Sustaining Life in a Corporate Concrete Jungle

Michael Pohling

Abstract:
This paper analyzes the staggeringly low fertility rate in Singapore and compares it to countries around the world. The research strives to find a highly statistically significant variable through simple linear regression analysis that attributes to the low fertility rate. The paper then provides a logical way to manipulate this variable to promote a sustainable fertility rate for the future growth and development of the country.

1. Introduction

It is undeniable that the future of a country depends on the ability of the population to promote a healthy rate of economic and social growth through a sustainable fertility rate. This truth is particularly evident in the country of Singapore because the fertility rate directly attributes to the growth of the completely urban economic environment within the city-state. The estimated total fertility rate of .79 in Singapore is lower than any other country in the world (CIA 2013). This low and downward-trending figure is arguably the single most relevant concurrent issue within the city-state that will have direct negative impact on the economic and social longevity of the country if no solution is found.

2. Discussion and Analysis: Finding the root of the problem

A low fertility rate is inherently a self-reinforcing effect in a developed society such as Singapore. As the birthrate falls, the population for each new generation that will mature and become responsible for future births decreases as well. This indicates that if the impetus driving the birthrate down is not found and addressed the problem will only continue to get worse.

2.1. Current coping strategy
The most dominant strategy to help alleviate the low fertility rate in Singapore is to encourage a high inflow of immigration. The National Population and Talent Division of Singapore estimates that an inflow of 20,000 – 25,000 new citizens per year will be needed to sustain the population of Singaporeans over the next couple of years (NPTD). The problem with this approach is that it is not sustainable in the long run because it does not reach the root of the problem. As more immigrants move into Singapore and the fertility rate continues to decline, the population begins to age rapidly. The median age has already increased from 30-39 within the past 20 years and it is estimated that the median age will be 47 by 2030 despite the possible success of the immigration strategy (NPDT). This aging further exacerbates the self-reinforcing effect of the low fertility rate because many immigrants move into Singapore without intention to bear a child.

2.2. Is the high cost of living the problem?

Many believe that the high cost of living and raising a child in Singapore directly attributes to the low fertility rate in Singapore. This reasoning might appear as the most logical explanation especially considering the demographic-economic paradox related to fertility rate. This paradox highlights the inverse correlation between wealth and fertility within nations. The paradox affirms the idea that a highly developed and relatively rich country such as Singapore should have a low birthrate due to low mortality rates and high costs associated with maintaining the developed social infrastructure and amenities (D-E Paradox). This trend can be displayed in Figure 1 below displaying data from the United States’ Central Intelligence Agency that shows the relationship between GDP per capita and fertility rates (CIA 2009).

Figure 1. The Demographic-Economic Paradox

Although Figure 1 demonstrates that there is clearly a negatively correlating trend, it is important to note through closer examination that after a country reaches a threshold of $20,000 GPD per capita the correlation appears to cease. Figure 2 below displays data from the CIA that only includes a set of countries with GPD per capita greater than $20,000 (CIA 2013).

Figure 2. Total Fertility with GPD per capita >$20,000

In this case there is even a positive correlation coefficient of .163 between the variables and Singapore is clearly the biggest outlier with a fertility rate visibly below every other country. The above graph argues that the abnormally low fertility rate is not simply a factor of high cost and there must be some other variable in question. This concept is agreed upon by the former Prime Minister Lee Kuan Yew who is even willing to offer a baby bonus equal to two years the average Singaporean’s salary in order to, “…prove that super-sized monetary incentives would only have a marginal effect on birth rates.” Yew asserts that he would offer this bonus for at least one year. He hopes that the results of this experiment will, “prove beyond any doubt that our low birth rates have nothing to do with economic or financial factors such as high cost of living or lack of government help for parents” (Lee 2013). Although Yew is correct about the failure of monetary incentives, one must beg to differ that he is entirely incorrect when he states that the low fertility rate has nothing to do with ‘economic factors’. This is because fertility rate is inherently an epitome of economic incentives. Economics is defined as a, “social science that studies how individuals, governments, firms and nations make choices allocating scarce resources to satisfy unlimited wants” (Economics). The decision to have a child requires one to sacrifice a large amount of his or her scarce resources to sustain someone that will be added to a society that is constantly consuming. This child will only add to the consumption with more unlimited wants and aspire to acquire an individual share of the increasingly scarce resources within the society. This means that the decision to have a child must be influenced by some economic cost that Prime Minister Yew overlooks.

2.3. The problem becomes clear in time

Singapore is notorious for being one of the hardest working countries in the world. Data affirms this with a study by the Federal Reserve Economic Data organization (FRED) finding that Singaporeans work on average 2287 hours a year (Feenstra 2011). Of the 52 countries participating in this study, the four listed below in Table 1 are the only countries that averaged above 2100 working hours a year. Note that the fertility rate data in the table comes from the CIA.

Country | Fertility Rate | Working Hours | Singapore | 0.79 | 2287 | Taiwan | 1.11 | 2144 | Hong Kong | 1.11 | 2344 | South Korea | 1.24 | 2193 | Table 1. Countries with Yearly Working Hours above 2100

These four countries with the most working hours also happen to be four out of the five countries listed by the CIA with the lowest fertility rates in the world. The fifth country not listed is Macau. It does not make this list because it was not included in FRED’s study. To keep the data consistent there will be no crossing of sources for the same variable. Figure 3 below represents the correlation of fertility rate and working hours using the same exact same countries from figure 2.

Figure 3. Yearly Working Hours and Total Fertility Rate

The above graph clearly displays a strong negative correlation between both variables. The correlation coefficient between all of the data is -.674. Accounting for all the 37 countries used in FRED’s study that had a GDP above $20,000, the two-tailed probability value for this data is .00000481. This value is simply too small for the data to not be considered statistically significant under almost any conventional alpha level. The data strongly indicates that long working hours have a negative impact on the fertility rate. This is also the most logical explanation for the problem. The more time people spend at work, the less time they have to commit to raising a child yet alone meeting and attracting a mate. The people of Singapore decide against having a child not due to monetary pressures, but rather the opportunity cost of their most valuable resource – time. It is also important to note that this decision is not necessarily made consciously. The work culture of the country keeps people so occupied by their jobs that they do not necessarily consider the opportunities that they are missing out on if they had more free time to socialize, meet mates, and raise a family.

3. Solving the problem by changing the work culture

It is clear that the culture of Singapore revolves around working long hours. It is also evident that these long hours are one of the major contributors to the low fertility rate. Offering a subsidy to the people for having children does nothing to solve the root problem because it does not give them more time. The most logical solution to the problem is to not focus on money, but instead attempt to change the work culture. The government must subsidize the companies rather than the people to initiate this change. There should be a subsidy provided to companies that can quote shorter working hours for employees that use a system to check in and out of work.

3.1. All parties will benefit from the subsidy

If corporations have an incentive for people to work shorter hours, then they will encourage workers to leave when they have completed the tasks on their daily agenda. The cultural norm of people staying idle at work after they have completed their jobs waiting for their boss to leave will effectively be eliminated. With shorter hours the workers will be happier with their lives and perform better for their companies. People will also stay focused and motivated to perform more efficiently with the less time they spend at work. Companies that take advantage of this subsidy in the correct ways will have the ability to increase employee happiness, maintain or raise productivity, and reap the lucrative payout from the government. The government will benefit greatly from offering this subsidy because when people work shorter hours they will help stimulate the economy and raise the fertility rate. The average Singaporean would not necessarily just eat dinner after work, watch some TV, and then go straight to bed. The working class will have time to spend money out socializing, go out and meet their future wives, spend time with their families, raise their children, and develop a culture for the country that is not entirely work-oriented.

3.2. Do company subsidies work?

If the government provides enough of an economic incentive it is guaranteed that the companies will be motivated to reduce their working hours to a more reasonable quota. The power of subsidies on companies can be demonstrated by the effect it has on American corporations. The United States government spends approximately 50% more on corporate subsidies than it does on social welfare programs (Budget). These large corporate subsidies effectively moderate and control certain variables such as energy consumption and production output over a wide variety of industries. Company subsidies are already used in Singapore to help deal with social issues caused by externalities of the low fertility rate. An example of this would be a subsidy called the Special Employment Credit. This subsidy gives periodic cash payouts to employers that hire older Singaporeans. Due to the success and effectiveness of this subsidy, the Singapore government even decided to extend the policy to 2016 (Tan). If the government is already willing to offer subsidies to deal with aging population, then it should not hesitate to offer a subsidy that will lower working hours and solve the root of the problem.

4. Conclusion

This paper has argued that the abnormally low fertility rate in Singapore must find a sustainable solution in order to secure the future welfare of the population. The findings in the research suggest that the cause of the problem can be greatly attributed to the over-worked population of Singapore. The most effective solution to the issue would be to change the work culture that is engrained within the population through government subsidies on businesses that encourage shorter working hours. If this subsidy is incorporated in a strategic and influential manner then all parties have the potential to benefit from it.

References

Budget 2012. (n.d.). Budget 2012. Retrieved November 14, 2013, from http://www.budget.gov.nl.ca/budget2012/

Central Intelligence Agency. (n.d.). The World Factbook. Retrieved November 14, 2013, from https://www.cia.gov/library/publications/the-world-factbook/rankorder/2127rank.html

Demographic-Economic Paradox. (2013, August 11). Wikipedia. Retrieved November 14, 2013, from http://en.wikipedia.org/wiki/Demographic-economic_paradox

Economics. (n.d.). Investopedia. Retrieved November 14, 2013, from http://www.investopedia.com/terms/e/economics.asp

Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2013), "The Next Generation of the Penn World Table" available for download at www.ggdc.net/pwt

Lee, K. Y. (2013). One man's view of the world. Singapore : Straight Times Press Books.

National Population And Talent Division. (n.d.). National Population And Talent Division. Retrieved November 14, 2013, from http://www.nptd.gov.sg/content/NPTD/home.html

Tan, M. (2012, February 18). More subsidies for firms that hire older Singaporeans. The Straight Times. Retrieved November 14, 2013, from http://www.spring.gov.sg/NewsEvents/ITN/Pages/More-subsidies-for-firms-that-hire- older-Singaporeans-20120218.aspx#.UoWknWQpYs1

Data Appendix

Fertility Rates, GPD, and Working Hours

All of the analyzed data pertaining to fertility rate and GPD in this paper comes from the reputable Central Intelligence Agency (CIA) that does government research for the United States. The data for working hours is taking from the respected Federal Reserve of Economic Data (FRED) that uses disciplined research methods to acquire accurate data. A table of the raw data used for research can be displayed below.

| GDP Per Capita | Working Hours | Total Fertility Rate | Australia | 43,300 | 1699 | 2.27 | Austria | 43,100 | 1662 | 1.77 | Barbados | 25,800 | 1764 | 1.42 | Belgium | 38,500 | 1545 | 1.65 | Canada | 43,400 | 1708 | 1.59 | Cyprus | 27,500 | 1839 | 1.46 | Czech Republic | 27,600 | 1830 | 1.29 | Denmark | 38,300 | 1527 | 1.73 | Estonia | 22,100 | 1923 | 1.45 | Finland | 37,000 | 1680 | 1.73 | France | 36,100 | 1476 | 2.08 | Germany | 39,700 | 1406 | 1.42 | Greece | 24,900 | 2038 | 1.4 | Hong Kong | 52,300 | 2344 | 1.11 | Hungary | 20,000 | 1959 | 1.41 | Iceland | 39,900 | 1739 | 1.88 | Ireland | 42,600 | 1802 | 2.01 | Italy | 30,600 | 1774 | 1.41 | Japan | 36,900 | 1706 | 1.39 | South Korea | 32,800 | 2193 | 1.24 | Lithuania | 22,000 | 1857 | 1.28 | Luxembourg | 81,100 | 1518 | 1.77 | Malta | 27,500 | 1833 | 1.53 | Netherlands | 42,900 | 1382 | 1.78 | New Zealand | 30,200 | 1697 | 2.06 | Norway | 55,900 | 1421 | 1.77 | Poland | 20,900 | 2047 | 1.32 | Portugal | 23,800 | 1942 | 1.51 | Singapore | 61,400 | 2287 | 0.79 | Slovakia | 24,600 | 1793 | 1.39 | Spain | 31,100 | 1685 | 1.48 | Sweden | 41,900 | 1640 | 1.67 | Switzerland | 46,200 | 1623 | 1.53 | Taiwan | 39,400 | 2144 | 1.11 | Trinidad and Tobago | 20,400 | 1639 | 1.71 | United Kingdom | 37,500 | 1650 | 1.9 | United States | 50,700 | 1704 | 2.06 |