INDEX OF CASHLESS TRANSACTION

Sancharita DattaUGC-SRF Ph.D. Research Scholar, Department of Economics

Jadavpur University, Kolkataand

Prof. Malabika Roy Department of Economics, Jadavpur University

What is Cashless Transaction?

• Exchange of goods and services and transfer of money from one to other, without the use of currencies but using the financial transaction system provided by the financial institutions.

WHY CASHLESS TRANSACTION?

• Lower transaction cost (from consumer side)

• Reduce cost of production of coins and currencies

• Reduce potential of black money

• Transparency in business accounts will help in collection of taxes.

GOVT. INITIATIVES (POST DEMONETIZATION)

• Unstructured Supplementary Service Data (USSD)

• Aadhar Enabled Payment system (AEPS)

• Digital Finance for Rural India: Creating Awareness and access through CSCs’

• 0.75% Discount on purchase of petrol/ diesel if payment is made through digital means.

• Development of 2 POS devices each in 1 lakh villages with population less than 10,000, through NABARD.

GOVT. INITIATIVES (POST DEMONETIZATION)

• Issuing of ‘Rupay Kisan Cards’ to 4.32 crore Kisan Credit Card holder to make digital transaction.

• MDR charges shall be borne by the Govt. for the transaction under 2000.

• Discount of 10% at Toll Plazas on NH for the payments using cards.

Why Need an Index?

• Demand Deposit with banks as a proportion of money supply is not a better way

• To define the extent of cashless transaction differently.

LITERATURE • Humphrey, Pulley and Vesala (1996) did a comparative study

between cash paper payment and electronic payments, theyanalyzed the pattern of payment instruments use over time forfifteen countries

• Westland, Kwok, Shu, Kwok, Henry Ho (1998) have done an analysison the acceptance of electronic cash (Mondex e cash) among thecustomers and merchants of the Hong Kong.

• Humphrey, Kim and Vale(2001), havedonea study of usage ofelectronic payments over cashbetween U.S, Europe, Norway andJapan on the basis of Cash to GDP ratio and number of noncashtransactions per persons.

Method • Exogenous effects

• Volume and value of the cashless transaction can increase due to the increase in the adult population.

• we have considered Per Capita volume of the cashless transaction as well as per capita value of the cashless transaction.

• The value of the cashless transaction can be increased because of the increase in the overall price level or production.

• We have considered Value of the cashless transaction as a proportion GDP

METHOD

• The Indexes, which we have considered for our analysis, are:

• Per Capita Volume Index of The Cashless Transaction.

• Per Capita Value Index of The Cashless Transaction.

• Value of The Cashless transaction as a proportion of GDP Index.

INDIVIDUAL DIMENSION INDEX

• We have used Mandira Sharma’s multidimensional index(2010)

• ith dimension index is computed using the followingformula.

• 𝑥𝑥𝑖𝑖 = actual value of the dimension• 𝑀𝑀𝑖𝑖 = maximum value of the dimension (sample maximum)• 𝑚𝑚𝑖𝑖 = minimum value of the dimension (sample minimum)

−−

=ii

iii mM

mxd

Unit free Bounded Homogeneous Monotonic

AGGREGATE INDEX

• By averaging all the normalized dimensions with weights we get our desired index.

• Where k = no. of dimensions,wi = Weights (using Principal Component Analysis)

• And rest of the symbols have their previous meaning

• For structural breaks we have used Cusum Test

∑=

−−

=k

i ii

iiikr mM

mxwdddI1

21 ],....,[

THE DIMENSIONS OF PER CAPITA VOLUME INDEX:

• The No. of cards per adult population

• The number of POS transaction (with debit and credit cards) per adult population.

• The number of NEFT transaction per adult population

• The number of RTGS transaction per adult population.

• The number of IMPS transaction per adult population.

• The number of ECS Debit & Credit +NACH transaction per adult population.

DIMENSIONS OF PER CAPITA VALUE INDEX

• Amount of POS transaction per adult population.

• Amount of NEFT transaction per adult population.

• Amount of RTGS transaction per adult population.

• Amount of IMPS transaction per adult population.

• Amount of ECS debit & credit + NACH transaction per adult population.

DIMENSIONS OF VALUE AS A PROPORTION OF GDP INDEX

• Amount of POS transaction as a proportion of GDP.

• Amount of NEFT transaction as a proportion of GDP.

• Amount of RTGS transaction as a proportion of GDP.

• Amount of IMPS transaction as a proportion of GDP.

• Amount of ECS debit & credit + NACH transaction as a proportion of GDP.

DATA SOURCE AND TYPE

Data Title Data Source1. Bank-wise value and volume of the electronic

transaction over the months RBI

2. Bank- Wise value and volume of NEFT, RTGS, Mobile Banking transaction over the months

RBI

3. Quarterly GDP data and growth rate (Expenditure approach, seasonally adjusted, at

constant prices (2011-12))

OECD

4. Adult Population Data (from the age group of 15 and above)

World Bank

• We have done the analysis on Indian economy overtime.• Month wise analysis• Total 76 time points from Sep 2012 to Dec 2018

MONTHLY GDP CALCULATION• Monthly growth rate (r) = quarterly growth rate/3• We assume the GDP has grown at this constant growth rate r so

• Where y1 = monthly GDP of 1st financial monthy2 = monthly GDP of 2nd financial monthy3 = monthly GDP of 3rd financial month

Such that 1st quarter GDP Q1 = y1 + y2 + y3.

Similarly we have the values of other months’ GDP

Per Capita Volume Index

0

0.2

0.4

0.6

0.8

1

1.2

2012

Nov

2013

Feb

2013

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Nov

-40

-20

0

20

40

60

80

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

Dependent Variable: _N_PER_CAPITA_VOLUME_IND

Method: Least Squares

Date: 11/14/19 Time: 17:51

Sample: 1 74

Included observations: 74

Variable

Coefficient

Std. Error

t-Statistic

Prob.  

TIMES

0.013777

0.000272

50.56951

0.0000

C

-0.104671

0.011758

-8.902426

0.0000

R-squared

0.972616

    Mean dependent var

0.411971

Adjusted R-squared

0.972236

    S.D. dependent var

0.300431

S.E. of regression

0.050060

    Akaike info criterion

-3.124549

Sum squared resid

0.180429

    Schwarz criterion

-3.062277

Log likelihood

117.6083

    Hannan-Quinn criter.

-3.099708

F-statistic

2557.275

    Durbin-Watson stat

0.129931

Prob(F-statistic)

0.000000

Per Capita Value Index

0

0.2

0.4

0.6

0.8

1

1.2

2012

Nov

2013

Feb

2013

May

2013

Aug

2013

Nov

2014

Feb

2014

May

2014

Aug

2014

Nov

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2018

May

2018

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2018

Nov

-30

-20

-10

0

10

20

30

40

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

Dependent Variable: _N_PER_CAPITA_VALUE_INDE

Method: Least Squares

Date: 11/08/19 Time: 15:10

Sample: 1 74

Included observations: 74

_N_PER_CAPITA_VALUE_INDE = C(1)*TIMES + C(2)*TIMES^2 + C(3)

Coefficient

Std. Error

t-Statistic

Prob.  

C(1)

-0.002912

0.000637

-4.571322

0.0000

C(2)

0.000209

8.23E-06

25.42146

0.0000

C(3)

0.062574

0.010352

6.044544

0.0000

R-squared

0.990310

    Mean dependent var

0.343077

Adjusted R-squared

0.990037

    S.D. dependent var

0.289388

S.E. of regression

0.028885

    Akaike info criterion

-4.211262

Sum squared resid

0.059240

    Schwarz criterion

-4.117854

Log likelihood

158.8167

    Hannan-Quinn criter.

-4.174000

F-statistic

3628.007

    Durbin-Watson stat

0.621307

Prob(F-statistic)

0.000000

Value/GDP Index

0

0.2

0.4

0.6

0.8

1

1.2

2012

Nov

2013

Feb

2013

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2013

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-20

-10

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40

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

Dependent Variable: VALUEGDP_R_1_N_

Method: Least Squares

Date: 11/08/19 Time: 15:12

Sample: 1 74

Included observations: 74

Variable

Coefficient

Std. Error

t-Statistic

Prob.  

TIMES

-0.003030

0.000942

-3.218286

0.0019

TIMES^2

0.000203

1.22E-05

16.66194

0.0000

C

0.109070

0.015302

7.127798

0.0000

R-squared

0.977045

    Mean dependent var

0.372986

Adjusted R-squared

0.976398

    S.D. dependent var

0.277924

S.E. of regression

0.042697

    Akaike info criterion

-3.429669

Sum squared resid

0.129437

    Schwarz criterion

-3.336261

Log likelihood

129.8977

    Hannan-Quinn criter.

-3.392407

F-statistic

1510.987

    Durbin-Watson stat

0.586894

Prob(F-statistic)

0.000000

FINDINGS (Individual dimension wise)

No. of Cards/1000 adults No. of POS/Adult Population No. of NEFT/Adult Population

No. of RTGS/Adult Population

No. of IMPS/ Adult Population No. of IMPS/Adult Population

0

0.2

0.4

0.6

0.8

1

1.2

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

0.1

0.2

0.3

0.4

0.5

0.6

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep 0

0.05

0.1

0.15

0.2

0.25

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

0.05

0.1

0.15

0.2

0.25

0.3

2012

Nov

2013

Apr

2013

Sep

2014

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2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

FINDINGS (Individual dimension wise)

Amount of POS/ Adult Population

Amount of NEFT/Adult Population

Amount of RTGS/Adult Population

Amount of IMPS/Adult Population

Amount of ECS+NACH/ Adult Population

0

200

400

600

800

1000

1200

2012

Nov

2013

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2013

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2014

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Jul

2014

Dec

2015

May

2015

Oct

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Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

5000

10000

15000

20000

25000

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep 0

20000

40000

60000

80000

100000

120000

140000

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

200

400

600

800

1000

1200

1400

1600

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

200

400

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800

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1200

1400

1600

2012

Nov

2013

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2013

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2014

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2014

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2015

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2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

FINDINGS (Individual dimension wise)

Amount of POS/ GDP Amount of NEFT/ GDP Amount of RTGS/ GDP

Amount of IMPS/ GDP Amount of ECS+NACH/ GDP

00.010.020.030.040.050.060.070.080.09

0.1

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

00.20.40.60.8

11.21.41.61.8

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

2

4

6

8

10

12

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

2012

Nov

2013

Apr

2013

Sep

2014

Feb

2014

Jul

2014

Dec

2015

May

2015

Oct

2016

Mar

2016

Aug

2017

Jan

2017

Jun

2017

Nov

2018

Apr

2018

Sep

FINDINGS (Individual dimension wise)

No. of Cards/ Adults Population

No. of POS/ Adult Population No. of NEFT/ Adult Population

No. of RTGS/Adult Population No. of IMPS/ Adult Population No. of ECS+NACH/AdultPopulation

-30

-20

-10

0

10

20

30

40

50

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

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50

60

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

50

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

FINDINGS (Individual dimension wise)

Amount of POS/ Adults Population

Amount of NEFT/ Adult Population

Amount of RTGS/ Adult Population

Amount of IMPS/ Adult Population Amount of ECS+NACH/Adult Population

-30

-20

-10

0

10

20

30

40

50

60

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

50

60

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

FINDINGS (Individual dimension wise)

Amount of POS/ GDP Amount of NEFT/ GDP Amount of RTGS/ GDP

Amount of IMPS/ GDP Amount of ECS+NACH/GDP

-30

-20

-10

0

10

20

30

40

50

60

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

50

60

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

40

50

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

-30

-20

-10

0

10

20

30

5 10 15 20 25 30 35 40 45 50 55 60 65 70

CUSUM 5% Significance

CONCLUSION

• Per capita volume of the cashless transaction increases significantly from January 2015,

• but the per capita value of the cashless transaction and value as a proportion of GDP has increased after demonetization period but the effects are not enough satisfactory.

• So post demonetization policies have a positive impact on the value of the cashless transaction rather volume.

CONCLUSION

• Only POS transaction and IMPS transaction significantly increases after the demonetization period.

• The effect are very slightly and the increments are not that as expected.

THANK YOU….

INDEX OF CASHLESS TRANSACTIONWhat is Cashless Transaction?WHY CASHLESS TRANSACTION?GOVT. INITIATIVES (POST DEMONETIZATION)GOVT. INITIATIVES (POST DEMONETIZATION)Why Need an Index?LITERATURE Method METHODINDIVIDUAL DIMENSION INDEXAGGREGATE INDEXTHE DIMENSIONS OF PER CAPITA VOLUME INDEX:DIMENSIONS OF PER CAPITA VALUE INDEXDIMENSIONS OF VALUE AS A PROPORTION OF GDP INDEXDATA SOURCE AND TYPEMONTHLY GDP CALCULATIONPer Capita Volume IndexPer Capita Value IndexValue/GDP IndexFINDINGS (Individual dimension wise)FINDINGS (Individual dimension wise)FINDINGS (Individual dimension wise)FINDINGS (Individual dimension wise)FINDINGS (Individual dimension wise)FINDINGS (Individual dimension wise)CONCLUSIONCONCLUSIONTHANK YOU….