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‘Old’ Europe’s wage dynamics and trade imbalances: Is there a link?

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Abstract

No evidence is found that gains in relative labour productivity have had a positive effect on the trade balance/GDP ratio for the ‘old’ EU members (excluding Germany) from 1961 to 2014. Rising relative wage rate is shown to have had strong—and negative—effects on the trade balance/GDP ratio for the EU-14, at least in the longer run. It follows that external rebalancing may be achieved through a sufficiently strong fall in the relative wage rates, without productivity changes having a role to play. This is not to claim that the EU-14 (and its members suffering trade deficits in particular) ought to attempt the devastating policy of ‘internal devaluation’. A constructive alternative would be to achieve the fall in the relative wage rates through faster growth of German nominal wage rates. Whether that alternative is practicable is another matter. But it can be argued that without that alternative being followed the European Union will remain a stagnant area plagued by recurrent crises caused by imbalanced trade among its Member States.

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Notes

  1. “Appendix 2”, below, indicates that the conventional assumption on the trade balance being a function of GDP growth and Real Effective Exchange Rate for the EU-14 (the latter unit labour cost-based, relative to Germany) does not produce reasonable results either.

  2. Eurostat’s AMECO database reports the indices of relative nominal unit labour costs and nominal compensation per employee for the ‘old’ EU member countries—both relative to the rest of the EU-15 (series PLCDQ and HWCDWQ respectively.) From these one calculates the indices of real labour productivity for the EU-14 relative to Germany. The P and W variables used here are the growth rates of relative productivity and average nominal wage respectively for the whole EU-14 area relative to Germany. Necessarily, all items for the EU-14 are weighted averages.

  3. Some evidence on German exports displacing the Southern EU ones can be found in Chen et al. (2012).

  4. Without the trade surpluses of these four countries the whole EU-14 would have run huge trade surpluses from 2000 to 2012.

  5. Regressing, by OLS, D(B) on P yields a negative and small regression coefficient (−0.065) with a marginal probability of 0.4193. The Adjusted R-squared for that OLS regression is 0.011.

  6. The bounds used for qualification of null applied here come from Pesaran et al. (2001). These bounds are asymptotic. As shown by Narayan (2004), for finite samples (such as ours), the critical bounds are more restrictive.

  7. The index (or level) of EU-14 wage rates relative to Germany is I(2). As such it cannot be included among the explanatory variables in ARDL (‘Bounds’) models.

  8. It is often assumed that ‘wage developments relative to productivity’, or unit labour costs, are really decisive for determination of the trade balance. If that was the case the long run regression coefficient for productivity would have been positive (while it appears to be negative) and significant (it is not) and equal to (minus) the long run coefficient for the wage variable (which is not the case either).

  9. The “Appendix 1” graph indicates that the ‘fitted’ and actual B are reasonably close to each other, though of course one could still wish to better account for ‘residuals’ in 1980, 1983 and 2001.

  10. Working with aggregates taken across EU-14 does not seem much more problematic than working with aggregates for Germany (which consists of Laender as diverse as Bavaria and Mecklenburg-Vorpommern, a part of the erstwhile GDR).

  11. ARDL models relating the trade deficits of Italy, Spain, Greece and Portugal to the changes in their respective labor productivity indices relative to the rest of EU-15 all produce negative (and statistically insignificant) regression coefficients for the productivity change. The regression coefficients for changes in the wage rates relative to the rest of EU-15 are negative in the ARDL models for Greece, Italy and Portugal and positive (though small and statistically insignificant) for Spain.

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Acknowledgements

The author is grateful to two anonymous referees for helpful comments and suggestions.

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Authors and Affiliations

  1. The Vienna Institute for International Economic Studies, Rahlgasse 3, 1030, Vienna, Austria

    Leon Podkaminer

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  1. Leon Podkaminer
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Correspondence to Leon Podkaminer.

Appendices

Appendix 1: ARDL model underlying the co-integrating and long-run forms in Table 3

Dependent variable: B

Method: ARDL

Date: 02/09/16 Time: 14:40

Sample (adjusted): 1966 2014

Included observations: 49 after adjustments

Maximum dependent lags: 4 (Automatic selection)

Model selection method: Akaike info criterion (AIC)

Dynamic regressors (5 lags, automatic): W

Fixed regressors: M M2 C

Number of models evalulated: 24

Selected Model: ARDL(4, 5)

Variable

Coefficient

SE

t-Statistic

Prob.*

B(−1)

0.658275

0.134626

4.889671

0.0000

B(−2)

0.095765

0.169480

0.565053

0.5755

B(−3)

−0.033586

0.166732

−0.201440

0.8415

B(−4)

−0.294053

0.135850

−2.164533

0.0371

W

0.052236

0.044355

1.177689

0.2466

W(−1)

−0.092886

0.054085

−1.717421

0.0945

W(−2)

−0.012867

0.053518

−0.240426

0.8114

W(−3)

0.020046

0.050960

0.393379

0.6964

W(−4)

−0.026929

0.050934

−0.528716

0.6002

W(−5)

−0.081050

0.038614

−2.098967

0.0429

M

−0.667566

0.223756

−2.983455

0.0051

M2

−3.042621

0.585027

−5.200823

0.0000

C

0.673899

0.160405

4.201226

0.0002

R2

0.815767

Mean dependent var

0.227858

Adjusted R2

0.754356

S.D. dependent var

0.982581

S.E. of regression

0.486991

Akaike info criterion

1.621169

Sum squared resid

8.537770

Schwarz criterion

2.123080

Log likelihood

−26.71864

Hannan-Quinn criter

1.811593

F-statistic

13.28375

Durbin-Watson stat

1.676908

Prob(F-statistic)

0.000000

  
  1. * p-values and any subsequent tests do not account for model selection

Below: actual and fitted B for the above ARDL model.

figure a

Appendix 2: GDP growth and exchange rates: poor determinants of the trade balance

In ‘standard economics’ the GDP growth (or growth differentials) and the exchange rates are important determinants of the trade balance. But it is not quite correct to expect that e.g. higher growth tends to lower the trade balance (through higher imports). Growth itself may be ‘export-led’—in which case higher growth would be associated with higher—not lower—trade balances.

The problematic role of ‘exchange rates’, however defined, as a factor behind the trade balance is not uncontroversial either. The literature abounds with empirical contributions which quite often yield rather sceptical conclusions concerning the exchange rate as a factor behind the trade balances. Observe though that our W variable considered in Sect. 4 (the change in the relative nominal wage rate) provides some measures of the exchange rate movements (especially for the countries sharing the same currency). It is no misuse of language to talk of ‘internal devaluation’—meaning cuts in nominal wage rates.

The model with B as a function of the GDP growth rate and the Real Effective Exchange Rate for the EU-14 (the latter unit labour cost-based, relative to Germany) does not produce convincing results. It suggests that (a) REER behaves ‘perversely’: devaluation is expected to lower the trade balance; (b) faster GDP growth is likely to lower the trade balance—but infinitesimally so—and that effect is highly uncertain (see the table below).

Co-integrating and long-run form

Dependent variable: D(B)

Selected model: ARDL(4, 0, 1)

Date: 09/13/16 Time: 13:29

Sample: 1961 2014

Included observations: 50

Cointegrating form

Variable

Coefficient

SE

t-Statistic

Prob.

D(B(−1))

0.224765

0.134950

1.665542

0.1034

D(B(−2))

0.163378

0.104421

1.564615

0.1254

D(B(−3))

0.212234

0.110868

1.914295

0.0626

D(E)

0.015629

0.020499

0.762427

0.4502

D(G)

−0.164625

0.049724

−3.310776

0.0019

D(M2)

−2.653424

0.373030

−7.113171

0.0000

CointEq(−1)

−0.302670

0.077444

−3.908216

0.0003

Cointeq = B − (0.0638*E −0.1951*G −6.0837*M2 −5.2493)

Long run coefficients

Variable

Coefficient

SE

t-Statistic

Prob.

E

0.063755

0.027851

2.289166

0.0273

G

−0.195138

0.142441

−1.369959

0.1782

M2

−6.083699

2.151831

−2.827219

0.0072

C

−5.249274

2.771023

−1.894345

0.0652

  1. Remark: G is the GDP growth rate for EU-14; E is the REER for EU-14. REER was calculated from the AMECO’s item XUNNQ. Contrary to widespread beliefs REER has not undergone a ‘continuous revaluation’ (relative to Germany.) The revaluation lasted from 2000 to 2008

No further attempt was made to complement the original variables (growth rates of productivity and wage rates) with other ‘possible’ explanatory variables (GDP growth, explicit exchange rate etc.) This is not to claim that the inclusion of such ‘possibly omitted’ items cannot be productive, or perhaps qualify the results achieved so far. Further research may need to be undertaken to support (or contradict) these results.

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Podkaminer, L. ‘Old’ Europe’s wage dynamics and trade imbalances: Is there a link?. Empirica 45, 395–408 (2018). https://doi.org/10.1007/s10663-016-9365-z

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