Presented at part of the ADEMU Project at the Macroeconomic and Financial Imbalances and Spillovers Workshop June 2017

1. Sectoral allocation and macroeconomic imbalances in
EMU
Niels Gilbert and Sebastiaan Pool
University of Groningen
De Nederlandsche Bank
June 24, 2017
1 / 48

2. Introduction
Introduction: real interest rate convergence
Figure: Ex-ante real interest rate 1 year bonds
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1995 1996 1997 1998 1999 2000 2001 2001 2003 2004 2005 2006 2007
IIPS REA (excl. LUX)
Source: Thomson Reuters, Consensus forecasts.
2 / 48

3. Introduction
Current account divergence
Figure: Current account euro area (billions)
-300
-200
-100
0
100
200
300
400
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
GIIPS REA
Source: IMF WEO database October 2015.
3 / 48

4. Introduction
Domestic demand boom
Figure: Growth was driven by domestic demand
export.pdf
100
120
140
160
180
200
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
b: Export (1998 = 100)
GIIPS REA
100
110
120
130
140
150
160
170
180
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
a: Domestic demand (1998 = 100)
GIIPS REA
Source: KLEMS Database, Euro area consists of AUT, BEL, ESP, FIN, FRA, GER, ITA and NLD
4 / 48

5. Introduction
Growth of nontradable sector
Figure: Growth of nontradeble sectors
80
100
120
140
160
180
200
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
a: Value added NT sector (top 33%)
GIIPS REA
80
100
120
140
160
180
200
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
b: Value added NT sector (top 33%,
excl. construction)
GIIPS REA
1999 = 100. Source: own calculations based on WIOD database (Timmer et al, 2015).
5 / 48

6. Introduction
Tradable versus nontradable TFP-growth
Figure: Euro area TFP growth per sector
97
99
101
103
105
107
109
111
113
TFP tradable (66%) TFP nontradable (33%)
Source: KLEMS Database, Euro area consists of AUT, BEL, ESP, FIN, FRA, GER, ITA and NLD
6 / 48

7. Literature
Literature
7 / 48

8. Literature
Literature
Allocation of capital in Southern Europe and effects on productivity
Empirically: Borio et al. (2016): credit booms associated with
reallocation of labor towards sectors with lower productivity growth.
Theoretically: exogenous interest rate drop can lead to growth of NT
sector (Fagan and Gasper, 2005, Piton, 2015) and contribute to
stagnating productivity growth (Benigno and Fornaro, 2014). Gopinath
et al. (2015): with financial frictions, also misallocation within sectors.
8 / 48

9. Literature
Literature
Allocation of capital in Southern Europe and effects on productivity
Empirically: Borio et al. (2016): credit booms associated with
reallocation of labor towards sectors with lower productivity growth.
Theoretically: exogenous interest rate drop can lead to growth of NT
sector (Fagan and Gasper, 2005, Piton, 2015) and contribute to
stagnating productivity growth (Benigno and Fornaro, 2014). Gopinath
et al. (2015): with financial frictions, also misallocation within sectors.
Vulnerability of nontradable-driven growth
NT driven, debt financed, growth risks violating intertemporal b.c.
(Giavazzi and Spaventa 2010) and can make economy financially
fragile (Kalantzis, 2015).
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10. This paper
This paper
10 / 48

11. This paper
This paper
Documents that following the introduction of the euro, Southern
Europe experienced broad-based growth of the nontradable sector,
extending beyond the construction sector
11 / 48

12. This paper
This paper
Documents that following the introduction of the euro, Southern
Europe experienced broad-based growth of the nontradable sector,
extending beyond the construction sector
Presents (open and closed versions of) a two region model of a
monetary union to show how the sharp fall in Southern interest leads
wage growth, CA deficit and growth of NT sector, while inducing an
opposite process in the North
12 / 48

13. This paper
This paper
Documents that following the introduction of the euro, Southern
Europe experienced broad-based growth of the nontradable sector,
extending beyond the construction sector
Presents (open and closed versions of) a two region model of a
monetary union to show how the sharp fall in Southern interest leads
wage growth, CA deficit and growth of NT sector, while inducing an
opposite process in the North
Confirms the negative relation between interest rate shocks and
growth of the nontradable sector in a panel-BVAR for the euro area
13 / 48

14. This paper
This paper
Documents that following the introduction of the euro, Southern
Europe experienced broad-based growth of the nontradable sector,
extending beyond the construction sector
Presents (open and closed versions of) a two region model of a
monetary union to show how the sharp fall in Southern interest leads
wage growth, CA deficit and growth of NT sector, while inducing an
opposite process in the North
Confirms the negative relation between interest rate shocks and
growth of the nontradable sector in a panel-BVAR for the euro area
Studies reform options that facilitate a smoother rebalancing process
14 / 48

15. Model
Model Overview
Two regions, North and South, that are to form a monetary union
Prior to monetary integration: fixed exchange rates, but wedge
between interest rates: r South > r North
Post monetary integration: price level stabilized at union level, single
risk free interest rate (debt-elastic interest rate premium remains)
Union as a whole is a closed economy
Labor is mobile across sectors, but not across regions
15 / 48

16. Model
Model Overview
Two regions, North and South, that are to form a monetary union
Prior to monetary integration: fixed exchange rates, but wedge
between interest rates: r South > r North
Post monetary integration: price level stabilized at union level, single
risk free interest rate (debt-elastic interest rate premium remains)
Union as a whole is a closed economy
Labor is mobile across sectors, but not across regions
Both regions exist of a representative household, tradable (T) and
nontradable (NT) firms operating in a monopolistically competitive
environment, and a simple government
Full business cycle model with capital, endogenous labor supply and
capital adj. costs
16 / 48

17. Model
Households (1)
17 / 48

18. Model
Households (1)
Households in each region j maximize lifetime utility:
Uj
t =
∞
v=0
(βj
)v
log Cj
t+v −
θj (Lj
t+v )1+σj
1 + σj
. (1)
Consumption good is a composite of tradables and nontradables:
Cj
t = (Cj,N
t )ηj
(Cj,T
t )1−ηj
. (2)
Consumer price index:
Pj
t =
(Pj,N
t )ηj
(Pj,T
t )1−ηj
(ηj )ηj
(1 − ηj )1−ηj . (3)
18 / 48

19. Model
Households (2)
Household can save/ borrow via one period risk free bonds. UIP:
rf ,n
t + ω = rf ,s
t , (4)
where ω is an exogenous pre-EMU risk premium (cf. Kollmann, 2015)
Stabilizing debt-elastic interest rate premium:
xj
t = ξe−Nj
t − 1. (5)
Budget constraint:
j
Bj j
t + Pj,T
t Cj,T
t + Pj,N
t Cj,N
t =
j
(1 + rj
t−1)Bj j
t−1 + πj
t + Lj
tW j
t , (6)
where rj
t = rf ,j
t + xj
t .
19 / 48

20. Model
Firms (1)
In both regions, the economy is occupied by two types of
monopolistically competitive intermediate firms producing varieties of
wholesale tradable (T) and wholesale nontradable (N) goods.
20 / 48

21. Model
Firms (1)
In both regions, the economy is occupied by two types of
monopolistically competitive intermediate firms producing varieties of
wholesale tradable (T) and wholesale nontradable (N) goods.
Both sectors hire labor from the household sector, buy capital from
the capital producers, and sell their wholesale goods to retailers.
21 / 48

22. Model
Firms (1)
In both regions, the economy is occupied by two types of
monopolistically competitive intermediate firms producing varieties of
wholesale tradable (T) and wholesale nontradable (N) goods.
Both sectors hire labor from the household sector, buy capital from
the capital producers, and sell their wholesale goods to retailers.
Retailers use the wholesale goods to produce the final goods
22 / 48

23. Model
Firms (1)
In both regions, the economy is occupied by two types of
monopolistically competitive intermediate firms producing varieties of
wholesale tradable (T) and wholesale nontradable (N) goods.
Both sectors hire labor from the household sector, buy capital from
the capital producers, and sell their wholesale goods to retailers.
Retailers use the wholesale goods to produce the final goods
Structure serves to realize monopolistic competition and adjustment
costs in a tractable manner
Note: Tradable consumption good serves as the investment good
23 / 48

24. Model
Firms (2)
Capital producers sell their capital for a price qj,Z
t :
qj,Z
t = Pj,T
t 1 + φ
Ij,Z
t
Kj,Z
t
− δ (7)
The intermediary price is set as a mark-up over their marginal costs
λj,Z
t such that aggregate prices are:
Pj,Z
t =
µj,Z
µj,Z − 1
λj,Z
t . (8)
24 / 48

25. Model
Prices
Absence of trade restrictions ensure law of one price: Pn,T
t = Ps,T
t
The monetary authority stabilizes the union’s price level
Pe
t = hPn
t + (1 − h)Ps
t ≡ 1. (9)
where h is the Northern share in the union.
25 / 48

26. Model
Market equilibrium conditions
Market for nontradables:
Y j,N
t = Cj,N
t + Gj,N
t . (10)
Market for tradables:
j
Y j,T
t =
j
Cj,T
t + Ij,T
t + Ij,N
t + ACj
t + ICj
t + Gj,T
t . (11)
Closure on the bond market:
NFAj
t =(1 + rf ,j
t−1)NFAj
t−1 + Pj,T
t (Y j,T
t − Cj,T
t − Ij,T
t − Ij,N
t −
ACj
t − ICj
t − Gj,T
t ). (12)
Finally, equilibrium in the market for financial assets requires:
NFAn
t + NFAs
t = 0. (13)
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27. Calibration
Calibration
Key parameters:
Both regions are of equal size
Discount factors set to match pre-EMU current account balances
(close to zero in both blocks)
Country specific risk premium set to match NFA dynamics
Productivity constant across blocks and sectors (baseline only)
Some sectoral and cross-country heterogeneity, but not key to results
Use Dynare for a numerical simulation of the full nonlinear model
Deterministic simulation, assuming perfect foresight
27 / 48

28. Results
Simulation results
28 / 48

29. Results
Simulation results
Figure: Consequences of monetary integration (1)
1,32
1,33
1,34
1,35
1,36
1,12
1,13
1,14
1,15
1,16
1 3 5 7 9 11 13 15
c: wage developments
Wage South Wage North (r-axis)
1,0%
1,5%
2,0%
2,5%
1 3 5 7 9 11 13 15
a: risk-free quarterly interest rate
RF South RF North
1,78
1,80
1,82
1,84
1,57
1,59
1,61
1,63
1 3 5 7 9 11 13 15
b: consumption
C South C North (r-axis)
1,06
1,07
1,08
1,09
1,1
1,11
1,12
1 3 5 7 9 11 13 15
d: real exchange rate
Real exchange rate (P_South / P_North)
29 / 48

30. Results
Simulation results
Figure: Consequences of monetary integration (2)
0,98
1
1,02
1,04
1,06
1,08
0,79
0,8
0,81
0,82
1 3 5 7 9 11 13 15
f: sectoral allocation (South)
KN/KT South LN/LT South (r-axis)
1,0%
1,5%
2,0%
2,5%
1 3 5 7 9 11 13 15
h: risk-adjusted quarterly interest rate
R South R North
0,84
0,86
0,88
0,9
0,92
0,94
0,73
0,74
0,75
0,76
1 3 5 7 9 11 13 15
g: sectoral allocation (North)
KN/KT North LN/LT North (r-axis)
-10%
-8%
-6%
-4%
-2%
0%
-60%
-50%
-40%
-30%
-20%
-10%
0%
1 3 5 7 9 11 13 15
e: external position (% GDP)
NFA South CA South (r-axis)
30 / 48

31. Results
Simulation results including ROW
Figure: Consequences of monetary integration - model including RoW
1.0%
1.5%
2.0%
2.5%
1 3 5 7 9 11 13 15
a: risk-free quarterly interest rate
RF South RF South 3cnt
0.94
0.95
0.96
0.97
1 3 5 7 9 11 13 15
b: exchange rate RoW / EA
Exchange rate RoW/ EA
31 / 48

32. Results
Simulation results including ROW
Figure: Consequences of monetary integration - model including RoW
0.95
1
1.05
1.1
0.79
0.8
0.81
0.82
1 3 5 7 9 11 13 15
d: sectoral allocation (South)
KN/KT South KN/ KT South 3cnt
LN/LT South (r) LN/LT South 3cnt (r)
1.0%
1.5%
2.0%
2.5%
1 3 5 7 9 11 13 15
a: risk-free quarterly interest rate
RF South RF South 3cnt
0.94
0.95
0.96
0.97
1 3 5 7 9 11 13 15
b: exchange rate RoW / EA
Exchange rate RoW/ EA
-80%
-60%
-40%
-20%
0%
-14%
-10%
-6%
-2%
2%
1 3 5 7 9 11 13 15
c: external position (South, % GDP)
CA South CA South 3cnt
NFA South (r) NFA South 3cnt (r)
32 / 48

33. Results
EMU Panel BVAR
33 / 48

34. Results
EMU Panel BVAR
BVAR representation
Xt =α0 + α1Dt + Φ(L)Xt−1 + εt, (14)
where Φ(L) ≡ Φ0 + Φ1L1 + ... + ΦpLp is a lag polynomial, Xt is a
stacked vector containing the observed variables:
34 / 48

35. Results
EMU Panel BVAR
BVAR representation
Xt =α0 + α1Dt + Φ(L)Xt−1 + εt, (14)
where Φ(L) ≡ Φ0 + Φ1L1 + ... + ΦpLp is a lag polynomial, Xt is a
stacked vector containing the observed variables:
Xt = (yN
t,i − ¯yN
t ), (yT
t,i − ¯yT
t ),
Bt,i
Yt,i
−
¯Bt
¯Yt
, (ir
t,i −¯ir
t ) ,
where yN
t,i and yT
t,i denote nontradable and tradable sector growth
ir
t,i is the ex-ante expected real interest rate
Bt,i
Yt,i
denotes a country’s current account balance (%GDP)
35 / 48

36. Results
Panel BVAR specification
Xt = (yN
t,i − ¯yN
t ), (yT
t,i − ¯yT
t ),
Bt,i
Yt,i
−
¯Bt
¯Yt
, (ir
t,i −¯ir
t ) , (15)
Cholesky Decomposition ordering as in (15)
Subtract the euro area mean
36 / 48

37. Results
Panel BVAR specification
Xt = (yN
t,i − ¯yN
t ), (yT
t,i − ¯yT
t ),
Bt,i
Yt,i
−
¯Bt
¯Yt
, (ir
t,i −¯ir
t ) , (15)
Cholesky Decomposition ordering as in (15)
Subtract the euro area mean
The data is observed at an annual frequency and therefore only one
lag is included
Pooled Bayesian estimation procedure
Agnostic Minnesota prior: the unit root coefficient takes a prior value
of 0.8 and Inverse-Wishart Distribution
Hyperparameters are set at “standard” values
37 / 48

38. Results
Data
Output growth for 10 euro area countries (Austria, Belgium,
Germany, Finland, France, Italy, Ireland, Netherlands, Spain and
Portugal) is calculated using Eurostat data
The disaggregated time-series are categorized in either the tradable or
nontradable sector
Annual nominal interest rates on 1-year government bonds minus
consensus forecast inflation expectations one year ahead to transform
the nominal interest rates into ex-ante real interest rates
WEO database to collect data on current account balances
The time-series cover the period 1996-2013
38 / 48

39. Results
Empirical results
39 / 48

40. Results
Empirical results
Figure: Bayesian estimation results for sample period 1996-2008
5 10 15 20
-0.3
-0.2
-0.1
0
Nontradable: yN
t;i ! 7yN
t
5 10 15 20
-0.3
-0.2
-0.1
0
Tradable: yT
t;i ! 7yT
t
5 10 15 20
-0.1
0
0.1
0.2
Current account:
Bt;i
Yt;i
!
7Bt
7Yt
5 10 15 20
0
0.2
0.4
Real rate: ir
t;i !7ir
t
Responseof:
Shock:
Sample 1996-2008. 68% credibility intervals are generated by drawing from the posterior distribution: 50, 000 draws of which
40, 000 draws are discarded as burn-in iterations. Time is quarterly.
40 / 48

41. Results
Empirical results
Figure: Bayesian estimation results for sample period 1996-2008
5 10 15 20
-0.3
-0.2
-0.1
0
Nontradable: yN
t;i ! 7yN
t
5 10 15 20
-0.3
-0.2
-0.1
0
Tradable: yT
t;i ! 7yT
t
5 10 15 20
-0.1
0
0.1
0.2
Current account:
Bt;i
Yt;i
!
7Bt
7Yt
5 10 15 20
0
0.2
0.4
Real rate: ir
t;i !7ir
t
Responseof:
Shock:
Sample 1996-2008. 68% credibility intervals are generated by drawing from the posterior distribution: 50, 000 draws of which
40, 000 draws are discarded as burn-in iterations. Time is quarterly.
Figure: Bayesian estimation results for sample period 1996-2013
5 10 15 20
-0.2
0
0.2
Nontradeable: yN
t;i ! 7yN
t
5 10 15 20
-0.2
0
0.2
Tradable: yT
t;i ! 7yT
t
5 10 15 20
0
0.2
0.4
Current account:
Bt;i
Yt;i
!
7Bt
7Yt
5 10 15 20
-0.2
0
0.2
0.4
0.6
0.8
Real rate: ir
t;i !7ir
t
Shock:
Sample 1996-2013. 68% credibility intervals are generated by drawing from the posterior distribution: 50, 000 draws of which
40, 000 draws are discarded as burn-in iterations. Time is quarterly.
41 / 48

42. Policy options
Policy options
Crisis can be modeled as a ‘Minsky moment’ in which risk aversion
suddenly increases
Fiscal policy also offers a fairly straightforward tool to lean against
excessive private borrowing
Various policy options that can accommodate a less disruptive
rebalancing process are examined
Increasing competition in the nontradable sector
Deepening the internal market
42 / 48

43. Policy options
Increasing competition in the nontradable sector
Figure: Product market reform in South, transition path
0.76
0.78
0.8
0.82
0.84
0.86
0.88
0.9
0.64
0.66
0.68
0.7
0.72
1 3 5 7 9 11 13 15
e: sectoral allocation
KN/KT South LN/LT South (r-axis)
5.68
5.70
5.72
5.74
5.76
5.78
4.58
4.60
4.62
4.64
4.66
4.68
1 3 5 7 9 11 13 15
c: GDP
GDP South GDP North (r-axis)
1.50
1.55
1.60
1.65
1.70
1.75
1 3 5 7 9 11 13 15
a: relative price of nontradables
PN/ PT South PN/ PT North
0.5%
1.0%
1.5%
-73%
-72%
-71%
-70%
1 3 5 7 9 11 13 15
f: external position (% GDP)
NFA South CA South (r-axis)
1.92
1.94
1.96
1.98
1.65
1.66
1.67
1.68
1.69
1.70
1.71
1 3 5 7 9 11 13 15
b: private consumption
C South C North (r-axis)
0.55
0.57
0.59
0.61
0.63
0.65
0.67
1 3 5 7 9 11 13 15
d: relative sectoral size
YN/YT South YN/ YT North
43 / 48

44. Policy options
Deepening the internal market
Figure: Deepening the EA internal market, transition path
5.10
5.15
5.20
5.25
5.30
4.04
4.08
4.12
4.16
4.20
4.24
1 3 5 7 9 11 13 15
c: GDP
GDP South GDP North (r-axis)
1.32
1.37
1.42
1.47
1.50
1.55
1.60
1.65
1 3 5 7 9 11 13 15
a: relative price of nontradables
PN/ PT South PN/ PT North (r)
-2.0%
-1.5%
-1.0%
-0.5%
0.0%
0.5%
-90%
-86%
-82%
-78%
1 3 5 7 9 11 13 15
e: external position South (% GDP)
NFA South CA South (r-axis)
1.8
1.81
1.82
1.83
1.84
1.53
1.54
1.55
1.56
1.57
1 3 5 7 9 11 13 15
b: private consumption
C South C North (r-axis)
0.60
0.62
0.64
0.66
0.68
0.70
0.72
1 3 5 7 9 11 13 15
d: relative sectoral size
YN/YT South YN/ YT North
0.92
0.94
0.96
0.98
1 3 5 7 9 11 13 15 17 19
f: exchange rate RoW / EA
Exchange rate RoW/ EA
44 / 48

45. Conclusion
Conclusion
CA deficit and growth of NT sector in Southern Europe are natural
consequences of the fall in real interest rates
Wage growth (competitiveness problems) consequence, rather than
prime cause of imbalances
Shift towards less-productive NT sector potential driver of aggregate
productivity slowdown
Southern boom can also explain pivot towards export growth and
wage moderation in Northern Europe
Policy options/counterfactuals:
Liberalizing the Southern nontradable sector does not improve the
region’s external position
Deepening the European market for tradables induces a shift of
productive resources towards the tradable sector and boosts growth
45 / 48

46. Back-up slides
Calibration parameters
Parameters Description Value
βn Discount factor households 0.990
βs Discount factor households 0.980
σ Inverse of the elasticity of work effort 2.00
θz Weight of leisure 1.000
ηz Share of nontradables in consumption 0.667
αT Share of labor in the production function 0.550
αN Share of labor in the production function 0.600
δ Depreciation rate of physical capital 0.030
µN,n Market power nontradable sector 5.000
µN,s Market power nontradable sector 3.500
µT,n Market power tradable sector 10.000
µT,s Market power tradable sector 10.000
h Relative share of North in union 0.500
φ Capital adjustment costs 2.000
46 / 48

47. Back-up slides
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Water Transport
Chemicals and Chemical Products
Basic Metals and Fabricated Metal
Rubber and Plastics
Air Transport
Electrical and Optical Equipment
Mining and Quarrying
Pulp, Paper, Paper , Printing and Publishing
Wood and Products of Wood and Cork
Other Non-Metallic Mineral
Other Supporting and Auxiliary Transport Activities; Activities of Travel Agencies
Transport Equipment
Coke, Refined Petroleum and Nuclear Fuel
Textiles and Textile Products
Machinery, Nec
Renting of M&Eq and Other Business Activities
Inland Transport
Financial Intermediation
Leather, Leather and Footwear
Wholesale Trade and Commission Trade, Except of Motor Vehicles and Motorcycles
Post and Telecommunications
Agriculture, Hunting, Forestry and Fishing
Electricity, Gas and Water Supply
Manufacturing, Nec; Recycling
Retail Trade, Except of Motor Vehicles and Motorcycles; Repair of Household Goods
Sale, Maintenance and Repair of Motor Vehicles and Motorcycles; Retail Sale of Fuel
Other Community, Social and Personal Services
Food, Beverages and Tobacco
Hotels and Restaurants
Real Estate Activities
Construction
Education
Public Admin and Defence; Compulsory Social Security
Health and Social Work
Private Households with Employed Persons
47 / 48

48. Back-up slides
Simulation results crash (Minsky moment)
-2%
0%
2%
4%
6%
8%
10%
12%
14%
-100%
-80%
-60%
-40%
-20%
0%
1 3 5 7 9 11 13 15
a: external position (% GDP)
NFA South CA South (r-axis)
0.87
0.89
0.91
0.93
0.95
0.97
0.74
0.75
0.76
0.77
1 3 5 7 9 11 13 15
c: sectoral allocation (North)
KN/KT North LN/LS North (r-axis)
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
1 3 5 7 9 11 13 15
d: risk-adjusted quarterly interest rate
R South R North
0.85
0.87
0.89
0.91
0.93
0.95
0.75
0.76
0.77
0.78
1 3 5 7 9 11 13 15
b: sectoral allocation (South)
KN/KT South LN/LS South (r-axis)
48 / 48