dr. david tennant

8/2/2019 Dr. David Tennant

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MODELLING THE RELATIVEEFFECTS OFFINANCIAL SECTOR FUNCTIONS ONECONOMIC GROWTH IN A DEVELOPING

COUNTRY CONTEXT USING COINTEGRATION

AND ERROR CORRECTION METHODS

PAPER PRESENTED AT THE FRANCIS CONFERENCE

September 28 30, 2007

DAVID TENNANT, CLAREMONT KIRTON &ABDULLAHI ADBULKADRI

DEPARTMENT OF ECONOMICS, UWI, MONA


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OVERVIEW OF PRESENTATION:

Background and Objectives

Proxies of Financial Sector Functions

Control Variables

Methods

Results and Findings

Conclusions


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BACKGROUND and OBJECTIVES

The Monterrey Consensus (2002) notes that many

developing countries increasingly depend on local funds to

finance their development needs.

Financial institutions can facilitate economic growth by

mobilizing savings, allocating these savings to the most

productive investments, and by facilitating the smooth flow

of trade needed in a market-driven economy.

Theoretical models supporting this view have been

developed by many economists.


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BACKGROUND and OBJECTIVES Contd

Many of the empirical studies of the finance-growth

relationship use broad proxies of financial sectordevelopment.

It would however be very useful to determine which of the

distinct functions of the financial sector have the greatestimpact on economic growth.

Holden and Prokopenko (2001), Levine and Zervos (1998),

and De Gregorio and Guidotti (1995) all cite difficultiesinvolved in developing proxies to accurately and

comprehensively capture the many different functions

performed by the financial sector.


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BACKGROUND and OBJECTIVES Contd

Levines (1997) five basic functions of the financial sector

are used as the basis of this study.

The Jamaican case study is used.

In the post-liberalization phase of the evolution of theJamaican financial sector, the country experienced afinancial crisis, and a government-led restructuring andsubsequent divestment of the sector.

Important conclusions are presented regarding the relativeimportance of financial sector functions to the creation ofeconomic growth, and the impact of financial crises on theeconomy.


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PROXIES of FINANCIAL SECTOR

FUNCTIONS:

Savings Mobilization

SMOB = Deposits / (Total Assets Loans)

A positive relationship between SMOB and economicgrowth is therefore expected.

Risk Diversification

The measure of risk diversification used (DRISK) focuses

on the degree of diversification by sector.


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oFUNCTIONS:

DRISKfor each type of financial institution is calculated by

first finding the percentage of total loans allocated by sector.

The standard deviation of the percentage of total loans

allocated to each sector is then used to measure the spread foreach institution from the state of uniform distribution.

A measure of the degree of diversification for the entire

financial sector is calculated using a weighted average.

A negative relationship betweenDRISKand economic

growth is expected.


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PROXIES of FINANCIAL SECTOR

FUNCTIONS:

Resource Allocation

RESAL = credit to private sector production / total loans.

It is expected that RESAL will have a positive relationship

with economic growth.

Corporate Control

The proxy used for corporate control (CORPC) assumesthat as connected party loans and/or connected partyfinancial investments increase, then the ability of financialinstitutions to exert corporate control decreases.


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PROXIES of FINANCIAL SECTOR FUNCTIONS:

CORPC = connected party loans and financial investments/ total loans and financial investments.

CORPCis expected to have a negative relationship witheconomic growth.

Ease of Trading

Using the approach of Levine and Zervos (1998),ETRAD =value of shares traded / current GDP.

Levine (1991) initially argued that a positive relationshipwith economic growth should be expected, he later notes theargument that very liquid markets encourage investormyopia, thus actually hurting economic growth (Levine

1996).


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CONTROL VARIABLES

A measure of trade openness (TRADE) was included,

and calculated as the sum of the countrys imports andexports divided by current GDP.

Exchange rate volatility (XRATEVOL) for each quarter

is calculated as the standard deviation of the percentage

change in the US$ real exchange rate for the four

preceding quarters.

Two dummy variables were used to account for

structural changes affecting the Jamaican financial

sector liberalization and crisis.


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METHODS

Data

Quarterly time series from 1986-2005 Due to missing data most estimations limited to

1989-2005

Augmented Dickey-Fuller test used to determine

stationarity

Cointegration Analysis

Used to determine long-run relationships among data

series

Two specifications were considered: (1) using

individual proxies (2) with interaction terms


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METHODS

Model (1):

Model (2):

ttttt

ttttt

eSTRUCTURESMOBRESALDRISK

CORPCETRADXRATEVOLTRADEGDP

+++++

++++=

8765

43210

lnlnln

lnlnlnlnln

tt

ttttt

ttttt

eSTRUCTURE

DRISKSMOBETRADSMOBRESALSMOB

RESALCORPCXRATEVOLTRADEGDP

+++++

++++=

8

765

43210

ln*lnln*lnln*ln

lnlnlnlnln


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METHODS

Error Correction Model

Used to examine short-run dynamics Enables us to determine short-run adjustments to long-

run equilibrium

tt

L

l

ltltl

L

l

ltltllt

L

l

ltl

L

l

ltl

L

l

ltl

L

l

ltl

L

l

ltltt

STRUCTUREDRISKSMOB

ETRADSMOBRESALSMOBRESAL

CORPCXRATEVOLTRADEECTGDP

+++

+++

++++=

=

=

=

=

=

=

=

8

0

7

0

6

0

5

0

4

0

3

0

2

0

11

ln*ln

ln*lnln*lnln

lnlnlnln


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RESULTS

Stationarity

LnGDP I(2), LnETRAD and LnTRADE I(0), allothers I(1)

Johansen Cointegration test indicated nine possible

cointegrating relationships for Model (1) and six for

Model (2)

Selection of reported equation was based on conformity

with theory

T bl 1 E ti t f I iti l M d l C i t ti


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Table 1 Estimates of Initial Model Cointegrating

Equation with lnGDP as Dependent Variable

Variable Name Coefficient t-Statistic

CONSTANT -6.972* -10.329

lnSMOB 1.206* 4.691

lnRESAL -1.870* -3.503

lnCORPC 0.224 1.432

lnDRISK -1.507* -9.442

lnETRAD -0.145* -5.513

CRISIS 0.270 0.791

lnTRADE 0.271 0.736

lnXRATEVOL 0.286* 8.085

* indicates significance at 1% level

T bl 2 E ti t f Alt ti M d l C i t ti


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Table 2 Estimates of Alternative Model Cointegrating

Equation with lnGDP as Dependent Variable

* indicates significance at 1% level

Variable Name Coefficient t-Statistic

CONSTANT -6.441* -48.186

lnCORPC -0.222* -7.686

lnRESAL 1.342* 15.490

lnSMOB*lnRESAL 1.232* 9.985

lnSMOB*lnDRISK -0.785* -7.704

lnSMOB*lnETRAD -0.361* -12.317

CRISIS 0.797* 15.474

lnTRADE 1.110* 13.285

lnXRATEVOL -0.117* -15.842


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FINDINGS


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FINDINGS

Model (2) outperforms Model (1)

Has more significant variables and conforms better with

theoretical expectations

Establishes long-run relationship between GDP and

dependent variables.

ECM indicates

No short-run relationship between GDP growth and

dependent variables

The speed of adjustment is ~35%

CRISIS has a negative, though, insignificant effect on

GDP growth, compared with positive and significant effect

in the long-run


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CONCLUSIONS

Sophisticated proxies of financial sector function

have been developed Based on Favara (2003)

ensure accuracy and conformity to theory

Savings mobilization is an essential factor through

which other proxies impact economic growth

Resource allocation

Ease of trading

Risk diversification


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CONCLUSIONS

Financial sector reform should:

Focus on savings mobilization and the efficient

allocation of mobilized savings

Emphasize removal of government distortions in

financial markets

Not be expected to yield immediate results

dr. david tennant

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