Abstract
This paper presents a VAR/VECM analysis of the monetary transmission process in Uzbekistan for the available data from 2000 to 2009. The general findings obtained support the hypothesis that the interest rate channel in Uzbekistan is relatively weak. Monetary transmission via the exchange rate channel seems to be stronger, even if the form of the channel remains quite ambiguous or rather chaotic. Partially this chaos can be blamed on the contradiction between existing restrictions on capital mobility and the dual objectives of a development of the financial sector and provision of macroeconomic stability. On an analytical level this paper suggests the use of a specific methodology for the future evaluation of monetary policy in Uzbekistan. This is especially important, because in future improved and/or more extensive data might alter some of the results obtained so far.
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Notes
These arguments raised in Dabla-Norris and Floerkemeier (2006) hold for the major part of transition countries.
In 2007 Uzbekistan exports (imports) were 32.60 % (30.20 %) of GDP.
Uzbekistan is conducting an import substitution policy focused on sectors like e.g. the automobile industry. The data reported by Pomfret (2009), i.e. a reduction of the ratio of cotton fibre, gold and natural gas in Uzbekistan’s exports from 68 % to around 60 % between 1999 and 2009, questions the effectivity of this strategy.
Data sources in Uzbekistan are sometimes less transparent as one would expect. All Uzbek data for endogenous variables has been provided by the Institute of Forecasting and Macroeconomic Research (IFMR). IFMR states that the primary source of M2 is the Ministry of Economy. The refinancing rate is provided by CBU. The source of GDP and CPI is the State Committee of Statistics of the Republic of Uzbekistan. The nominal exchange rate is obtained from the database of the Economist. The series RGDP and RER are computed by using the CPI and the consumer price index of the US obtained from the IFS data base. The federal funds rate of the US is also obtained from the latter source.
Testing for unit roots requires the use of tests with the power to detect common as well as ideosynchratic components of eventual non-stationarity. This point is even more relevant for cointegrated models. The used unit root tests employed ADF-style test-equations including intercepts and time trends in order to account for data generating processes allowing for a persistent deviation of the data from a drift. For the same reason the modified information criteria suggested in Ng and Perron (2001) were used for the automatic lag length choice. In addition the choice of a quadratic Kernel in the estimation of the spectrum generated a stronger reduction of non-stationarity issues after differencing. Since the power of those tests is known to be very low, unfortunately we got contradicting results. Conclusions have been based on the most convincing results.
This is done by using joint Wald tests.
The LM statistic is for small samples superior to the Q-statistic of the Portmanteau test.
Details for the procedures chosen can be found in Luetkepohl (2005).
A recently initiated project at IFMR using updated data might deliver more insights into eventual structural breaks and the fluctuation of liquidity during the recent financial crises.
Ranaweera (2003) already found the same effect in an earlier sample of Uzbek data.
Akimov and Dollery (2009) elaborate on this argument with respect to the CPI.
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Acknowledgments
The author thanks the Institute of Forecasting and Macroeconomic Research (IFMR) for the provision of some of the Uzbek time series data. For the data obtained from alternative Uzbek institutions IFMR provided the contacts to these institutions. The author also acknowledges financial support by the Federal Ministry for Economic Cooperation and Development of the Federal Republic of Germany within its program CIM. In addition the author thanks two anonymous referees for their proposals for improvements of the paper.
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Appendix
Appendix
See Tables 1, 2, 3, 4, 5, 6, 7 and Figs. 1, 2, 3, 4, 5, 6, 7.
Impulse responses: MODINT: 3 CE, intercepts and trends
Impulse responses: MODINT: 4 CE, intercepts and trends
Impulse responses: MODINT: 4 CE, intercepts and trend
Impulse responses: MODRFR: 3 CE, intercepts and trends
Impulse responses: MODRFR: 3 CE, intercepts and trend
Impulse responses: MODRFR: 4 CE, intercepts and trend
Forecast error decompositions
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Hespeler, F. A VECM evaluation of monetary transmission in Uzbekistan. Econ Change Restruct 46, 219–253 (2013). https://doi.org/10.1007/s10644-012-9125-4
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DOI: https://doi.org/10.1007/s10644-012-9125-4