4. Economic transformation in Central Europe
4.1. Analytical background of comparative analysis
4.1.2. Transformation vs. growth theory and competitiveness
Th e former centrally planned economies were not only cut off from autonomous market-based international relations. Th eir capital allocation mechanism was biased towards resource-oriented sectors. Th e main long-lasting hindrance to growth has been, however, either destruction (as in the case of e.g. Ukraine) or underdevelopment (as in the case of other Central European, less controlled by the then Soviet Union countries) of market institutions and market-based rules of thumb. Together with generally insuffi cient social capital, these elements of institutional infrastructure and quality of economic governance determined the starting point of market transformation and continued to exert strong impact on the growth pace of new Central European market economies. Th is way of in-terpreting impediments to development are refl ected in a modern generation of growth and comparative studies [Rapacki & Próchniak 2012; Ahlerup, Olsson
& Yanagizawa 2009; Jong-A-Pin 2009; Rapacki 2009; Acemoglu & Johnson 2005;
Malaga 2004; Campos & Coricelli 2002; Havrylyshyn 2001].
Any international comparisons of economic performance and growth re-quire a consistent tool of analysis and appraisal. Th e main focus in this Chapter centers on the pace of development since the introduction of market reforms in 1989/1990. Th us, a growth model based on a Cobb-Douglas production function seems to be a suitable tool for comparative static and dynamic analyses. Follow-ing Gylfason and Hochreiter [2010, pp. 7–10] and assumFollow-ing constant returns to scale, real GDP – Y is a function of (4.1):
4 At the end of 1989, the free market exchange rate (at ‘bureau de change’) was four times higher than the offi cial rate of the NBP, and about 80% of household cash holdings were kept in US dollars and German Marks [Kowalski & Stawarska 1999].
Y = AHaKbNcL1–a–b–c, (4.1) where:
A – total factor productivity (TFP), H – human capital,
K – fi xed capital,
N – natural capital, including land, L – labor,
a, b, c – GDP elasticities of growth factors.
By dividing both sides of equation 4.1 by L we express output per head (4.2) as a function of total factor productivity A, human capital per head H/L, fi xed capital per head K/L and natural capital per head N/L:
a b c
Y H K N
L A L L L
§ · § · § ·
¨ ¸ ¨ ¸ ¨ ¸© ¹ © ¹ © ¹. (4.2)
Basically, in all CECs under investigation labor growth was low or even de-clined. It was due to institutional and technological changes that made some la-bor redundant. With natural capital playing in the European context and under globalization a lesser role, the main contemporary driving forces of growth are total factor productivity, which means general effi ciency improvement – A, real capital per head – K/L and human capital per head – H/L. Following Gylafson and Hochreiter [2010, pp. 8–9] and assuming for simplifi cation c = 0 and output elasticity of fi xed capital is 1/3 and output elasticity of human capital is 2/3 equa-tion 4.2 can be now expressed as follows (4.3):5
1 1 1 Total factor productivity6 (TFP) – A represents a part of economic output which is unexplained by inputs of labor (hours worked) or capital used. Th us TFP summarizes various institutional and technological sources co-determining growth paths of modern economies.7 First of all they encompass the impact of
5 Th is simplifi cation is used in relevant literature: [Mankiw, Romer &Weil 1992, quoted aft er Gylafson & Hochreiter 2010; see also Rapacki & Próchniak 2012].
6 Also called multifactor productivity (MFP) [see: Shackleton 2013, p. 3].
7 It is worth emphasizing that in the standard approach to production function analysis, parameter A represents unit technology eff ectiveness. As such it indicates a certain moment in time and can be used in particular in a comparative static approach. I owe this clarifi cation to W. Jurek.
the most important building blocks of globalization (see Chapter 1), which are:
implemented technological and organizational innovations and economies of scale and scope, stemming from openness and various forms of trade, including intra-industry trade and trade in tasks [Rynarzewski & Zielińska-Głębocka 2006;
Grossman & Rossi-Hansberg 2008; Kellman & Shachmurove 2012].
Typically TFP also refl ects social capital understood as a broad institutional development and incorporates relationships and rules that create a societal frame-work of interactions. Th is framework, when well developed, facilitates coordi-nation and cooperation and thus general economic governance (see Chapters 5 and 6). Economic governance is a broad concept covering the quality of main market reforms and then the economic policies that followed (see Chapters 2 and 3). Th ese qualitative factors played a major role in the path of Poland’s and other CECs development and are still a reservoir of potential effi ciency reserves.
Th ey also are important in the context of South European EU member states and Turkey. Th ese countries, in comparison to the UE core countries, were latecom-ers to the global economy and as such had to begin a delayed process of catching up. Consequently their general effi ciency was and still is lower than Northern EU countries. Th is is why the South European EU members and Turkey can be used as a reference point for Poland and Central European countries in their catching up process and also their reactions to the global fi nancial crisis (see Chapter 6).
Human capital per capita – H/L may be quantifi ed in terms of the number of schooling years or other measures of education development. Following Gylaf-son and Hochreiter [2010, pp. 9–10] quantifi cation of the K/Y relationship8 may be expressed as in equation (4.4):
Kt = It + (1 – δ)Kt–1. (4.4) Where It stands for gross investment in year t, and δ represents rate of deprecia-tion. Dividing (4.4) by Y, denoting rate of growth of Y and K by g, and rearrang-ing we have equation (4.5) [Gylafson & Hochreiter 2010, p. 10];
1
K g I
Y g δ Y
§ ·
¨© ¸¹ . (4.5)
Denoting investment ratio I/Y by s and substituting equation (4.5) into (4.3) we have:
8 K/Y is assumed to be proportional to the investment rate I/Y.
Equation (4.6) conceptually generalizes factors determining evolvement of output per head. Assuming that the rate of depreciation – δ is similar in the com-pared countries, their output per capita depends on total factor productivity, human capital per head, rate of growth of capital – g, and investment ratio – s.
Th erefore, equation (4.6), bringing together all major groups of growth factors, creates a sound conceptual framework for an international comparative static and dynamic analyses of Poland and the Central and South European economies in their course of catching up.
Th e fundamental objectives of macroeconomic stabilization and liberal insti-tutional reforms in CECs were high sustainable growth based on improved inter-national competitiveness. In general, analysis and assessment of competitiveness of a given economy can be based on two approaches. Th e fi rst is founded on the-oretical and empirical models of the scale and variations of deviation of the real eff ective exchange rate (see Chapter 2) from the equilibrium exchange rate[see:
Egert 2004; Marrevijk 2004; Rubaszek & Serwa 2009].
Th e international cost and price contexts of the CECs competitiveness are the best outlined in the Balassa-Samuelson framework [Balassa 1964; Samuel-son 1964]. Following De Grauwe and Schnable [2005, pp. 538–541] and using a two-factor Cobb-Douglas function for production conditions in the tradable sector, T and nontradable NT sector we have [Kowalski, Kowalski & Wihlborg 2007, pp. 80–81]:
( ) ( )γi 1γi
i i i i
Y A K L 0 < γi < 1 i = T, NT. (4.7) Marginal producvtivity of labor calculated from (4.7) is expressed as in (4.8)
(1 ) ( ) ( )i i (1 ) (1 )
In the competitive conditions the marginal productivity of labor (4.9) corresponds to real wage in the respective i sector, where real wage is the ratio of W/P in the tradable and the nontradable sectors:
Assuming that WT = WNT = W and following equation (4.9) we obtain (4.10):
in (4.10) and rearranging (4.10) we get (4.11):
T NT
NT T
Q P
cQ P . (4.11)
Assuming for the CECs that their EMU partners tradable prices, PET, are exog-enous and constant and that purchasing parity holds, we can express the CEC price level of tradables, PCT, as in formula (4.12):
/
P – the CEC exchange rate against the euro.
Substituting PT in (4.11) by the RHS of formula (4.12) we obtain expression (4.13) showing the Balassa-Samuelson eff ect framework, and thus integrating all major cost and price determinants of CEC international competitiveness. More-over, formula (4.13) shows a diffi cult interrelation between real sector develop-ments, namely productivity developdevelop-ments, and monetary policy (infl ation and exchange rate) challenges in the course of Poland’s and other CECs future EMU membership
Th e second approach to measuring international competitiveness is based on comparative analysis of primary statistical data such as GDP per capita, infl ation rate, unemployment rate, exports growth rate, etc., leading to compound indi-ces such as those published by the World Economic Forum (WEF) or Institute for Management Development (IMD) [see: World Economic Forum 2013; IMD 2013]. Th ose compound indices are composed on the basis of a sample of pri-mary statistical data characterizing given economies and subjective measures of their business and institutional environment quality.
Th is approach was pioneered by M. Porter [1990], who brought and applied his methodology initially set for evaluation of companies’ competitiveness to the macroeconomic level. At present, in this commonly used framework, the competi-tive advantage of a particular economy is derived from comparacompeti-tive advantages both at a company and a sectoral level. Porter’s approach distinguishes four groups of national competitiveness determinants [Gorynia 2007, pp. 93–95; Kowalski 2012, pp. 25–26]: resource supply, demand factors, sectoral cooperation network, and fi nally factors contributing to the business environment. Transformation of these potential determinants into an actual set defi ning a competitive advantage of a particular country requires favorable but oft en only temporary exogenous conditions and an adequate economic policy aimed at triggering autonomous ad-justment processes [Gorynia 2007, p. 93]. Th is general competitiveness concept is, aft er some adjustments, used for example in Global Competitiveness Reports (GCR). Th e recent GCRs are based on twelve pillars of competiveness (Table 4.1).
Th e pillars of competitiveness used in the GCRs apparently refer to mecha-nisms and models of the contemporary international economics [see: Rynarze-wski & Zielińska-Głębocka 2006; Krugman & Obstfeld 2006; Carbaugh 2013].
Th e GCR distinguishes three main and two interim phases of development and competitiveness (see Table 4.2). Two criteria are used to allocate countries into particular stage of development namely [GCR 2012–2013, p. 8]:
– level of GDP per capita at market exchange rates and
– share of exports of mineral goods in total exports of goods and services.9
9 It is assumed that countries whose mineral products exports surpass 70% of their total exports (measured by a fi ve-year average) are factor-driven [GCR 2012–2013, p. 9].
Table 4.1. Twelve pillars of competitiveness and main stages of development according to GCR
Basic requirements Institutions Factor-driven economies Infrastructure
Macroeconomic stability Health and primary education
Effi ciency enhancers Higher education and training Key for effi ciency-driven economies
Goods market effi ciency Labor market effi ciency Financial market sophistication Technological readiness Market size
Innovation & sophistication factors
Business sophistication Key for innovation-driven economies
Innovation
Source: Global Competitiveness Report [World Economic Forum 2011–2012, p. 8].
Table 4.2 shows how GCR rankings are constructed: for countries falling be-tween two stages, the weights change smoothly allowing for gradual transition to the next stage of development [GCR 2012–2013, p. 9]. Th e WEF country rank-ings strongly accentuate social and human capital factors (Table 4.1); among ba-sic requirements, institutions, infrastructure and macroeconomic stability can be considered aspects of social capital, whereas such effi ciency enhancers like health primary, education and higher education, and training represent human capital. Effi ciency of markets, sophistication, technological readiness and innova-tion (innovainnova-tion and sophisticainnova-tion factors) can be viewed as products of both social and human capital.