×

Are values reported using quantities and prices in consumption expenditure data? (English) Zbl 1426.62369

Summary: For about 125 items of food, the Consumer Expenditure Survey (CES) schedule of the Indian National Sample Survey asks the interviewer to obtain both quantity and value of household consumption during the reference period from the respondent. This would appear to put a great burden on the respondent and call for reduction in the number of items in the schedule. But it is likely that interviewers actually proceed by asking the respondent to recall quantity and price usually paid (instead of quantity and value) and multiplying the two to get value, item-wise, as price usually paid might be easy to recall, and survey protocol does not disallow it. Whether this is done and, if so, how frequently, is of obvious importance to the planners of this important living standards survey, as efforts to reduce the number of items to lighten the respondent burden continue. In this study, a method, using unit records for vegetable items in the NSS’s 2011–2012 CES, is devised to estimate the proportion of interviews in which values of vegetable consumption were in fact determined by the multiplication method. The findings suggest that this method was much more prevalent than “independent” recall of values. This paper concludes that the survey would benefit if the price-and-quantity method were explicitly laid down as the method to be followed to obtain value, as it releases valuable interview time for more important items. Research using unit values from NSS CES data as a proxy for prices would also interpret and use such unit values better, were the practice to be followed uniformly.

MSC:

62P20 Applications of statistics to economics
91B84 Economic time series analysis
Full Text: DOI

References:

[1] Alho J, Spencer B (2005) Statistical demography and forecasting. Springer series in statistics. Springer, Berlin · Zbl 1080.62103
[2] Commission Planning (2009) Report of the expert group to review the methodology for estimation of poverty. Government of India, Planning Commission, Delhi, p 2009
[3] Deaton A (1998) Getting prices right: What should be done? J Econ Perspect 12(1):37-46 · doi:10.1257/jep.12.1.37
[4] Hanisch JU (2007) Rounding of income data: an empirical analysis of the quality of income data with respect to rounded values and income brackets with data from the European community household panel. Peter Lang Pub Incorporated, New York
[5] Indrayan A, Holt MP (2016) Concise medical encyclopaedia of biostatistics for medical professionals. CRC Press, Boca Raton · doi:10.1201/9781315372891
[6] Institute for Resource Development (1990) An assessment of DHS-I data quality. DHS Methodological Reports No. 1, Columbia
[7] McNabb DE (2014) Non-sampling error in social surveys. Sage Publications Inc., Thousand Oaks
[8] NSSO (2014) Level and pattern of consumer expenditure 2011-2012, NSS 68th round (July 2011-June 2012). Ministry of Statistics and Programme Implementation, Government of India, Delhi, p 2014
[9] Perali F (2003) The behavioral and welfare analysis of consumption. Kluwer Academic Publishers, Amsterdam · doi:10.1007/978-1-4757-3729-5
[10] Preese DA (1981) Distributions of final digits in data. Statistician 30(1):31-60 · doi:10.2307/2987702
[11] Shryock HS, Larmon EA, Siegel JS (1973) The methods and materials of demography, vol I. United States Bureau of the Census, Washington
[12] Slesnick D (1998) Empirical approaches to the measurement of welfare. Journal of Economic Literature 36(4):2108-2165
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.