Macro-Stability of
Swiss WIR-Bank Spending:
Balance, Velocity, & Leverage
by James Stodder (RPI) & Bernard Lietaer (UC-Berkeley)
James Stodder, (Ph.D., Economics, Yale 1990)
Lally School of Management & Technology
Rensselaer Polytechnic Institute at Hartford
Hartford, Connecticut, USA
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I will try to show:
1. The WIR system, based on centralized
electronic credits, is self-adjusting.
2.a. Small Companies show countercyclical
WIR Velocities.
2.b. Large Companies show countercyclical
WIR Balances.
3. These self-adjusting, countercyclical
credits are non-inflationary.
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Swiss WIR-Bank, 80 Years Old
Founded during Great Depression, in 1934,
around ideas of German-Argentine businessman:
Silvio Gesell (1862-1930).


Wirtschaftsring, or “Cercle Économique”

WIR = “WE” in German

Since 1955, Small-to-Medium Businesses only.
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In 2008, WIR-Bank had
70,200 Participants
Turnover 1.6 Billion SFr ($1.5 b. US)



WIR clients maintain two accounts, one in
Swiss Francs (SFr), the other in WIR.
WIR accounts can be used to clear (in WIR)
trades only with other WIR clients.
Since 1973, WIR credits are not supposed
to trade for SFr (although this still happens)
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Distribution of WIR Client-Firms
Number
Number
Industry
Swiss
WIR
RETAIL, of which
Registered
Non-Registered
62,380
SERVICES, of which
Registered
Non-Registered
Portion
(1,000 SFr)
(1,000 SFr)
(Swiss Fr.)
Turn/Balance =
WIR/Swiss
Turnover
Balance
Av. Bal.
Velocity
14,275
5,933
8,342
22.9%
9.5%
13.4%
345,757
223,822
121,935
127,100
64,958
62,142
8,904
10,949
7,449
2.72
3.446
1.962
164,709
10,380
3,817
6,563
6.3%
2.3%
4.0%
213,515
112,186
101,329
88,788
30,745
58,044
8,554
8,055
8,844
2.405
3.649
1.746
HOSPITALITY, of which
Registered
Non-Registered
28,006
3,438
2,099
1,339
12.3%
7.5%
4.8%
73,021
61,872
11,148
22,416
16,156
6,261
6,520
7,697
4,676
3.257
3.83
1.781
CONSTRUCTION, of which
Registered
Non-Registered
57,268
21,162
6,992
14,170
37.0%
12.2%
24.7%
527,619
280,169
247,450
210,477
82,462
128,015
9,946
11,794
9,034
2.507
3.398
1.933
MANUFACTURING, of which
Registered
Non-Registered
38,421
7,310
1,820
5,490
19.0%
4.7%
14.3%
230,196
87,418
142,778
101,884
26,092
75,792
13,938
14,336
13,805
2.259
3.350
1.884
WHOLESALE, of which
Registered
Non-Registered
21,762
4,138
1,027
3,111
19.0%
4.7%
14.3%
223,631
80,371
143,260
73,787
15,462
58,325
17,832
15,056
18,748
3.031
5.198
2.456
TOTALS, of which
Registered
Non-Registered
372,546
60,703
21,688
39,015
16.3%
5.8%
10.5%
1,613,739
845,838
767,901
624,452
235,874
388,578
10,287
10,876
9,960
2.584
3.586
1.976
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(1) Why are Centralized
Electronic Credits
Self-Adjusting?
- because they are
created by trade itself
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WIR-Credit is Self-Adjusting



If I agree to let you baby-sit for me, then my
account is debited, and your account is credited,
by the same amount.
There is no “monetary base” or “high powered
money” (reserves within the central bank), or
“bank money multiplier.”
Bank balances are self-adjusting, growing or
contracting in direct proportion to trade.
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(2) This Self-Adjusting
Credit is Counter-Cyclical
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Long-term Correlation with Unemployment
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Do changes in GDP lead to changes in WIR?
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Maybe.
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Overall, Counter-Cyclical link is strong:
GDP (-) => WIR-Turnover (+)
Table 2
Indep. Var=>
D(LrGdpMa2(-1))
R2
D(LrWIRTurnover)
1953-2012
D(LrWIRTurnover)
1953-1972
D(LrWIRTurnover)
1973-2012
-1.0191
-1.4789
-1.0141
[-3.613]*** [-2.746]** [-2.606]**
0.951
0.977
0.936
t-stats in [ ]: ***: p < 0.01
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(2) Why is this Countercyclical Credit
Important to Small and Medium
Enterprises (SMEs)?
- because they are so credit
constrained in downturns.
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Employees and Owners
in Small to Medium Firms
can be shown to have:
• Higher Risk of Layoffs & Bankruptcy
• Less Access to Bank Credit
WINTER-EBMER & ZWEIMÜLLER “Firm Size Wage Differentials
in Switzerland,” American Economic Review (1999)
TERRA, Maria Christina “Credit constraints in Brazilian firms,”
Revista Brasilera de Economia (2003)
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Is ↑ WIR Turnover in a Recession
from Money, Velocity, or Both?
Recall the “Quantity of Money" Equation:
‘ Turnover ’ = M * V = P * Q = GDP
=>
%∆M + %∆V = %∆P + %∆Q = %∆GDP
where M = Money (Balances)
V = Velocity
P = Price Level
Q = Goods & Services Purchased
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%∆ Turnover [= %∆ Money + %∆ Velocity]
=> M2 Velocity is very Pro-Cyclical
%∆M
%∆M + %∆V
%∆V
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See Updated Graph HERE
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(2b) Why do Larger Firms
use WIR Counter-cyclically?
1) Because it helps them hold onto SME
customers and suppliers in tough times.
2) This is similar to countercyclical pattern
of large firms providing trade credits to
smaller customers and distributors.
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SMEs are more subject to Credit Risk
Consider B2B Trade Credits, on terms like
“2% 10, net 30.”
Trade Credits are:
• A major form of credit for SMEs in OECD
• 20% of Large-Firm Accounts Receivable
• Used in a highly countercyclical way
Nilsen, J., “Trade credit and the bank lending channel,”
Journal of Money Credit and Banking (2002)
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Both Registred and Non-Registered Firms are
Counter-Cyclical in Turnover:
GDP (-) => WIR-Turnover Construction (+)
Table 11
D(LrVAma2(-1))
R2
Registered
1995-2008
Non-Registered
1995-2008
D(LrWirTurnCons)
D(LrWirTurnCons)
-1.0524
-0.7599
[-3.139]***
0.776
[-1.852]○
0.718
t-stats in [ ]:***: p < 0.01;
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o:
p < 0.15
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Registered firms Countercyclical in Velocity,
Non-Registered firms are so in Balances.
Value Added (-) => WIR-Turnover (+)
Table 7, 9
DOLS estim.
D(LrVAma2(-1))
R2
Registered
1995-2008
Non-Registered
1995-2008
D(LrWirVELOC)
D(LrWirBALAN)
-1.8710
[-3.627]***
0.214
-0.7791
[-0.781]
0.660
t-stats in [ ]: ***: p < 0.01, ** : p < 0.05,*
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Lemma on Balances + Velocities
Lemma 3: If, in a Secondary Currency



(i) Turnover is countercyclical for both large firms
and SMEs;
(ii) Large firms use this currency only with SME
customers; and
(iii) Large firms allow good SME customers to
settle a greater portion of their bills in secondary
currency during recessions, it follows that:
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Lemma 3, cont.


Secondary Balances are countercyclical for Large
firms; Velocities are countercyclical for SMEs.
These terms “drive” or dominate Turnover: the
Output elasticity of Balances is more negative for
Large firms than the elasticity of Velocities. The
opposite is true for SMEs:
𝑳
 𝑩𝑸
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<0<
𝑉𝑄𝐿 ,
𝑺
𝑽𝑸
< 0 < 𝐵𝑄𝑆 .
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Table 10: Balance or Velocity Dominance
in “Standard Counter-Cyclical Pattern”
Registered
Non-Registered
Null Hypothesis: 𝑉𝑄𝑅 − 𝑇𝑄𝑅 = 0,
𝑹
Alternative Hypothesis: 𝑽𝑹
𝑸 − 𝑻𝑸 < 𝟎
Null Hypothesis: 𝐵𝑄𝑁𝑅 − 𝑇𝑄𝑁𝑅 = 0,
𝑵𝑹
Alternative Hypothesis: 𝑩𝑵𝑹
𝑸 − 𝑻𝑸 < 𝟎
DOLS Estim. FMOLS Estim. DOLS Estim. FMOLS Estim.
𝑇𝑄𝑅 = -0.5249,
𝑇𝑄𝑅 = -0.7861, 𝑇𝑄𝑁𝑅 = -0.5192, 𝑇𝑄𝑁𝑅 = -0.6702,
𝑽𝑹
𝑸 = -1.8710.
𝑵𝑹
𝑵𝑹
𝑽𝑹
=
-0.8557.
𝑩
𝑩
=
-0.7791.
𝑸
𝑸 = -1.1036.
𝑸
P-values:
1.13E-04,
6.31E-03
P-values:
0.4366,
0.3509
P-values:
0.0399,
0.3979
P-values:
3.64E-03,
0.3279
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SUM,
All Effects
CONST
Yates
Pearson
0.0856
0.0441
Count_B=
Count_V=
Reg
6
15
0.6650
Count_B=
Count_V=
HOSP
NA
Count_B=
Count_V=
MANUF
0.2059
Count_B=
Count_V=
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0.0833
Reg
0
2
NA
Reg
1
0
0.0350
Reg
2
1
Non-Reg
11
7
Table 12: Countercyclical Dominance of
WIR Balances (B) or Velocity (V)
Registered and Non-Registered Firms,
Several Functional Specifications
RETAIL
Non-Reg
1
0
Count_B=
Count_V=
SERV
Non-Reg
0
0
0.2357
Count_B=
Count_V=
WHOL
Non-Reg
0
5
NA
0.0528
Count_B=
Count_V=
NA
Reg
0
2
Non-Reg
0
1
0.0578
Reg
2
4
Non-Reg
3
0
0.0098
Reg
0
5
Non-Reg
4
1
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(3) Why are Self-Adjusting,
Countercyclical Credits
likely to be
Non-Inflationary?
- Because they are
More Countercyclical
than Ordinary Money.
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US Macro-Stability: Better since WWII,
(But Room for Improvement!)
Average U.S. Business Cycle, 1854 to 2006
Contraction
1854-1919
(16 cycles)
45%
1919-1945
(6 cycles)
55%
34%
1945-2006
(10 cycles)
66%
15%
0
Expansion
85%
10
20
30
40
50
60
70
Months
Source:
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http://www.nber.org/cycles.html
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%∆ Turnover [= %∆ Money + %∆ Velocity]
=> M2 Velocity is very Pro-Cyclical
%∆M
%∆M + %∆V
%∆V
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(4) The Question of Inflation



To fight inflation, Central Banks are forced to
tighten money supply, even if it leads to a
recession.
But a more ‘Micro’ Monetary Policy can reach
sectors untouched by standard monetary
expansion – without putting upward pressure
on prices.
Making up for lost purchasing power is not
inflationary; it is anti-deflationary.
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As the internet allows Marketers to go from
Broadcasting to ‘Point-Casting’
Similarly, WIR allows Monetary Authority to
move from Macro- to Micro-Credit.

Expended WIR credits don’t go to those who have
the most credit, but those who have the least.

This seems “fairer” (can gain political support).

Rather than inflationary, it is anti-deflationary.
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Data suggest WIR is more countercyclically leveraged than M2




Most used in highly cyclical sectors (Construction:
37%, Retail: 23%)
Large Non-Registered firms: high SFr/WIR ratio.
Similar to pattern of Trade-Credits –underappreciated credit channel.
SMEs relying on WIR are most credit- constrained
in recessions.
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For Paper, email me:
stoddj@rpi.edu
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