Abstract

This study evaluates the price setting behavior across main cities of Pakistan by employing the micro data from retail price survey. The most contemporary research technique of Duration Analysis is employed where survivor functions are estimated by most illustrious nonparametric Kaplan-Meier and Nelson-Aalen Estimators. Hazard Functions for various product groups are also estimated by employing parametric Weibull Hazard Model. Results confirm that perishable food items have shortest duration of one week for most of the spells, where government regulation caused prices to change more frequently. It is found that on average small cities faced lower hazard and thus comparably lesser price change, whereas, months of March, April and October witnessed relatively high hazard rates. The study classifies nine commodity groups into two categories. First is high frequency group and second is increasing hazard group. These classifications are believed to assist policy makers in assessing inflation dynamics in Pakistan. The study significantly contributes to the existing literature, firstly, by applying more scrupulous nonparametric and parametric techniques of Survival analysis. To the best of our knowledge, this technique is not yet applied in Pakistan for examining the price behavior. Secondly, as the price setting mechanism in Pakistan is not studied before by employing the high frequency micro price data, therefore, panel data estimation contribute significantly to the existing literature.

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