CPI bias and real living standards in Russia during the transition

Abstract

The economies of the former Soviet Bloc experienced large declines in output during the decade of transition which began with the collapse of the Soviet Union in 1991. Yet there are many reasons to believe that measured output and official deflators provide a poor proxy for the change in real living standards in transition economies. This paper uses the Engel curve methodology developed by Hamilton [Hamilton, B. 2001. "Using Engel's Law to Estimate CPI Bias" American Economic Review 91 (3): 619-630] to examine changes in real living standards in Russia during the transition period and to provide an estimate of how much the official Russian CPI has overstated consumer inflation. We also examine changes in consumer durables, home production, and subjective well-being to further evaluate changes in living standards. Our findings indicate that CPI bias has caused a substantial understatement of the growth performance of the Russian economy during the transition. Even just allowing household final consumption to be deflated with bias, we find that the level of real per capita GDP in 2001 may be understated by up to 30% compared with using a bias-corrected deflator. Our analysis of consumer durables, home production, and subjective well-being supports the conclusion that the decline in living standards has been substantially less than what is inferred by looking at official statistics on real output.

Small area estimation-based prediction methods to track poverty: validation and applications

“…During the WMS consumption data was collected for broad (aggregated) categories: 79 food (7 day recall) and 48 non-food items compared with the use of more detailed categories during the KIHBS: 140 food items (7 day recall) and 184 non-food items (1 month recall). 20 Gibson et al [15] also find that subjective wellbeing indicated a much milder decline in living standards between 1994 and 2001 than official estimates had suggested. …”

“…14 Only the estimated parameters of the consumption variance equation are assumed to be stable over time, while the consumption variance predictors are allowed to change. 15 stagnation, increase) and sample size. Classified by the direction of poverty change and the geographic area, a total of 25 different settings can be considered.…”

“…14 Fourth, the technique is convenient to implement given the freely and readily downloadable PovMap2 software. 15 …”

“…This latter observation could be obtained if inflation between 1994 and 1998 had somehow been overstated. Indeed, Gibson et al [15] find evidence of a substantial overstatement in the CPI for urban Russia. To the extent that this latter finding holds for Russia more generally, and that the price deflators that accompany the RLMS data track the Russian CPI, it is possible that poverty in 1998, estimated from RLMS data, is also overstated.…”

Spatial Variation in Prices and Expenditure Inequalities in Australia

“…Yet another reason for investigating spatial differences in price movements in Australia is contained in the results of Gibson et al . () for Russia and Barrett and Brzozowski () for Australia. Using the Engel curve‐based methodology, proposed by Hamilton () and Costa (), these studies showed that the conventional consumer price index (CPI) measure will provide biased estimates of price movements.…”