Apr 20, 2023Apr 20, 2023 11

The Macro-Stability of Swiss WIR-The Macro-Stability of Swiss WIR-Bank Spending: Bank Spending:

Balance versus Velocity EffectsBalance versus Velocity Effects

International Conference on Community and International Conference on Community and Complementary Currencies, Univ. Lyon, Feb. 17, 2011Complementary Currencies, Univ. Lyon, Feb. 17, 2011

James Stodder, (Ph.D., Economics, Yale 1990)Lally School of Management & Technology

Rensselaer Polytechnic Institute at HartfordHartford, Connecticut, USA

Apr 20, 2023Apr 20, 2023 22

I will try to show:I will try to show:1.1. A WIR-type system – based on electronic A WIR-type system – based on electronic

credits – can be credits – can be self-adjustingself-adjusting..

2.2. These self-adjusting credits are These self-adjusting credits are counter-counter-cyclicalcyclical for for SMEsSMEs & & Micro-Finance ClientsMicro-Finance Clients..

3.3. Larger Companies use WIR Larger Companies use WIR lessless but but more more counter-cyclicallycounter-cyclically. Their use of WIR is . Their use of WIR is more more highly leveragedhighly leveraged. .

4.4. Counter-cyclical credits can be Counter-cyclical credits can be good anti-good anti-povertypoverty policy. policy.

5.5. Self-adjusting, counter-cyclical credits can Self-adjusting, counter-cyclical credits can also be also be non-inflationarynon-inflationary..

Apr 20, 2023Apr 20, 2023 33

Apr 20, 2023Apr 20, 2023 44

Swiss WIR-Bank, 75 Years OldSwiss WIR-Bank, 75 Years Old Founded during Great Depression, in Founded during Great Depression, in 19341934, ,

around ideas of German-Argentine businessman: around ideas of German-Argentine businessman:

Silvio GesellSilvio Gesell (1862-1930).

WirtschaftsringWirtschaftsring = “Cercle Économique” = “Cercle Économique”

WIRWIR = “WE” = “WE” in Germanin German

Since 1955, Since 1955, Small-to-MediumSmall-to-Medium Businesses Businesses only. only.

Apr 20, 2023Apr 20, 2023 55

In 2008, WIR-Bank had In 2008, WIR-Bank had 70,200 Participants70,200 Participants

Turnover Turnover 1.6 Billion SFr 1.6 Billion SFr ($1.5 b. US)($1.5 b. US)

WIR clients maintain two accounts, one in WIR clients maintain two accounts, one in Swiss Francs Swiss Francs (SFr), the other in (SFr), the other in WIRWIR..

WIR accounts can be used to clear (in WIR) WIR accounts can be used to clear (in WIR) trades only trades only with other WIR clientswith other WIR clients..

Since 1973, Since 1973, WIR credits cannot be tradedWIR credits cannot be traded for SFr (although this still happens)for SFr (although this still happens)

DistributionDistribution of WIR Client-Firms of WIR Client-Firms

Apr 20, 2023Apr 20, 2023 66

Number Number Portion (1,000 SFr) (1,000 SFr) (Swiss Fr.) Turn/Balance =

Industry Swiss WIR WIR/Swiss Turnover Balance Av. Bal. Velocity

RETAIL, of which 62,380 14,275 22.9% 345,757 127,100 8,904 2.72

Registered 5,933 9.5% 223,822 64,958 10,949 3.446

Non-Registered 8,342 13.4% 121,935 62,142 7,449 1.962

SERVICES, of which 164,709 10,380 6.3% 213,515 88,788 8,554 2.405

Registered 3,817 2.3% 112,186 30,745 8,055 3.649

Non-Registered 6,563 4.0% 101,329 58,044 8,844 1.746

HOSPITALITY, of which 28,006 3,438 12.3% 73,021 22,416 6,520 3.257

Registered 2,099 7.5% 61,872 16,156 7,697 3.83

Non-Registered 1,339 4.8% 11,148 6,261 4,676 1.781

CONSTRUCTION, of which 57,268 21,162 37.0% 527,619 210,477 9,946 2.507

Registered 6,992 12.2% 280,169 82,462 11,794 3.398

Non-Registered 14,170 24.7% 247,450 128,015 9,034 1.933

MANUFACTURING, of which 38,421 7,310 19.0% 230,196 101,884 13,938 2.259

Registered 1,820 4.7% 87,418 26,092 14,336 3.350

Non-Registered 5,490 14.3% 142,778 75,792 13,805 1.884

WHOLESALE, of which 21,762 4,138 19.0% 223,631 73,787 17,832 3.031

Registered 1,027 4.7% 80,371 15,462 15,056 5.198

Non-Registered 3,111 14.3% 143,260 58,325 18,748 2.456

TOTALS, of which 372,546 60,703 16.3% 1,613,739 624,452 10,287 2.584

Registered 21,688 5.8% 845,838 235,874 10,876 3.586

Non-Registered 39,015 10.5% 767,901 388,578 9,960 1.976

(1) Why are Centralized (1) Why are Centralized Electronic Credits Electronic Credits

Self-AdjustingSelf-Adjusting??

Apr 20, 2023Apr 20, 2023 77

- because they are - because they are created by trade itselfcreated by trade itself

WIR-Credit is WIR-Credit is Self-AdjustingSelf-Adjusting

If I agree to let you baby-sit for me, then my If I agree to let you baby-sit for me, then my account is debited, and your account is credited, account is debited, and your account is credited, by the same amount.by the same amount.

There is There is no “monetary base” no “monetary base” or “high powered or “high powered

money” (reserves within the central bank), or money” (reserves within the central bank), or “bank money multiplier.”“bank money multiplier.”

Bank balances are Bank balances are self-adjustingself-adjusting, growing or , growing or contracting in direct proportion to trade.contracting in direct proportion to trade.

Apr 20, 2023Apr 20, 2023 88

(2) This Self-Adjusting (2) This Self-Adjusting Credit is Credit is Counter-CyclicalCounter-Cyclical

Apr 20, 2023Apr 20, 2023 99

Apr 20, 2023Apr 20, 2023 1010

Long-term Correlation with Unemployment Long-term Correlation with Unemployment

Do changes in GDP lead to changes in WIR?Do changes in GDP lead to changes in WIR?

Apr 20, 2023Apr 20, 2023 1111Maybe.Maybe.

Do changes in UE lead to changes in WIR?Do changes in UE lead to changes in WIR?

Apr 20, 2023Apr 20, 2023 1212Not Obvious to the “Naked Eye”!Not Obvious to the “Naked Eye”!

Modern Macroeconomic Modern Macroeconomic Time Series EconometricsTime Series Econometrics

““Error Correction Models” bring Error Correction Models” bring together together long-term stability long-term stability and and short-short-term deviations term deviations

We can see if short-term deviations in We can see if short-term deviations in one series lead to later deviations in a one series lead to later deviations in a second series. Thereby, we can even second series. Thereby, we can even show show direction of causalitydirection of causality..

Apr 20, 2023Apr 20, 2023 1313

Apr 20, 2023Apr 20, 2023 1414

Overall, Counter-CyclicalOverall, Counter-Cyclical link is link is strongstrong: : GDPGDP (-)(-) => => WIR-Turnover WIR-Turnover (+)(+)

1952-2008 1953-2008D(LrGDP(-1)) -0.9444

  [-2.760]******

D(LrGDP_MA2(-1)) -1.7499

[-3.176]******

Adjusted R2 0.836 0.794t-stats in [ ]t-stats in [ ]: ***: ***: p < 0.01, : p < 0.01, **** : p < 0.05 : p < 0.05

(2a) Why is Counter-Cyclical Credit (2a) Why is Counter-Cyclical Credit so Important to so Important to

Small and Medium Enterprises (SMEs) Small and Medium Enterprises (SMEs) andand to Micro-Finance Clients? to Micro-Finance Clients?

Apr 20, 2023Apr 20, 2023 1515

- because they are so credit - because they are so credit constrained in downturns.constrained in downturns.

Apr 20, 2023Apr 20, 2023 1616

Employees and OwnersEmployees and Owners in in Small to Medium FirmsSmall to Medium Firms

can be shown to have: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)

GrowthGrowth Latin Amer. Microfinance Latin Amer. Microfinance DownDown

Apr 20, 2023Apr 20, 2023 1717

CRECIMIENTO IMFs ELF (%)

-10.00%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

P rom edio C.A . 42.97% 48.85% 26.34% -6.98%

P rom . IM Fs E LF 41.80% 40.30% 25.70% 13.80%

Dic -07 Jun-08 Dic -08 Jun-09

Sergio Navajas – IDB (Nov. 2009)

ProfitsProfits Latin Amer. Microfinance Latin Amer. Microfinance DownDown

Apr 20, 2023Apr 20, 2023 1818

ROE IMFs ELF (%)

-5 .00%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

P rom . C.A . 19.23% 17.59% 16.50% 14.12% -2.39%

P rom . IM Fs E LF 22.40% 19.30% 20.70% 15.20% 8.40%

Jun-07 Dic -07 Jun-08 Dic -08 Jun-09

Sergio Navajas – IDB (Nov. 2009)

DefaultsDefaults Latin Latin Amer. Microfinance Amer. Microfinance UpUp

Apr 20, 2023Apr 20, 2023 1919

PAR > 30 IMFs ELF (%)

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

Prom . C .A. 4.50% 3.47% 4.29% 4.99% 9.63%

Prom . IMFs ELF 3.30% 2.80% 4.30% 3.70% 5.00%

Jun-07 D ic -07 Jun-08 D ic -08 Jun-09

Sergio Navajas – IDB (Nov. 2009)

(3) Why do Larger Firms use (3) Why do Larger Firms use WIR more Counter-Cyclically?WIR more Counter-Cyclically?

Because it helps them to hold onto Because it helps them to hold onto SME customers and suppliers in SME customers and suppliers in

tough times.tough times.

Apr 20, 2023Apr 20, 2023 2020

Is Is ↑↑ TurnoverTurnover in a Recession in a Recession from from ↑↑ MoneyMoney,, ↑ ↑ VelocityVelocity, or Both?, or Both?

Apr 20, 2023Apr 20, 2023 2121

The “Quantity of Money" Equation:

‘ Turnover ’ = M * V = P * Q

where M = Money (Balances) V = Velocity P = Price Level Q = Goods & Services Purchased

Apr 20, 2023Apr 20, 2023 2222

Non-Registered Firms Non-Registered Firms may be may be More Counter-Cyclical More Counter-Cyclical In their WIR activity: In their WIR activity:

GDPGDP (-) (-) =>=> WIR-Turnover (+)WIR-Turnover (+)

Registered 1995-2008

Non-Reg. 1995-2008

D(LRGDP(-2)) -0.5937 -1.4037

(-1.498)o (-6.193)***Adjusted R2 0.142 0.408

t-stats in [ ]t-stats in [ ]: ***: ***: p < 0.01, : p < 0.01, **** : p < 0.05, : p < 0.05, **: p < 0.10; : p < 0.10; oo: p < 0.15: p < 0.15

Apr 20, 2023Apr 20, 2023 2323

Non-Registered Firms Non-Registered Firms may be may be More Counter-Cyclical More Counter-Cyclical In their WIR activity: In their WIR activity:

GDPGDP (-) (-) => => WIR-WIR-BalancesBalances (+) (+)

Registered 1995-2007

Non-Reg. 1995-2007

D(LRGDP(-2)) 1.8827 -1.2617

(1.535)o (-1.606)o

Adjusted R2 0.157 0.429t-stats in [ ]t-stats in [ ]: ***: ***: p < 0.01, : p < 0.01, **** : p < 0.05, : p < 0.05,

**: p < 0.10; : p < 0.10; oo: p < 0.15: p < 0.15

Apr 20, 2023Apr 20, 2023 2424

Non-Registered Firms Non-Registered Firms may be may be More Counter-Cyclical More Counter-Cyclical In their WIR activity: In their WIR activity:

GDPGDP (-) (-) => => WIR-Turnover Construction (+)WIR-Turnover Construction (+)

Registered 1995-2008

Non-Reg. 1995-2008

D(LRGD_2PAV(-2)) -2.2225 -2.3287

(-2.189)* (-3.382)**Adjusted R2 0.678 0.864

t-stats in [ ]t-stats in [ ]: ***: ***: p < 0.01, : p < 0.01, **** : p < 0.05, : p < 0.05, **: p < 0.10; : p < 0.10; oo: p < 0.15: p < 0.15

Apr 20, 2023Apr 20, 2023 2525

Non-Registered Firms Non-Registered Firms may be may be More Counter-CyclicalMore Counter-Cyclical in their WIR activity: in their WIR activity:

GDPGDP (-) (-) => => WIR-Balances Construction (+)WIR-Balances Construction (+)

Registered 1995-2007

Non-Reg. 1995-2007

D(LRGDP_2AV(-1)) -4.5543 -8.7371

(-1.428) (-2.166)*Adjusted R2 0.658 0.853

t-stats in [ ]t-stats in [ ]: ***: ***: p < 0.01, : p < 0.01, **** : p < 0.05, : p < 0.05, **: p < 0.10; : p < 0.10; oo: p < 0.15: p < 0.15

Apr 20, 2023Apr 20, 2023 2626

Registered Clients Non-Reg. Clients

Registered Clients Non-Reg. Clients

Sign. Occurs. Sign. Occurs.

Sign. Occurs. Sign. Occurs.

Av. Coeff. Av. Coeff.

Av. Coeff. Av. Coeff.

Indust Regress Counter Pro Counter Pro

Regress Counter Pro Counter Pro

Construct Bal_GDP 4 0 5 1 Bal_UE 4 0 2 0

-6.3029 0.0000 -12.1508 9.6924

0.3892 0.0000 1.0193 0.0000

Turn_GDP 2 0 6 0

Turn_UE 0 0 3 0

-2.9235 0.0000 -2.2687 0.0000 0.0000 0.0000 0.3526 0.0000

Hospitality Bal_GDP 0 0 0 4 Bal_UE 1 0 0 2

0.0000 0.0000 0.0000 11.6929

0.0000 0.0000 0.0000 -0.7665

Turn_GDP 0 0 0 3

Turn_UE 0 0 3 0

0.0000 0.0000 0.0000 3.7542 0.0000 0.0000 3.7542 0.0000

Manufact Bal_GDP 0 0 0 0 Bal_UE 0 0 0 4

0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 -1.0435

Turn_GDP 0 0 0 0

Turn_UE 2 0 1 1

0.0000 0.0000 0.0000 0.0000 0.1361 0.0000 0.1045 -0.4438

Retail Bal_GDP 0 0 1 1 Bal_UE 2 0 3 0

0.0000 0.0000 -6.7843 4.4931

0.6636 0.0000 0.5120 0.0000

Turn_GDP 0 1 3 1

Turn_UE 2 2 0 4

0.0000 4.6710 -3.7539 3.6228 0.1685 -0.2142 0.0000 -0.2145

Services Bal_GDP 1 1 0 7

Bal_UE 2 0 3 0

-4.2293 2.5030 0.0000 3.6148

0.6636 0.0000 0.5120 0.0000

Turn_GDP 1 6 0 3

Turn_UE 2 0 4 0

0.0000 1.5850 0.0000 4.6598 0.2845 0.0000 0.5373 0.0000

Wholesale Bal_GDP 0 0 0 0 Bal_UE 0 1 3 1

0.0000 0.0000 0.0000 0.0000

0.0000 -0.1072 0.1435 -0.1380

Turn_GDP 2 2 1 3

Turn_UE 2 0 2 4

-3.1803 1.5431 -3.5616 2.3725 0.1997 0.0000 0.1647 -0.1638

Three Regression PatternsThree Regression Patterns

Apr 20, 2023Apr 20, 2023 2727

Registered Clients Non-Reg. Clients

Registered Clients Non-Reg. Clients

Sign. Occurs. Sign. Occurs.

Sign. Occurs. Sign. Occurs.

Av. Coeff. Av. Coeff.

Av. Coeff. Av. Coeff.

Indust Regress Counter Pro Counter Pro

Regress Counter Pro Counter Pro

Construct Bal_GDP 4 0 5 1 Bal_UE 4 0 2 0

-6.3029 0.0000 -12.1508 9.6924

0.3892 0.0000 1.0193 0.0000

Turn_GDP 2 0 6 0

Turn_UE 0 0 3 0

-2.9235 0.0000 -2.2687 0.0000 0.0000 0.0000 0.3526 0.0000

Hospitality Bal_GDP 0 0 0 4 Bal_UE 1 0 0 2

0.0000 0.0000 0.0000 11.6929

0.0000 0.0000 0.0000 -0.7665

Turn_GDP 0 0 0 3

Turn_UE 0 0 3 0

0.0000 0.0000 0.0000 3.7542 0.0000 0.0000 3.7542 0.0000

Manufact Bal_GDP 0 0 0 0 Bal_UE 0 0 0 4

0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 -1.0435

Turn_GDP 0 0 0 0

Turn_UE 2 0 1 1

0.0000 0.0000 0.0000 0.0000 0.1361 0.0000 0.1045 -0.4438

Retail Bal_GDP 0 0 1 1 Bal_UE 2 0 3 0

0.0000 0.0000 -6.7843 4.4931

0.6636 0.0000 0.5120 0.0000

Turn_GDP 0 1 3 1

Turn_UE 2 2 0 4

0.0000 4.6710 -3.7539 3.6228 0.1685 -0.2142 0.0000 -0.2145

Services Bal_GDP 1 1 0 7

Bal_UE 2 0 3 0

-4.2293 2.5030 0.0000 3.6148

0.6636 0.0000 0.5120 0.0000

Turn_GDP 1 6 0 3

Turn_UE 2 0 4 0

0.0000 1.5850 0.0000 4.6598 0.2845 0.0000 0.5373 0.0000

Wholesale Bal_GDP 0 0 0 0 Bal_UE 0 1 3 1

0.0000 0.0000 0.0000 0.0000

0.0000 -0.1072 0.1435 -0.1380

Turn_GDP 2 2 1 3

Turn_UE 2 0 2 4

-3.1803 1.5431 -3.5616 2.3725 0.1997 0.0000 0.1647 -0.1638

1. Unemployment 1. Unemployment Counter-Cyclical Effects Counter-Cyclical Effects StrongerStronger

Apr 20, 2023Apr 20, 2023 2828

Registered Clients Non-Reg. Clients

Registered Clients Non-Reg. Clients

Sign. Occurs. Sign. Occurs.

Sign. Occurs. Sign. Occurs.

Av. Coeff. Av. Coeff.

Av. Coeff. Av. Coeff.

Indust Regress Counter Pro Counter Pro

Regress Counter Pro Counter Pro

Construct Bal_GDP 4 0 5 1 Bal_UE 4 0 2 0

-6.3029 0.0000 -12.1508 9.6924

0.3892 0.0000 1.0193 0.0000

Turn_GDP 2 0 6 0

Turn_UE 0 0 3 0

-2.9235 0.0000 -2.2687 0.0000 0.0000 0.0000 0.3526 0.0000

Hospitality Bal_GDP 0 0 0 4 Bal_UE 1 0 0 2

0.0000 0.0000 0.0000 11.6929

0.0000 0.0000 0.0000 -0.7665

Turn_GDP 0 0 0 3

Turn_UE 0 0 3 0

0.0000 0.0000 0.0000 3.7542 0.0000 0.0000 3.7542 0.0000

Manufact Bal_GDP 0 0 0 0 Bal_UE 0 0 0 4

0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 -1.0435

Turn_GDP 0 0 0 0

Turn_UE 2 0 1 1

0.0000 0.0000 0.0000 0.0000 0.1361 0.0000 0.1045 -0.4438

Retail Bal_GDP 0 0 1 1 Bal_UE 2 0 3 0

0.0000 0.0000 -6.7843 4.4931

0.6636 0.0000 0.5120 0.0000

Turn_GDP 0 1 3 1

Turn_UE 2 2 0 4

0.0000 4.6710 -3.7539 3.6228 0.1685 -0.2142 0.0000 -0.2145

Services Bal_GDP 1 1 0 7

Bal_UE 2 0 3 0

-4.2293 2.5030 0.0000 3.6148

0.6636 0.0000 0.5120 0.0000

Turn_GDP 1 6 0 3

Turn_UE 2 0 4 0

0.0000 1.5850 0.0000 4.6598 0.2845 0.0000 0.5373 0.0000

Wholesale Bal_GDP 0 0 0 0 Bal_UE 0 1 3 1

0.0000 0.0000 0.0000 0.0000

0.0000 -0.1072 0.1435 -0.1380

Turn_GDP 2 2 1 3

Turn_UE 2 0 2 4

-3.1803 1.5431 -3.5616 2.3725 0.1997 0.0000 0.1647 -0.1638

2. Non-Registered 2. Non-Registered Counter-Cyclical Effects Counter-Cyclical Effects StrongerStronger

Registered Clients Non-Reg. Clients

Registered Clients Non-Reg. Clients

Sign. Occurs. Sign. Occurs.

Sign. Occurs. Sign. Occurs.

Av. Coeff. Av. Coeff.

Av. Coeff. Av. Coeff.

Indust Regress Counter Pro Counter Pro

Regress Counter Pro Counter Pro

Construct Bal_GDP 4 0 5 1 Bal_UE 4 0 2 0

-6.3029 0.0000 -12.1508 9.6924

0.3892 0.0000 1.0193 0.0000

Turn_GDP 2 0 6 0

Turn_UE 0 0 3 0

-2.9235 0.0000 -2.2687 0.0000 0.0000 0.0000 0.3526 0.0000

Hospitality Bal_GDP 0 0 0 4 Bal_UE 1 0 0 2

0.0000 0.0000 0.0000 11.6929

0.0000 0.0000 0.0000 -0.7665

Turn_GDP 0 0 0 3

Turn_UE 0 0 3 0

0.0000 0.0000 0.0000 3.7542 0.0000 0.0000 3.7542 0.0000

Manufact Bal_GDP 0 0 0 0 Bal_UE 0 0 0 4

0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 -1.0435

Turn_GDP 0 0 0 0

Turn_UE 2 0 1 1

0.0000 0.0000 0.0000 0.0000 0.1361 0.0000 0.1045 -0.4438

Retail Bal_GDP 0 0 1 1 Bal_UE 2 0 3 0

0.0000 0.0000 -6.7843 4.4931

0.6636 0.0000 0.5120 0.0000

Turn_GDP 0 1 3 1

Turn_UE 2 2 0 4

0.0000 4.6710 -3.7539 3.6228 0.1685 -0.2142 0.0000 -0.2145

Services Bal_GDP 1 1 0 7

Bal_UE 0 0 0 1

-4.2293 2.5030 0.0000 3.6148

0.0000 0.0000 0.0000 -0.1150

Turn_GDP 1 6 0 3

Turn_UE 2 0 4 0

0.0000 1.5850 0.0000 4.6598 0.2845 0.0000 0.5373 0.0000

Wholesale Bal_GDP 0 0 0 0 Bal_UE 0 1 3 1

0.0000 0.0000 0.0000 0.0000

0.0000 -0.1072 0.1435 -0.1380

Turn_GDP 2 2 1 3

Turn_UE 2 0 2 4

-3.1803 1.5431 -3.5616 2.3725 0.1997 0.0000 0.1647 -0.1638

Apr 20, 2023Apr 20, 2023 2929

3. Non-Reg. show 3. Non-Reg. show More Counter-Cyclical BalanceMore Counter-Cyclical Balance

SMEs are more subject to SMEs are more subject to CreditCredit Risk Risk

Apr 20, 2023Apr 20, 2023 3030

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)

(4) Why are (4) Why are more counter-cyclical more counter-cyclical credit systems credit systems more useful more useful

to the poor to the poor – and vice versa– and vice versa??

Apr 20, 2023Apr 20, 2023 3131

-Because the poor Because the poor spend morespend more, , and more of their spending and more of their spending stays within the communitystays within the community..

Basic Keynesian MultiplierBasic Keynesian Multiplier

Thursday, April 20, 2023Thursday, April 20, 2023 3232

Y = C + I + G + X – M = a + bY + I + G + X – mY => ∆Y/∆G = 1/(1- b + m)

Where b = ‘Marginal Propensity to Consume’ and m = ‘Marginal Propensity to Import’

The The Keynesian ‘MultiplierKeynesian ‘Multiplier’ is larger’ is larger

Apr 20, 2023Apr 20, 2023 3333

for expenditures by for expenditures by poorpoor, who:, who: * spend* spend greater % of their own greater % of their own income (=> income (=> larger blarger b)), and, and

* * maymay spend greater % within spend greater % within own communityown community (=> (=> smaller msmaller m))..

Basic Keynesian MultiplierBasic Keynesian Multiplier

Thursday, April 20, 2023Thursday, April 20, 2023 3434

∆Y/∆G = 1/(1- b↑ + m↓) b = ‘Marginal Propensity to Consume’

and m = ‘Marginal Propensity to Import’

Effect is to increase MultiplierEffect is to increase Multiplier

(5) Why are Self-Adjusting, (5) Why are Self-Adjusting, Counter-Cyclical Credits are Counter-Cyclical Credits are

Non-InflationaryNon-Inflationary??

- - Because they are Because they are moremore counter-cyclical counter-cyclicalthan Ordinary Money.than Ordinary Money.

Apr 20, 2023Apr 20, 2023 3535

Apr 20, 2023Apr 20, 2023 3636

US Macro-Stability: Better since WWII, US Macro-Stability: Better since WWII, ((But Room for Improvement!)But Room for Improvement!)

Source: http://www.nber.org/cycles.html

45% 55%

66%34%

Apr 20, 2023Apr 20, 2023 3737

%∆ Money Turnover [ %∆ Money Turnover [ = %∆ (= %∆ (MMoney x oney x VVelocity) elocity) ] ] is Too is Too ProPro-Cyclical-Cyclical

% ∆ (M x V)

% ∆ V

% ∆M

Apr 20, 2023Apr 20, 2023 3838

(5) The Question of Inflation(5) The Question of Inflation To fight inflation, Central Banks are forced to To fight inflation, Central Banks are forced to

tighten money supply, even if it leads to a tighten money supply, even if it leads to a recessionrecession..

But a more But a more ‘Micro’ Monetary Policy‘Micro’ Monetary Policy can reach can reach sectors sectors unreached unreached by traditional monetary by traditional monetary expansion – expansion – without putting upward pressure without putting upward pressure on priceson prices..

Making up for lost purchasing power is not Making up for lost purchasing power is not inflationaryinflationary, but , but anti-deflationary. anti-deflationary.

Apr 20, 2023Apr 20, 2023 3939

As the internet allows Marketers to go from As the internet allows Marketers to go from BroadcastingBroadcasting to to ‘Point-Casting’‘Point-Casting’

So WIR system allows So WIR system allows Monetary AuthorityMonetary Authority to to go from go from Macro-Macro- to to Micro-CreditMicro-Credit. .

Expended WIR credits don’t go mostly to those who Expended WIR credits don’t go mostly to those who already havealready have much, but those who much, but those who have nonehave none..

This is of course fairer (can gain political support). This is of course fairer (can gain political support).

In addition, it should be In addition, it should be anti-deflationary.anti-deflationary.

Apr 20, 2023Apr 20, 2023 4040

For previous paper, go to:For previous paper, go to:ewp.rpi.edu/hartford/~stoddj

For For SlidesSlides, email me:, email me:stoddj@rpi.edu