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Principle of population

Introduction
In An Essay on the Principle of Population, Thomas Robert Malthus predicted that the population growth must eventually outstrip the growth of resources. Therefore, he argued that low population growth and high economic growth could not happen at the same time. In the pre-industrial world for millennia, Malthus’ principle seemed to appear. However, in contrast to Malthus’ projection, not only low population growth rates but also high economic growth rates were observed in the industrialising capitalist countries of Europe during the 20th century. This inconsistency between Malthus’ principle and the case of European countries induced various opinions about Malthus’ proposition and analyses explaining how those countries could escape from stagnation.
This paper examines why Malthus’ thesis failed to apply in the case of European countries industrialised and capitalised. It, first, introduces Malthus’ principle briefly then analyses the inconsistency between Malthus’ principle and data and other factors that Malthus overlooked. After this, the analysis focuses on several forces which played important roles in saving those countries from Malthusian Trap and triggering for the demographic transition from stagnation to sustained growth.
Malthus’ thesis in An Essay on the Principle of population
Thomas Robert Malthus’ Essay was published anonymously in 1798. In the essay, Malthus predicted that “the power of population is indefinitely greater than the power in the earth to produce subsistence for man” (Malthus, 1798 cited in Avery, 2005:8). Contrary to Godwin and Condorcet, Malthus believed that the scientific progress, especially to agriculture and industry, may not be able to lead humanity forward to a golden age since a growing population would probably outstrip food production thus, living standards cannot be benefited by the scientific progress.
According to Buchholz (1999), on the basis of data from United States reported by Benjamin Franklin, Malthus concluded that food supply could not keep pace with population because population, when unchecked, is capable of increasing exponentially whereas food production grows at an arithmetic ratio. For instance, the number of people would increase by 1,2,4,8,16,32,64,128,512,etc while subsistence would grow 1,2,3,4,5,6,7,8,9,etc every twenty-five years.
However, contrary to Malthus’ anticipation, human population did not obviously increase at this rate in history. Therefore, he also introduced that there are various forces operating to keep the population. Malthus classified the forces by two different checks – “positive checks” and “preventive checks”. The positive checks to population growth include disease, famine and war hence, they raise the death rate. The preventive checks, however, lower fertility by birth control, late marriage and moral restraint. In contrast to positive checks, preventive checks can be practiced.
The inconsistency between Malthus’ model and statistics
Although Malthus’ study was based on real data, Malthus missed several factors when he analysed statistics and also overlooked the technological progress. It gives us a hint why Malthus’ theory failed to apply in the case of the industrialising capitalist countries of Europe since Malthus’ thesis is not necessarily true.
The idea of Malthus’ thesis was that population growth must exceed the growth of subsistence, primarily food production, in the end. The reason for this is that population growth is exponential whereas subsistence increases in an arithmetic ratio. However, the statement that exponential growth must finally be greater than linear growth is not true because of one element: time. Deming (2004) states that “exponential growth of any arbitrary value only exceeds arithmetic growth in one uninteresting case: infinite time.” Therefore, Malthus idea is not undoubtedly true.
Using data supplied by Benjamin Franklin, Malthus could state that population can double every twenty-five years or even faster. Basically, Malthus’ assertion had no problem because Malthus chose relatively conservative examples from data. However, Malthus missed an obvious statistical point. According to Buchholz (1999), Malthus did not distinguish immigrants from natural-born Americans. In other words, Malthus just saw rising number of children who were born in United States as well as arrived in the country by boat. However, Malthus missed the fact that the statistical data included the increasing number of immigrants thus, Malthus did not divide them into two separate groups: natives and immigrants. Therefore, Malthus’ statement cannot be necessarily true because increasing population in United States during that period already included not only natural-born Americans but also immigrants.
Besides, Malthus overlooked technological advancement, especially in medicine and agriculture. Lee (2003) states that better health and medical treatment e.g. the development of the small vaccine, improved personal hygiene, improvements in nutrition etc can lower mortality. Since 1740, there was an increase in population in Europe. It means that disease, one of the positive checks, did not operate to keep the population well. In addition, unlike Malthus’ projection, food supply can keep the pace with population in consequence of the agricultural revolution such as seed breeding, crop rotation, the use of horses etc. Sachs (2008) explains that “food production can indeed grow geometrically because production depends not only on land but also know-how.” In practice, agricultural productivity per worker doubled in England between 1700 and 1800. As food productivity increased, England could not only feed her citizen but also export the crops such as cereals and flour. Because of the advancement in agriculture, increased food supplies were permitted and, consequently, famines disappeared from Europe (except for Ireland in 1840s). This fact gives us another clue not matched with Malthus’ thesis.
Moreover, a Malthusian birth spiral did not occur even though there was a higher standard of living as a result of the advances in medicine and agriculture. When Malthus looked at population statistics, Malthus did not notice the decline in the death rate. The decrease in mortality might be able to make an increase in population possible.
The Facts
Malthus’ theory can be tested to determine whether or not the thesis was correct. Since 1798 when Malthus firstly published ‘An Essay on the Principle of Population’ human populations have increased (from about 1 billion to 6 billion between 1800 and 2000). According to Malthus’ theory, food consumption per capita in 2000 should be lower than in 1800. For example, if one person had one basket in 1800, 256 people had to share 9 baskets in 2000. However, contrary to the theory, food supply has continually increased and the ratio is less than Malthus’ prediction. Furthermore, Deming (2004) also gives several facts:
* From 1600 through 1974, the percentage of the population in Great Britain employed in agriculture dropped from 67 percent to about 6 percent.
* From 1800 through 1990, the price of wheat in the United States – expressed as a percentage of wages – fell 96 percent.
* From 1800 to 2000, the population of England and Wales increased from about 9 million to more than 50 million while the inflation – adjusted price of wheat fell by more than 90 percent.
* From 1961 through 1998, the world population increased from 3.1 billion to 5.9 billion – but over the same time period world daily average-consumption of food calories increased from 2,250 to 2,800
The facts listed above would seem to refute Malthus’ thesis. Malthus’ supporters may criticise those facts since time is not enough for population growth to exceed food production. However, contrary to this opinion, 200 years may seem to be enough time to test the hypothesis. Furthermore, Malthus’ thesis by scientific status is questionable because the theory cannot be proved within any finite value of time.
Social Forces: birth control and urbanisation
Heilbroner (2000) states that there are two important factors saved European countries from Malthus trap: birth control and enormous urbanisation. This section examines how these two mechanism worked and analyses their roles in the transition.
Actually, the upper classes seem to have practiced birth control all through history thus, the rich could be richer whereas the poor had more children for increasing productivity. However, Heilbroner points out:
“as England and the West enjoyed a gradually widening affluence, the poor not only ate and clothed themselves better, but they also learned how to limit their offspring like the wealthier’ classes.” (Heilbroner, 2000:93)
Consequently, the number of families having one or two children rather than four or more increased. It means that birth rates was dropping thus, there were lower population growth rates than before although food production grew over the same time period. Therefore, birth control undoubtedly played an important role in Europe experienced low population growth rates during the 20th century.
Moreover, enormous urbanisation is equally significant when confuting Malthus’ projection. Children can be economic assets on the farm whereas they are economic liabilities in the city. As urbanisation progressed, people naturally considered birth control practices to minimise their liabilities and, in consequence, the industrialising capitalist countries of Europe could be prevented from population explosion before taking place.
Demographic Transition
Recent years, the demographic transition has been recognised as one of the major forces explaining how European countries were saved from Malthusian trap. There are various mechanism triggering for the demographic transition from stagnation to sustained growth. Galor (2005) proposed five mechanism as possible triggers: the decline in infant and child mortality, the rise in the level of income per capita, the rise in the demand for human capital: main mechanism and reinforcing mechanism and other theories.
Firstly, the decline in infant and child mortality was proposed as a possible trigger. In many developed countries, the decline in infant and child mortality rates preceded the decrease in fertility rates. 1 indicates that, in Western Europe, the decline in mortality rates started about a century before the decline in fertility. In particular, as demonstrated in 2, mortality rates in England started to decline since 1730s while fertility rates continually increased until 1820s.
In conclusion, those s show that there was population growth in Western Europe countries because the number of surviving offspring increased up to higher desirable level, but population growth rate could be lower because of the decline in infant and child mortality.
The rise in income per capita had a role in the demographic transition. As demonstrated in 1, not only the decline in fertility but also the demographic transition across the European countries occurred simultaneously during the same decade. In the same period, the level of income also increased as urbanisation and technology progressed. Consequently, Western European countries could reach the higher level of income per capita than before. In other words, the decline in fertility occurred when the rise in income per capita in the Post-Malthusian Regime was intensified thus, the demographic transition could happen. Consequently, sustained economic growth and low population growth could be both possible since the increased income played a role in the demographic transition.
As the third mechanism, the rise in the demand for human capital was suggested. According to Galor and Weil (1999), the demand for human capital increased in the second phase of the Industrial Revolution since technological progress accelerated gradually the increased demand for human capital as well as the investment in the human capital of children. There were two effects, which the technological progress and the rise in the human capital brought about, on population growth. Firstly, technological advancement reduced household’s budget constraints. Second, children could be provided more resources for the quality and these resources were reallocated.
In consequence of technological progress, parents could spend more budget to increase the average quality of their children in the early stage. However, as the demand for human capital also increased, further investments in human capital was required hence, it induced in a decrease in fertility rate. Therefore, in the second phase of the Industrial Revolution, technological brought about the increase in the demand for human capital as well as the shortage of a supply response and, ultimately, the decline in fertility generating the demographic transition because of the further investment inhuman capital. Consequently, the rise in the demand for human capital brought about the demographic transition thus, the transition could make a decline in population growth possible whereas there existed the increase in economic growth.
There are also several factors reinforcing the demographic transition as the fourth mechanism and they are closely connected with human capital.
First, the decline in child labour reinforced the decline in fertility rates. As the importance of the rise in human capital and the reduced number of surviving offspring, the wage differential between parental labour and child labour increased. In addition, “industrialists supported laws that abolish child labour.” (Doepke, 2004 cited in Galor, 2005:501) It induced parents to further invest in children for increasing their quality and to reduce the desirable number of children.
The rise in life expectancy reinforced the reduction in fertility rates. In consequence of the rise in a technological demand for human capital, investments in human capital, especially, further education for children also increased. Furthermore, the return to parental investment in children’s quality increased as a result of the rise in the duration of productive life. It means that the rise in life expectancy not only induced further investment in education but also associated with the decline in fertility rates since the desirable number of surviving offsprings reduced.
During the last two centuries, there is the decline in the gender gap and it has reinforced the demographic transition as well. As technology progressed and capital accumulated, mental-intensive tasks required more than physical-intensive tasks and, consequently, the demand for women’s labour increased. Accordingly, the reduction in the wage differential between men and women occurred and it motivated women to participate in labour production. Consequently, the cost of child rearing was proportionally increased more than household’s income because of a increase in women’s labour force participation and, eventually, it induced a decline in fertility as well as a shift from stagnation to growth.
Galor (20005) proposes natural selection and the evolution of preference for offspring quality as another factor. Galor argues that individuals with a high valuation for quality gained an evolutionary advantage and generated higher income. Therefore, as evolutionary process intensified, fertility would decline and technological progress also intensified. The reason for this is that a rise in investment in human capital generated the increased returns to human capital and it reinforced the substitution toward offspring’s quality.
Overall, those factors as the fourth mechanism mentioned decreased fertility rates thus, reinforced the demographic transition. Furthermore, the decline in child labour and in the gender gap and the rise in life expectancy also induced further investments in children’s quality. Consequently, they played a significant role in sustained economic growth.
Finally, the old-age security hypothesis and exogenous shocks like luck are suggested as an additional mechanism. Although there are some arguments whether or not those two hypotheses induce the demographic transition, they act as a mechanism for the beginning of the demographic transition.
Conclusion
According to Malthus, economic growth induces population growth, but a growing population would eventually outstrip food production since the rise in population growth is greater than the rise in economic growth. Therefore, living standards might be driven back toward subsistence level. Malthus’ projection seems to be correct in history, especially during the pre-industrial world.
However, contrary to Malthus’ theory, European countries recorded low population rates while they experienced high economic growth rates during the 20th century. Hence, Malthus’ principle cannot explain the case of those industrialising capitalist countries of Europe. There are several reasons why Malthus’ thesis fails to apply in that case.
First of all, the inconsistency between Malthus’ model and statistical data demonstrates why Malthus’ principle failed to describe the case. When Malthus made a model by analysing statistical data from the United States, Malthus missed an obvious statistical point: Malthus did not distinguish immigrants from natural-born Americans. Therefore, Malthus’ thesis cannot be necessarily true. Furthermore, Malthus also overlooked two significant factors: time and technological advancements in medicine and agriculture. The theory can only make sense under one condition: infinite time. It means Malthus’ hypothesis is enough questionable because it cannot be proved by scientific status. In addition, unlike Malthus’ projection, technological advances made high economic growth possible, in spite of population growth. Several facts support the inconsistency.
Second, social forces i.e. birth control and enormous urbanisation also played an important role. In consequence of birth control and urbanisation, European countries not only experienced low population growth but were also prevented from population explosion before taking place whereas there was high economic growth during the same period.
Finally, the demographic transition has been recognised as a prime force. There are several factors triggering the demographic transition. For instance, the decline in infant and child mortality, the rise in the level of income per capita, the rise in the demand for human capital etc. All those factors reinforce the demographic transition as well as the sustained economic growth. Therefore, how the industrialising capitalist countries of Europe were saved from stagnation during the 20th century can be also analysed by the demographic transition.
In conclusion, Malthus’ principle did fail to apply in the case of European countries in the 20th century even though it could demonstrate the situation of the pre-industrial world. In contrast to Malthus’ projection, it shows that low population growth rates can be occurred in spite of high economic growth rates.

Case Analysis On Merloni Elettrodomestici Spa Economics Essay

Merloni Elettrodomestici SpA is an Italian company based in Fabriano and is one of Europe’s biggest makers of home appliances. In February 2005, Merloni Elettrodomestici was renamed Indesit Company, Indesit being the best known of the Group’s brands outside Italy. The Company was also operating under its “historic” brand, Ariston, and the regional brands Hotpoint, Scholtes and Stinol.
During the perio from 1984 to 1986, Merloni undertook a number of initiatives to improve efficiency in inventory control and logistics. One such initiative was the transit point experiment where in the Milano region, regional distribution centre was eliminated in favour of tranit points which held zero inventory.
The following is an analysis of the Transit Point Experiment conducted by Merloni:
Cost saving in terms of infrastructure cost of regional warehouses and their maintenance.
The company would require lesser amounts of overall inventory to be maintained.
As regional warehouses would be closed there would be lesser labor requirements.
Transit Point methodology works similar to JIT where-in the required amount of goods are shipped at the required time.
Since it works more on the Pull from the customer and due to elimination of regional warehouses, the effect of bullwhip should be lower.
Because the regional warehouses will be eliminated, the capacity storage of the central warehouses should be expanded to meet the requirements of the extra Cycle inventory. This would come as an additional cost to the company.
Intensive planning of daily shipment should be done. It is not only required to calculate the exact amount of goods to be shipped but also the arrangement of the goods (to eliminate time in loading/unloading activities).
Because of this intensive planning more skilled administration staff would be required.
If the customer does not order wihin 3pm, the delivery of the product would happen only after the second day. This can lower customer satisfaction.
Since no inventory is maintained in near-by locations (as all goods come from central warehouse) if there is any excess demand or out of stock condition (for retailers), the goods will have to be fetched from central warehouse which would take a lot of time. This can lead to loss of goodwill with retailers especially those serving the rural markets.
Demand variability is not easily supported by employing Transit Point methodology. If there is an urgent demand for goods in excess of truckload capacity then it can lead to huge additional cost.
Another important point which is not mentioned in the case is the importance of the transportation medium. If any of the vehicles breaks-down it could lead to huge delays and pile up of demand. Merloni needs to keep some extra vehicle for a backup. It also needs to maintain the vehicles in good condition. The cost of this has not been accounted for. Since the experiment was carried out only in Milano a relatively smaller numbers of trucks (1 Trailer truck and 3 Small trucks) were required.
If the Transit Point methodology is applied through-out Italy, Merloni will need to build up infrastructure and teams to coordinate the the movement of trucks and their transactions.
In Merloni, it is the responsibility of the warehouse manager to manage and develop the customer relationship. If the warehouses are eliminated Merloni would still need additional office space for the warehouse managers who also act as Customer Relationship Managers.
Another important question is where would Merloni keep the spare parts required for its service personnel. If these too are kept at the central warehouse it could lead to delay thus have a negative impact on the quality of service.
The Merloni experiment was conducted when the weather was good. If the weather is bad near the central warehouse but alright in other areas where there is demand, then it can lead to delays. The cost of such delays would be large as Merloni would have to use extra vehicles to ensure the earliest delivery of all the goods once the weather becomes good.
Quantitative Analysis:
Now we shall look at a quantitative analysis of cost incurred by the company before and after using Transit Point methodology. The case is for region of Roma (information as per exhibit 10). (Ax) would represent cost incurred by using Pre-Transit Point methodology and (Bx) would denote cost incurred by using Transit Point methodology.
Calculate the Average Volume/Month at the Regional Distribution Centre (RDC) in Roma.
Assuming 20 working days in a month.
Average daily demand served from regional warehouse = 154.8 pieces
Average Volume/Month = Average daily demand x No of working days
= 154.8 x 20
= 3096 pieces.
Operating Cost at RDC
From exhibit 10 of the case it can be seen that the operating cost at Roma is 3605 Lire/Piece/Month
Average inventory levels at RDC = 1200 pieces (from Exhibit 8a)
Total Operating Cost/Month at Roma RDC = Operating Cost/Piece/Month x Avg Inventory
= 3605 x 1200
= 4326000 Lire
Therefore, Operating Cost per piece sold = Total operating cost / No of pieces sold
= 4326000 / 3096
= 1397.28 Lire – (A1)
As per the case, by using Transit Point methodology the Operating Cost has reduced to 20%.
Therefore, New Operating Cost per piece sold = 20 % of original Total Operating Cost
= 0.20 x 1397.28
= 279.45 Lire -(B1)
Inventory Cost at RDC
From exhibit 10 of the case it can be seen that the inventory cost at Roma is 1035 Lire/Piece/Month.
Total Inventory Cost / Month = Invetory Cost/Piece/Month x Avg Inventory
= 1035 x 1200
= 1242000 Lire
Inventory cost per piece sold = Total inventory cost / No of pieces sold
= 1242000 / 3096
= 401.16 Lire. – (A2)
Using the Transit Point methodology, zero inventory is maintained.
Therefore, Inventory cost per piece sold = 0 Lire – (B2)
Short Haul Transportation Cost
The short haul transportation cost is the cost of transporting goods from regional warehouse or transit point to retailers. This cost would be common for both pre and during Transit Point methodoly usage period
Short Haul Transportation cost = 4300 Lire/Piece – (A3),(B3)
Long Haul Transportation Cost
is the cost of transporting goods from the central warehouse to the regional warehouse or transit point.
During the pre Transit Point period goods were transported from the central warehouse to the regional warehouses using trailer trucks.
Total number of pieces to be shipped per month = 3096 pieces
Capacity of one trailer truck = 120 pieces
Therefore, Number of trailer trucks required = Total quantity / Capacity of trailer truck
= 3096 / 120
= 25.8 trucks
Distance between Roma and Fabriano = 165 Km approx. (source: http://www.distance-calculator.co.uk/distance-from-fabriano-to-rome.htm)
From Exhibit 11, Cost of using a trailer truck for transport upto 165 Km = 0.36 Million Lire
Therefore, Total transporation cost = Cost/Truck x No of trailer trucks
= 360000 x 25.8
= 9288000 Lire
Transportation cost per piece sold = Total transportation cost / No of pieces sold
= 9288000 / 3096
= 3000 Lire – (A4)
In Transit Point methodology both trailer truck and smaller trucks can be used depending upon the lot size.
Since the average daily demand is 154.8 pieces, a minimum of one trailer truck will have to be used every day.
i.e. Total volume of goods carried by trailer trucks/month = No of trailer truck in a month x Volume carried by 1 trailer truck
= 20 x 120
= 2400 pieces
The remaining amount would be carried by smaller trucks.
Volume to be carried by smaller trucks = 3096 -2400
= 696 pieces.
Therefore, No of smaller trucks required per month = Volume carried by smaller trucks / Capacity of smaller truck
= 696 / 45
= 16 trucks
This means that in addition to trailer truck a smaller truck also needs to be done for 4 days in every week.
From Exhibit 11, Cost of using a smaller truck for transport upto 165 Km = 0.2 Million Lire
Total transportation cost = (Cost / Trailer truck x No of trailer trucks) (Cost / Small truck x No of smaller trucks)
= (360000 x 20) (200000 x 16)
= 10400000 Lire
Transportation cost per piece sold = Total transportation cost / No of pieces sold
= 10400000 / 3096
= 3359.17 Lire -(B4)
Inventory cost at central warehouse
Because the regional warehouses are going to be removed, some amounts of inventory will be moved to the central warehouse.
Total inventory level at all 17 regional warehouses = 14330 pieces
Assuming 50% of this is Cycle Stock and the remaining Safety Stock, the Cycle Stock (= 7165) will be moved to the central warehouse.
Average Safety stock = 7165 / 17
= 421 pieces.
Safety stock required at central warehouse as per Risk Pooling = 421 x √17
= 1735 pieces.
Therefore, additional stock required at central warehouse = Safety stock Cycle stock
= 1735 7165
= 8900 pieces.
Assuming inventory cost as those prevailing in Roma, the extra inventory cost at central warehouse = 8900 x 1035
= 9211500 Lire
Additional inventory cost/month/piece sold = 9211500/(20*3096)
= 148.76 Lire -(B5)
Therefore, Total Cost incurred by the company before deploying Transit Point methodology
= (A1) (A2) (A3) (A4)
= 1397.28 401.16 4300 3000
= 9098.44 Lire
Total Cost incurred by the company by deploying Transit Point methodology
= (B1) (B2) (B3) (B4) (B5)
= 279.45 0 4300 3359.17 148.76
= 8087.38 Lire
Therefore by using Transit Point methodology, Merloni has saved 1011.06 Lire.
Now taking this Transit point experiment to India, we can make the following observations
Geography – The geography of India is different from Italy. India is equally wide in North- South and East – West directions. The approximate width is ~3500Kms. This is very high compared to Italy. The towns and cities are farther apart compared to Italy. For a product like home appliances (refrigerator , washing machine , dish washer etc) the market is still in towns and cities in India. The road conditions are also not that good. This means the transportation time between cities will be more compared to Italy. Another point to consider is the demand in a town; this may not be enough to meet a truck load of products. Company will have to find a way to store the excess products which is not being supplied. See exhibit1 for details.
Infrastructure – Another option we can consider is to have a transit point method for big cities like Mumbai, New Delhi, and Bangalore etc. We can have a transit point set up in outskirts of city and we can have small trucks to distribute units to retailers. This will help to free up or reduce the storage space in ware house in each city. But this again will depend on where you have the center ware house located and will be applicable only if ware house is in a day’s drive from the city. Also we can try this in states like Kerala where the towns are closer by. But even though this frees up inventory storage space, company may still have to have a small space to store items which don’t get distributed or collected the same day. As given in Merloni case we will not be able to leave products in alley or plan to keep in sales office as space is a big constraint.
As in Merloni case we may not be able to reuse the storage space for an exhibition house in the case of India, as the storage location is located in outskirts of city in most places. The market segment for home appliances is the people who stay in the city limits and will be reluctant to travel so much for buying a home appliance.
Transportation – The fuel price costs and spare parts costs will contribute to the transportation cost and will drive it higher. This in turn will result in a higher transportation cost per unit and will eat into the margins. This will be significant in case of a transit point experiment since the delivery is made per day. Another concern is the quality of service – timely delivery and state of goods delivered. The time of delivery is very critical in the case of a transit point plan. The delivery to the hub should reach on time to ensure the timely delivery of goods to retailers. With the poor condition of roads and lack of service/repair support along the way, there is a significant risk associated with timely delivery. If a truck breaks down, it is definitely going to add half a day delay to the delivery.
Inventory – As explained in Infrastructure section, the transit point plan will help to reduce inventory held in big cities and move the same to central ware house location. This again may help company to close down its own Storage location in cities and use private/public warehouse option for the storage of minimal inventory in cities.
Customer Service – With the transit point plan, the timely delivery of goods in big cities will improve. This will make the retailers in this area happy. But if we try to implement this pan India, it will result in poor delivery times and dissatisfaction. The reasons for this are given above.
Labor

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