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SPATIAL COMPARISONS OF PRICES AND EXPENDITURE IN A HETEROGENEOUS COUNTRY: METHODOLOGY WITH APPLICATION TO INDIA

Published online by Cambridge University Press:  31 January 2014

Amita Majumder ,
Ranjan Ray  and
Kompal Sinha
Amita Majumder
Affiliation:
Indian Statistical Institute
Ranjan Ray*
Affiliation:
Monash University
Kompal Sinha
Affiliation:
Monash University
*
Address correspondence to: Ranjan Ray, Room E 863, Building 11, Department of Economics, Monash University, Clayton, Victoria 3800, Australia; e-mail: ranjan.ray@monash.edu.
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Abstract

This study addresses two significant limitations in the literature on cross-country expenditure comparisons: (a) treatment of all countries, large and small, as single entities with no spatial differences inside the countries, and (b) use of Divisia price indices, rather than Rank 3 preference-based “exact price” indices, in the expenditure comparisons. This paper compares alternative preference consistent methods for estimating spatial price differences in a large heterogeneous country, namely India, that are benchmarked against the spatial prices generated by the Laspyeres and Tornqvist price indices. Unlike the use of conventional price indices, the use of demand-systems-based methods allows the incorporation of price-induced substitution effects between items. The paper illustrates the usefulness of the methodology by using the “exact” spatial price indices, in conjunction with the inequality-sensitive welfare measure due to Sen, to rank the Indian states and examine changes in ranking during one of the most significant periods in independent India. The results have methodological and empirical implications that extend far beyond India.

Keywords

True Cost of Living IndexInequality-Sensitive Real Expenditure ComparisonsSpatial Price IndicesHasse DiagramsUnit Values
Type
Articles
Information
Macroeconomic Dynamics , Volume 19 , Issue 5 , July 2015 , pp. 931 - 989
Copyright
Copyright © Cambridge University Press 2014 

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References

REFERENCES

Almas, I. (2012) International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food. Mimeo, Norwegian School of Economics and Business Administration, Bergen.CrossRefGoogle Scholar
Asian Development Bank (2008) Research Study on Poverty-Specific Purchasing Power Parities for Selected Countries in Asia and the Pacific. Technical Report, Asian Development Bank, Manila. Available at http://www.adb.org/sites/default/files/Poverty-Specific-PPP.pdf.Google Scholar
Atella, V., Menon, M., and Perali, F. (2004) Estimation of unit values in cross sections without quantity information and implications for demand and welfare analysis. In Dagum, C. and Ferrari, G. (eds.), Household Behaviour, Equivalence Scales, Welfare and Poverty (pp. 195–220). New York: Physica-Verlag.CrossRefGoogle Scholar
Aten, Betina and Menezes, T. (2002) Poverty Price Levels: An Application to Brazilian Metropolitan Areas. Presented at the World Bank ICP Conference, Washington, DC, March 11–15.Google Scholar
Atkin, D. and Donaldson, D. (2012) Who's Getting Globalized? The Size and Nature of Intranational Trade Costs. Working Paper, Economics Department, Massachusetts Institute of Technology. Available at http://economics.mit.edu/faculty/ddonald/papers.Google Scholar
Banks, J., Blundell, R., and Lewbel, A. (1997) Quadratic Engel curves and consumer demand. Review of Economics and Statistics 79, 527–539.CrossRefGoogle Scholar
Barnett, W.A. (2007) Multilateral aggregation-theoretic monetary aggregation over heterogeneous countries. Journal of Econometrics 136, 457–482.CrossRefGoogle Scholar
Christensen, L.R., Jorgenson, D.W., and Lau, L.J. (1975) Transcendental logarithmic utility functions. American Economic Review 65 (3), 367–383.Google Scholar
Clements, K.W. and Izan, H.Y. (1981) A note on estimating Divisia index numbers. International Economic Review 22, 745–747.CrossRefGoogle Scholar
Coondoo, D., Majumder, A., and Chattopadhyay, S. (2011) Estimating spatial consumer price indices through Engel curve analysis. Review of Income and Wealth 57 (1), 138–155.CrossRefGoogle Scholar
Coondoo, D., Majumder, A., and Ray, R. (2004) A method of calculating regional consumer price differentials with illustrative evidence from India. Review of Income and Wealth 50 (1), 51–68.CrossRefGoogle Scholar
Cox, T.L. and Wohlgenant, M.K. (1986) Prices and quality effects in cross-sectional demand analysis. American Journal of Agricultural Economics 68 (4), 908–919.CrossRefGoogle Scholar
Datt, G. and Ravallion, M. (1998) Why have some Indian states done better than others at reducing rural poverty? Economica 65, 17–38.CrossRefGoogle Scholar
Deaton, A. (1988) Quality, quantity and spatial variation of price. American Economic Review 78 (3), 418–430.Google Scholar
Deaton, A. and Dupriez, O. (2011) Spatial Price Differences within Large Countries. Working paper 1321, Woodrow Wilson School of Public and International Affairs, Princeton University.Google Scholar
Diewert, E. (1976) Exact and superlative index numbers. Journal of Econometrics 4, 115–145.CrossRefGoogle Scholar
Feenstra, Robert C., Inklaar, Robert, and Timmer, Marcel (2012) The Next Generation of the Penn World Table. University of California, Davis, and University of Groningen.CrossRefGoogle Scholar
Feenstra, R.C., Ma, H., and Rao, D.S.P., (2009) Consistent comparisons of real incomes across time and space. Macroeconomic Dynamics 13 (Supplement), 169–193.CrossRefGoogle Scholar
Feenstra, R.C. and Reinsdorf, M.B. (2000) An exact price index for the almost ideal demand system. Economics Letters 66, 159–162.CrossRefGoogle Scholar
Gibson, J. and Rozelle, S. (2005) Prices and unit values in poverty measurement and tax reform analysis. World Bank Economic Review 19 (1), 69–97.CrossRefGoogle Scholar
Hill, R.J. (2000) Measuring substitution bias in international comparisons based on additive purchasing power parity methods. European Economic Review 44, 145–162.CrossRefGoogle Scholar
Hill, R.J. (2004) Constructing price indexes across space and time: The case of the European Union. American Economic Review 94 (5), 1379–1410.CrossRefGoogle Scholar
Hill, R.J. and Timmer, Marcel (2004) Standard Errors as Weights in Multilateral Price Indices. Research memorandum GD-73, Groningen Growth and Development Centre.Google Scholar
Hoang, L.V. (2009) Estimation of Food Demand from Household Survey Data in Vietnam. DEPOCEN working paper 2009/12.Google Scholar
Hulten, C.R. (1973) Divisia index numbers. Econometrica 41 (6), 1017–1025.CrossRefGoogle Scholar
Lancaster, G. and Ray, R. (1998) Comparison of alternative models of household equivalence scales: The Australian evidence on unit record data. Economic Record 74, 1–14.CrossRefGoogle Scholar
Legendre, P. and Fortin, M.J. (2010) Comparison of the Mantel test and alternative approaches for detecting complex multivariate relationships in the spatial analysis of genetic data. Molecular Ecology Resources 10, 831–844.CrossRefGoogle ScholarPubMed
Levene, H. (1960) Robust tests for equality of variances. In Olkin, Ingram, Ghurve, Sudhish, Hoeffding, Wassily, Madow, William, and Mann, Henry (eds.), Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling, pp. 278–292. Stanford, CA: Stanford University Press.Google Scholar
Majumder, A., Ray, R., and Sinha, K. (2011) Estimating Intra Country and Cross Country Purchasing Power Parities from Household Expenditure Data Using Single Equation and Complete Demand Systems Approach: India and Vietnam. Economics discussion paper 34/11, Monash University. Forthcoming in Review of Income and Wealth.Google Scholar
Majumder, A., Ray, R., and Sinha, K. (2012) Calculating rural-urban food price differentials from unit values in household expenditure surveys: A comparison with existing methods and a new procedure. American Journal of Agricultural Economics 94 (5), 1218–1235.CrossRefGoogle Scholar
Mantel, N. (1967) The detection of disease clustering and a generalized regression approach. Cancer Research 27, 209–220.Google Scholar
McKelvey, C. (2011) Price, unit value and quantity demanded. Journal of Development Economics 95 (1), 157–169.CrossRefGoogle Scholar
Neary, J.P. (2004) Rationalizing the Penn World Table: True multilateral indices for international comparisons of real income. American Economic Review 94 (5), 1411–1428.CrossRefGoogle Scholar
Nordstokke, D.W. and Zumbo, B.D. (2010) A new nonparametric test for equal variances. Psicologica 31, 401–430.Google Scholar
O'Donnell, C.J. and Rao, D.S.P. (2007) Predicting Expenditure Shares for Computing PPP Exchange Rates. Mimeo, University of Queensland, Brisbane.Google Scholar
Oulton, N. (2012) How to measure living standards and productivity. Review of Income and Wealth 58 (3), 424–456.CrossRefGoogle Scholar
Prais, S.J. and Houthakker, H.S. (1971) The Analysis of Family Budgets, 2nd ed.Cambridge, UK: Cambridge University Press [originally published 1955].Google Scholar
Rao, D.S.P., Rambaldi, A., and Doran, H. (2010) Extrapolation of purchasing power parities using multiple benchmarks and auxiliary information: A new approach. Review of Income and Wealth 37 (4), 345–361.Google Scholar
Selvanathan, E. (1991) Standard errors for Laspeyres and Paasche index numbers. Economics Letters 35, 35–38.CrossRefGoogle Scholar
Sen, A. (1976) Real national income. Review of Economic Studies 43 (1), 19–39.CrossRefGoogle Scholar
World Bank (2011) World Development Report: Conflict, Security and Development. Washington, DC: World Bank.Google Scholar