Constructing the true cost of living index from the Engel curves of the PIGLOG model

Fry, Vanessa; Pashardes, Panos

doi:10.1002/jae.3950040104

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…The cost-of-living index is expressed as the ratio of the minimal cost required to achieve a certain utility level and the price change of a commodity. Many previous studies, such as Deaton and Muellbauer (1980), Fry and Parshardes (1989), Lewbel (1989), Pollak (1989), Diewert (2001) and Kakwani and Hill (2002), have focused on the cost-of-living index of demand systems. Among them, Kakwani and Hill (2002) develop an axiomatic approach to construct bilateral and multilateral spatial cost-of-living indexes.…”

Section: Estimation Modelmentioning

confidence: 99%

Shrinkage of regional differences in the cost‐of‐living index in Japan

Ogura

2021

Australian Economic Papers

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This study aims to clarify the existence of regional differences and the impact of the 2008 Lehman (Brothers) shock, the collapse of a major U.S. securities firm that triggered the global financial crisis, on these differences based on the regional cost‐of‐living index (RCLI) in Japan. We apply a methodology developed by Kakwani and Hill, which is an axiomatic approach for constructing the multilateral spatial cost‐of‐living indices, to compare the price levels of households between regions of Japan. The results show, overall, a shrinkage of regional differences after the Lehman shock. However, the impact of the Lehman shock on the cost of living varies from region to region. In Japan, the Lehman shock lowered the RCLI in urban areas rather than rural areas. This finding implies that urban areas in Japan are more susceptible to macro shocks, which reduce regional differences with rural areas. Furthermore, based on the results of the cost‐of‐living index by group commodity, we offer a policy implication for the fundamental elimination of regional differences between Japan's urban and rural areas. This would encourage, for example, an increase in the cost of living in rural areas through increased public transport investment and costs, an accompanying increase in rent of housing in surrounding areas and an increase in communication costs owing to the spread of high‐speed internet services, such as 5G.

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Section: Estimation Modelmentioning

confidence: 99%

Shrinkage of regional differences in the cost‐of‐living index in Japan

Ogura

2021

Australian Economic Papers

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“…When a consumer expenditure dataset covers regions facing different price situations, the region-specific Engel curves for individual items estimated from such a dataset contain information about regional price level differentials, which if retrieved, can be used to construct regional TCLIs. This kind of procedure has already been suggested by Fry and Pashardes (1989). They investigate the conditions under which the Törnqvist price index number can be a reasonable approximation to the TCLI underlying a Price Independent Generalized Log linear (PIGLOG) demand system.…”

Section: Introductionmentioning

confidence: 99%

Estimating Spatial Consumer Price Indices Through Engel Curve Analysis

Coondoo

Majumder

Chattopadhyay

2011

Review of Income and Wealth

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In this paper we propose a method of estimating spatial multilateral price index numbers from cross‐section consumer expenditure data on different items using Engel curve analysis. The novelty of the procedure is that it overcomes the problem of data inadequacy, a problem that is shared by most of the developing countries. The procedure does not require item‐specific price/unit value data and price index numbers can be calculated from consumer expenditure data grouped by per capita income/total consumer expenditure class in a situation where unit level data are not available. To illustrate the method, we use published state‐specific data of the 50th round (1993–94) and 55th round (1999–2000) consumer expenditure surveys of India's National Sample Survey Organization (NSSO) and calculate the spatial consumer price index numbers for 15 major states of India, with All‐India taken as base, separately for the rural and the urban sector for each round.

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“…Therefore, to the extent that commodity prices do not change in proportion, households with certain demographic characteristics may face a faster or slower increase in their cost of living than other households. Fry and Pashardes (1989), for instance, report that inflation was biased against large families in the UK over the period 1978-83. Other studies reporting on the demographic aspect of inflation biases include Blundell and Lewbel (1991), Dickens, Fry and Pashardes (1993), Crawford (1994) and Jorgenson and Slesnick (1999). Issues concerning the importance of consumer heterogeneity in the measurement of the cost of living are also raised in the recently published CPI Commission report in the USA (Boskin et al, 1998;Deaton, 1998;Pollak, 1998;Jorgenson, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…These results are explained by (i) the deflation effects being insignificant for children of age 0-10 and significant for children of age 11-18 and (ii) the DDR hypothesis increasing the effects of inflation on the cost of living of households with one child when necessities increase in price faster than luxuries. Over the period 1970-80, prices in the UK increased faster for necessities than luxuries (Fry and Pashardes, 1989). The diagrams in section F1.2 of Figure 1 show that the demographic bias of inflation obtained from the IB model is also higher when the DDR hypothesis is imposed.…”

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confidence: 96%

Comparing the True Cost of Living Indices of Demographically Different Households

Lyssiotou

Pashardes

2004

Bulletin of Econ Res

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The comparison of true cost of living indices between demographically different households (relative equivalence scale) is argued to be sensitive to the way demographic characteristics enter demand analysis. In particular, parameters reflecting the cost of demographic characteristics at base prices, though themselves do not have welfare (equivalence scale) interpretation, can alter the benchmark from which demographically varying inflation effects are measured. The empirical analysis, based on a rank-3 demand system applied to UK individual household data, shows that the inflation adjustment of child benefits can vary with the way demographic costs at base period prices are specified. . We would like to thank two anonymous referees and the joint editor for useful comments and suggestions. We would also like to thank Theofanis Mamuneas for comments and Aris Spanos and Thanasis Stengos for helpful discussions on an earlier version of the paper. Financial support from the University of Cyprus and availability of the UK Family Expenditure Survey data from the Office for National Statistics (through the ESRC Data Archive) are thankfully acknowledged. We are solely responsible for the interpretation of the data and all errors.

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Constructing the true cost of living index from the Engel curves of the PIGLOG model

Cited by 8 publications

References 9 publications

Shrinkage of regional differences in the cost‐of‐living index in Japan

Shrinkage of regional differences in the cost‐of‐living index in Japan

Estimating Spatial Consumer Price Indices Through Engel Curve Analysis

Comparing the True Cost of Living Indices of Demographically Different Households

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