Calculating Rural‐Urban Food Price Differentials from Unit Values in Household Expenditure Surveys: A Comparison with Existing Methods and A New Procedure

Abstract

While purchasing power parity (PPP) between countries has received a great deal of attention, PPP calculations within countries have received less attention. The idea that one unit of currency has the same purchasing power in all regions in large countries is false. This paper addresses this limitation by proposing a methodology for calculating rural‐urban PPP in India. The paper introduces a concept of item‐specific PPP that exploits the analogy with an item‐specific equivalence scale. The methodology relies on demographically‐varying preferences to estimate PPP. The results underline the need to incorporate spatial differences in PPP calculations in countries with heterogeneous preferences.

Determinants of sheep and goat meat consumption in Switzerland

“…Unit values are obtained by dividing recorded expenditures for every household and food item by the corresponding quantity for every household. In contrast to the approach of Cox and Wohlgenant (1986), Majumder et al (2012) and Hoang (2009) used regionally aggregated quality adjusted unit values as market prices based on the quality adjusted unit values for every household which is consistent with the hypothesis that households are facing the same price in the same market. We enhanced the approach by additionally aggregating over month and years.…”

“…For beef, pork, veal and sheep and goat meat the Swiss Federal Office for Agriculture calculates monthly average consumer prices by regions which we take as market prices. For the other items (poultry meat and fish) missing information of price data were replaced using the approach presented in Majumder et al (2012) who extended the approach of Cox and Wohlgenant (1986). They proposed to adjust unit values for the impact of quality and use them as market prices (see also e.g., Park et al 1996;Thiele 2010).…”

“…D i , D y and D m are dummies for region, year and month. We follow Majumder et al (2012) and estimate equation (4) by using medians instead of means which is a more robust statistic with respect to outliers. Furthermore, we applied a robust M-estimator instead of ordinary least squares which limits the influence of outliers (see e.g., Finger 2013, for details).…”

“…Even though the use of detailed micro-data (i.e., highly disaggregated data with respect to time, product groups and households) is superior to other approaches (e.g., Akbay et al 2007;Lazaridis 2003;Majumder et al 2012;Thiele 2008), we face two major methodological challenges when analyzing this household expenditure survey data for sheep and goat meat. First, many households do not purchase this kind of meat every month leading to a large share of zero observations.…”

“…Second, no direct price data are provided in our data set. To overcome these problems we combine recently proposed approaches to a) avoid selection biases associated with zero consumption using Tobit regressions (e.g., Ma et al 2006;Yimer 2011), and b) we derive quality adjusted price levels at the household level using the approach proposed by Majumder et al (2012) or regional market prices where available.…”