Mariusz Próchniak
The aim of this chapter is to determine the relative competitive position of Poland and other EU countries from Central and Eastern Europe and the evolution of this position over the time of the global crisis. The competitive position is measured here using the total factor productivity concept.
The analysis of total factor productivity (TFP) is conducted using the growth accounting framework. Growth accounting is an empirical exercise aimed at calculat- ing how much economic growth is caused by changes in measurable factor inputs and in the level of technology. The level of technology, which cannot be directly observed, is measured as a residual. This means that we define technical progress as that part of economic growth which cannot be explained by changes in measurable factor inputs. This residual technical progress is interpreted as the increase in the total productivity of the inputs, denoted as TFP.
The basic model of growth accounting includes two measurable factor inputs: labor and physical capital. To calculate the TFP growth rate, the following equation is used:
TFP growth = !A A = !Y Y − sK !K K+ 1 − s
(
K)
!L L ⎡ ⎣ ⎢ ⎤ ⎦ ⎥,where Y – output (GDP), A – level of technology, K – physical capital, L – labor, sK – phys- ical capital share in income.1
In previous editions of the report, we extended the basic model of growth account- ing. In the 2013 edition, we estimated total factor productivity in various sectors of the economy for Poland and selected other countries in Central-Eastern and Western Europe (10 sectors were examined according to the NACE-2 classification) (Próchniak, 2013). In the 2012 and 2014 editions, in addition to the basic model of growth account- ing, we also estimated the human capital-extended version, which was related to the
1 This paper is a follow-up study to the author’s previous analyses on the subject (see for instance:
Próchniak, 2012, 2013, 2014). The methodology of the analysis is described in detail in the 2008 edition of the report (Próchniak, 2008).
main topics of these editions of the report (Próchniak, 2012, 2014). Since the purpose of this study is to assess changes in total factor productivity in the context of the global crisis, in order to verify the research hypotheses it is sufficient to use the basic model, with physical capital and labor, estimated at the level of the entire economy.
A new element in this edition of the study is sensitivity analysis, meaning that TFP changes in alternative variants of the model (with different assumptions) are estimated. The sensitivity analysis makes it possible to show a broader picture of the dynamics of total factor productivity. Such an analysis is also important because the growth accounting framework is based on a number of assumptions that need to be adopted, affecting the results obtained.
The analysis covers 11 CEE countries, referred to as the EU11 (Poland, Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Romania, Slovakia, and Slovenia).2 All the calculations were also carried out for the EU15, or the 15 “old”
EU members in Western Europe. Data for the EU15 constitute a reference point. We do not show the detailed estimates for individual EU15 countries but only aggregated figures for the entire group. The calculations for the EU15 are weighted averages to make the results comparable.
The analysis covers the 2005–2014 period. To assess the impact of the global crisis, we also present summary statistics of selected variables for the following subperiods: 2005–2007, 2008–2010, 2011–2013, and 2014. The years from 2005 to 2007 show the situation before the global crisis, the 2008–2010 period can be seen as the time of the crisis, while the years 2011–2013 describe the situation immediately after the crisis. The year 2014 was also singled out in order to highlight the latest trends of the examined variables. The division of the analyzed period into various subperiods also makes it possible to show the changes in total factor productivity during various stages of EU membership.
In this round of research, we updated all the time series of the analyzed variables. All the steps of the analysis were recalculated. Moreover, some time series have new coverage. Thus, all the results are fully documented in the study and the analysis does not use information from previous editions of the report.
The following time series were collected for the purposes of our analysis: (a) the growth rate of GDP, (b) the growth rate of labor, and (c) the growth rate of physi- cal capital. The data are derived from the following sources: the World Bank (World
2 Rapacki and Próchniak (2006) establish the growth accounting framework for the whole group of
post-socialist countries. Another study by Rapacki and Próchniak (2012) analyzes the TFP growth rates in the 10 Central and Eastern European countries (CEE-10) compared with the 29 emerging economies from other regions of the world, with a comparable 1993 per capita income level to that observed in the CEE- 10 countries: five post-socialist transition countries, four countries from the Middle East, four East Asian economies, 11 countries from Latin America, and five African countries.
Bank, 2015), the International Monetary Fund (IMF, 2015), and the International Labor Organization (ILO, 2015).
The economic growth rate is the real annual GDP growth rate, taken from the IMF database.
The growth rate for labor is the change in total employment according to the International Labor Organization data (ILO, 2015). These statistics have the same coverage for all the countries and are derived from Labor Force Surveys (LFS). The figures refer to employed persons (including self-employment), regardless of whether in a given period they worked or were employed but did not work. We are aware this measure is imperfect; however, it is difficult to find for all the EU countries complete time series that would work better in showing the dynamics of labor and would be a reliable source of information.3 At the time of the analysis, employment statistics
were only available for the first three quarters of 2014 (in the case of two CEE coun- tries, Croatia and Romania, for only two quarters). Therefore, when calculating the 2014 employment dynamics, we compare these figures with those for the first three quarters of 2013 (in the case of Croatia and Romania, for the first two quarters of 2013) in order to compare with the corresponding period of the previous year.
The amount of physical capital is calculated using the perpetual inventory method. Since this method requires a number of assumptions, it is worth performing sensitivity analysis to assess the robustness of the results to the assumptions made. In the basic model, we assume a 5% depreciation rate and an initial capital/output ratio of 3. In the perpetual inventory method, the initial year should be earlier than the first year for which TFP is calculated; in our analysis the perpetual inventory method starts in 2000; this is the year for which we assume a capital/output ratio of 3. The capital/output ratio for the basic model is in line with estimates by King and Levine (1994), who note that the ratio for the 24 OECD countries was around 2.5. However, it is expected that the level of capital productivity in CEE economies (especially during the first decade of transition) was lower than in OECD countries. Therefore, in the alternative vari- ant of the model, we perform calculations assuming an initial capital/output ratio of 5 (which indicates a lower level of capital productivity because, given the value of 5, a larger stock of capital is necessary to achieve a given volume of output). In an alternative variant of the model, we assume that the depreciation rate is 10%. In both models, investments are measured by gross fixed capital formation.
3 A problem with choosing an appropriate measure is much more evident in the case of human capital.
Any variable representing human capital can be questioned, even more so than in the case of labor. This is one of the reasons why many empirical studies on growth accounting ignore human capital, taking into account only labor and physical capital.
Table 9.1. Labor, physical capital, and TFP contribution to economic growth in the basic
2005 2006 2007 2008 2009
growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%)
Bulgaria L 0.4 0.2 3 4.3 2.1 33 4.6 2.3 36 3.3 1.7 27 –3.2 –1.6 29 K 3.3 1.7 26 5.2 2.6 40 6.0 3.0 46 6.7 3.3 54 8.4 4.2 –76 TFP 4.5 4.5 71 1.8 1.8 27 1.2 1.2 18 1.2 1.2 19 –8.1 –8.1 147 GDP 6.4 6.4 100 6.5 6.5 100 6.4 6.4 100 6.2 6.2 100 –5.5 –5.5 100 Croatia L –0.6 –0.3 –7 0.9 0.4 9 1.8 0.9 18 1.3 0.7 31 –1.8 –0.9 13 K 4.2 2.1 49 4.2 2.1 42 4.7 2.4 47 4.9 2.5 119 5.3 2.7 –38 TFP 2.5 2.5 58 2.4 2.4 49 1.8 1.8 36 –1.0 –1.0 –50 –8.7 –8.7 125 GDP 4.3 4.3 100 4.9 4.9 100 5.1 5.1 100 2.1 2.1 100 –6.9 –6.9 100 Czech Rep. L 1.7 0.9 13 1.3 0.7 10 1.9 1.0 17 1.6 0.8 26 –1.4 –0.7 15 K 4.1 2.0 30 4.3 2.1 30 4.4 2.2 38 5.2 2.6 85 5.0 2.5 –55 TFP 3.8 3.8 57 4.2 4.2 60 2.6 2.6 45 –0.3 –0.3 –11 –6.3 –6.3 140 GDP 6.8 6.8 100 7.0 7.0 100 5.7 5.7 100 3.1 3.1 100 –4.5 –4.5 100 Estonia L 1.9 1.0 10 5.9 2.9 28 0.9 0.5 6 –0.2 –0.1 2 –9.5 –4.7 32 K 6.3 3.1 33 7.2 3.6 35 9.0 4.5 57 9.2 4.6 –86 6.3 3.1 –21 TFP 5.4 5.4 57 3.9 3.9 37 2.9 2.9 37 –9.8 –9.8 184 –13.2 –13.2 89 GDP 9.5 9.5 100 10.4 10.4 100 7.9 7.9 100 –5.3 –5.3 100 –14.7 –14.7 100 Hungary L 0.2 0.1 2 0.7 0.4 9 –0.1 0.0 –44 –1.2 –0.6 –67 –2.5 –1.3 19 K 3.4 1.7 43 3.4 1.7 44 3.2 1.6 1455 3.3 1.6 184 3.1 1.6 –23 TFP 2.2 2.2 55 1.8 1.8 47 –1.4 –1.4 –1311 –0.2 –0.2 –17 –7.1 –7.1 104 GDP 4.0 4.0 100 3.9 3.9 100 0.1 0.1 100 0.9 0.9 100 –6.8 –6.8 100 Latvia L 1.2 0.6 6 6.0 3.0 27 2.6 1.3 13 –0.2 –0.1 4 –13.9 –6.9 39 K 5.9 2.9 29 7.7 3.8 35 8.7 4.4 44 8.6 4.3 –154 5.8 2.9 –16 TFP 6.6 6.6 65 4.1 4.1 38 4.4 4.4 44 –6.9 –6.9 250 –13.7 –13.7 77 GDP 10.1 10.1 100 11.0 11.0 100 10.0 10.0 100 –2.8 –2.8 100 –17.7 –17.7 100 Lithuania L 0.4 0.2 3 –0.4 –0.2 –2 1.6 0.8 8 –1.7 –0.8 –29 –7.7 –3.8 26 K 4.1 2.1 26 4.7 2.4 30 6.1 3.0 31 7.9 3.9 135 6.3 3.2 –21 TFP 5.5 5.5 71 5.6 5.6 72 6.0 6.0 61 –0.2 –0.2 –6 –14.2 –14.2 95 GDP 7.8 7.8 100 7.8 7.8 100 9.8 9.8 100 2.9 2.9 100 –14.8 –14.8 100 Poland L 3.2 1.6 44 3.4 1.7 27 4.4 2.2 33 3.7 1.8 36 0.4 0.2 13 K 1.3 0.6 17 1.7 0.9 14 2.5 1.2 18 3.7 1.9 36 4.1 2.1 126 TFP 1.4 1.4 39 3.7 3.7 59 3.3 3.3 49 1.4 1.4 28 –0.6 –0.6 –39 GDP 3.6 3.6 100 6.2 6.2 100 6.8 6.8 100 5.1 5.1 100 1.6 1.6 100 Romania L –1.8 –0.9 –22 1.9 1.0 12 0.7 0.3 5 0.2 0.1 1 –1.3 –0.7 10 K 3.4 1.7 41 4.4 2.2 28 5.8 2.9 46 8.2 4.1 56 9.2 4.6 –70 TFP 3.4 3.4 81 4.7 4.7 60 3.1 3.1 49 3.1 3.1 43 –10.5 –10.5 160 GDP 4.2 4.2 100 7.9 7.9 100 6.3 6.3 100 7.3 7.3 100 –6.6 –6.6 100 Slovakia L 3.1 1.5 23 3.9 2.0 24 2.4 1.2 11 3.2 1.6 28 –2.8 –1.4 28 K 3.6 1.8 27 4.6 2.3 28 5.0 2.5 24 5.4 2.7 47 5.0 2.5 –51 TFP 3.3 3.3 50 4.1 4.1 49 6.8 6.8 64 1.4 1.4 25 –6.1 –6.1 123 GDP 6.7 6.7 100 8.3 8.3 100 10.5 10.5 100 5.8 5.8 100 –4.9 –4.9 100 Slovenia L 0.4 0.2 4 1.3 0.6 11 2.5 1.2 18 1.1 0.6 17 –1.5 –0.8 10 K 3.8 1.9 48 3.8 1.9 34 4.4 2.2 31 5.0 2.5 76 5.2 2.6 –34 TFP 1.9 1.9 48 3.1 3.1 55 3.5 3.5 51 0.2 0.2 7 –9.6 –9.6 124 GDP 4.0 4.0 100 5.7 5.7 100 6.9 6.9 100 3.3 3.3 100 –7.8 –7.8 100 EU15 L 2.0 1.0 49 1.8 0.9 28 1.8 0.9 29 0.9 0.5 485 –1.8 –0.9 20 K 2.0 1.0 48 2.0 1.0 31 2.2 1.1 36 2.4 1.2 1230 2.1 1.1 –24 TFP 0.1 0.1 3 1.3 1.3 41 1.1 1.1 35 –1.6 –1.6 –1615 –4.7 –4.7 104 GDP 2.0 2.0 100 3.2 3.2 100 3.1 3.1 100 0.1 0.1 100 –4.5 –4.5 100
model, 2005–2014
2010 2011 2012 2013 2014
growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%) growth (%) contr. (% points) contr. (%)
–6.2 –3.1 –785 –2.9 –1.4 –78 –1.1 –0.5 –90 0.0 0.0 2 1.4 0.7 52 5.2 2.6 660 2.9 1.5 79 2.3 1.2 199 2.3 1.2 134 2.1 1.1 76 0.9 0.9 225 1.8 1.8 99 –0.1 –0.1 –9 –0.3 –0.3 –36 –0.4 –0.4 –28 0.4 0.4 100 1.8 1.8 100 0.6 0.6 100 0.9 0.9 100 1.4 1.4 100 –4.0 –2.0 88 –3.2 –1.6 672 –3.1 –1.6 71 5.4 2.7 –296 2.1 1.0 –126 3.4 1.7 –75 1.9 0.9 –403 1.6 0.8 –36 1.3 0.6 –70 1.1 0.6 –69 –2.0 –2.0 87 0.4 0.4 –169 –1.4 –1.4 65 –4.3 –4.3 466 –2.4 –2.4 295 –2.3 –2.3 100 –0.2 –0.2 100 –2.2 –2.2 100 –0.9 –0.9 100 –0.8 –0.8 100 –1.0 –0.5 –20 –0.3 –0.1 –7 0.4 0.2 –17 1.0 0.5 –52 0.6 0.3 12 3.5 1.8 72 3.4 1.7 92 3.2 1.6 –155 2.7 1.3 –144 2.2 1.1 43 1.2 1.2 48 0.3 0.3 15 –2.8 –2.8 273 –2.8 –2.8 296 1.1 1.1 44 2.5 2.5 100 1.8 1.8 100 –1.0 –1.0 100 –0.9 –0.9 100 2.5 2.5 100 –4.4 –2.2 –88 6.2 3.1 37 1.9 1.0 21 1.0 0.5 32 0.0 0.0 –1 1.7 0.9 35 1.4 0.7 9 3.4 1.7 37 4.0 2.0 123 3.9 1.9 158 3.8 3.8 153 4.5 4.5 54 2.0 2.0 42 –0.9 –0.9 –55 –0.7 –0.7 –57 2.5 2.5 100 8.3 8.3 100 4.7 4.7 100 1.6 1.6 100 1.2 1.2 100 0.0 0.0 –1 0.8 0.4 26 1.7 0.9 –52 1.6 0.8 71 5.5 2.7 98 2.2 1.1 105 1.4 0.7 44 1.2 0.6 –35 0.8 0.4 38 1.1 0.5 19 0.0 0.0 –4 0.5 0.5 30 –3.1 –3.1 187 –0.1 –0.1 –9 –0.5 –0.5 –17 1.1 1.1 100 1.6 1.6 100 –1.7 –1.7 100 1.1 1.1 100 2.8 2.8 100 –6.4 –3.2 243 1.3 0.6 12 1.6 0.8 16 2.1 1.0 25 –0.7 –0.4 –13 1.4 0.7 –53 0.1 0.0 1 1.8 0.9 18 3.0 1.5 37 2.5 1.3 47 1.2 1.2 –90 4.6 4.6 87 3.5 3.5 67 1.6 1.6 38 1.8 1.8 66 –1.3 –1.3 100 5.3 5.3 100 5.2 5.2 100 4.1 4.1 100 2.7 2.7 100 –5.3 –2.6 –166 0.5 0.2 4 1.8 0.9 24 1.3 0.7 21 2.1 1.0 35 1.4 0.7 43 1.3 0.6 11 1.7 0.9 24 1.5 0.7 23 1.9 1.0 32 3.6 3.6 222 5.2 5.2 85 1.9 1.9 52 1.8 1.8 57 1.0 1.0 32 1.6 1.6 100 6.0 6.0 100 3.7 3.7 100 3.3 3.3 100 3.0 3.0 100 –2.5 –1.2 –32 0.6 0.3 6 0.2 0.1 5 –0.1 –0.1 –5 1.9 0.9 29 3.6 1.8 46 3.3 1.6 36 3.7 1.9 94 3.3 1.6 106 3.1 1.5 48 3.3 3.3 86 2.6 2.6 58 0.0 0.0 2 0.0 0.0 –1 0.8 0.8 24 3.9 3.9 100 4.5 4.5 100 2.0 2.0 100 1.6 1.6 100 3.2 3.2 100 0.0 0.0 2 –1.1 –0.6 –24 1.4 0.7 123 –0.2 –0.1 –2 –6.9 –3.5 –144 4.4 2.2 –191 3.8 1.9 81 4.1 2.0 368 4.2 2.1 59 2.5 1.2 52 –3.3 –3.3 289 1.0 1.0 42 –2.2 –2.2 –391 1.5 1.5 43 4.6 4.6 192 –1.1 –1.1 100 2.3 2.3 100 0.6 0.6 100 3.5 3.5 100 2.4 2.4 100 –2.1 –1.0 –23 –0.1 0.0 –2 0.6 0.3 16 0.0 0.0 0 1.0 0.5 22 2.8 1.4 31 3.1 1.6 52 3.9 1.9 107 2.7 1.4 145 2.3 1.2 50 4.1 4.1 92 1.5 1.5 49 –0.4 –0.4 –24 –0.4 –0.4 –46 0.7 0.7 29 4.4 4.4 100 3.0 3.0 100 1.8 1.8 100 0.9 0.9 100 2.4 2.4 100 –1.5 –0.7 –61 –3.1 –1.5 –252 –1.3 –0.7 25 –1.9 –1.0 97 1.4 0.7 50 2.6 1.3 105 1.4 0.7 112 1.0 0.5 –19 0.4 0.2 –21 0.5 0.2 17 0.7 0.7 56 1.5 1.5 240 –2.5 –2.5 94 –0.2 –0.2 24 0.5 0.5 33 1.2 1.2 100 0.6 0.6 100 –2.6 –2.6 100 –1.0 –1.0 100 1.4 1.4 100 –0.4 –0.2 –10 0.4 0.2 12 –0.3 –0.2 48 –0.3 –0.1 –140 –4.7 –2.3 –178 1.2 0.6 29 1.1 0.6 35 1.2 0.6 –169 1.0 0.5 457 0.8 0.4 31 1.7 1.7 81 0.9 0.9 53 –0.8 –0.8 221 –0.2 –0.2 –217 3.2 3.2 247 2.1 2.1 100 1.6 1.6 100 –0.4 –0.4 100 0.1 0.1 100 1.3 1.3 100
The last assumption concerns the factor shares in GDP. We assume that all the factor shares in income are the same.4 In most empirical studies, a physical capital
share of 0.3 is assumed. However, for some countries (especially Poland), the physical capital share of 0.3 significantly overestimates the TFP growth rate. Thus, in line with suggestions by some economists (see e.g. Welfe, 2001), this share in the basic model has been increased to 0.5 in order to better fit the real values. This means that, in the basic model, labor and physical capital shares are both equal to one-half. In contrast, in the alternative variant, we assume that the physical capital share in income equals one-third while the labor share is two-thirds.
Table 9.1 shows the detailed breakdown of economic growth in the basic model. The values in the respective cells of the table show: (a) the growth rate of labor (L), physical capital (K), TFP, and GDP, (b) the contribution of labor, physical capital, and TFP to economic growth in percentage points, (c) the contribution of labor, physical capital, and TFP to economic growth in percentage terms.
Tables 9.2 and 9.3 sum up the data given in Table 9.1. Table 9.2 shows the average values of the TFP growth rates in the basic model for the individual EU11 countries and the EU15 group as a whole throughout the 2005–2014 period as well as in four different subperiods: (a) before the global crisis (2005-2007), (b) during the crisis or economic slowdown (2008-2010), (c) in the post-crisis 2011–2013 period, which, for some countries, marked a time of recovery while for others was a period of continued poor macroeconomic performance, (d) in 2014. Table 9.3 shows the percentage values of TFP contribution to economic growth in the basic model throughout the 2005–2014 period and in the four distinguished subperiods. Moreover, both tables provide the minimum and maximum values of a given variable for the entire period.
Tables 9.4 and 9.5 refer to the alternative variant of the model with the following assumptions: a 10-percent depreciation rate, an initial capital/output ratio of 5, and a physical capital share in income of one-third. The structure of these tables (includ- ing the division into subperiods) is the same as in Tables 9.2 and 9.3. For the sake of conciseness, we do not report in the study the detailed results of the growth account- ing for the alternative model (as in Table 9.1).
The global financial crisis and economic recession could disrupt the mechanisms driving the economy and lead to new trends and relationships between some mac- roeconomic variables. For example, in years with negative GDP growth, the changes in TFP influence economic growth in a different way than in years with positive GDP
4 Arbitrary values of factor shares are widely assumed in empirical studies (King and Levine, 1994,
Wang and Yao, 2003, Caselli and Tenreyro, 2005). Wang and Yao (2003) show that different assumptions about factor shares do not yield different outcomes. Caselli and Tenreyro (2005) obtain similar conclusions from models based on arbitrary and real factor shares.
growth.5 Consequently, model estimations may involve some atypical outcomes that
should be interpreted with caution.
Table 9.2. TFP growth rates in the basic model (%)
Country The whole 2005–2014 period 2005–2007 2008–2010 2011–2013 2014
Mean Min Max Mean Mean Mean
Bulgaria 0.2 –8.1 4.5 2.5 –2.0 0.5 –0.4 Croatia –1.3 –8.7 2.5 2.2 –3.9 –1.8 –2.4 Czech Republic 0.1 –6.3 4.2 3.5 –1.8 –1.8 1.1 Estonia –0.2 –13.2 5.4 4.1 –6.4 1.8 –0.7 Hungary –0.8 –7.1 2.2 0.8 –2.4 –0.9 –0.5 Latvia 0.7 –13.7 6.6 5.0 –6.5 3.2 1.8 Lithuania 1.6 –14.2 6.0 5.7 –3.6 3.0 1.0 Poland 1.6 –0.6 3.7 2.8 1.4 0.9 0.8 Romania 0.5 –10.5 4.7 3.7 –3.6 0.1 4.6 Slovakia 1.5 –6.1 6.8 4.7 –0.2 0.2 0.7 Slovenia –0.1 –9.6 3.5 2.8 –2.9 –0.4 0.5 EU15 0.1 –4.7 3.2 0.8 –1.5 0.0 3.2
Source: Author’s calculations.
Table 9.3. TFP contribution to economic growth in the basic model (%)
Country The whole 2005–2014 period 2005–2007 2008–2010 2011–2013 2014
Mean Min Max Mean Mean Mean
Bulgaria 53 –36 225 39 130 18 –28 Croatia 96 –169 466 48 54 121 295 Czech Republic 97 –11 296 54 59 194 44 Estonia 54 –57 184 44 142 14 –57 Hungary –94 –1,311 187 –403 28 69 –17 Latvia 64 –90 250 49 79 64 66 Lithuania 74 –6 222 68 104 65 32 Poland 30 –39 86 49 25 19 24 Romania 57 –391 289 63 164 –102 192 Slovakia 41 –46 123 54 80 –7 29 Slovenia 73 7 240 51 62 119 33 EU15 –105 –1,615 247 26 –477 19 247
Source: Author’s calculations.
5 For example, an increase in TFP has a positive impact on economic growth during an expansionary
Table 9.4. TFP growth rates in the alternative variant of the model (%)
Country The whole 2005–2014 period 2005–2007 2008–2010 2011–2013 2014
Mean Min Max Mean Mean Mean
Bulgaria 2.6 –4.6 7.2 4.9 1.1 2.4 0.8 Croatia 0.9 –5.9 5.5 4.9 –1.3 –0.1 –1.4 Czech Republic 2.2 –3.7 6.7 6.0 0.5 –0.1 2.4 Estonia 2.2 –9.0 8.4 7.0 –3.1 3.0 0.8 Hungary 1.1 –4.5 4.9 3.4 –0.1 0.4 –0.1 Latvia 3.2 –8.8 9.7 7.9 –2.9 4.5 3.3 Lithuania 4.0 –10.2 8.7 8.6 –0.3 4.3 2.0 Poland 3.4 1.6 5.8 4.5 3.5 2.6 2.0 Romania 3.1 –7.2 7.2 6.5 –0.7 2.0 7.2 Slovakia 3.5 –3.2 9.1 7.0 2.2 1.9 1.9 Slovenia 2.0 –7.0 5.7 5.3 –0.5 1.4 1.5 EU15 2.0 –2.4 5.3 2.8 0.5 1.5 5.3
Source: Author’s calculations.
Table 9.5. TFP contribution to economic growth in the alternative variant of the model (%)
Country The whole 2005–2014 period 2005–2007 2008–2010 2011–2013 2014
Mean Min Max Mean Mean Mean
Bulgaria 218 53 1,075 76 405 225 57 Croatia –13 –1118 408 105 39 –247 176 Czech Republic 103 64 147 92 94 125 97 Estonia 90 36 254 76 146 57 69 Hungary 195 –3 893 376 166 110 –3 Latvia 50 –303 134 77 –40 90 124 Lithuania 123 67 387 102 189 98 67 Poland 92 61 150 82 104 99 61 Romania 107 –96 302 113 98 44 302 Slovakia 90 61 143 82 90 101 82 Slovenia 128 –142 588 99 133 159 103 EU15 245 –226 1,163 103 215 362 405
Source: Author’s calculations.
The data in Tables 9.1–9.3 yield a number of findings. Over the entire period, the highest TFP growth rate (in the basic model) was recorded in Lithuania, Poland, and
Slovakia. In 2005–2014, total factor productivity grew at an average rate of 1.6% per annum in Lithuania and Poland, and 1.5% in Slovakia. In the remaining EU11 countries, the growth of productivity was much slower, not exceeding 0.7%, and sometimes it was even negative. Latvia and Romania recorded TFP growth rates of 0.7% and 0.5% per annum respectively in 2005–2014; in Bulgaria, the Czech Republic, Slovenia and Estonia, total factor productivity did not change significantly throughout the studied period (the TFP growth rates stood at 0.2%, 0.1%, – 0.1%, and –0.2%); while Hungary and Croatia noted a fall in TFP by 0.8% and 1.3% on average respectively.
Comparing the results achieved by the CEE countries with the average outcomes for the EU15 group, it turns out that the CEE countries displayed more rapid TFP growth on average. In the EU15, total factor productivity actually did not change over the 2005–2014 period (the growth rate was 0.1%). This last figure means that almost the entire economic growth of the EU15 area can be attributed to and explained by both physical capital and employment dynamics. Five of the 11 CEE countries recorded a positive TFP growth rate in 2005–2014 at a level of 0.5% or more. Consequently, over the entire 2005–2014 period, the competitive position of many EU11 countries – as measured by changes in total factor productivity – improved, compared with the Western European economies. This especially applies to Poland, which displayed the most rapid TFP growth in the analyzed period.6
Of course, we must point out that the part of TFP which is due to increased labor productivity should be partly considered as a human capital contribution to economic growth. Because of the difficulties in calculating the stock of human capital for the studied group of countries, TFP in our approach also includes the impact of human capital on economic growth.
The best performance of Poland in terms of changes in the total factor productivity compared with the other EU11 economies can undoubtedly be treated as the country’s success. In studies carried out several years ago, the Baltic states had the best achieve- ments in terms of TFP growth rates. Prior to the global crisis, they showed very rapid economic growth, which was hard to explain by changes in labor and physical capital, and consequently it was attributed to TFP. The position of Poland in these analyses was moderate – not as good as that of the Baltic states, but neither was it trailing the group. The extension of the time horizon significantly changed the outcomes for individual countries in favor of Poland, while worsening the position of the Baltic states. This is visible when the results for the individual subperiods are discussed.
The highest variance of TFP growth rates in the analyzed period was noted in the Baltic states. The strong differences in how productivity grew in these countries
resulted to a large extent from high fluctuations in GDP growth rates. The Baltic states recorded rapid economic growth in the first few years of their EU membership, at times exceeding 10% per annum. These countries were also hardest hit by the implications of the global crisis because, in 2009, they noted a double-digit fall in GDP. As a result, TFP changes in the Baltics were the most differentiated among EU11 countries. The difference between the highest and the lowest TFP growth rates was slightly above 20 percentage points in Latvia and Lithuania (ranging from –13.7% to 6.6% in Latvia and from –14.2% to 6.0% in Lithuania) and almost 19 p.p. in Estonia. In the remaining CEE countries except the Baltic states and Poland, the spread of the TFP growth rates ranged from 15 p.p. in Romania to 9 p.p. in Hungary. Poland, which exhibited regular growth in output throughout the 2005–2014 period and was the only EU country to avoid recession, recorded exceptionally small variations in TFP, at 4.3 percentage points. Even the countries of Western Europe as a whole recorded greater fluctua- tions in productivity growth in 2005–2014 than Poland. This last result is another reason to positively assess Poland’s achievements in terms of total factor productivity. Apart from the fact that Poland recorded the fastest growth of productivity in the last 10 years, it was the most stable of the whole group of Central and Eastern European countries. In Poland, the slowest growth of TFP in the examined period was recorded in 2009 (–0.6%), while the fastest growth appeared in 2006 (3.7%).
Based on the data in Table 9.2, it is worth analyzing the dynamics of total factor productivity in the individual subperiods. Before the global crisis, in 2005–2007, all the CEE countries recorded a positive growth rate of TFP. It was the highest in the Baltic states (5.7% in Lithuania, 5.0% in Latvia, and 4.1% in Estonia), which – as already mentioned – was due to very rapid GDP growth in these countries before the crisis. The growth rate of TFP in Poland at that time was moderate at 2.8% on average (the same as in Slovenia). Apart from the Baltic states, Slovakia (4.7%), Romania (3.7%), and the Czech Republic (3.5%) also recorded better results than Poland. The other three CEE countries, Bulgaria, Croatia, and Hungary, showed slower dynamics in terms of total factor productivity in 2005–2007, at 2.5%, 2.2%, and 0.8% respectively. Throughout the 2005–2007 period, the TFP growth rates in all the CEE countries were no worse than in the EU15 as a whole: in the latter group TFP grew at a rate of 0.8%, which means at the same pace as in Hungary.
The crisis brought significant changes in the dynamics of total factor productivity. In 2008–2010, all the CEE countries except Poland recorded negative TFP growth. The Baltics, which recorded the highest pre-crisis TFP growth rates, performed the worst in terms of productivity growth during the crisis, with negative growth rates at –6.5% in Latvia, – 6.4% in Estonia, and –3.6% in Lithuania. Poor results in 2008–2010 were also recorded in Croatia (–3.9%), Romania (–3.6%), Slovenia (–2.9%), and Hungary
(–2.4%). Poland was the only country with positive TFP growth, at 1.4% in 2008–2010. In this period, the EU15 group as a whole recorded a decline in TFP by 1.5% on average.
In 2011–2013, the majority of the CEE countries began to improve their positions compared with previous years in terms of TFP dynamics. The Baltic states again recorded positive TFP growth rates. They stood at 3.2% in Latvia, 3.0% in Lithuania, and 1.8% in Estonia. Poland maintained positive TFP growth at 0.9% per annum, slightly worse than in previous years. Bulgaria, Slovakia, and Romania also noted posi- tive TFP growth rates, but very close to zero (not exceeding 0.5%). Slovenia and Hun- gary displayed negative TFP growth rates in this period, ranging from 0% to –1% a year, while in Croatia and the Czech Republic, the TFP decline was greater, at almost 2%. In the EU15 group, total factor productivity did not change from 2011 to 2013.
In 2014, the CEE countries posted varied outcomes in terms of TFP dynamics. Some