Recovering Historical Inflation Data from Postage Stamps Prices

Philip Hans Franses,Eva Janssens

doi:10.3390/jrfm10040021

Abstract

For many developing countries, historical inflation figures are rarely available. We propose a simple method that aims to recover such figures of inflation using prices of postage stamps issued in earlier years. We illustrate our method for Suriname, where annual inflation rates are available for 1961 until 2015, and where fluctuations in inflation rates are prominent. We estimate the inflation rates for the sample 1873 to 1960. Our main finding is that high inflation periods usually last no longer than 2 or 3 years. An Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model for the recent sample and for the full sample with the recovered inflation rates shows the relevance of adding the recovered data.

Highlights

Introduction and MotivationThe World Bank collects annual inflation rates for all countries in the world
One would perhaps want to know if a current high inflation period, which indicates a period with risky economic fluctuations, has occurred before and which measures were taken to reduce inflation
We present a new and very simple method that aims to reconstruct historical inflation rates

Summary

Introduction and Motivation

The World Bank collects annual inflation rates for all countries in the world. For developed countries, such data can be available for a long span of time, because statistical bureaus for the countries exist for a long time.. We seek to alleviate the issue of changing products over time by considering a product. IOthnetwmoodteylpiessaosfimmpolde els to see if (rscethagmarenpsgssieopsnriimcne)os.dp eoBl,sowttahhlimsletoatdhmeelposstshupegrrgiicseesatsMshtIraDovnAegSeprxerpgedrleaiscnstaiivoteno,rpwyohwviacehrluofieftstfhaonernsiuntaaflmlaipntisfolapntri.iocOnesrn.aeSteemscttoioodqneu4laridsteearallyssimple regression model, while the other is a MIDAS regression, which fits annual inflation rates to quarterly stamps prices.. IOthnetwmoodteylpiessaosfimmpolde els to see if (rscethagmarenpsgssieopsnriimcne)os.dp eoBl,sowttahhlimsletoatdhmeelposstshupegrrgiicseesatsMshtIraDovnAegSeprxerpgedrleaiscnstaiivoteno,rpwyohwviacehrluofieftstfhaonernsiuntaaflmlaipntisfolapntri.iocOnesrn.aeSteemscttoioodqneu4laridsteearallyssimple regression model, while the other is a MIDAS regression, which fits annual inflation rates to quarterly stamps prices.2 Both models suggest strong predictive power of the stamps prices.

The Data

Recovery of Historical Inflation Rates

Conclusions