cost of living

Naira has depreciated over the years; as a result posed great threat on cost of living. The cost of living has been on the increase owing to continuous depreciation of naira. Such depreciation became obvious since last quarter of 2015 as the exchange rate of naira depreciated from ₦150 to as high as ₦500 per dollar. Nigeria being an import dependent economy where virtually everything is imported including toothpick faces the risk of decline in purchasing power; this in turns affects standard of living of common man negatively. Consistent with the above, depreciation in both nominal and real exchange rate is likely to have some implications on cost of living. Theoretically, increase in nominal implies depreciation in naira value while increase in real exchange rate implies that foreign goods are expensive. Decrease in real exchange rate is an appreciation and implies that foreign goods are cheap. Some empirical evidence support this assertion. Jongbo (2014) asserts that real depreciation of exchange rate raises the cost of imported goods and by so doing increases input costs which in turn raises prices of finished goods. Increase in the prices of goods consequently reduces the purchasing power of the households.

It is certainly the case that a COGI can mismeasure the change in the cost of living (the classic example of this is to do with the tendency for consumers to substitute away from more expensive goods as prices change whilst no account is taken of this commodity substitution under COGI frameworks) but with frequent rebasing and chaining as carried out in the UK this problem may not be so serious. Proponents of COLI point out that its main benefit is that it provides a useful conceptual framework when addressing many practical issues that will be faced by National Statistical Institutes in the actual calculation of their index such as quality change and the incorporation of new goods 23 . In these

by the Czech Statistical Offi ce, specifi cally the HBS and the SILC. Both surveys provide representative data. Especially consumer spending data according to the COICOP classifi cation was collected from the HBS. The SILC data, which especially deals with the income side and living standards, was compared to the HBS. The main objective of this paper was to determine how big are revenue and expenditure diff erences between households according to the social status of a household’s head. As a negative eff ect can also be seen the rising percentage of households at risk of poverty. It was found out that households where its head is employed or self-employed are very similar to each other. Another groups whose characteristics have been very similar are pensioners and unemployed. Particular consumer expenditures of each social group were also surveyed. The largest item of household expenditures for all four social groups is the cost of living category including housing, water, electricity, gas and other fuels, followed by the category food and non-alcoholic beverages. The analysis of cost of living has showed that these costs have grown the most among pensioners since 2006 (by more than one third). Housing costs are also among the fastest growing costs of living. In 2011 pensioners’ households spent 52% of their income on housing and food. Pensioners spent the same amount of money on housing as in 2006 however the expenditures on food have decreased. It is possible that pensioners’ households have started buying cheaper food or have reduced its consumption. The paper also deals with households at risk of poverty. Based on a unifi ed EU methodology the poverty line is defi ned as 60% of median income. The least vulnerable households facing risk of poverty are of employees while the most vulnerable ones are households headed by an unemployed person.

While financial planning students are expected to be able to understand client retirement plans, subtle differences in cost-of-living adjustments can have ma jor i mpact on the success of client retirement plans. This teaching note compares the cost-of-living adjustments in the largest government sponsored retirement systems and a hypothetical traditional privately sponsored plan. Using a Monte Carlo simulation, we estimate the impact on retirement experience from the different COLAs. These differences are large, with differing protection from future inflation and differing risk for running out of money during retirement. This teaching note will help instructors address Certified Financial Planner (CFP) Board Learning Outcome G.52 “Retirement Needs Analysis”. The material may also be used in economics, human resources, public administration, and other classes addressing policy aspects of retirement plans.

The paper aims to estimate the Fisher index during the period 1994-1997 to explore how well the Laspeyres index can serve as the cost of living index. It is shown that the Laspeyres results in an upward substitution bias, and the bias appears to be higher for the ultra-poor and the poor. It means that for the very poor group the Laspeyres index overestimates their cost of living. With a limited budget the poor tends to have substitution to ensure a certain level of living standard. This suggests a remarkable point that if the basket weights are not revised frequently the Laspeyres index can present a significant bias from the cost of living, and this bias tends to be higher for the poor group. Since there is not a significant difference in the CPI between the poor and the non-poor and the whole population, CPI can be used as an approximate index of living cost of the poor as well as the non-poor for a period from one to three years.

In the U.S., it is generally accepted that the objective of CPI measurement is to measure changes in the purchasing power of money (for details, see, e.g., the Bureau of Labor Statistics (2007)). That is, the CPI is a “cost of living” index (COLI). Changes in a cost of living index are defined as the ratio of the expenditure function evaluated at different prices. Current COLI measurement implicitly assumes that the expenditure function is associated with a static expenditure minimization problem.

This is not a new topic for research. The first study which explicitly con­ sidered the idea that different individuals experience different cost of living changes seems to date from 1707 when, in response to a student at Oxford, William Fleetwood calculated how much it would cost to buy a certain bun­ dle of goods at current (1707) prices compared to the same bundle of goods at the prices prevailing 400 years earlier during the reign of Henry VI. The bundle of goods he chose was supposed to reflect the typical annual spending pattern of an 18th century student - 4 hogsheads of ale, etc. His conclu­ sion was that “£5 in H V I ’s days ” would make a student “fall as rich as he who has now £20” . Afriat (1977) points out that he might have taken another individual as an example - he gives the example of a civil servant - and gives the figures £25 and £50 as the costs of achieving the civil ser­ vant’s standard of living in each period. On the basis of these data (5,20) and (25,50) a consumer price index for the average would be 2.3. This would be good news for the civil servant and bad news for the student since if their incomes were uprated according to the consumer price index the civil servant would receive £58.30 in 1707 compared to £11.70 for the student. One would be over-compensated, the other under-compensated. In the 1974 Reith Lectures, Dahrendorf argued that

The aim of our paper is to discuss the problems of operationaliz- ing the concept of a “cost-of-living-index” (COLI). For this purpose we are …rst undertaking a theoretical analysis of Diewert’s theory of superlative index numbers as one possible approach to approximate a COLI. We show that Diewert’s superlative index approach is arguable in many points and that the approach requires restrictive assump- tions which are not likely to be met in observed households’ behav- iour. To get a better idea about the deviation of observed households’ behaviour from the neoclassical assumptions about utility maximizing behaviour, we are estimating an Almost Ideal Demand System and a Quadratic Almost Ideal Demand System with cross section micro data from the German income and expenditure survey. Using the results of the demand system estimations we calculate COLIs and compare them with superlative index numbers and the Laspeyres price index.

This paper demonstrates that all these indicators are in fact severely biased, sufficiently understating the cost of living in Russia. It discusses construction of each indicator and reveals reasons for biases. Confronting Russian actual prices for foods with those in the US, the paper shows that prices in these countries are comparable. Moreover, the Russian prices are tending to catch up with the US prices. Two periods are considered, the end of 2004 and the middle of 2008. Some indicators are available only on the regional level. In such a case, the Novosibirsk Oblast is considered as a representative of typical Russian region, since prices and incomes here are not far from the national averages. To convert Russian monetary figures to US dollars, average monthly and quarterly exchange rates are used. They are computed as the arithmetic means of daily exchange rates drawn from the web site of the Central Bank of Russia (http://www.cbr.ru/currency_base/dynamics.asp).

Compute % increase in cost of household basket over 2005-6, compare to CPI inflation rate.... MEASURING THE COST OF LIVING 14.[r]

This paper proposes a Spatial Cost of Living Index for the case of Colombia using the food consumption. We propose the estimation of an Almost Ideal Demand System in order to keep constant the level of utility (economic approach) of the consumer instead of a fixed basket (axiomatic approach). Furthermore, the estimation of the AIDS considers the potential bias generated by the zero consumption of some of the households, a typical characteristic of the expenditure surveys. Using this methodology, the expenditure ratio is calculated for two representative consumers in two different spatial units. This approach allows capturing the substitution the consumer makes when facing different price levels, which is one of the most essential characteristic of consumer theory.

Based on the FRS, Table 2 reports weekly nominal rental prices across British regions in 1997 and 2008, the increase from 1997 to 2008 (column 3) and the percentage increase relative to the national mean (column 4). The table documents that the populations of London and the South East experience higher rents compared to both the UK average and the remaining regions and this is persistent over time. In 2008 the average weekly rent was about £163 in London and £123 in the South East while the UK average rent equalled £92. Northern Ireland and Scotland remain the “cheapest” regions in terms of housing costs. Looking at the UK as a whole between 1997 and 2008, the nominal price for rent increased by about £41 with an average change of 79%; the increase in price for rents in London was 89% (£77) higher than the national one while in the North East the increase was about 28%, lower than that of the UK. These statistics coupled with those reported by Figure 1 suggest that graduate workers in London and the South East are more likely to have experienced both a higher cost-of-living and a more rapid increase in costs due to their higher housing expenditure over the sample period implying that the relative increase in their real wages might be smaller than those of counterparts living in less expensive regions.

by newspapers from all tendencies. 680 For example, he mentioned that the Socialist newspaper, La Vanguardia, questioned its evolution and methodology early on, saying that despite what the number claimed, the cost of living had not declined between 1933 and 1935. 681 The Federation of Commercial Employees (Federación de Empleados de Comercio) conducted its own price research because they distrusted government figures. 682 A review of Figuerola’s 1935 article and the 1935 DNT report compared the official results with the figures obtained by the Railway Union (Unión Ferroviaria). It questioned the value of the monetary condition of the presupuesto teórico and the exclusion of certain goods. However, it claimed that the DE’s publication would encourage analysis and future research. 683 A study from a magazine related to the financial and industrial sectors asserted that the lack of consideration of several goods led to a superficial index that, translated into laws, could become “disastrous for humble households”. 684 The periodical also highlighted that the CLI referred solely to urban workers. 685 This chapter argues that because detailed specifications about the monetary and demographic conditions of the budget and its components were provided in the 1935 DNT report, the 1933 CLI was subject to methodological critiques that influenced Figuerola’s behaviour. Distrust in its predecessor, however, related to the use of index numbers. The different positions that existed as soon as the index was launched show, following Daniel, 686 that there was no consensus behind the objectification of the cost of living. The DE needed social power to establish a valid method, and so, it would seem, Figuerola encouraged the complementary yearlong survey to reinforce its position. Yet, notwithstanding Figuerola’s claim that the tasks of the DE “still remain hidden and consequently almost ignored”, 687 it is clear that the 1933 CLI was used and criticised,

Furthermore, differentials in purchasing powers might usefully be considered by policy makers. For this purpose, we estimated the cost deriving from the application of different Minimum Income schemes by geographical areas: the adoption of such a measure would cost 1.4 billions of Euros, if one adopt strict wealth constraints, and 1.5 billions of Euros when provisions currently assumed by Italian Government for the experimentation of the measure are used: in both cases, the amounts here suggested are much lower than the costs estimated from several Italian research institutes with regard to a single amount for Italy as a whole. It is worth mentioning some possible future works which might improve the threshold evaluation, the estimation of households’ resources, and which might shed light on some aspects only marginally examined or not considered at all. Undoubtedly, a fundamental issue is price surveying of goods included in the bundle. More thorough data would be useful, particularly breaking down by municipalities’ demographic dimensions. Another problem only mentioned here regards the most suitable price to use - either minimum or medium prices, or something in-between: this theoretical problem involves a mainly practical one, that is to what extent the poor are really able to buy the necessary goods at their minimum prices.

Between January 1, 1973, and June 30, 1975, a total of 75 infants weighing 1,000 gm or less at birth were admitted to the Neonatal Intensive Care Unit at Cedars-Sinai Medical Center in L[r]

Drink Tobacco Clothing Fuel Petrol Durable Household Goods Transport Equipment Residual Expenditure... o Table 2: Comparison of the true index, base year utility level T B, with the Lasp[r]

We have demonstrated an effect on energy expenditure of temperature variability, in terms of daily variation and the effect of a sudden temperature change. This had subsequent effects on the resources allocated to egg production. Since daily temperature ranges have increased in some areas due to climate change (Easterling et al., 1997; IPCC, 2001), temperature variation is likely to become more important in determining daily living costs in these areas. Where day-to-day variation in temperature is decreasing, by contrast, daily living costs may also be reduced. Although recent increases in mean temperatures (IPCC, 2001), and a reduction in energy expenditure with temperature would be expected to reduce daily living costs (Kendeigh et al., 1977; Walsberg, 1983), our results suggest that increasing temperature variability might counteract this affect. The effect of the exact pattern of temperature change is thus likely to be important in predicting biotic responses to future climate change.

The plan of this paper is as follows. In section 2 we …rst review the formal de…nition of a true cost-of-living index. We then discuss the construction of the RPI and how it relates to a true index. In section 3 we brie‡y outline the main approaches to constructing true cost-of-living indices. The method which is adopted in calculating the true index is important. Some approaches may give results which are partly driven by their underlying assumptions regarding the form of the relationship between economic welfare and consumption patterns. We use a method of calculating bounds on a true index which is not subject to this criticism as it does not require the form of this relationship be speci…ed. We propose to use the revealed preference method which is described in Varian (1982) and elsewhere. The cost of this approach is that it cannot provide a precise measure of the true index and we must therefore make do instead with bounds. The general idea is to place bounds on the set of consumption bundles which would yield the same level of welfare as the base bundle. Blundell, Browning and Crawford (1998) show that these bounds can be signi…cantly improved by means of nonparametric expansion paths estimated from household-level data. Further, this procedure allows bounds to be developed for nonhomothetic preferences. We apply this approach in section 4 and report results which compare chained …xed- weight indices of the type used in the construction of the RPI with bounded true cost-of-living indices. Section 5 concludes.

Cost-of-living trends Part A of' the SOEC report records trends in the cost-of-living indexes at the various places of employment from·l July 1979 to 1 July 1980.. 100, t·he · situation [r]

were calculated based on market shares of a particular base year. For example, Jud and Joseph (1974) used 1960 market shares as weights in their study which examined the period 1958-1968. However, for the purposes of this study, the weights calculated are based on an average of the previous three years demand. Thus, the weights are changing throughout the estimation period and should prove to be more representative. These weights when totalled equal one. The CPIs were further adjusted to account for prices in the origin. This is based on the premise that domestic tourism is a major competitor for holiday trips abroad. However, there is no evidence of any data available which facilitates the construction of a comparable weight to represent domestic tourism prices. The procedure followed here is that the substitute cost derived from the substitute foreign destinations is multiplied by 0.5 and to this is added 0.5 times the cost of living in the origin country. The CPI data was collected for each of Ireland’s four main source markets and the competing destinations within those markets. The CPI must be adjusted for changes in the exchange rate between each origin and destination and then, divided by the CPI of the origin country for each year. The series is calculated by using the 1985 CPI value as the base year for each destination. All prices are in real terms. Prior to the weights being applied to the CPIs in the substitute cost variable, the CPI should be first converted into real terms.