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The purpose of this paper is to extend the methodology proposed in Majumder et al. (2012) for the estimation of the item-specific purchasing power parities (PPPs) within countries, to the cross-country context. It estimates item-specific intra-country PPPs (i.e. spatial prices) and inter-country PPPs in a unified framework using unit records of household food expenditures from three Asian countries: India, Indonesia and Vietnam, covering contemporaneous time periods. The study addresses a key limitation of the International Comparison Program (ICP) exercise, namely, that it treats all countries, large and small, as homogeneous entities. Moreover, it directly calculates bilateral PPPs between countries based on their expenditure patterns and prices alone and directly estimates the price-level indices (PLI) and their standard errors, allowing formal tests of the hypothesis of PLI being unity. The usefulness of the estimated PPPs is illustrated by applying them to comparisons of real food expenditures between the three countries, and benchmarking the comparisons with those using the ICP PPPs.

The methodology is based on the fact that a spatial price index can be viewed as a true cost of living index (TCLI). Using a general cost function underlying the Rank 3 quadratic logarithmic systems, the TCLI is calculated for a reference utility level.

The study provides formal statistical tests of the hypothesis of item invariance of the PPPs. The usefulness of the proposed methodology is illustrated by applying the estimated PPPs in comparisons of food expenditures between subgroups in the three countries. The sensitivity of the expenditure comparisons to the use of item-wise PPPs underlines the need to provide price information on highly disaggregated PPPs to a much greater extent than the ICP has done to date.

The choice of these three Asian countries was dictated by the fact that, though comparability of items between them remains an issue as with all cross-country comparisons. Also, in the absence of price data, this study followed the practice in Majumder et al. (2012, 2015a, 2015b) in using as proxies the raw unit values of the food items, but adjusted for quality and demographic factors using the procedure introduced by Cox and Wohlgenant (1986) and extended by Hoang (2009).

It addresses some limitations of the ICP, namely, ICP treats all countries as single entities with the purchasing power of the country’s currency assumed to be the same in all regions within the country, ICP uses the US dollar as the numeraire (this ignores the fact that the PPPs required in bilateral welfare comparisons between developing countries with vastly different consumption habits from the “international norm” are quite different from the ICP PPPs) and ICP uses distribution invariant prices to calculate PPPs, which overlooks the fact that the poor pay different prices from the “representative” individual.

This study highlights the importance of estimating and using item-specific PPPs in cross-country comparisons by formally testing and rejecting the assumption of item invariant PPPs and by providing empirical evidence that they do make a difference to the welfare comparisons between countries. This study provides PPPs based on food items only, which may be more relevant for poverty comparisons.

It introduces, for the first time, the concept of item-specific PPPs between countries as estimable parameters and operationalizes this concept by using them in cross-country welfare comparisons.

This paper aims to illustrate the usefulness of the proposed procedure to evaluate the Goods and Services Tax (GST) in India by applying it to provide evidence on optimal commodity tax rates.

In the optimal commodity tax literature, the commonly used Ramsey–Samuelson–Diamond–Mirrlees framework assumes invariance of budget allocation between pre- and posttax regimes and uses only the first-order conditions in the two-stage optimization procedure. This paper proposes an iterative method that overcomes the above limitations in obtaining the optimal tax rates.

It is found that the optimal commodity taxes are highly sensitive to the procedure used to estimate them. The resulting tax rates turn out to be close to the GST tax slabs. The results also show that on both absolute and relative measures, for all the selected states considered here and for All-India, the optimal tax systems are progressive for two chosen values of the inequality aversion parameter.

There is a very limited literature on the computational methodology to calculate optimal commodity taxes, and consequently, the evidence is quite scarce as well. In combining contributions to the computation of optimal taxes with empirical evidence, this paper fills a significant gap in the literature. The context of India gives it added value since the GST has recently been introduced in India, and to the best of the authors’ knowledge, this is one of the first attempts at evaluating the Indian GST through the spectacles of optimal taxes.

This paper aims to detect gender bias in education expenditure on “students”, who are children and young adults, in a household in the rural and the urban sectors of West Bengal. Outlay equivalent ratios have been calculated using the Engel curve approach, where the budget share function is log quadratic in income, to identify items relating exclusively to education of school/college going students. Heckman’s (1979) two-step procedure is used for estimation to address selection bias The 68th round (July 2011 to June 2012) household level consumption expenditure survey data of the National Sample Survey Organisation have been used for the analysis.

Engel curve approach is used to capture parental preference for student’s welfare and to find the existence of male student favouritism in the field of education. In case of exclusive adult goods, the addition of a student will reduce the resource allocated for adult goods leading to negative income effect. If a household favours males over females, then that household is likely to sacrifice more for a male student’s education than that for a female student. To address selection bias, Heckman’s two-step procedure has been used.

The authors find that not all education items relate exclusively to students of a household. Expenditure on books is not exclusively for students, whereas other educational items, such as stationary and photocopy charges, tuition fees and private coaching fees, are found to be students’ items only. Transport cost is found to be an adult good. Further, we find evidence of pro male bias in expenditure on educational items, and the extent of gender bias is more in the urban sectors compared to the rural sectors in West Bengal.

The objective of this paper is to identify the educational items exclusively for “students” and to test the difference in the allocation of resources in education, with respect to these items, between a male student and a female student for both sectors in West Bengal, using the outlay equivalent ratios.

This study aims to apply a proposed methodology for calculating spatial prices in a heterogeneous country setting such as India with limited price information. Based on the empirical evidence, the study plans to draw the spatial price map of India with different colours denoting states and districts with varying level of spatial prices.

This study shows that a procedure proposed by Lewbel (1989), based on the idea by Barten (1964) that household composition changes have “quasi-price effects”, can be used to estimate spatial prices in the absence of information on regional prices.

The evidence on spatial price differences in India, which is the most comprehensive to date because it goes down to district level, shows that the proposed procedure has considerable potential in future applications on other data sets with limited price information. The policy importance of the results is underlined by the sensitivity of the demand elasticities to the inclusion/omission of spatial price variation.

The study uses “pseudo unit values” based on household composition and demographic effects on demand as proxy for the missing price information. While the work of Atella et al. (2004) suggests that such proxies are accurate representations of true prices, nevertheless, they are proxies and the results should be treated with caution.

The evidence on spatial prices in India that point to a high degree of price heterogeneity between regions implies that welfare applications such as income distributional and poverty studies must take account of the price heterogeneity within the country. The implications extend beyond India to cross-country exercises such as the purchasing power parity calculations undertaken by the International Comparison Project.

This is one of the first studies that provide evidence on spatial price heterogeneity within a country without requiring regional price information. Methodologically, the paper builds on the suggestion of Lewbel (RES, 1989) in showing how the demographic effects on household expenditure pattern can be used to estimate spatial prices. The value of the contribution lies in the use that the estimated spatial prices can be put to in calculating inequality and poverty rates and in standard of living comparisons between regions in the country.

The purpose of this study is to examine the sensitivity of regional and world poverty rates to the purchasing power parities (PPP) used in the calculations. The PPPs are required to convert the “international poverty line” typically denominated in US dollar to its local currency equivalent in the various countries. While recent studies on world poverty differ with respect to the specification of the international poverty line (IPL), they universally use the PPP available from the international comparison program (ICP). This study provides a departure and calculates PPPs using the Gini–Elteto–Koves–Szulc (GEKS) price index and country product dummy (CPD) model as alternatives to the ICP PPPs. The GEKS and CPD PPPs are compared with the ICP PPPs. The paper then compares the global and regional poverty rates based on the three sets of PPPs and presents evidence of significant revision to the poverty rates if we depart from the use of the ICP PPPs. The study tests for the presence of serial correlation between price movements in different countries and investigates its impact on the PPPs. The methodological contribution of this paper is to establish the close nexus between price indices and poverty rates via the PPPs used in obtaining the local currency unit (LCU) denominated IPL.

The PPP calculations in this paper relate to the ICP round, 2011. Along with the ICP PPPs from published reports (with India as the numeraire country), we report the following indices, namely, the GEKS, weighted CPD and its two spatially correlated generalisations. The ICP PPPs are used as benchmark. The ICP group in the World Bank made the price and expenditure information for 2011 available. Corresponding poverty rates are calculated at the country, regional and global levels.

The empirical evidence points to the fact that while at the country level the alternative calculations have high impact on the implied poverty rates, at the regional and global level the rates are reasonably quite robust.

Three points are worth noting, namely, as opposed to the PPP for “Individual consumption expenditure by households” (ICEH), which is the PPP used for international poverty monitoring by the World Bank and others, we have used the ICP PPPs for “Actual individual consumption” (AIC); although ICP uses the GEKS procedure above the BH level, we independently calculated these PPPs using the price information provided, and the base country has been moved from the USA to India.

One can come up with independently estimated PPPs that do not require the elaborate and expensive procedure set up by the ICP and can arrive at robust poverty rates at the regional and global level.

The change in base has been made as India shares many of the features of a developing country including high poverty rates, but at the same time provides a market and an economy size that places it in the top tier of nations. In addition, poverty comparisons amongst developing countries can be made using these PPPs directly, without reference to the USA. The poverty calculations are based on the PovcalNet program.

There is no clear answer to the question “how robust are the global poverty numbers to departures from the ICP PPPs?” in the literature nor is there any evidence on the robustness of the ICP PPPs themselves to changes in the ICP methodology. Given that the ICP uses the Gini–Elteto–Koves–Szulc (GEKS) multilateral price index in aggregation of ICP PPP basic heading data, in an attempt to partially answer this question this study examines the sensitivity of measures of relative prices (and poverty) to using CPD (and various spatial versions) and GEKS methods, using price data provided by the World Bank. It also verifies how these PPPs track the published 2011 ICP PPPs, which are used as benchmark.

Many aspects of well-being depend critically on individual-level expenditure and consumption. The Millennium Development Goals include the promotion of gender equality and the empowerment of women, which partly have to do with women’s access to resources within households. Many important questions in labour, public and development economics also hinge on the intra-household distribution of resources. This paper aims to estimate the resource shares within a household in the rural and urban sectors of West Bengal through a collective household model, where each household member has a specific utility function. The sharing rule parameters, that determine the apportionment of resources between members within a household, are estimated in an intra-household collective framework. The analysis is based on a system of log-quadratic Engel curves estimated using the 68th round (2011–2012) household-level consumption expenditure data of the Indian National Sample Survey Office (NSSO) for rural and urban sectors separately for the state of West Bengal.

The sharing rule parameters (that determine the apportionment of resources between members) within a household are estimated in an intra-household collective framework as suggested by Dunbar et al. (2013). The analysis is based on a Quadratic Almost Ideal Demand System (QUAIDS) estimated using the 68th round (2011–2012) household-level consumption expenditure data of the Indian NSSO.

In this paper, the authors estimate the sharing rule of total household expenditure between couples in a household in the state of West Bengal. They use a modified version of the QUAIDS and the 68th round (2011–2012) household-level consumer expenditure data provided by the NSSO. From the exercise, it emerges that on an average, the resource shares between husband and wife in a household is about 66:34% in the rural sector and about 60:40% in the urban sector. Based on a classification of households by the distribution of resource shares, where higher resource share for the husband is classified as “Husband dominated” and the reverse as “Wife dominated”, the percentage of “Husband dominated” households is much more in both sectors. This unequal distribution of resources may have far-reaching consequences on allocation of expenditure on the children of the household. The authors leave this exercise as a future project.

This paper is an attempt to estimate the sharing rule for households using NSSO consumption expenditure data. This paper also highlights the intra household unequal resource allocation through the sharing rule. They use a modified version of the QUAIDS and the 68th round (2011–2012) household-level consumer expenditure data provided by the NSSO. From the exercise, it emerges that on an average, the resource shares between husband and wife in a household is about 66:34% in the rural sector and about 60:40% in the urban sector. Based on a classification of households by the distribution of resource shares, where higher resource share for the husband is classified as “Husband dominated” and the reverse as “Wife dominated”, the percentage of “Husband dominated” households is much more in both sectors. This unequal distribution of resources may have far-reaching consequences on allocation of expenditure on the children of the household. The authors leave this exercise as a future project.

The contribution of this study is both methodological and empirical. It provides a method of estimating preference consistent true cost of living indices and demonstrates the use of unit values (food items), adjusted for quality and demographic effects, as prices. Using NSS data, changes in living standards (measured by per capita real expenditure) in India are examined between 1999/2000 and 2009/2010. The paper aims to discuss these issues.

From the adjusted unit values, “exact” price indices are computed using QAIDS-based preference consistent methods that allow between-item substitution effects and variation across states.

A comparison of the nominal and price deflated real expenditures under alternative temporal price scenario during 1999/2000-2009/2010 shows that the states largely preserve their ranks over the periods, in spite of differential temporal price movement. However, comparison of the nominal and price-deflated real expenditure growth reveals that the rankings are sensitive to the price deflator used.

The results question the wisdom of the treatment of large countries with heterogeneous preferences, e.g. India, as single entities in PPP calculations as in the ICP project. Hence, the results have methodological and empirical implications that extend beyond India.

The study provides evidence on the issue of spatial difference in the temporal movement in prices, where no such evidence exists, and contains the first evidence on living standards in India in the post global financial crisis era. Also, this is the first attempt to base calculation of temporal movement in prices, as measured by the “exact” price indices, on the adjusted unit values of food items.