nach oben

Empirical Economics

Erschienen in:

17.08.2016

Money-based underlying inflation measure for Russia: a structural dynamic factor model approach

verfasst von: Elena Deryugina, Alexey Ponomarenko

Erschienen in: Empirical Economics | Ausgabe 2/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

We estimate a dynamic factor model for the cross section of monetary and price indicators. We extract the common part of the dataset’s fluctuations and decompose it into structural shocks. We argue that one of the shocks identified has empirical properties (in terms of impulse response functions) that are fully in line with the theoretically expected relationship between money growth and inflation, confirming that the process identified has the capacity for economic interpretation. Based on this finding, we decompose recent inflationary developments in Russia into those that are associated with changes in monetary stance and other shorter-lived shocks.

Vorheriger Artikel Time-varying persistence in US inflation

Nächster Artikel Exchange rate volatility and bilateral exports of Malaysia to Singapore, China, Japan, the USA and Korea

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

In fact considering the relative insignificance of interbank money markets (particularly domestic) in Russia and the high volatility of short-term interest rates, it is doubtful that any money market interest rate or any of the Bank of Russia’s interest rates per se could safely be regarded as a policy rate over the last decade. In fact during that period the monetary policy regime in Russia had undergone a transformation from exchange rate management to more conventional reliance on steering interest rates [see Lainela and Ponomarenko (2012) for review]. This precludes making use of short-term interest for identification of money supply shocks as suggested in Benati (2008) or Chadha et al. (2010).

The money holdings of other financial institutions in Russia are insignificant. We therefore saw no reason to include these as a separate component.

As in Ponomarenko et al. (2014), the foreign currency denominated aggregates were adjusted for a re-evaluation effect caused by exchange rate fluctuations.

Although this indicator is not part of conventional monetary aggregates and could presumably be subject to significant measurement error, it may be regarded as an important monetary instrument in the Russian economy (at least in the early 2000s). The estimate was constructed as in Ponomarenko et al. (2014).

The two principal “classical” testing methodologies for unit roots are the Dicky–Fuller and Phillips–Perron. However, the tests are well known to have low power to reject unit roots. Also, the non-stationarity results with these tests are often an artifact of a short estimation period, which would apply to the data for Russia, and may reflect economic disequilibrium. We therefore apply KPSS unit root test with Bartlett kernel as recommended by Jönsson (2006) for the short time samples.

As pointed out in Forni and Gambetti (2010), a large number of static factors are needed to allow for cross-sectional dynamic heterogeneity among variables (i.e., leading or lagging relationship). We obviously expect to find such a relationship between money and prices and therefore are willing to include many static factors in the model. However, we found that adding more than three static factors leads to non-stationarity of the VAR. As discussed in Section 4.2, this number of static factors allows us to obtain a reasonable share of explained cross-sectional variance.

This lag length choice is supported by both Akaike and Schwartz criteria if two-step estimation method is applied (i.e., the unobserved factors are estimated by principal components and are treated as data). The model seems to be robust in relation to the lag length choice: setting \(L=3\) or \(L=4\) does not change the results significantly.

The fact that this effect predominantly shows up in non-food inflation seems plausible as this category of goods is most sensitive to import price fluctuations.

See, e.g., the Bank of Russia Quarterly Inflation Review (2007 Q4, 2011 Q1 and 2012 Q1) for a more detailed review of these episodes.

Andrews DWK (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59:817–858CrossRef

Benati L (2008) The ‘great moderation’ in the United Kingdom. J Money Credit Bank 40(1):121–147CrossRef

Blake A, Mumtaz H (2012) Applied Bayesian econometrics for central bankers, CCBS Technical Handbook No. 4, Bank of England

Bruggeman A, Camba-Mendez G, Fischer B, Sousa J (2005) Structural filters for monetary analysis—the inflationary movements of money in the euro area. Working paper series, No. 470, ECB

Chadha JS, Corrado L, Sun Q (2010) Money and liquidity effects: separating demand from supply. J Econ Dyn Control 34(9):1732–1747CrossRef

Forni M, Gambetti L (2010) The dynamic effects of monetary policy: a structural factor model approach. J Monetary Econ 57:203–216CrossRef

Forni M, Giannone D, Lippi M, Reichlin L (2009) Opening the black box: structural factor models with large cross-sections. Economet Theor 25:1319–1347CrossRef

Forni M, Hallin M, Lippi M, Reichlin L (2000) The generalized dynamic factor model: identification and estimation. Rev Econ Stat 82:540–554CrossRef

Forni M, Lippi M (2001) The generalized dynamic factor model: representation theory. Economet Theor 17:1113–1141

Giannone D, Reichlin L, Sala L (2004) Monetary policy in real time. NBER Macroecon Annu 19:161–200CrossRef

Jönsson K (2006) Finite-sample stability of the KPSS test. Working papers 2006:23, Lund University, Department of Economics

King M (2007) The MPC ten years on. Lecture delivered on 2 May 2007 to the Society of Business Economists

Korhonen I, Mehrotra A (2010) Money demand in post-crisis Russia: de-dollarisation and re-monetisation. Emerg Mark Finance Trade 46(2):5–19CrossRef

Lainela S, Ponomarenko A (2012) Russian financial markets and monetary policy instruments. BOFIT Online No. 3

Mehrotra A, Ponomarenko A (2010) Wealth effects and Russian money demand. Discussion paper series, No. 13, BOFIT

Mumtaz H, Solovyeva A, Vasilieva E (2012) Asset prices, credit and the Russian economy. Joint research paper No. 1, CCBS, Bank of England

Nicoletti-Altimari S (2001) Does money lead inflation in the euro area? Working paper series, No. 63, ECB

Nobili A (2009) Composite indicators for monetary analysis. Working paper series, No. 713, Bank of Italy

Oomes N, Ohnsorge F (2005) Money demand and inflation in dollarized economies: the case of Russia. J Comp Econ 33(3):462–483CrossRef

Papademos LD, Stark J (2010) Enhancing monetary analysis. ECB, Frankfurt

Ponomarenko A, Solovyeva A, Vasilieva E (2013) Financial dollarization in Russia: causes and consequences. Macroecon Finance Emerg Mark Econ 6(2):221–243

Ponomarenko A, Vasilieva E, Schobert F (2014) Feedback to the ECB’s monetary analysis: the bank of Russia’s experience with some key tools. J Bank Finan Econ 2(2):116–150

Stock JH, Watson M (2011) Dynamic factor models. In: Clements MP, Hendry DF (eds) Oxford handbook of forecasting. Oxford University Press, Oxford

Uhlig H (2005) What are the effects of monetary policy on output? Results from an agnostic identification procedure. J Monet Econ 52:381–419CrossRef

Titel: Money-based underlying inflation measure for Russia: a structural dynamic factor model approach
verfasst von: Elena Deryugina
Alexey Ponomarenko
Publikationsdatum: 17.08.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 2/2017
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-016-1125-1

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 2/2017

A capable wife: couple’s joint decisions on labor supply and family chores

The impact of targeting policy on spouses’ demand for public goods, labor supplies and sharing rule

The effect of cash flow on investment: an empirical test of the balance sheet theory

Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs

Sudden stops and output: an empirical Markov switching analysis

The housing market and excess monetary liquidity in China

Premium Partner