We have refined the index somewhat, making it more directly related to natural disaster proneness, by excluding disasters of a political nature. For this reason we have excluded damage caused by civil strife. We have tested the correlation of this index with GDP per capita, and again found no statistically significant correlation between the two variables Table 3, which summarizes the more detailed data of Appendix 2c, shows that, according to this index, SIDS tend to be more disaster prone than other countries.
Three such variables are environmental fragility, dependence on foreign sources of finance and demographic changes. However, we have decided not to include these three variables on the following grounds: Non-measurability. This applies to environmental fragility. Although some environment indices exist see for example UNEP , the data they convey is not suitable for the purpose of our index, as was explained above.
Relation with GNP per capita. This applies to indices related to dependence on international financial transfers remittances and international aid and to outward migration. These tend to be related to the economic performance of the country concerned. These were left out because, as stated above, the object of the vulnerability index is not to measure economic performance, but economic fragility in the face of external forces. Max Xi - Min Xi where: Vij stands for the degree of vulnerability arising from the ith variable for country j.
Xij stands for the value of the ith variable included in the vulnerability index, for country j. Max Xi and Min Xi stand for the maximum and minimum value of the ith variable for all countries in the index. If a given country's vulnerability variable takes a value of Xij equal to the minimum value of that same variable, the value for Vij would be zero, and this would correspond to minimum vulnerability arising from that same variable.
On the other hand, the greater the gap between the reading of a particular country's vulnerability variable and the minimum value of that same variable, the higher will be the value of Vij, so that the country with the maximum value would have a vulnerability score of 1 with respect to that variable. In this manner, the index would take a value of between 0 and 1. In our case, we have three sub-indices which represent different dimensions of vulnerability and which are to be combined together to yield a single valued indicator.
The simplest method of combining the effect of the sub-indices is taking a simple average. This would be an equally weighted index. An alternative is to use different weights for each variable, on the assumption that the different variables have a different impact on vulnerability. Unfortunately, in the case of our index, there is no way in which such weights can be established on a priori grounds or on statistical grounds. The best one can do in this case is to assume different weights and compare the results.
In our case, the sub-indices are uncorrelated, and therefore significantly different weights are likely to produce different results. We have experimented with two sets of weights. The first is an equally weighted index.
The magnitudes of both sets of weights are essentially arbitrary, but there is the following reason for the ranking in the second set. It could be argued that economic exposure is the most important factor that renders a country economically vulnerable to forces outside its control, since this variable is related to the extent to which the country's economic performance is determined by conditions in the rest of the world.
The index of transport cost, reflecting insularity and remoteness, is also related to economic vulnerability, in that, among other things, it allows for an element of uncertainty in foreign trade, but it can be held that this variable is not as important as economic exposure. The equally weighted index produced similar, though not identical results, in that in general SIDS tended to register high vulnerability scores.
The main difference was that countries which were disaster prone registered higher scores in the equally weighted index The results to be reported below will focus on the index with the second sets of weights, based on the arguments just put forward.
It is pertinent to state here that alternative weighting schemes would not solve the problem of subjective choice in this regard. The scores are summarized in Table 4. This table also gives a summary of scores of an index which assigns equal weights to the three sub-indices.
As stated, the general tendency that SIDS have higher vulnerability score is apparent in both indices. The results shown in Appendix 1 and Table 4 are interesting, and confirm the assumption that SIDS tend to be more vulnerable than other groupings of countries.
In general, SIDS registered higher vulnerability scores than developing countries. As stated elsewhere in this study, the composite index is a form of average, which hides the effect of the individual sub-indices.
Although separate sub-indices do not have the appeal of a single composite index giving a single-valued ranking, there is something to be said in favour of presenting the sub-indices separately. One reason is that they individually convey useful information. Another reason is that a composite index, as Hicks and Streeten argue, implies some form of trade-off between the variables composing the index, which have to be met together.
Averaging would conceal, for example, situations where the effect of one variable cancels out the effect of another. For these reasons we are also presenting the sub-indices in Appendix 3. This Appendix shows that SIDS, especially the small ones, tend to be vulnerable as a result of the three variables, although there a number of exceptions. This is confirmed in Table 5 which gives averages of GDP per capita and of the Human Development Index for detailed data see Briguglio, , Appendices 7 and 9 of different country groups and compares them to the Vulnerability Index.
As a matter of fact, their scores are higher, on average, than those of developing countries in general. However, on average, these countries are characterized by a high vulnerability scores. The question may arise here is to whether or not the data in Table 5 suggests that the economic fragilities of SIDS are actually the reason for their relatively high GDP per capita and Human Development Index.
The fact that many SIDS have done relatively well in terms these indices, has prompted some observers to argue that being small and insular is not a disadvantage alter all. This line of argument may of course contain an element of truth, in that smallness has its advantages, including a high degree of flexibility in the face of changing circumstances.
However the handicaps and fragilities described above are a reality in many SIDS, and the success stories of some of them was probably achieved in spite and not because of their small size and insularity. Unlike larger states, small ones can never take their viability for granted, and they are perpetually in a sink or swim situation. The interest of these powers in SIDS has given rise to what may be called "artificial" props to the economy of the islands, in terms of, among other things a relatively large amounts of transfers and free technical assistance; and b preferential access to the markets of developed countries in industrial and agricultural products.
Because of their intrinsic economic vulnerabilities, many SIDS may not have survived as independent states in the absence of these "artificial" props. Furthermore, it could be argued that the relatively large financial transfers to SIDS may have pushed up their GDP per capita to levels higher than what one would expect from countries continually facing the constraints associated with small size and limited resources.
The relatively high growth rates which many SIDS experienced during the eighties may also give a misleading picture of the strength of the economies of these countries. In many instances, the growth pattern of such countries has been unstable and erratic as was the case in many Caribbean Islands, see World Bank, , p. For this purpose we have constructed a simple index which, for ease of reference and for lack of a better name, we call the "Vulnerability Adjusted Development Index" VADI.
This index consists of a simple average of the GDP per capita and the vulnerability index. The results are given in Appendix 3, where it can be seen that in the case of most SIDS the vulnerability index "weights down" the GDP per capita index.
For example, Antigua and Barbuda have a very high vulnerability score ranked number 1 in terms of vulnerability among all countries. At the same time, this country has a relatively high GDP per capita score ranked 78, where rank 1 indicates the poorest country among the included in the table.
A list of such countries also appears in Appendix 3. Again here, the results appear to be interesting, since they indicate that many small states, most of whom are also islands, have an economy which appears stronger in terms of GDP per capita, than in terms of a Vulnerability Adjusted Development Index.
Normally, the criteria as to which variables are to be included and weighted are chosen by the compiler. In general one finds that there are no hard and fast rules for rejecting or accepting the results.
Indices of this type are also sometimes criticized because they contain errors of measurement. Care however has been taken to base the choice of variables on plausible assumptions as to what renders an economy vulnerable to forces outside its control, and to use suitable methods of measurement and weighting, guided by the simplicity and comprehensibility criteria outlined at the beginning of Section 4.
For example, in the case of the economic exposure index, it is quite possible for a country to be very economically exposed, but has not yet developed enough or is not competitive enough to foster foreign trade. Such errors in measurement may have been the cause of a number of unexpected, and perhaps implausible, rankings in the Vulnerability Index.
Clearly, this aspect of the index needs to be investigated at some more depth. Moreover, certain data are not very easy to procure. The most difficult task in this regard would seem to be that of obtaining regular updated data on disaster proneness. The index produced by UNDRO is an important step in this direction, but it has to be produced on a yearly basis.
There is also the need for further study to improve the remoteness index by means of data which measures this variable, keeping other things constant.
The index chosen in the present study has the merits that it can be very easily obtained from balance of payments statistics. But it may capture factors which are not directly related to remoteness, such as monopolistic practices in the domestic carrier-companies and other market distortions. Conclusion In this study we have described the most important factors which render a small island developing state relatively weaker than other countries in the face of factors outside its control, and we have proposed a method for constructing an index to measure economic vulnerability.
Assess its effectiveness in promoting economic development. Compare inward looking and outward looking strategies and discuss the assertion that the latter is superior. The First Stage of Import Substitution : All present day industrial and developing countries protect their manufacturing industries for the domestic markets. While the industrial countries of.
You are expected to refer relevant articles from recognized sources on the said areas and provide your own views and analysis with proper reasoning. Export means shipping the goods and services out of the port of a country. This theory was put into practice by developing nations throughout the 20th century as a response to economic inferiority to nations with significant industrial output. An import quota is a restriction placed on the amount of a particular good that can be imported.
This sort of barrier is often associated with the issuance of licenses. For example, a country may place a quota on the volume of imported citrus fruit that is allowed.
This type of trade barrier is "voluntary" in that it is created by the exporting country rather than the importing one. A voluntary export restraint VER is usually levied at the behest of the importing country and could be accompanied by a reciprocal VER.
Canada could then place a VER on the exportation of coal to Brazil. This increases the price of both coal and sugar but protects the domestic industries.
Instead of placing a quota on the number of goods that can be imported, the government can require that a certain percentage of a good be made domestically. The restriction can be a percentage of the good itself or a percentage of the value of the good.
In the final section, we'll examine who benefits from tariffs and how they affect the price of goods. The benefits of tariffs are uneven. Because a tariff is a tax, the government will see increased revenue as imports enter the domestic market. Domestic industries also benefit from a reduction in competition, since import prices are artificially inflated.
Unfortunately for consumers—both individual consumers and businesses—higher import prices mean higher prices for goods.
If the price of steel is inflated due to tariffs, individual consumers pay more for products using steel, and businesses pay more for steel that they use to make goods. In short, tariffs and trade barriers tend to be pro-producer and anti-consumer.
The effect of tariffs and trade barriers on businesses, consumers, and the government shifts over time. In the short run, higher prices for goods can reduce consumption by individual consumers and by businesses. During this period, some businesses will profit, and the government will see an increase in revenue from duties.
In the long term, these businesses may see a decline in efficiency due to a lack of competition, and may also see a reduction in profits due to the emergence of substitutes for their products. For the government, the long-term effect of subsidies is an increase in the demand for public services, since increased prices, especially in foodstuffs, leave less disposable income. Tariffs increase the prices of imported goods.
Because of this, domestic producers are not forced to reduce their prices from increased competition, and domestic consumers are left paying higher prices as a result. Tariffs also reduce efficiencies by allowing companies that would not exist in a more competitive market to remain open.
The figure below illustrates the effects of world trade without the presence of a tariff. In the graph, DS means domestic supply and DD means domestic demand. At a lower price, domestic consumers will consume Qw worth of goods, but because the home country can only produce up to Qd, it must import Qw-Qd worth of goods. When a tariff or other price-increasing policy is put in place, the effect is to increase prices and limit the volume of imports. Because the price has increased, more domestic companies are willing to produce the good, so Qd moves right.
This also shifts Qw left. The overall effect is a reduction in imports, increased domestic production, and higher consumer prices. The role tariffs play in international trade has declined in modern times. One of the primary reasons for the decline is the introduction of international organizations designed to improve free trade, such as the World Trade Organization WTO.
Because of this, countries have shifted to non-tariff barriers , such as quotas and export restraints. Organizations like the WTO attempt to reduce production and consumption distortions created by tariffs. They will be different customers with their own reasons for buying your products. In this guide: Introduction How can I start exporting? Is my product suitable for exporting? Printer-friendly version. Invest NI Helpline. Also on this site.
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