The Macro-Stability of Swiss WIR-
Bank Spending:
Balance versus Velocity Effects
International Conference on Community and
Complementary Currencies, Univ. Lyon, Feb. 17, 2011
James Stodder, (Ph.D., Economics, Yale 1990)
Lally School of Management & Technology
Rensselaer Polytechnic Institute at Hartford
Hartford, Connecticut, USA
13-Apr-20 1

13-Apr-20 2

I will try to show:
1.
2.
A WIR-type system – based on electronic credits – can be self-adjusting.
These self-adjusting credits are countercyclical for SMEs & Micro-Finance Clients.
3.
4.
Larger Companies use WIR less but more counter-cyclically. Their use of WIR is more highly leveraged.
Counter-cyclical credits can be good antipoverty policy.
5.
Self-adjusting, counter-cyclical credits can also be non-inflationary.
13-Apr-20 3

Swiss WIR-Bank, 75 Years Old

Founded during Great Depression, in 1934, around ideas of German-Argentine businessman:
Silvio Gesell (1862-1930).

Wirtschaftsring = “Cercle Économique”

WIR = “WE” in German

Since 1955, Small-to-Medium Businesses only.
13-Apr-20 4

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 cannot be traded for SFr (although this still happens)
13-Apr-20 5

Distribution of WIR Client-Firms
13-Apr-20
Industry
Number
Swiss
Number Portion
WIR WIR/Swiss
RETAIL, of which 62,380 14,275
Registered 5,933
Non-Registered 8,342
22.9%
9.5%
13.4%
SERVICES, of which 164,709 10,380
Registered
Non-Registered
3,817
6,563
6.3%
2.3%
4.0%
HOSPITALITY, of which 28,006
Registered
Non-Registered
3,438
2,099
1,339
CONSTRUCTION, of which 57,268 21,162
Registered
Non-Registered
6,992
14,170
MANUFACTURING, of which 38,421
Registered
Non-Registered
7,310
1,820
5,490
WHOLESALE, of which 21,762
Registered
Non-Registered
4,138
1,027
3,111
TOTALS, of which 372,546 60,703
Registered
Non-Registered
21,688
39,015
12.3%
7.5%
4.8%
37.0%
12.2%
24.7%
19.0%
4.7%
14.3%
19.0%
4.7%
14.3%
16.3%
5.8%
10.5%
(1,000 SFr) (1,000 SFr) (Swiss Fr.) Turn/Balance =
Turnover Balance Av. Bal. Velocity
345,757 127,100 8,904 2.72
223,822 64,958 10,949 3.446
121,935 62,142 7,449 1.962
213,515 88,788
112,186 30,745
101,329 58,044
8,554 2.405
8,055 3.649
8,844 1.746
73,021 22,416
61,872 16,156
11,148 6,261
6,520 3.257
7,697 3.83
4,676 1.781
527,619 210,477 9,946 2.507
280,169 82,462 11,794 3.398
247,450 128,015 9,034 1.933
230,196 101,884 13,938 2.259
87,418 26,092 14,336 3.350
142,778 75,792 13,805 1.884
223,631 73,787 17,832 3.031
80,371 15,462 15,056 5.198
143,260 58,325 18,748 2.456
1,613,739 624,452 10,287 2.584
845,838 235,874 10,876 3.586
767,901 388,578 9,960 1.976
6

13-Apr-20
7

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.
13-Apr-20 8

13-Apr-20 9

Long-term Correlation with Unemployment
13-Apr-20 10

Do changes in GDP lead to changes in WIR?
13-Apr-20
Maybe.
11

Do changes in UE lead to changes in WIR?
13-Apr-20
Not Obvious to the “Naked Eye”!
12

Modern Macroeconomic
Time Series Econometrics

“Error Correction Models” bring together long-term stability and short-term deviations

We can see if short-term deviations in one series lead to later deviations in a second series. Thereby, we can even show direction of causality.
13-Apr-20 13

13-Apr-20
Overall, Counter-Cyclical link is strong:
GDP (-) => WIR-Turnover (+)
1952-2008 1953-2008
D(LrGDP(-1)) -0.9444
[-2.760] ***
D(LrGDP_MA2(-1)) -1.7499
[-3.176] ***
Adjusted R 2 0.836
t-stats in [ ]: *** : p < 0.01, ** : p < 0.05
0.794
14

(2a) Why is Counter-Cyclical Credit so Important to
Small and Medium Enterprises (SMEs) and to Micro-Finance Clients?
- because they are so credit constrained in downturns.
13-Apr-20 15

13-Apr-20
Employees and Owners in Small to Medium Firms can be shown to have:
• Higher Risk of Layoffs & Bankruptcy
• Less Access to Bank Credit
WINTEREBMER & ZWEIMÜLLER “Firm Size Wage
Differentials in Switzerland,” American Economic Review (1999)
TERRA, Maria Christina “Credit constraints in Brazilian firms,”
Revista Brasilera de Economia (2003)
16

Growth Latin Amer. Microfinance Down
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
-10.00%
CRECIMIENTO IMFs ELF (%)
Promedio C.A.
Prom. IMFs ELF
Dic-07
42.97%
41.80%
Jun-08
48.85%
40.30%
Dic-08
26.34%
25.70%
Jun-09
-6.98%
13.80%
13-Apr-20 17
Sergio Navajas – IDB (Nov. 2009)

Profits Latin Amer. Microfinance Down
ROE IMFs ELF (%)
25.00%
20.00%
15.00%
10.00%
5.00%
0.00%
-5.00%
Prom. C.A.
Prom. IMFs ELF
Jun-07
19.23%
22.40%
Dic-07
17.59%
19.30%
Jun-08
16.50%
20.70%
Dic-08
14.12%
15.20%
Jun-09
-2.39%
8.40%
13-Apr-20 18
Sergio Navajas – IDB (Nov. 2009)

Defaults Latin Amer. Microfinance Up
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
PAR > 30 IMFs ELF (%)
13-Apr-20
0.00%
Jun-07
Prom. C.A.
4.50%
Prom. IMFs ELF 3.30%
Dic-07 Jun-08
3.47%
2.80%
4.29%
4.30%
Dic-08 Jun-09
4.99%
3.70%
9.63%
5.00%
Sergio Navajas – IDB (Nov. 2009)
19

(3) Why do Larger Firms use
WIR more Counter-Cyclically?
Because it helps them to hold onto
SME customers and suppliers in tough times.
13-Apr-20 20

Is ↑ Turnover in a Recession from ↑ Money , ↑ Velocity , or Both?
The “Quantity of Money" Equation:
‘ Turnover ’ = M * V = P * Q where M = Money (Balances)
V = Velocity
P = Price Level
Q = Goods & Services Purchased
13-Apr-20 21

Non-Registered Firms may be
More Counter-Cyclical In their WIR activity:
GDP (-) => WIR-Turnover (+)
Registered
1995-2008
-0.5937
Non-Reg.
1995-2008
-1.4037
D(LRGDP(-2))
(-1.498) o (-6.193) ***
Adjusted R 2 0.142
0.408
t-stats in [ ]: *** : p < 0.01, ** : p < 0.05,
* : p < 0.10; o : p < 0.15
13-Apr-20 22

Non-Registered Firms may be
More Counter-Cyclical In their WIR activity:
GDP (-) => WIR-Balances (+)
Registered
1995-2007
1.8827
Non-Reg.
1995-2007
-1.2617
D(LRGDP(-2))
(1.535) o (-1.606) o
Adjusted R 2 0.157
0.429
t-stats in [ ]: *** : p < 0.01, ** : p < 0.05,
* : p < 0.10; o : p < 0.15
13-Apr-20 23

Non-Registered Firms may be
More Counter-Cyclical In their WIR activity:
GDP (-) => WIR-Turnover Construction (+)
Registered
1995-2008
-2.2225
Non-Reg.
1995-2008
-2.3287
D(LRGD_2PAV(-2))
(-2.189) * (-3.382) **
Adjusted R 2 0.678
0.864
t-stats in [ ]: *** : p < 0.01, ** : p < 0.05,
* : p < 0.10; o : p < 0.15
13-Apr-20 24

Non-Registered Firms may be
More Counter-Cyclical in their WIR activity:
GDP (-) => WIR-Balances Construction (+)
Registered
1995-2007
-4.5543
Non-Reg.
1995-2007
-8.7371
D(LRGDP_2AV(-1))
(-1.428) (-2.166) *
Adjusted R 2 0.658
0.853
t-stats in [ ]: *** : p < 0.01, ** : p < 0.05,
* : p < 0.10; o : p < 0.15
13-Apr-20 25

Three Regression Patterns
13-Apr-20
Indust Regress
Construct Bal_GDP
Turn_GDP
Hospitality Bal_GDP
Turn_GDP
Manufact Bal_GDP
Turn_GDP
Retail Bal_GDP
Turn_GDP
Services Bal_GDP
Turn_GDP
Wholesale Bal_GDP
Turn_GDP
Registered Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Non-Reg. Clients
Av. Coeff.
Registered Clients Non-Reg. Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Regress Counter Pro
Av. Coeff.
Counter Pro Counter Pro Counter Pro
4
-6.3029
0 5
0.0000 -12.1508
1 Bal_UE
9.6924
2 0 6 0 Turn_UE
-2.9235 0.0000 -2.2687 0.0000
4
0.3892
0
0.0000
0
0.0000
0
0.0000
2
1.0193
3
0.3526
0
0.0000
0
0.0000
0
0.0000
0
0.0000
0 4 Bal_UE
0.0000 11.6929
0 0 0 3 Turn_UE
0.0000 0.0000 0.0000 3.7542
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
0 0 0 0 Turn_UE
0.0000 0.0000 0.0000 0.0000
1
0.0000
0
0.0000
0
0.1361
0
0.0000
0
0.0000
0
0.0000
0
0.0000
3
3.7542
0
0.1045
2
-0.7665
0
0.0000
4
0.0000 0.0000 0.0000 -1.0435
2 0 1 1
-0.4438
0
0.0000
0
0.0000
1
-6.7843
1 Bal_UE
4.4931
0 1 3 1 Turn_UE
0.0000 4.6710 -3.7539 3.6228
1
-4.2293
1
2.5030
0
0.0000
7
3.6148
1 6 0 3
0.0000 1.5850 0.0000 4.6598
Bal_UE
Turn_UE
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
2 2 1 3 Turn_UE
-3.1803 1.5431 -3.5616 2.3725
2
2
0
0
3
4
0
0.6636 0.0000 0.5120 0.0000
2
0.1685
2 0 3 0
0.6636 0.0000 0.5120 0.0000
0.2845
0
2
0.1997
2
-0.2142
0.0000
1
0
0.0000
0.5373
4
-0.2145
0
0.0000
0.0000 -0.1072 0.1435 -0.1380
0
0.0000
3
2
0.1647
1
4
-0.1638
26

1. Unemployment Counter-Cyclical Effects Stronger
13-Apr-20
Indust Regress
Construct Bal_GDP
Turn_GDP
Hospitality Bal_GDP
Turn_GDP
Manufact Bal_GDP
Turn_GDP
Retail Bal_GDP
Turn_GDP
Services Bal_GDP
Turn_GDP
Wholesale Bal_GDP
Turn_GDP
Registered Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Non-Reg. Clients
Av. Coeff.
Registered Clients Non-Reg. Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Regress Counter Pro
Av. Coeff.
Counter Pro Counter Pro Counter Pro
4
-6.3029
0 5
0.0000 -12.1508
1 Bal_UE
9.6924
2 0 6 0 Turn_UE
-2.9235 0.0000 -2.2687 0.0000
4
0.3892
0
0.0000
0
0.0000
0
0.0000
2
1.0193
3
0.3526
0
0.0000
0
0.0000
0
0.0000
0
0.0000
0 4 Bal_UE
0.0000 11.6929
0 0 0 3 Turn_UE
0.0000 0.0000 0.0000 3.7542
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
0 0 0 0 Turn_UE
0.0000 0.0000 0.0000 0.0000
1
0.0000
0
0.0000
0
0.1361
0
0.0000
0
0.0000
0
0.0000
0
0.0000
3
3.7542
0
0.1045
2
-0.7665
0
0.0000
4
0.0000 0.0000 0.0000 -1.0435
2 0 1 1
-0.4438
0
0.0000
0
0.0000
1
-6.7843
1 Bal_UE
4.4931
0 1 3 1 Turn_UE
0.0000 4.6710 -3.7539 3.6228
1
-4.2293
1
2.5030
0
0.0000
7
3.6148
1 6 0 3
0.0000 1.5850 0.0000 4.6598
Bal_UE
Turn_UE
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
2 2 1 3 Turn_UE
-3.1803 1.5431 -3.5616 2.3725
2
2
0
0
3
4
0
0.6636 0.0000 0.5120 0.0000
2
0.1685
2 0 3 0
0.6636 0.0000 0.5120 0.0000
0.2845
0
2
0.1997
2
-0.2142
0.0000
1
0
0.0000
0.5373
4
-0.2145
0
0.0000
0.0000 -0.1072 0.1435 -0.1380
0
0.0000
3
2
0.1647
1
4
-0.1638
27

2. Non-Registered Counter-Cyclical Effects Stronger
13-Apr-20
Indust Regress
Construct Bal_GDP
Turn_GDP
Hospitality Bal_GDP
Turn_GDP
Manufact Bal_GDP
Turn_GDP
Retail Bal_GDP
Turn_GDP
Services Bal_GDP
Turn_GDP
Wholesale Bal_GDP
Turn_GDP
Registered Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Non-Reg. Clients
Av. Coeff.
Registered Clients Non-Reg. Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Regress Counter Pro
Av. Coeff.
Counter Pro Counter Pro Counter Pro
4
-6.3029
0 5
0.0000 -12.1508
1 Bal_UE
9.6924
2 0 6 0 Turn_UE
-2.9235 0.0000 -2.2687 0.0000
4
0.3892
0
0.0000
0
0.0000
0
0.0000
2
1.0193
3
0.3526
0
0.0000
0
0.0000
0
0.0000
0
0.0000
0 4 Bal_UE
0.0000 11.6929
0 0 0 3 Turn_UE
0.0000 0.0000 0.0000 3.7542
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
0 0 0 0 Turn_UE
0.0000 0.0000 0.0000 0.0000
1
0.0000
0
0.0000
0
0.1361
0
0.0000
0
0.0000
0
0.0000
0
0.0000
3
3.7542
0
0.1045
2
-0.7665
0
0.0000
4
0.0000 0.0000 0.0000 -1.0435
2 0 1 1
-0.4438
0
0.0000
0
0.0000
1
-6.7843
1 Bal_UE
4.4931
0 1 3 1 Turn_UE
0.0000 4.6710 -3.7539 3.6228
1
-4.2293
1
2.5030
0
0.0000
7
3.6148
1 6 0 3
0.0000 1.5850 0.0000 4.6598
Bal_UE
Turn_UE
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
2 2 1 3 Turn_UE
-3.1803 1.5431 -3.5616 2.3725
2
2
0
0
3
4
0
0.6636 0.0000 0.5120 0.0000
2
0.1685
2 0 3 0
0.6636 0.0000 0.5120 0.0000
0.2845
0
2
0.1997
2
-0.2142
0.0000
1
0
0.0000
0.5373
4
-0.2145
0
0.0000
0.0000 -0.1072 0.1435 -0.1380
0
0.0000
3
2
0.1647
1
4
-0.1638
28

3. Non-Reg. show More Counter-Cyclical Balance
13-Apr-20
Indust Regress
Construct Bal_GDP
Turn_GDP
Hospitality Bal_GDP
Turn_GDP
Manufact Bal_GDP
Turn_GDP
Retail Bal_GDP
Turn_GDP
Services Bal_GDP
Turn_GDP
Wholesale Bal_GDP
Turn_GDP
Registered Clients
Av. Coeff.
Non-Reg. Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Registered Clients Non-Reg. Clients
Sign. Occurs. Sign. Occurs.
Av. Coeff.
Regress Counter Pro
Av. Coeff.
Counter Pro Counter Pro Counter Pro
4
-6.3029
0
0.0000
5
-12.1508
1 Bal_UE
9.6924
2 0 6 0 Turn_UE
-2.9235 0.0000 -2.2687 0.0000
4
0.3892
0
0.0000
0
0.0000
0
0.0000
2
1.0193
3
0.3526
0
0.0000
0
0.0000
0 0 0 4 Bal_UE
0.0000 0.0000 0.0000 11.6929
0 0 0 3
0.0000 0.0000 0.0000 3.7542
Turn_UE
1
0.0000
0
0.0000
0
0.0000
0
0.0000
0
0.0000
3
3.7542
2
-0.7665
0
0.0000
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
0 0 0 0 Turn_UE
0.0000 0.0000 0.0000 0.0000
0 0 1 1 Bal_UE
0.0000 0.0000 -6.7843 4.4931
0 1 3 1
0.0000 4.6710 -3.7539 3.6228
Turn_UE
1
-4.2293
1
2.5030
0
0.0000
7
3.6148
1 6 0 3
0.0000 1.5850 0.0000 4.6598
Bal_UE
Turn_UE
0
0.0000
0
0.0000
0
0.0000
0 Bal_UE
0.0000
2 2 1 3 Turn_UE
-3.1803 1.5431 -3.5616 2.3725
0
0.0000
2
0.1361
2
0.6636
2
0.1685
0
0.0000
2
0.2845
0
0.0000
2
0.1997
0
0.0000
0
0.0000
0
0.0000
2
-0.2142
0
0.0000
0
0.0000
1
-0.1072
0
0.0000
0
0.0000
1
0.1045
3
0.5120
0
0.0000
0
0.0000
4
0.5373
3
0.1435
2
0.1647
4
-1.0435
1
-0.4438
0
0.0000
4
-0.2145
1
-0.1150
0
0.0000
1
-0.1380
4
-0.1638
29

SMEs are more subject to Credit Risk
Consider Business to Business (B2B)
Trade Credits, on terms like “2% 10, net 30.”
Such Trade Credits, like B2B CCs, are:
• A primary form of credit for SMEs in US
• Used in a highly counter-cyclical way
Nilsen, J., “Trade credit and the bank lending channel,”
Journal of Money Credit and Banking (2002)
13-Apr-20 30

(4) Why are more counter-cyclical credit systems more useful to the poor
– and vice versa ?
-Because the poor spend more, and more of their spending stays within the community.
13-Apr-20 31

Basic Keynesian Multiplier
Y = C + I + G + X – M
= a + bY + I + G + X – mY
=> ∆Y/∆G = 1/(1b + m )
Where b = ‘Marginal Propensity to Consume’ and m = ‘Marginal Propensity to Import’
Monday, April 13, 2020 32

The Keynesian ‘Multiplier’ is larger for expenditures by poor, who:
* spend greater % of their own income (=> larger b) , and
* may spend greater % within own community (=> smaller m) .
13-Apr-20 33

Basic Keynesian Multiplier
∆Y/∆G = 1/(1-
+
)
b = ‘Marginal Propensity to Consume’ and m = ‘Marginal Propensity to Import’
Effect is to increase Multiplier
Monday, April 13, 2020 34

13-Apr-20
(5) Why are Self-Adjusting,
Counter-Cyclical Credits are
Non-Inflationary ?
Because they are more counter-cyclical than Ordinary Money.
35

US Macro-Stability: Better since WWII,
( But Room for Improvement!)
Average U.S. Business Cycle, 1854 to 2006
Contraction Expansion
1854-1919
(16 cycles)
45% 55%
1919-1945
(6 cycles)
34% 66%
13-Apr-20
1945-2006
(10 cycles)
15% 85%
0 10 20 30
Months
40 50 60 70
Source: http://www.nber.org/cycles.html
36

%∆ Money Turnover [ = %∆ (Money x Velocity) ] is Too Pro-Cyclical
% ∆M
% ∆ (M x V)
% ∆ V
13-Apr-20 37


(5) 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 unreached by traditional monetary expansion – without putting upward pressure on prices.

Making up for lost purchasing power is not inflationary , but anti-deflationary.
13-Apr-20 38

As the internet allows Marketers to go from
Broadcasting to ‘Point-Casting’
So WIR system allows Monetary Authority to go from Macro- to Micro-Credit.

Expended WIR credits don’t go mostly to those who already have much, but those who have none.

This is of course fairer (can gain political support).

In addition, it should be anti-deflationary.
13-Apr-20 39

For previous paper, go to:
For Slides, email me:
13-Apr-20 40