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MSc.: Catalin Condrache

Academy of Economic Studies Doctoral School of Finance and Banking Romania’s potential growth rates and output gap. MSc.: Catalin Condrache Supervisor: Prof. Moisa Altar Bucharest, July 2008. Contents. Preliminary aspects

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MSc.: Catalin Condrache

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  1. Academy of Economic StudiesDoctoral School of Finance and BankingRomania’s potential growth rates and output gap MSc.: Catalin Condrache Supervisor: Prof. Moisa Altar Bucharest, July 2008

  2. Contents • Preliminary aspects • Methods for estimating potential GDP • Model Definition • Modeling Romania’s situation • Estimating and testing methodology • Conclusions and future research

  3. Abstract • The present working paper sets a goal to assess the impact of production progress, stock of capital, employment in the economy and human capital, within GDP formation. The approach is slightly different from that used so far in estimating potential GDP in the models for Romania’s production function, because in my opinion the current approach reveals the evolution of the potential GDP more realistically. In order to improve the production function model for Romania, I augmented the model by human capital approximation.

  4. Preliminaryaspects • Definitions Potential GDP – represents the level of real GDP which the economy can produce without generating inflationary pressures. Output Gap – represents the difference, expressed in percentage points, between actual real GDP andpotential GDP. • Importance The concept of potential GDP plays a key role in understanding the economic long term growth theory. According to this theory the long term growth rate in GDP is explained by fundamentals factors, such as: the structure of the economy, demographic and educational factors, technology, etc.

  5. Methods for estimating potential GDP • UnivariateMethods • Hodrick – Prescott Filter • Band Pass Filter • Models with unobserved components - Kalman Filter • MultivariateMethods • Production Function, Cobb – Douglas • Multivariate unobserved components models • Structural Vector Autoregression model

  6. Difficultiesin estimating potential GDP • Shortsample of usable data for Romania • Structural changes happened during the analyzed period • Official GDP data is published with a lag, being subsequently subject to revision • Unreliable statistical data for capital stock

  7. Model Definition • The types of production function used in the literature are particular forms of theconstant elasticity of substitution –CES • In all models, the Cobb – Douglas production function is used • The following equation seems to be a better approximation: • In order to surprise the dynamic of GDP we take the log

  8. Modeling Romania’s situation • Data series: quarterly 1998 Q1 -2007 Q4 • Real GDP (expressed in 2000 ct price) • Gross Formation of Fixed Capital (2000 ct price) - GFFC • Real accumulated capital • Employment in the economy • Human Capital

  9. Modeling Romania’s situation • Challenge –estimation of capital stock • Harberger (1978)- assumes a capital growth rate equal to the average growth rate of real GDP. • K1 = K0 x (1 – φ) + I1 • g = 4.70% (average growth rate of real GDP – for the period considered) • Φ = 5.0% (depreciation of fixed capital)

  10. Modeling Romania’s situation • Evolution of labor force – structural brake • The series was adjusted by assuming zero growth between 2001 Q4 – 2002 Q1, and the data prior to 2001 Q4 was recursively corrected using the quarterly difference taken from the data based on the previous methodology

  11. Modeling Romania’s situation • The following data sets likely to figure as human capital: • Share of capital education expenditure in GDP • Share of employed with secondary and university education in the employment group over 15 years of age (Eurostat data; in line with levels 3 – 6 of ISCDE 1997) • Share of employed with university education in the employment group over 15 years of age • Share of employed with secondary and university education in employment group over 25 years of age • Share of employed with university education in the employment group over 25 years of age • Share of male with secondary and university education in the employment group over 15 years of age

  12. Estimating and testing methodology • Census – X12 algorithm has beenused to seasonally adjust all time series • The employment in the economy data series was adjusted for structural break • In order to surprise the dynamic of GDP, I take a log of the Cobb – Douglas function

  13. Modeling and testing methodology • The firs estimation showed a Durbin–Watson =0.536 (autocorrelation) • Remedy for serial correlation: Cochrane-Orcutt • ρ = 0.723194.

  14. Modeling and testing methodology • New error estimate • New equation • After all the adjustments were implemented, I obtained • New DW = 1.975663 LogGDP = 1.673 + 0.29*LogK + 0.11*LogL + 0.62*LogH

  15. Modeling and testing methodology • The coefficients are statistically different from zero at a 5% significance level • The percentage of the total variation in the dependent variable explained by the independent variables, R2, is at a good level of 84% • By adding the human capital to the C–D production function the R-squared has improved, increasing the accuracy of the forecasting • Constant returns to scale assumption, was tested using Wald test

  16. Modeling and testing methodology • Normality test • The residuals seems to be almost normally distributed • Kurtosis is almost 3 • Skewness is very close to zero • Jarque-Berra – is at a small value

  17. Calculating potential growth rates and output gap • Resulted production function • LogGDP = 1.673 + 0.29*LogK + 0.11*LogL + 0.62*LogH • The Total Factor Productivity (TFP) has the major impact • According to the GDP regression function, in order to create sustainable economic growth for the medium term, the solution is to rise human capital and stock of capital mainly • Country like Romania would attract capital and loose qualified labor force

  18. Calculating potential growth rates and output gap • Growth rates of real GDP and potential GDP

  19. Calculating potential growth rates and output gap • Output –gap

  20. Conclusions and future research • The results show an increasing annual potential GDP growth rate, from an average of 3.70% in the period 1998 – 2002, to values of around 6% in recent period • Romania experienced in the past 10 years, a potential GDP growth rates above the those registered by new EU Central and Eastern European member states in their periods of high growth • The factors with the biggest impact in growth rates of potential GDP are total factor productivity, human capital and stock of capital • Estimating the production function, was the first step in understanding and analyzing real convergence • The convergence process concept has its origin in the exogenous model of growth of Robert Solow. According to it, the existence of some economies that have similar characteristics in terms of preferences and technologies, of some declining marginal efficiency as well as of a perfect flexibility from the production factors generates a reduction of the incomes differences between the countries (regions)

  21. Thank you for your consideration!

  22. Bibliography • Melihovs A., Gundars D. 2006 - “The role of production progress and human capital in the economic growth of Latvia”, Latvia Bank Working Paper No 3 • Böwer U., Guillemineau C. 2006 - “Determinants of business cycle synchronization across Euro aria”, European Central Bank, Working Paper Series, No.587 • Denis et al. 2006 - “Calculating potential growth rates and output gaps”, European Commission, Economic Papers 2006 • Galatescu A., Radulescu B., Copaciu M. 2007 - “Potential GDP estimation for Romania”, Romanian Central Bank Working Paper No 20 • Romania Government - “Convergence Program” 2007 • Harberger A. 1978 – “Perspective on capital and technology in less developed countries”, Contemporary Economic Analysis • Bergoing R., Kehoe P., Kehoe T., Soto R. 2001 - “A decade lost and found: Mexico and Chile in the 1980s”, Review of Economic Dynamics, vol. 5 • Jenkins H. 1995 - “Education and production in the United Kingdom”, Economic Discussion Paper No 101 • Romer P. 1990 - “Human capital and growth: theory and evidence”, Carnegie-Rochester Conference Series on Public Policy

  23. Bibliography • Benk S., Jakab Z. , Vadas G. 2005 - “Potential output estimation for Hungary: a survey of different approach”, Magyar Nemzeti Bank Occasional Paper No. 43 • European Commission – “Economic forecasts autumn 2006” • Hamilton J. 1994 - “Time series analysis”, Princeton University Press, Princeton, New Jersey • Harvey A.,Jaeger A. 1993 - “De-trending, styled facts and the business cycle”, Journal of Applied Econometrics, vol.8 • Guarda P. 2002 - “Potential output and the output gap in Luxemburg: some alternative methods”, Banque Centrale du Luxemburg, Working Paper No.4 • Musso A., Westermann Th. 2005 - “Assessing potential output growth in the Euro aria: a growth accounting perspective” European Central Bank, Occasional Papers, No.22 • National Institute of Statistics - “Romanian’s statistical yearbook” / 2006 • McQuinn K., Whelan K. 2006 - “Prospect for growth in the euro aria”, Central Bank and Financial Services Authority of Ireland, Working Paper • Dew-Becker I., Gordon R. 2006 - The slowdown in European productivity growth: a table of tigers, tortoises and textbook labor economics”, NBER

  24. Bibliography • Bandinger H. 2001 - “Growth effects of economic integration – the case of the EU member states”, IEF Working Papers / Research Institute for European affairs • Caraiani, P. 2004 - “Estimating total factor productivity in the Romanian economy”, Romanian Journal of Economic Forecasting, No1 • Caraiani, P. 2004 - “The impact of human capital on the economic growth – the case of Romania 1990-2002”, Romanian Journal of Economic Forecasting, No.3 • Sources of data – National Institute of Statistics, AMECO, EUROSTAT

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