1. Dissertation paper Determinants of inflation in Romania Student: Balan Irina Supervisor: Professor Moisa Altar ACADEMY OF ECONOMIC STUDIES DOCTORAL SCHOOL OF FINANCE AND BANKING

2. Contents Literature review The data Estimating the inflation rate CPI model PPI model Concluding remarks

3. LITERATURE REVIEW using cointegration and error-correction models Domac I. and Elbirt C. (1998) argue that the roots of Albanian inflation are rahter conventional: inflation is positively associated with money growth and exchange rates but negatively with real income Brada and Kutan (1999) - the Czech Republic, Hungary and Poland - import price changes play the most important role in explaining inflation dynamics, while nominal wage growth and money supply are quantitatively unimportant Nikolic M. (2000) estimated the determinants of Russian inflation in a single equation framework - money growth is a core determinant of Russian inflation Golinelli R. and Orsi R. (2002) - analysed the determinants of the inflation rate in the Czech Republic, Hungary and Poland and they found that the exchange rate is the main long term factor influencing domestic prices, and can be seen to be the common inflation-adjusting mechanism utilised in all three countries

5. THE DATA (all variables in logarithms) quarterly data sample: 1991:1 - 2003:4 source: National Bank of Romania, Romanian Institute of Statistics p - Consumer Price Index (fixed base 1996=100) p_ppi - Producer Price Index (fixed base 1996=100) m - broad money (M2) w - nominal wages y - industrial production index (fixed base 1996=100) e - nominal exchange rate (ROL/USD )

6. THE GOAL to estimate the determinants of inflation methods: Cointegration technique, VAR and VEC models

7. Estimating the inflation rate unit root tests

8. Estimating the inflation rate VAR analysis Johansen cointegration test Unrestricted Cointegration Rank Test HypothesizedTrace5 Percent1 Percent No. of CE(s)EigenvalueStatisticCritical ValueCritical Value None ** 0.671155 144.7644 87.31 96.58 At most 1 ** 0.516027 90.26820 62.99 70.05 At most 2 ** 0.429085 54.70761 42.44 48.45 At most 3 * 0.296258 27.24240 25.32 30.45 At most 4 0.185047 10.02659 12.25 16.26 *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 4 cointegrating equation(s) at the 5% level Trace test indicates 3 cointegrating equation(s) at the 1% level HypothesizedMax-Eigen5 Percent1 Percent No. of CE(s)EigenvalueStatisticCritical ValueCritical Value None ** 0.671155 54.49624 37.52 42.36 At most 1 * 0.516027 35.56059 31.46 36.65 At most 2 * 0.429085 27.46521 25.54 30.34 At most 3 0.296258 17.21581 18.96 23.65 At most 4 0.185047 10.02659 12.25 16.26 *(**) denotes rejection of the hypothesis at the 5%(1%) level Max-eigenvalue test indicates 3 cointegrating equation(s) at the 5% level Max-eigenvalue test indicates 1 cointegrating equation(s) at the 1% level A. CPI model

9. impulse response functions variance decomposition Variance Decomposition of P: PeriodS.E.PEMWY 1 0.056720 100.0000 0.000000 0.000000 0.000000 0.000000 2 0.114275 93.85281 2.451476 2.716686 0.892874 0.086158 3 0.158674 87.38295 3.384578 3.737108 4.504839 0.990522 4 0.192170 80.12246 4.351817 3.949469 9.803749 1.772504 5 0.214628 74.43547 5.603106 3.842002 13.63369 2.485737 6 0.230038 70.31289 6.864842 3.870439 15.82085 3.130981 7 0.241042 67.40471 7.922160 4.046781 16.91413 3.712217 8 0.249382 65.35814 8.715221 4.348139 17.40862 4.169876 9 0.256012 63.91147 9.275760 4.725601 17.60252 4.484657 10 0.261499 62.87060 9.657330 5.134743 17.67093 4.666394

10. SHORT-RUN DYNAMICS VEC representation D(P) = C(1)*( P(-1) - 1.170937515*W(-1) + 0.2982640716*Y(-1) + 0.002647872491*(@TREND(91:1)) + 8.729001573 ) + C(2)*( E(-1) - 1.222579591*W(-1) + 0.03272644293*Y(-1) - 0.008874279592 *(@TREND(91:1)) + 7.60235849 ) + C(3)*( M(-1) - 1.069243511 *W(-1) - 0.7280624046*Y(-1) - 0.006766951579*(@TREND(91:1)) + 0.0527490756 ) + C(4)*D(P(-1)) + C(5)*D(P(-2)) + C(6)*D(P(-3)) + C(7)*D(E(-1)) + C(8)*D(E(-2)) + C(9)*D(E(-3)) + C(10)*D(M(-1)) + C(11)*D(M(-2)) + C(12)*D(M(-3)) + C(13)*D(W(-1)) + C(14)*D(W( -2)) + C(15)*D(W(-3)) + C(16)*D(Y(-1)) + C(17)*D(Y(-2)) + C(18) *D(Y(-3)) + C(19)

11. R 2 0.906 Adj. R 2 0.848

12. residual tests

13. stability test

14. In-sample fit for the model

15. B. PPI model VAR analysis Johansen cointegration test

16. impulse response functions variance decomposition

17. SHORT-RUN DYNAMICS VEC representation D(P_PPI) = C(1)*( P_PPI(-1) - 2.48984122*M(-1) + 1.410028341*W(-1) + 1.007226247*Y(-1) + 0.006980471507*(@TREND(91:1)) + 14.88603259 ) + C(2)*( E(-1) - 2.47182148*M(-1) + 1.338029779 *W(-1) + 1.185997149*Y(-1) + 0.01758795447*(@TREND(91:1)) + 11.13242619 ) + C(3)*D(P_PPI(-1)) + C(4)*D(P_PPI(-2)) + C(5) *D(P_PPI(-3)) + C(6)*D(E(-1)) + C(7)*D(E(-2)) + C(8)*D(E(-3)) + C(9)*D(M(-1)) + C(10)*D(M(-2)) + C(11)*D(M(-3)) + C(12)*D(W(-1)) + C(13)*D(W(-2)) + C(14)*D(W(-3)) + C(15)*D(Y(-1)) + C(16)*D(Y( -2)) + C(17)*D(Y(-3)) + C(18)

18. R 2 0.933 Adj. R 2 0.895

19. residual test

20. stability test

21. In-sample fit for the model

22. Conclusions the empirical results indicate that there is a long-run equilibrium relantionship between prices and e, m, w and y; the findings show that in the long run inflation in Romania is positively related to the nominal exchange rate, money growth and nominal wage growth, while it is negatively related to the output (proxied by the industrial production index); in terms of the magnitude of effects shocks to wages and nominal exchange rate have relatively larger impacts on prices; the empirical findings from the error-correction model showed that inflation adjusts to its equilibrium fairly rapidly; in the short run inflation is determined by its past values, the exchange rate and by the output;

23. the significant and negative coefficient on the variable of the nominal exchange rate implies that the appreciation of the Romanian leu in the transition period has contributed to reducing inflation; in the CPI model, in the short run, inflation is also determined by the money supply while in the PPI model moeny doesn’t affect inflation; in the CPI model, in the short run, wages doesn’t influence inflation, while in the PPI model it does.

24. REFERENCES: Arratibel Olga, Rodriguez-Palenzuela Diego, Thimann Christian (2002)- Inflation dynamics and dual inflation in accession countries: A “new keynesian” perspective, ECB WP. Brada Josef, King Arthur E.,. Kutan Ali M. (2000) - Inflation bias and productivity shocks in transitions economies: The case of the Czech Republic, ZEI WP. Bertocco Giancarlo, Fanelli Luca, Paruolo Paolo (2002)- On the determinants of inflation in Italy: evidence of cost-push effects before the European Monetary Union. Enders Walter – Applied Econometric Time Series, JohnWiley $ Sons, Inc. Engle R. F.,. Granger C. W. J (1987)- Cointegration and error correction: representation, estimation and testing, Econometrica. Gali J., Gertler M., Lopez-Salido J. D. (2001) - European inflation dynamics, European Economic Review. Gerlach Stefan, Svensson Lars E. O. (2000)- Money and inflation in the euro area: A case for monetary indicators?, NBER WP. Golinelli Roberto, Orsi Renzo (2002) - Modelling inflation in EU accession countries: The case of the Czech Republic, Ezoneplus WP.

25. Golinelli R., Orsi R. (1998)- Exchange rate, inflation and unemployment in East European economies: the case of Poland and Hungary. Golinelli R., Rovelli R.( 2001) - Painless disinflation? Monetary policy rules in Hungary (1991 - 1999). Hamilton James, D. (1994) – Time Series Analysis, Princeton University Press. Hubrich Kirstin (Aug. 2003)- Forecasting euro area inflation: does aggregating forecast accuracy?, ECB WP. Johansen Soren (1991)– Estimation and Hypothesis Testing of Contegration Vectors in Gaussian Vector Autoregressive Models, Econometrica, vol. 59, No. 6. Kim Byung-Yeong (2001)- Determinants of inflation in Poland: A structural cointegration approach, Bofit Discussion Papers. Lyziak Tomasz (2003) - Consumer inflation expectations in Poland, ECB WP. Mohanty M. S., Klan Marc - What determines inflation in emerging market economies?, BIS WP;

26. CPI model

27. PPI model