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Thanks are due to Patricia Brukoff, Nick Gigineishvili, Richard Haas, David Hendry, Bogdan Lissovolik, Paulo Neuhaus, and Bert van Selm for comments, suggestions, and encouragement. Eka Galdava, Judith Rey, and Tamuna Tabatadze provided excellent assistance in compiling the database and editing the text.
The BRO group includes the Baltics, Russia, and other former Soviet Union countries.
Measured as a ratio of foreign to total deposits.
Another implication is that, even if it is possible to successfully find one cointegrating vector corresponding to equation (1), it does not imply that a stable money demand function can be estimated from the data.
As implemented in GiveWin.
The log of real GDP is interpolated under the assumption that the series follows a unit root process.
Sequential testing starting from the highest order of six allows for reduction of the lag length to four. Given high uncertainty surrounding the correct lag length, I opt for the over-parameterized model. Monte Carlo studies in Gonzalo (1994) show that efficiency loss from choosing a too long lag structure is small, while a too short lag structure has a severe impact on maximum likelihood estimates. Estimates of cointegrating vector obtained from the four-lag model are almost identical to those obtained from the six-lag specification.
The correlation between log changes in M2 and M3 is nevertheless very high (0.88).
F-tests have been used to test the restrictions. Akaike, Schwarz, Hannan-Quinn, and the Final Prediction Error criteria have been used for judging adequacy of the reductions.
The same conclusion is reached by Gigineishvili (2002), who estimates a similar inflation model using different assumptions about equilibrium in the goods market and different econometric techniques.
Standard errors of some coefficients are higher, but this is not surprising, given that the new estimates are based on a shorter and therefore less informative sample.