using the cohort survival method. Neither method explicitly considers the effects of migration, but the cohort survival technique can be modified into a migration-adjusted cohort survival method. For the purposes of this paper, basic regression and
  • 6. Population in NL 6 cohort survival projections will be used along side a migration-adjusted cohort projection to demonstrate the effect of migration on population trends. 2.1 Regression Appropriateness The statistical population projection method (linear regression) generates reliable estimates for stable regions. Planners and economic developers in these regions can use this method to predict population and employment growth over a medium to long term time frame. The major advantage of this method is that it provides a confidence interval around the projections so the user can consider the margin of error. It is a straight-forward technique accessible to those with introductory statistical training. This method can be a powerful planning tool. Technique Statistical functions in Microsoft Excel have been used to calculate three regression equations for Newfoundland and Labrador: population change over time, employment change over time, and population change versus employment change. These equations have been used to project population and employment growth over the next 40 years (2001-2041). A 95% confidence interval has been calculated around the extrapolated values to indicate the margin of error. Data The regression equations are calculated from annual population and employment statistics dating from 1976 to 2001. This data was drawn from CANSIM Tables 051-0001 (population) and 282- 0002 (labour force), published by Statistics Canada (Statistics Canada, 2004a,b). These were accessed through the University of Waterloo Library’s E-STAT license. Assumptions and Limitations Regional planners and economic developers must be weary of this method’s limitations. This method rests on the central assumption that a linear relationship exists between two variables. The reality is that not all relationships are linear and most phenomena are the result of multiple factors. In the case of population projections there is a widely held belief that any given region has a limited “carrying capacity”. In other words, populations cannot grow indefinitely. At some point linear population growth must slow and level off. Further, populations do not grow over
  • 7. Population in NL 7 time in isolation of other factors. Survival, fertility and migration rates change over time. Extreme events (ie. war, famine, AIDS) cannot be included in these models. Nor is the cyclical nature of many economies considered under the basic application of this method. But while linear regression does not reflect all of these factors it may highlight them. If planners and economic developers are working from a population regression equation they might be more likely to notice when actual observations vary significantly from the equation’s predictions. Significant variations are cause for in-depth analysis that can reveal important changes in demographic factors. 2.2 Cohort Survival Appropriateness The cohort survival method is based on a closed system natural increase model. It adds detail to estimated population totals through a breakdown of the population by age and gender. Planners and economic developers can use this method to predict demand for “educational facilities, community and recreation services, services for the elderly, etc.” (Newkirk, 2002). It is particularly pertinent in a time when the baby boom generation is poised to retire. This method reflects the magnitude of population aging. Technique The cohort survival method begins with an age-gender population table for a known period. To project the subsequent time period, the population of each age cohort is progressed into the following age cohort. An age-gender specific survival rate (1 - death rate) is applied. Typically the final age cohort is open-ended (ie. 70 and older). New births are added to the bottom of the table, based on age-specific fertility rates for those women of child-bearing age. Appendix A includes the age-gender population table for 2001, and predicted tables spanning every five years until 2041. Data The cohort survival tables are calculated from 2001 population statistics. This data was drawn from CANSIM Tables 051-0001 (population), 102-4505 (fertility), and 102-0504 (mortality),
  • 8. Population in NL 8 published by Statistics Canada (Statistics Canada, 2004a,c,d). These were accessed through the University of Waterloo Library’s E-STAT license. Assumptions and Limitations These projections are not completely reliable because the process involves two key assumptions. The first assumption is that cohort survival rates will remain constant over time. Advances in medicine and healthy lifestyles are likely to affect cohort survival over the next 40 years. It is likely that baby boomers will live considerably longer than their parents and grandparents. At the other end, the estimation process assumes that fertility rates for each five year female cohort will remain constant over time. While family size does seem to be a long term trend it is also true that advances in science have been increasing the age at which women can safely give birth. While the cohort projections are useful it does not seem likely that survival and fertility coefficients will remain constant over the next 40 years. Perhaps the model should be expanded to consider survival and fertility trends. For the purposes of this paper, the most important limitation of cohort survival is that it treats regions as closed systems. The method assumes that the only population increases come from births and the only decreases come from deaths. In reality there are also flows into and out of all regions. Newkirk (2002) suggests that this limitation is only a problem “if migration represents a significant activity in the community being studied” (p. 121). It will become clear that migration can significantly affect the population of Newfoundland and Labrador. This limitation is overcome by an extension of the basic method. 2.3 Migration-adjusted Cohort Survival Appropriateness Newkirk (2002) explains that, for regions with a significant level of migration activity, a migration-adjusted cohort model can be employed. This method builds on the basic cohort survival method by considering the effect of age-gender specific net-migration rates.
  • 9. Population in NL 9 Technique Adjusting the basic cohort survival method for migration involves adding an additional step to the beginning of the process. Newkirk (2002, p. 122) explains that for each subsequent time interval the process involves: 1. Adjusting the age-gender groups for expected net migration. 2. Calculating the natural increase (births). 3. Progressing the population through age groups, adjusting for survival. Data Because migration is not evenly distributed across age-gender cohorts, detailed migration data is required for this analysis. CANSIM Table 051-0012 (interprovincial migration) was employed in addition to other data employed in the basic cohort survival method. Absolute net-migration for each age-gender cohort in 2001 was converted into migration rates by dividing net-migration by cohort size. Assumptions and Limitations Although this method removes the closed-system assumption from the basic cohort method, it retains the assumption that fertility and death rates remain constant over time. It further assumes that the migration observed in 2001 will remain constant over time. The error in this assumption will be demonstrated in section 3.4. An additional problem arises through the calculation of migration rates. Some researchers argue that in-migrants represent a proportion of the population in the region from which they migrated, not a proportion of the population in the region to which they are migrating. For simplicity many researchers divide the net number of migrants by the population size of the region under study. This approach has been employed here.
  • 10. Population in NL 10 3.0 Results Analysis 3.1 Regression Figure 1 Newfoundland and Labrador Projected Population Growth (By Linear Regression 2001-2041) 700,000 650,000 600,000 Population 550,000 500,000 450,000 400,000 1976 1981 1986 1991 1996 2001 2006 2011 2016 2021 2026 2031 2036 2041 Ye ar High Interval Low Interval Regression Line Actual Population The regression method results in a linear function which can be used to extrapolate future population growth (or, in this case, population decline). The function can be expressed as, P = 3,207,195.57 1,328.08Y (where P represents the total population and Y represents the year). This equation indicates that every year the Newfoundland and Labrador population declines by 1,328 people. It also suggests that in the year 0 AD, over three million people inhabited the province. We know that this is not the case, but nevertheless the regression equation is useful in forward-looking projections. A graph of the linear function (black line) can be seen in Figure 1. The green line represents actual population data. The red dotted lines represent a 95% confidence interval. The actual population may fall on the regression line, but will almost certainly fall between these two confidence intervals. As a result of this analysis the Newfoundland and Labrador population in 2041 is estimated to be 496,573 ± 31,099.
  • 11. Population in NL 11 Figure 2 Newfoundland and Labrador Projected Population and Employment Growth (By Linear Regression 2001-2041) 650,000 600,000 550,000 Population 500,000 450,000 400,000 350,000 1976 1981 1986 1991 1996 2001 2006 2011 2016 2021 2026 2031 2036 2041 Year Although the province’s population is expected to decline, its employment is expected to grow. The regression equation, E = 2,825.23Y 5,194,286.77 (where E represents the number of employed persons and Y represents the year), can be used to predict 572,009 employed persons in 2041 (± 25,529). This suggests that there could be more jobs in the province than people in 2041. Figure 2 plots the population and employment functions together. The point where employment growth meets population decline is in October, 2022. It is far-fetched to suggest that this eventuality will occur. Current population and employment trends will not remain constant over the next 40 years. As employment growth continues and the province’s economic situation improves it is likely that former residents will return, reversing the net-out-migration trend and flattening or inverting the population growth line. As well, there is logically a relationship between population and employment growth. Unfortunately the nature of this relationship is not evident in the data for this province (see the cross-correlation in Appendix C). Clearly the conclusion that employment will surpass population is ungrounded. But this analysis does demonstrate that labour supply should be a concern for planners and economic developers in Newfoundland and Labrador.
  • 12. Population in NL 12 3.2 Basic Cohort Survival Figure 3 Newfoundland and Labrador Population Structure (2001) 90+ 85-89 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 (30,000) (20,000) (10,000) - 10,000 20,000 30,000 Males Females The 2001 age-gender distribution of Newfoundland and Labrador’s population is represented by Figure 3. Note the baby boom and echo generation bumps. These pronounced groups are slightly younger and closer together in Newfoundland and Labrador than other parts of the country. The baby boom generation includes those in their late thirties through to those in their early fifties. The echo generation here is aged 15-19. In 2001 there were 5.8 working age (15-64) Newfoundlanders and Labradoreans for every one aged 65 or more. However, by 2041, the basic cohort survival method predicts only two working age citizens for every one aged 65 or more (see Figure 4). The total population is expected to fall to 428,695 by 2041, 67,878 fewer people than predicted by the linear regression model. The difference in these projections stems from the decline in child-bearing age female cohorts.
  • 13. Population in NL 13 Figure 4 Newfoundland and Labrador Population Structure (2041) 90+ 85-89 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 (30,000) (20,000) (10,000) - 10,000 20,000 30,000 M ales Females For future reference it should be noted that the baby boom and echo generations persist in this basic cohort projection. The baby boom generation is only visible in the female population by 2041 (aged 70-79) because of low survival rates among the senior male population. But the gradually aging baby boom generation can be clearly seen in the full set of population pyramids found in Appendix A. 3.3 Migration-adjusted Cohort Survival Newfoundland and Labrador get into trouble when migration is added to the basic cohort survival method. It was noted in the previous section that pronounced baby boom and echo generations persist to some degree throughout the 40 years of estimates. But under the migration- adjusted cohort survival method, the echo generation effectively disappears between 2011 and 2016 (see population pyramids in Appendix B). This trend results in a 2041 population estimated at only 284,421 individuals. That is 144,274 fewer people that the basic cohort projection method, and only 1.28 working age citizens for every one aged 65 or more (see Figure 5).
  • 14. Population in NL 14 Figure 5 Newfoundland and Labrador Population Structure (2041) 90+ 85-89 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 (30,000) (20,000) (10,000) - 10,000 20,000 30,000 Males Females There are two factors behind this profoundly different population projection. First, the echo generation effectively disappears because the highest net-out-migration is among 20-24 year olds (see Figure 6). Approximately one in five 20-24 years olds leaves Newfoundland and Labrador. There is only a slightly greater loss of males than females in this age group. This effect is more moderate in every other age cohort. But because this cohort and the two following it have the highest female fertility rates, the net-out-migration has a double-punch effect. The natural population increase is slowed because young women are leaving just when they are most likely to have children. This is the second factor driving the projected population into the ground. It can be seen when comparing female cohorts under the basic cohort survival method with those from the migration adjusted cohort method. In Figure 7, a spike of women aged 15-19 in 2001 can be seen in all three time series. But in Figure 8 this demographic spike is eroded completely within 20 years.
  • 15. Population in NL 15 Figure 6 Net Migration by Age Group (NL, 2001) 500 0 Migrants -500 -1000 -1500 -2000 0-4 5-9 10- 15- 20- 25- 30- 35- 40- 45- 50- 55- 60- 65- 70- 75- 80- 85- 90+ 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89 Age Figure 7 Newfoundland and Labrador Projected Change in Female Cohorts 25,000 2001 20,000 2021 2041 Population 15,000 10,000 5,000 - 4 + 4 4 4 4 4 4 4 4 0- 90 -8 -7 -6 -5 -4 -3 -2 -1 80 70 60 50 40 30 20 10 Age Group
  • 16. Population in NL 16 Figure 8 Newfoundland and Labrador Projected Change in Female Cohorts 25,000 2001 20,000 2021 2041 Population 15,000 10,000 5,000 - 4 + 4 4 4 4 4 4 4 4 0- 90 -8 -7 -6 -5 -4 -3 -2 -1 80 70 60 50 40 30 20 10 Age Group 3.4 2003 Migration Rates There is some preliminary evidence that Newfoundland and Labrador’s migration rates are improving. Perhaps this is the result of specific financial incentives that the province has aimed at university and college students, but it is more likely related to changing economic conditions across the country. The Economic Research and Analysis Division of Newfoundland and Labrador’s Department of Finance gives this update: The province’s population on July 1, 2003 was 519,570, a gain of 300 over 2002, the first increase in more than a decade. The gain was due to natural population change of 223 and positive net migration of 77. This net migration contrasts with the previous five years when an average negative net migration of 7,049 was recorded. Last year’s positive performance was due to solid economic growth locally and temporary economic weakness in other parts of the country which dampened job prospects in those regions (Newfoundland and Labrador, 2004a, 11).
  • 17. Population in NL 17 By 2003 estimates (preliminary data from Statistics Canada, 2004e), the province’s net-out- migration for 20-29 year olds has been cut in half since 2001 (see Figure 9). Meanwhile there appears to be a net-in-migration of young families (adults aged 30-49 and children aged 0-14). Figure 9 Net Migration by Age Group (NL, 2003) 400 200 0 Migrants -200 -400 -600 -800 -1000 0-4 5-9 10- 15- 20- 25- 30- 35- 40- 45- 50- 55- 60- 65- 70- 75- 80- 85- 90+ 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89 Age To demonstrate the effect of changing migration rates, preliminary 2003 migration rates were run through the migration-adjusted cohort model. The resulting 2041 population distribution (Figure 10) is quite similar to the 2041 population distribution which was produced using the basic cohort survival method (Figure 4) in section 3.2. In fact, the overall result is a total population nearly identical to the basic cohort projection.
  • 18. Population in NL 18 Figure 10 Newfoundland and Labrador Population Structure (2041) 90+ 85-89 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 (30,000) (20,000) (10,000) - 10,000 20,000 30,000 M ales Females 3.5 Comparing the Four Models Figure 11 Comparison of Four Population Projections 600,000 500,000 400,000 300,000 200,000 100,000 - 2001 2006 2011 2016 2021 2026 2031 2036 2041 3.1 Regression 3.2 Basic Cohort 3.3 Migration-Adjusted Cohort 3.4 2003 Migration Rates
  • 19. Population in NL 19 Figure 11 is a compilation of the four models which have been developed: linear regression, basic cohort survival, 2001 migration-adjusted cohort survival and 2003 migration-adjusted cohort survival. All four of the projections that have been developed predict a continued decline in Newfoundland and Labrador’s population. Migration rates from 2001 had a precipitous effect on the first migration-adjusted cohort model. But more recent migration rates have little effect on the basic cohort survival model. It would appear that the province’s future growth is quite sensitive to migration rate fluctuations. 4.0 Conclusions The results confirm that common population projection techniques are limited by their ability to account for fluctuating migration rates. A dramatic shift in Newfoundland and Labrador’s migration rates between 2001 and 2003 significantly altered the migration-adjusted cohort projections. Improved economic circumstances (or declining circumstances elsewhere) can alter migration rates and change population growth trends. Population growth can, in turn, affect economic growth. Changing migration rates, population growth and economic growth are interrelated patterns that can feed into one another. Therefore, complex computer modeling is required to reliably predict change over time. Meanwhile, this paper has shown that more accessible methods can be used by planners and economic developers to understand the range of outcomes that are possible in a region. While they may not always provide reliable population estimates, these methods can be used to identify the demographic factors to which a region’s growth is most sensitive. This paper has also revealed the importance of interprovincial migration to Newfoundland and Labrador’s labour market. The province would have seen a disastrous population decline if the 2001 migration rates had continued over time. Luckily migration rates have improved considerably over the past 3 years. The obvious conclusion is that Newfoundland and Labrador’s long term growth is sensitive to fluctuating migration rates. There is evidence that these migration rates are linked to changing economic conditions in Newfoundland and Labrador, but also to economic conditions outside the province over which it has less control. There is also some academic evidence that Newfoundlanders and Labradoreans do not make migration
  • 20. Population in NL 20 decisions that are entirely economically rational. The province’s decision makers would benefit from further study of migration and economic growth. There is need for further migration research and interventions by economic development professionals in Newfoundland and Labrador. While migration trends have improved at the provincial level there is no indication as to whether or not this improvement has been consistent across communities. Nor is there any indication as to whether these new rates will hold over time. Indeed, it is likely that provincial and local migration rates are constantly fluctuating. It is important that planners and economic developers monitor migration trends, given the profound role migration could play in the province’s long-term growth. An evolving set of recruitment, retention and repatriation interventions (see Appendix E) can help these professionals affect positive growth.
  • 21. Population in NL 21 Works Cited Brean, J. “Lord’s siren call.” National Post 28 February 2004: A1. Coastal Communities Network (5 July 2004). “Migrating Youth Leave an Aging Population Behind in Rural Nova Scotia: Rural Nova Scotia Aging at an Alarming Rate [Media Release]. Pictou, NS: CCN. Gmelch, G. and B. Richling (1988). “'We’re Better Off Here': Return Migration to Newfoundland Outports.” Anthropology Today 4 (4): 12 – 14. House, J.D., S.M. White, and P. Ripley (1990). Going Away…And Coming Back: Economic Life and Migration in Small Canadian Communities. St. John’s, NL: Institute of Social and Economic Research, Memorial University of Newfoundland. Looker, E.D. (2001). “Policy Research Issues for Canadian Youth: An Overview of Human Capital in Rural and Urban Areas.” Hull: Applied Research Branch, Human Resources Development Canada. Newfoundland and Labrador (2004a). The Economy 2004. St. John’s, NL: Economic Research & Analysis Division, Department of Finance, Government of Newfoundland and Labrador. Newfoundland and Labrador (2004b). Government of Newfoundland and Labrador Website. http://www.gov.nf.ca/, accessed 1 December 2004. Newkirk, R. (2002). Techniques for Regional Planning. Waterloo, ON: University of Waterloo under license from ingenious solutions inc. Place aux Jeunes. Place aux Jeunes Website. http://www.placeauxjeunes.qc.ca/, accessed 1 December 2004. Reimer, B. and R.D. Bollman (October, 2004). “Strategic observations for rural community decisions (ideas for communities that have decided that they want to grow).” Notes to accompany workshop presented at the National Rural Conference, Red Deer, Alberta. Retrieved 29 November 2004, from http://nre.concordia.ca/__ftp2004/observations/StrategicObservationsSept30.pdf Statistics Canada (2004a). Estimates of population, by age group and sex, Canada, provinces and territories, annual [Beyond 20/20 data file]. CANSIM Table 051-0001. Ottawa: Her Majesty the Queen in Right of Canada. Statistics Canada (2004b). Labour force survey estimates (LFS), by sex and detailed age group, annual [Beyond 20/20 data file]. CANSIM Table 282-0002. Ottawa: Her Majesty the Queen in Right of Canada.
  • 22. Population in NL 22 Statistics Canada (2004c). Live births, crude birth rate, age-specific and total fertility rates, Canada, provinces and territories, annual [Beyond 20/20 data file]. CANSIM Table 102-4505. Ottawa: Her Majesty the Queen in Right of Canada. Statistics Canada (2004d). Deaths, by age group and sex, Canada, provinces and territories, annual [Beyond 20/20 data file]. CANSIM Table 102-0504. Ottawa: Her Majesty the Queen in Right of Canada. Statistics Canada (2004e). Interprovincial migrants, by age group and sex, Canada, provinces and territories, annual [Beyond 20/20 data file]. CANSIM Table 051-0012. Ottawa: Her Majesty the Queen in Right of Canada. Von Kintzel, C. “Care kits remind students of good old N.S.” Chronicle Herald 24 March 2004.