Quarterly inflation rate target and forecasts in Romania

Main Article Content

Mihaela Simionescu


In this study, we proposed some inflation rate predictions based on econometric models that performed better than the targets of the National Bank of Romania. Few econometric models (multiple regressions model and a vector-autoregression) were used to predict the quarterly inflation rate in Romania during 2000:Q1-2016:Q4. The GDP growth has a negative impact on inflation rate in Romania, an increase in logarithm of GDP with one percentage point determining a decrease in inflation logarithm with less than 0.1 units according to both proposed models. However, an increase in inflation rate in the previous period determined an increase in this variable in the current period. The inverse of unemployment rate is positively correlated with the index of prices. The causal relationship between inflation rate and unemployment rate is reciprocal. In the first period the index of prices evolution is explained only by changes in this variable. The inflation rate volatility is due mainly to the evolution of this indicator, the influence decreasing insignificantly in time, not descending under 88%. More than 99% of the variation in unemployment rate is explained by the own volatility for all lags. The annual forecasts based on these models performed better than the targets on the horizon 2015-2016.

Article Details

How to Cite
SIMIONESCU, Mihaela. Quarterly inflation rate target and forecasts in Romania. Economics, Management and Sustainability, [S.l.], v. 1, n. 1, p. 6-13, dec. 2016. ISSN 2520-6303. Available at: <https://jems.sciview.net/index.php/jems/article/view/1>. Date accessed: 10 aug. 2022. doi: https://doi.org/10.14254/jems.2016.1-1.1.


Abubakar, A. M. (2016). Inflation Targeting as a Monetary Policy Framework: A Critical Appraisal. Imperial Journal of Interdisciplinary Research, 2(6), 1-30.
Armstrong, J. S., Green, K. C., & Graefe, A. (2015). Golden rule of forecasting: Be conservative. Journal of Business Research, 68(8), 1717-1731. CrossMark: http://crossmark.crossref.org/dialog/?doi=10.1016/j.jbusres.2015.03.031&domain=pdf.
Arratibel, O., Kamps, C. and Leiner-Killinger, N. (2009). Inflation forecasting in the new EU member states.
Ball, L. M., & Sheridan, N. (2004). Does inflation targeting matter?. In The Inflation-Targeting Debate (pp. 249-282). University of Chicago Press.
Bernanke, B. S., & Woodford, M. (1997). Inflation forecasts and monetary policy (No. w6157). National Bureau of Economic Research.
Canova, F. (2007). G-7 inflation forecasts: random walk, Phillips curve or what else? Macroeconomic Dynamics, 11(01), 1-30. doi: http://dx.doi.org/10.1017.S1365100506050334.
Damian, M. (2011). The disinflation process in Romania within the context of the European integration. The USV Annals of Economics and Public Administration, 10(3), 45-54.
Falnita, E., & Sipos, C. (2007). A multiple regression model for inflation rate in Romania in the enlarged EU.
Gonçalves, C. E. S., & Salles, J. M. (2008). Inflation targeting in emerging economies: What do the data say? Journal of Development Economics, 85(1), 312-318. doi:10.1016/j.jdeveco.2006.07.002.
Meşter, T. I. (1998). VEC Model of Developing Country Inflationary Dynamics–An Empirical Study–The Case of Romania. Journal of Economics, 24(2), 2.
Stein, R. (2015). Inflation Targeting Rules and Seasonality Bias in Inflation Expectations. Bank of Israel. Retrieved from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2688006.
Woglom, G. (2000). Inflation targeting in South Africa: a VAR analysis. Journal for Studies in Economic and Econometrics, 24(2), 1-18. Retrieved from: https://www3.amherst.edu/~grwoglom/Infltargetarticle.doc