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The author would like to thank Steve Barnett, Roberto Benelli, Kevin Fletcher, Lorenzo Giorgianni, Davide Lombardo, Wes McGrew, Andre Meier, Greta Mitchell-Casselle, Hossein Samiei, Murat Ucer and Joanne Yoong for helpful comments and discussions.
Real interest rates are difficult to measure as they involve inflation expectations. In constructing Figure 1, we first assume that rational expectations hold, such that
where rt and it are the real and nominal interest rate respectively.
Based on our assumptions, the last term should approach zero as we average over a large number of observations. The average (1/T)Σtrt=(1/T)Σt(it-πt+1)/(1+ πt+1) is, therefore, our measure of the real interest rate.
Cross-country interest rate comparisons have to be treated carefully given the differences in maturities and the nature of interest rates used. For most emerging market countries, bond markets are not well-developed and the securities traded typically have very short maturities. In the construction of Figure 1, we have used the 1-year interbank rate from DataStream to make the data as comparable as possible.
The exceptions are the Czech Republic, Estonia, Hungary, Latvia, Poland and Slovakia for which we have shorter time series. For these countries, we compute μ as the average growth rate of the first 10 years of available data. We drop Bulgaria due to data limitations.
For Brazil, we used an estimate of 0.45 as suggested by the IMF desk economist.
We could not replicate Gollin (2002)’s analysis for Turkey since the national accounts data does not provide the necessary breakdown of operating surplus.
Latvia is an extreme case, which is a result of the short sample and a large capital share of income as measured by Gollin (2002).
Time-varying transition probabilities also feature in Diebold, Lee and Weinbach (1994). In the current context, the model is an extension of Hamilton (1988), which features time-invariant transition probabilities.
We use changes in debt stocks, rather than the actual budget balance figures themselves, due to the availability of a longer time series for gross debt.
It-1 refers to the information set as of period t-1.
The function fminval in MATLAB was used.
We only present the results using one-year maturities to match the survey data that we use later. Nevertheless, similar regressions were carried out for all maturities and theresults are available from the author upon request.
As noted in Hansen and Hodrick (1980), the use of overlapping observations induces a moving-average process in the error-term. We adjust our estimates of the standard errors to account for this.