Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

1 if St
k ( k 1,2)
Skt
0 otherwise
Pr(S
t
j | St
1
i) pij
, i,
j
2
j1
p
ij
1
2 2
2 1
=1,2
Where y t is the quarterly growth rate in the output
level, S t is an unobserved state variable that
progresses based on first order Markov process with
transition probabilities given in equation. The
dynamic forces in long run are administered through
changes in unconditional variance of different
regimes based on a first order Markov switching
process. The variance of the growth rate in GDP
may then be computed as,
E(σ 2 t |(ŷ) T ) = (σ) ̂ E(S 12 t = 1|(ŷ) T )
+ (σ) ̂ 22 E(S t |(ŷ) T )
Where, (σ) ̂ 12 is the estimate of volatility in state
̂ 22 is the estimate of volatility in state 2.
1, (σ)
DISCUSSION OF RESULTS
The results of GARCH model estimation indicate
that the AR order of mean equation for Pakistan and
Japan is one, while the order for USA is three. Both
coefficients of ARCH (0.3285) and GARCH
(0.7065) effect for Pakistan are statistically
significant. Similarly, ARCH and GARCH terms
are also significant for USA and Japan. Taking an
overall view of GARCH coefficient in all four
economies, observed relatively similar estimates
and significant. Whereas, the ARCH term in
Pakistan is quite discrepant with a larger estimate
likewise Japans’ GARCH term estimate is relatively
smaller than other economies. Moreover, the sum of
α1 and β1 indicates persistence of volatility of
0.9838 for USA and India respectively, versus
almost 1.0 for Pakistan. Reviewing the economy, is
0.8574 for Japan, while 0.9732 analysis provided by
[6] about non-linear time series, the existence of
highest volatility in overall output growth level is in
Pakistan, USA and India in term of persistence of
volatility is relatively high, but it is relatively low in
Japan.
The results of Markov switching heteroscedasticity
show (Table4) the propensity to remain in the low
variance state p22, as 0.9911 for Pakistan, 0.97489
for USA, 0.9940 and 0.8751 for India and Japan
respectively. Similarly, the probability p11 is
estimated as 0.9960, 0.9634, 0.9780, and 0.9802 for
Pakistan, USA, Indian, and Japan respectively.
Moving towards the variance in low volatility state
denoted by σ2, and is estimated at 4.554 for
Pakistan, 1.654 for USA, 4.817 and 3.229 for India
and Japan respectively. Likewise, the variance of
high volatility state is 15.65 for Pakistan, 3.69 for
USA, 8.185 and 6.878 for India and Japan
respectively.
Table 4: Real GDP growth rate: Markov
Switching Heteroscedasticity Model
estimation
Pakistan US
3.692348* A
India
8.18513
15.651
4*
2
σ
9* (0.451562) (0.93273
1
(0.82542
5)
4) 1.654349* 4.816646
2
σ 2 (0.131418) (0.30515 *
4.55434
(0.54131 0.9634823 0.978002 2)
P 11
9* 1)
(0.004 (0.045222) * (0.01977 1*
0.99600
467)
39)
P 22
16*
0. 0.974889* 0.993964
(0.013 (0.019308) (0.00640 3*
99
019)
1)
11
Japan
6.877717*
(1.43580)
3.228977*
(0.23889
0.9802704 1)
(0.01592 *
0.8751064 05)
(0.09447 *
07)
Interestingly, 08 the variances in high volatility state
in Pakistan, * USA, India and Japan are more than
three times, over two times, nearly one and half
times and two times higher than the variances in
low volatility state, respectively. Thus the break in
variance of GDP growth rate has been quantified in
in these economies, similar way as discussed by
Kim, Nelson, and Piger (2001). The standardized
residual was attained based on GARCH model
methodology, therefore proceeded towards the
Markov switching variance model. As shown in
following figures these results validate the structural
break in variance; and confirmed significant
structural break in variance of the GDP for Pakistan
and India. There also persists break in variance of
GDP growth for USA and Japan; Evaluating the
case of Pakistan, during the period of 1960s and
1970s low variance period is evident, on other hand
high variance period largely continued afterwards.
Pakistan high variance continued for a longtime due
to interchanging governments, lack of
synchronization among economic policies, further
long term policies were not emphasized. Whereas,
taking into account the Indian economy who largely
remained in low variance region before 1980s and
then again moved to low variance period since late
2000s.
Economic policies were coherent, GDP continued to
grow at a steady pace; but between 1980s and 2000s
the economy undergone a high variance period that
was largely due to gradual liberalization of the
international markets. Faulty economic policies and
structural problem continued during this phase, till
macroeconomic reforms introduced in 1990s played
a long term role in diverting economy back to low
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