1 / 59

NAIRU Estimation in Romania ( including a comparison with other transition countries)

THE ACADEMY OF ECONOMIC STUDIES DOCTORAL SCHOOL OF FINANCE AND BANKING. NAIRU Estimation in Romania ( including a comparison with other transition countries). Student: Otilia Iulia Ciotau Supervisor: Professor Moisa Altar. BUCHAREST,2004. Contents. The paper’s incentives

taylor
Download Presentation

NAIRU Estimation in Romania ( including a comparison with other transition countries)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. THE ACADEMY OF ECONOMIC STUDIES DOCTORAL SCHOOL OF FINANCE AND BANKING NAIRU Estimation in Romania(including a comparison with other transition countries) Student: Otilia Iulia Ciotau Supervisor: Professor Moisa Altar BUCHAREST,2004

  2. Contents • The paper’s incentives • Features of unemployment rate in Romania • Estimation methods • Comparison of results • Concluding remarks

  3. Natural Rate and NAIRUIs there any difference? • Natural rate of unemployment - Friedman (1968), Phelps (1968): the level of unemployment to which the economy would converge in the long run in the absence of structural changes to the labor market; • NAIRU (Non-Accelerating Inflation Rate of Unemployment) - Modigliani and Papademos (1975): the rate of unemployment at which there is no tendency for inflation to increase or decrease

  4. Are NAIRU estimates useful? • “I have become convinced that the NAIRU is a useful analytic concept. It is useful as a theory to understand the causes of inflation. It is useful as an empirical basis for predicting changes in the inflation rate. And, it is useful as a general guideline for thinking about macroeconomic policy.” Stiglitz, J. , Reflections on the Natural Rate Hypothesis

  5. Features of Unemployment Rate in Romania • The labor market have been strongly affected by the adjustment process from centrally planned to market-oriented economies; • Mass lay-offs; • Issues aboutunderestimation of unemployment rate (masked unemployment, methodology); • Labor force working in informal economy; • Active measures for unemployment mitigation (Law no76/2002).

  6. Unemployment Rate in Romania (1994:1 – 2004:1)

  7. Estimation methods • Statistical methods • Hodrick-Prescott Filter • Univariate UC • Bivariate UC (Okun’s approach) • Multivariate UC • Reduced-form methods • Phillips curve with constant NAIRU • Elmeskov method • Phillips curve with time-varying NAIRU

  8. Hodrick-Prescott ( =1600)

  9. - is generated by the stochastic process: kt and kt* are uncorrelated w.n. with the same variance. - and its reduced form is a restricted ARMA(2,1): Univariate UC for Romania • Fitted model:

  10. - same variance to each harmonic. is a pulse intervention variable: Seasonal component and intervention variable • The seasonal pattern is the sum of [s/2] (two for quarterly data) cyclical components, with frequencies:

  11. The maximum likelihood estimates are: 95% confidence interval for NAIRU: (2003:2) 7.249-9.896% (2003:3) 7.268-9.915% (2003:4) 7.27 -9.918% (2004:1) 7.045-9.693% Back

  12. Period: 25.9808 ( 6.49521 'years') • Amplitude: 0.0142053 • Rho: 0.94072 • Variance: 0.000111226 Estimated parameters for the cycle:

  13. 95% confidence interval for unemployment rate forecast: (2004:2) 6.201 - 8.296% (2004:3) 5.15 - 8.224% (2004:4) 5.208 - 9.055% (2005:1) 6.202 - 10.68% Unemployment Rate Forecast

  14. Univariate UC for Czech R.and Lithuania • Fitted model: • Intervention variables: Irr 2002. 1 & Irr 2003. 4 for Czech R.

  15. NAIRU (UC-1 trend) Czech R.

  16. UC-1 slope for Czech R.

  17. Unemployment gap Czech R.

  18. Bivariate UC: unemployment rate and real GDP (1994:1-2003:3) • Okun’s law • SUTSE (Seemingly Unrelated Time Series Equations): • Intervention variable: • For unemployment series: irr 2002:1; • For GDP: level 1997:1.

  19. Period: 22.6553 ( 5.66383 'years'); • Amplitude unemployment gap :0.02405; • Amplitude GDPgap:0.04185; • Rho: 0.9697843. Estimated parameters for the cycle: Common cycles

  20. 95% confidence interval for NAIRU: (2003:1) 9.333-10.375% (2003:2) 9.298-10.34% (2003:3) 9.342 -10.384% NAIRU (trend UC-2) and unemployment gap (cycle UC-2) UC-1 NAIRU

  21. Potential Output (trend UC-2) and Output Gap

  22. Unemployment Rates in Transition Economies

  23. Series are linked via the off diagonal elements in and ; • This approach allows for detection of common features (Engle and Kozicki 1993): like trend, cycle, seasonal. Multivariate framework • SUTSE model for six countries: • Estimated parameters for the similar cycle: • Rho = 0.96 • Period = 21.56 (5.38987 ‘years’)

  24. Correlation between cyclical components • Czech R. • Hungary 0.983 • Lithuania -0.244 -0.146 • Polonia 0.041 0.137 0.958 • Slovakia 0.176 0.104 0.459 0.523 • Romania 0.548 0.441 -0.004 0.155 0.848

  25. Short-run commovements between unemployment rate in Czech R. and Hungary

  26. Correlation between seasonal components • Czech R. • Hungary 0.176 • Lithuania -0.151 0.669 • Polonia 0.218 0.799 0.504 • Slovakia -0.019 0.8880.8260.673 • Romania 0.049 0.806 0.655 0.942 0.791

  27. Seasonal comovements between unemployment rate in Poland and Romania

  28. Seasonal components in unemployment rate: Romania

  29. Seasonal components in unemployment rate: Poland

  30. Seasonal comovements between unemployment rate in Hungary and Slovakia

  31. Seasonal components in unemployment rate: Hungary

  32. Seasonal components in unemployment rate: Slovakia

  33. NAIRU (UC-2 trend) and unemployment gap in Romania Amplitude: 0.5306

  34. NAIRU (UC-2 trend) and unemployment gap in Czech R. Amplitude: 0.94145

  35. NAIRU (UC-2 trend) and unemployment gap in Lithuania Amplitude: 0.74114

  36. NAIRU (UC-2 trend) and unemployment gap in Poland Amplitude: 0.552935

  37. NAIRU (UC-2 trend) and unemployment gap in Slovakia Amplitude: 0.1882

  38. NAIRU (UC-2 trend) and unemployment gap in Hungary Amplitude: 0.32301

  39. Testing for hysteresis • ADF, PP: we cannot reject the unit root hypothesis for any of the six series; • Zivot and Andrews (1992) : unit root test with structural break endogenously determined (prg. EViews)

  40. Zivot, Andrews test results

  41. Breakpoints endogenously determined by ZA test

  42. Estimation of a constant NAIRU requires the introduction of a constant in (1): • For a time-varying NAIRU we use (1) as the measurement equation for a state space representation estimated with Kalman filter. Reduced-form methods • “Triangle model of inflation” (Gordon) where

  43. Constant NAIRU (u* = 6.98%)

  44. Elmeskov Method • simplified „accelerationist” version of Phillips curve: • An estimate of is obtained for any two consecutive periods as which is substituted in (1) to give:

  45. Elmeskov Method

  46. Time-varying NAIRU • The basic inflation equation: • is supplemented by a second equation that explicitly allows the NAIRU to vary with time: • The method of estimation is Kalman filter with a standard deviation of 0.2 for the state variable as a “smoothing prior” (Gordon 1997).

  47. Time-varying NAIRU

  48. Comparison of results

  49. Conclusion • The Romanian NAIRU is lower than in the other countries studied and also rather small comparing to Europe; • NAIRU in Romania is smooth comparing to the other five countries; • Uncertainty of the results

  50. Further direction for research • Estimating NAIRU based on unemployment rate calculated according to international accepted standard • Using the series from claimant count just for improving the accuracy in a bivariate UC model; Harvey and Chung(2000), Estimating the underlying change in unemplyment in the Uk

More Related