Conditional convergence, regional disparities and economic growth. The evidence from the V4 regions
(XXVI.Medzinárodné Kolokvium o Regionálnych Vedách
14. - 16.6.2023, Boretice)
Ing. Martin Maris, Ph.D.
Institute of Regional and Rural Development
Faculty of European Studies and Regional Development
Slovak University of Agriculture in Nitra
1
Economic growth and convergence theory
Facts about the economic growth (Kaldor, 1963):
Per capita output grows over time, and its growth rate does not tend to diminish
Physical capital per worker grows over time
The rate of return to capital is nearly constant
The ratio of physical capital to output is nearly constant
The share of labor and physical capital in national income are nearly constant
The growth rate of output per worker differs substantially across countries
Kuznets (1973, 1981) brings other characteristics of modern economic growth. The rapid structural transformation involving shifts from agriculture to industry and services. This process provokes urbanization, shifts from home work to employee status and increasing of education....increased role of foreign commerce...technological progress....and more
Economic growth and convergence theory
What is convergence?
Hypothesis that poorer economies per capita income will tend grow faster than richer economies (catch-up effect); (Sollow-Swan growth model)
Several types of convergence (Galor,1996):
Absolute convergence: lower initial GDP will lead to a higher average growth rate
Conditional convergence: a country's income per worker converges to a country-specific long-run level as determined by the structural characteristics of that country
Club convergence: over time, observing different "clubs "or groups of countries with similar growth trajectories is possible.
Economic growth and convergence theory
■ Many amendments and flaws to this theory was attributed (Romer, 1986; Lucas, 1988; Sachs and Warner, 1995;)
■ Many countries don't show convergence of growth at all; there is no sign of catching-up with the growth rates (among developing countries) towards to developed ones
■ Convergence within the EU
■ Empirics differ in its conclusions about the convergence achievement within the EU (Yin et al.,2003; Vojinovic, 2009; Borsi and Metiu, 2015; and Strielkowsky and Hoschle, 2016)
■ Also club-convergence and convergence of so called NMS found mixed results (Varblane and Vahter, 2005; Rapacki and Prochniak, 2009; Szelesand Marinescu, 2010; Dobrinskyand Havlik, 2014)
Materials and Methods
■ The paper aims to find evidence about the conditional convergence hypothesis on a sample of regions of the V4 countries on the NUTS3 level
■ Standard, neoclassic production function may be specified as
Yt = AtKtaL\-a (1.0)
However in a steady state
Iny = lnA+-^ [Ins - ln(n + g + 8] (1.1)
And if assumed that steady state is the same for all economies, than
Mny = lny0 + InA (1.2)
We speak about the absolute convergence, otherwise
Mny = g + ——^   ® UnA0 +---—- [lnsK - ln(n + g + 8)] +---—- [lnsH - ln(n + g + 8)] - InyA
I 1 — a — p 1 — a — p )
Known as conditional convergence (Mankiw, Romer and Weil, 1992); speed of the convergence appx: x = -t_1iog(i - tpy
The model
cross-sectional data on NUTS3 regional level were used (n = 115) time span: 2004-2020
Mnyit= ft + $xlnyi>t_x + ft/ns - ft ln(n + g + 5) + e,
Spatial dispersion of convergence (5-convergence)
2 2 °logy,t — °log y,t+T > 0
Capital city by size
• 423,737
• 423,738- 1,165,581 0 1,165,582 - 1,696,128 O 1 696,129 - 1,702.139
0   62.5 125 250 375 500
Results
■ Coefficient (3 {GDPt_n) became negative and statistically significant what suggests presence of the (3 -convergence; on the yearly basis= -0.013 (17-year data span)
■ Estimation of the speed of the convergence, according to
/? = -(1 - e~xt)
According to results
-(l - e~u) = -0.2292
Hence: X = 0.0153
Linear regression
Nujmber (3f obs £13, HI) Prob > F R-squared Root MSE
Robust
diff GDP  I  Coefficient    std. err.
115 17 . 76 0.0000 0.3421 .15346
P> 11
[95% conf. interval]
GDPn J_-. 2292468
GFCFg J_zl- 293046
EOPa I 2.567581 cons   | 2.864249
0444422	-5 .	.16	:.	000	-.3173121	-.1411816
4895167	-2 .	.64	:.	009	-2.263056	-.3230364
.671883	3.	.82	:.	000	1.2362	3 . S98962
.376106	7.	.62	:.	000	2 .11897	3 . 609528
Estimated speed of the convergence is 1.53% what is a small value
o-convergence
Overall trend of the deviation shows irregular pattern
Two-sample test shows a significant difference in the mean values of both samples (t-observed: -17.047; p-value<0.0001)
Based on the results, we might confirm the presence of the 3-convergence and o-convergence
Std. deviation
Fitted values
Results
IPL518
IPL514
*f*&i«ipL416 ■curniD ■ PL 113
ip«^r s-p°i*pL213 .p,„.
_r^«-^*"!!™*l4BSK»«L418 "PL11.
118
ISK042
8
PL633 16
IPL418
PL617
>L522
■PL^pl22B ■ HU331
mm
2064
42
CZOl
■a
IHU323 ■ HU
IHU313
IHU221
^uno
■ HU211 IHU222
IHU223
—i-1-1—
8.5 9 9.5
Real GDP in 2004 per capita
ICZ010
IHU110
10
Conclusion
■ The study aims on evaluation of the convergence process within the V4 countries
■ The (3 coefficient became highly significant, and the o coefficient shows a substantial decline over the research period
■ Furthermore, it should be noted that the convergence process has a selective character
■ The highest level convergence have shown Poland and the lowest Hungary