European Integration, Productivity Growth and Real Convergence: Evidence from the New Member States

1
European Integration, Productivity Growth and
Real ConvergenceEvidence from the New Member
States

• Ali M. Kutan and Taner M. Yigit
• Kutan Southern Illinois University
  Edwardsville ZEI, Bonn EMG, London and WDI,
  Michigan.
• Yigit Bilkent University, Ankara

2
Objective

• To analyze the determinants of labor productivity
  in 8 new members of the European Union that
  joined in 2004
• CEE8 - the Czech Republic, Estonia, Hungary,
  Poland, Latvia, Lithuania, Slovakia and Slovenia

3
Focus

• On the impact of globalization and integration
  factors explaining productivity
• CEE8 provides a good case study
• Since 1990s significant opening up and
  integration towards the West have been taking
  place

4
MotivationWhy labor productivity?

• Growth in labor productivity raised income per
  capita in CEE8 countries more than that in
  employment and population (World Bank Report,
  2008)
• CEE8 labor productivity has grown at a rate
  greater than many other emerging and developing
  countries, including Russia and Ukraine (Rada and
  Taylor, 2006).

5
Why labor productivity?

• The net cumulative productivity change during
  1995-2006 ranged from 109 (Estonia) to 41 (
  Slovenia)
• The biggest productivity increases took place in
  the three Baltic States Estonia (109 ),
  Lithuania (104 ) and Latvia (93 )
• Hungary and Poland are the next biggest
  productivity gainers with a net cumulative gain
  of 75 and 68 , respectively
• Net cumulative productivity gain in EU 15 during
  the same time period was only 24.2

6
Why labor productivity?
7
Why labor productivity?

• Significant volatility in labor productivity is a
  concern what causes it?
• Implications for real income convergence and
  euro-area policy
• Income growth through productivity increases is
  important if excessive population movements from
  the new members to the old are to be avoided and
  if the EU's budget is not to be strained by
  transfers to lagging economies.

8
Theoretical Model

• We use the theoretical model developed in Bernard
  and Jones (RESTAT,1996a AER, 1996b) and Cameron
  et al (EER, 2005)
• It is shown that productivity growth is the
  result of country specific innovation or
  technology transfers from frontier countries

9
Innovation Variables

• Theory suggest that both domestic and
  international factors boost innovation. Most
  commonly used variables in the literature are
  FDI, trade, R D spending, and human capital
• We are particularly interested in international
  factors here as they are directly related to the
  integration efforts of CEE8 countries

10
Technology transfer

• Technology transfer is defined as the distance in
  productivity level between non-frontier countries
  and the frontier country
• Employed as a proxy for technology transfer and
  convergence in technical efficiency
• Trade data is typically used to control for the
  rate of technological transfer

11
Empirical Specification
12
Empirical Specification

• Dependent variable Labor productivity growth
• Zt vector includes globalization variables
  (exports, imports, and FDI,) and domestic
  innovation variables (human capital, and R D
  expenditures). Domestic investment is also
  included as a control variable
• Distance variable, a proxy for the rate of
  technology transfer from the frontier, is
  measured by the absolute value of the log ratio
  of productivity of country i to the productivity
  of EU15.

13
Expected signs

• Innovation variables are expected to have all
  positive, but recent studies show that imports
  may have a negative influence (Kasahara and
  Rodrique, JDE, 2008 and Blalock and Veloso, WD,
  2007).
• Imports may have a positive or negative sign
  depending upon (i) the composition of imports
  (i.e., high-tech vs consumption goods), (ii) the
  relative cost of imports with respect to local
  substitutes, (iii) varieties, and (iv) the
  relative usage of imported intermediaries in
  production with respect to domestic ones

14
Expected signs

• Distance variable is measured by the absolute
  value of the log ratio of productivity of country
  i to the productivity of EU15.
• As the productivity gap between country i and the
  frontier EU15 widens, this ratio grows smaller,
  making the absolute value of the log a larger
  number. With larger numbers, or a larger gap, the
  productivity growth of country i is expected to
  be faster, indicating a positive coefficient.

15
Methodology and Sample Period

• The estimations are carried out using a fixed
  effects panel estimation correcting for potential
  heteroskedasticity in the cross sectional
  dimension
• Sample period 1995-2006 Annual data

16
Dependent and Explanatory Variables

• Dependent variable change in labor productivity
  of industry obtained from the Transition Reports
  of the EBRD
• FDI, exports, imports, domestic investment, and
  education (expressed as a ratio of GDP, except
  education of population)
• Distance (the absolute value of the log ratio of
  productivity of country i to the productivity of
  EU15) is computed using data real output per
  worker.
• Other data sources AMECO of the European
  Commission's Directorate General for Economic and
  Financial Affairs and the EuroStat

17
Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance) Table 1 Descriptive Statistics Mean (Variance)
Prod. Growth Distance RD Education Import Export FDI
CZE 3.7 (59.2) 1.28 (0.01) 1.2 (0.03) 86.3 (11.5) 62.6 (43.4) 60.8 (78.0) 5.7 (11.3)
EST 9.0 (58.1) 2.05 (0.06) 0.6 (0.15) 85.7 (14.3) 74.2 (38.7) 74.8 (25.8) 8.0 (24.0)
HUN 6.2 (12.7) 1.60 (0.01) 0.8 (0.02) 69.8 (39.7) 63.0 (116.4) 22.2 (1.2) 7.3 (12.9)
LAT 7.7 (38.9) 2.28 (0.04) 0.4 (0.01) 81.9 (8.8) 54.2 (36.0) 43.7 (7.1) 4.5 (3.5)
LIT 8.6 (47.9) 2.43 (0.05) 0.6 (0.01) 83.9 (11.5) 58.8 (33.2) 50.4 (31.7) 3.5 (3.8)
POL 5.6 (12.6) 1.71 (0.02) 0.6 (0.00) 79.6 (18.2) 31.9 (36.6) 29.1 (39.5) 3.4 (1.1)
SLA 4.0 (23.9) 1.81 (0.01) 0.7 (0.04) 83.1 (23.1) 73.3 (96.6) 67.8 (107.4) 4.5 (22.2)
SLE 3.3 (32.8) 0.74 (0.01) 1.5 (0.01) 74.9 (23.1) 57.0 (23.8) 55.7 (27.3) 1.9 (3.5)
EU15 1.9 (0.01) 61.3 (15.5) 31.6 (11.8) 35.6 (11.7) 2.3 (2.8)
18
Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates Table 2 Productivity Growth Estimates
  (1) (2) (3) (4) (5) (6) (7)
C -54.05 -53.11 -53.81 -51.44 -62.68 -61.81 -55.43
  (-3.18) (-3.03) (-3.15) (-2.8) (-3.11) (-2.91) (-3.36)
Distance(-1) 9.69 9.15 10.38 9.98 9.57 9.47 8.62
  (2.04) (1.86) (1.88) (1.76) (1.68) (1.64) (1.84)
RD(-1) 0.30 -1.22 0.45 0.36 0.31 0.33 0.55
  (0.05) (-0.2) -0.08 (0.06) (0.05) (0.06) (0.1)
Education(-1) 0.73 0.76 0.73 0.70 0.96 0.95 0.83
  (3.83) (3.74) (3.75) (3.39) (3.53) (3.38) (4.28)
Imports(-1) -0.58 -0.57 -0.58 -0.57 -0.58 -0.58 -0.58
  (-6.21) (-5.91) (-6.20) (-6.12) (-5.91) (-5.60) (-6.54)
Exports 0.50 0.47 0.51 0.51 0.40 0.40 0.43
(3.55) (3.08) (3.30) (3.21) (2.39) (2.37) (2.93)
FDI 0.35 0.38 0.34 0.33 0.40 0.40 0.36
  (2.73) (2.77) (2.58) (2.35) (2.66) (2.55) (2.86)
Investment 0.25 0.23 0.24 0.24 0.09 0.08 0.16
  (1.34) (1.19) (1.20) (1.19) (0.39) (0.37) (0.79)
DRD 11.06  
  (0.74)  
DEducation 0.14 0.13 0.04 0.05
      (0.26) (0.23) (0.08) (0.09)
DImports -0.09 0.29 0.28
    (-0.36) (0.86) (0.80)  
DExports -0.51 -0.51 -0.34
        (-1.54) (-1.49) (-1.47)
DFDI -0.08
            (-0.12)
R2 0.411 0.389 0.406 0.397 0.382 0.389 0.444
N 78 78 78 78 78 78 78
19
Empirical Findings

• Among the domestic factors, RD expenditures do
  not have any impact on productivity changes,
  perhaps due to very small amounts (1-2 percent of
  GDP)
• However, secondary school enrollment ratio has a
  very significant effect on productivity changes
  (coefficient value .73)

20
Empirical Findings

• Regarding international factors, exports and FDI
  variables have a positive and significant
  coefficients (0.50 and 0.35, respectively)
• However, imports has a negative and significant
  effect and its economic significance is large
  (the estimated coefficient is - 0.58)
• Overall, globalization has a net positive impact
  on productivity A 1 percent increase in global
  activity (FDI and net trade flows) improves labor
  productivity by 0.27 (0.500.35 -0.58) percent.

21
Empirical Findings

• With respect to technological transfer, the
  distance coefficient is positive and
  statistically significant, indicating significant
  technology transfer from EU 15 facilitating
  catching up by CEE8 countries towards EU
  standards
• However, international and domestic variables
  used here do not seem to help facilitate
  technology transfer rate, perhaps due to a
  relatively small number of observations we have.

22
Further Research Areas

• Further evidence at micro level is necessary to
  better understand the imports-productivity link
• Almost no research on this issue for CEE8
  countries
• Halpern et al. (2006) employ a panel data of
  Hungarian firms to test the impact of imports on
  productivity. They argue that imports may
  influence labor productivity through a quality
  and a variety channel and find empirical evidence
  supporting these channels

23
Further Research Areas

• Why variables typically used in the literature
  (FDI, trade, R D) do not seem to facilitate
  technology transfer rate
• Data problems small sample size?
• Unobserved or informal factors such as informal
  economy and its size?
• The estimated model explains only 41 percent of
  variation in labor productivity growth.
• Further research employing more formal and
  informal indicators of productivity would be
  fruitful.

24
Conclusions and Policy Implications

• Two channels of labor productivity growth
  (country-specific innovation and technology
  transfer) are at work
• As innovation variables, globalization (FDI and
  exports) and human capital have been the key
  sources of positive productivity growth in CEE8
  during 1995-2006
• There is convergence of transfer technology,
  raising productivity growth which is essential
  for convergence to core European income levels
• Policymakers need to design further reforms to
  encourage exports and FDI growth

25
Conclusions and Policy Implications

• Policymakers need to better understand the forces
  driving the rate of technology transfer as
  variables typically used in the literature may
  not seem facilitate it entirely. For example, how
  important is the informal economy for
  productivity? How does it facilitate technology
  transfer?
• Aggregate impact of imports on labor productivity
  is negative. Although policymakers care about
  aggregate impacts, it is important to look at the
  disaggregated data to better understand the
  imports-productivity link to design appropriate
  policies to deal with the problem
• Overall, further research on the primary drivers
  of labor productivity growth at the aggregate,
  sectoral and firm level would be worthwhile.