Naslov
Growth and convergence across croatia: evidence from county-level data

Autori
Šergo, Zdravko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Global Challenges for Competitiveness: Business and Goverment Perspective / Kersen-Škabić, Ines ; Krtalić, Sandra - Pula : Fakultet ekonomije i turizma Dr. Mijo Mirković Sveučilišta Jurja Dobrile u Puli, 2007, 56-70

ISBN
978-953-7498-02-3

Skup
Business & Goverment Perspective

Mjesto i datum
Pula, Hrvatska, 27.09.2007. - 29.09.2007

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
unconditional; Solow and augmented Solow regression; counties; Croatia

Sažetak
This paper seeks to reconcile the growth empiric’ s technique of Mankiw, Romer, and Weil with the empirical technique of Barro and Sala-í-Martin through the application of an econometric analysis on the regional database of Croatia covering the 1991-2003 period. The paper is organized as follows. In the second section, we derive in brief the estimation equation within the neoclassical growth model, and then we discuss the differences between β -convergence versus σ -convergence, and try to augment the explanatory power by adding human capital variable to the model. The third section says something about the data, sources and limitations of the data. In the fourth section, we summarize the empirical results of estimation of steady state and convergence equations and in the last section, we conclude. 2. THE NEOCLASSICAL GROWTH MODEL 2.1. The steady-state output per capita The Solow growth model starts with a constant returns-to-scale production function. Given the assumptions and definitions, MRW (1992) show that equation can be solved for the steady-state capital-labour ratio In similar way yt converge to the steady-state value y* defined as Substituting previous equation into the production function and taking logs yields the steady-state output per capita: log y* =1/(1-   log A0 + gt) +  /(1 –  ) log s –  /(1 –  ) log (n + g +  ), g, the rate of technological improvement, reflects the advancement of knowledge and, along with the rate of depreciation and the term A0 is assumed to be constant across counties. So, let 1/(1-   log A0 + gt) equal a, where a is constant across counties. Then, for each county log y* = a +  /(1 –  ) log s –  /(1 –  ) log (n + g +  ). Above equation predicts that the log level of output per worker is positively related to the log difference between the gross investment rate s and the term [n+g+ ]. 3. DATA AND SOURCES We chose to test the model on data from cross-section of counties. Such data are available from a database in the Statistical Almanacs of Croatia, which contains series on real GDP, investment, and population for all counties in Croatia. The data are available at annual frequencies, and we concentrate on the variables of interest between 1991 and 2003. The rate of growth of working age population, n is measured by average rate of growth of county's population in working age (15-64 years old). The rate of savings, s, is measured by the ratio of investment to GDP, and the rate of secondary school, h is measured by the ratio of the working age population with secondary school to working age population. Both the s and h (as human capital) variables are averages for the period 1991-2003. The log of GDP per working age person in 1991 and 2003 measures y. (g+δ ) is not directly observable and is assumed constant at a value of 0.05. We concentrate on a sample of 21 counties ; all data together with the accompanying dummy war variable of the counties affected by the Homeland War in the period 1991-1995. are critically observed. 4. CONCLUSION In regard to our main research, the failure of the neoclassical growth model to adequately explain the growth experiences of Croatia counties is not surprising if we have in mind unsuccessful results of unconditional and conditional convergence regression. There is no tendency for poor Croatia's counties to unconditionally grow faster on average than rich counties in Croatia. The rate of divergence in encompassing transition time is approximately 0.12%, and 0, 09% in unconditionally and conditional augmented convergence, in respect, per year among counties of the Croatia. The augmented Solow model result are theoretically excepted (beside proxy for saving) – there is evidence of convergence and these results give us confidence that our data can be used to address other issues concerning regional economic development in Croatia. The significant value of human capital results suggest that 10% rise in h will raise the productivity by almost 1, 5 % (1, 6% with dummy) in the long run. As we know that the endogenous growth models predicts divergence and that differences between counties can persist indefinitely even if they share the same rates of accumulation of capital and population growth, and because the empirical validity of Solow model’ s prediction about smooth convergence has been heavily questioned in this paper – the next research efforts ought to be testing the endogenous growth model. SELECTED BIBLIOGRAPHY: Barro, Robert J. and Xavier Sala-i-Martin, (1995): Economic Growth, New York: McGraw-Hill Družić, Ivo (1997): Razvoj i tranzicija hrvatskog gospodarstva, Zagreb: HAZU, Politička kultura Šergo, Zdravko, Tomčić, Zdenko (2003): On The Determinants Of The Croatia Economic Growth 1960-2000, From Transition To Development: Globalisation And Political Economy Of Development In Transition Economies, Conference Proceedings, Part I, University Of Sarajevo, Bosnia And Herzegovina, 2003, 277-300. Statistički ljetopis hrvatskih županija, various issues

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija

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