Download Modeling and Forecasting Residential Electricity

Oil and the Macroeconomy of
Kazakhstan
Prepared for the 30th USAEE North American
Conference, Washington DC
By
Ferhat Bilgin, Ph.D. Student and Fred Joutz
Department of Economics
George Washington University
Objectives
• Analyze the role of oil in Kazakhstan’s economy. Specifically,
study the effects of oil price on the macroeconomic dynamics
of Kazakhstan
• Attempt to find long-run relationship and short-run dynamics
• The hypothesis is that capital stock and oil price are the major
determinants of GDP growth; and growth of GDP and oil price
are the main sources of government revenue growth.
Summary of Results
• We found both long run and short run GDP and Revenue growth model
• The long-run relationship yields
– Rise of the oil price and accumulation of capital stock raise the level of
GDP.
– Higher level of government revenue is determined by higher level of
GDP and world oil price
• In the short run
– GDP growth rate is driven by changes in contemporaneous and lagged
oil price, but government taxation has a negative effect on GDP growth
– Oil price has a direct positive effect on government revenue in addition
to the effects through error correction mechanism
Organization
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Brief Economic History of Kazakhstan
Literature Review
General Model
Data
Empirical Model for the DGP – Unrestricted VAR
Cointegration Testing and Analysis
Equilibrium Correction Model
Kazakhstan: Gross Domestic Product
Basic Oil Exporting Country Macroeconomic Model:
Linkage Economic Growth, Fiscal Revenues, Capital Stock, and Oil Sector
Government Revenue, real and nominal
Unit: USD
Oil Price, real and nominal
• In USD
Kazakhstan’ oil output, oil exports
Unit: in million barrels a day
Oil export’s share in total exports
Oil output’s share in total output
Unit: (%)
Inflation (1992 – 2010)
Inflation
(%)
1992
1993
1994 1995
1996
1997
1998
1999
2000
1381
1662
1402 176
39
17
7
8
13
2001
2002
2003
2004
2005 2006
2007
2008
2009
2010
6
7
7
8
11
17
7
7
Inflation 8
(%)
9
Inflation (1995-2010)
Unit: (%)
Employment (in millions)
Literature Review
Gronwald, Mayr and Orazbayev (2009): studied the effects of oil price
decline on Kazakhstan’s real GDP, budget revenue, exports and real
exchange rate => oil price decline has negative effect on these variables
Rautava (2004): studied the effects of oil price on Russian GDP and
government revenue using CVAR and VeqEM approach.
10% permanent increase in oil price => 2.2 % rise in GDP, 4.6% in Rev.
10% increase in oil price => 0.5% rise in GDP, 3.9% in Gov’t Rev.
Ito (2008): studied the effects of oil price on Russian GDP and inflation
using CVAR and VEC approach and found that oil price has a positive
effect on GDP and inflation
Venezeula: El-Anshasy, Bradley, Joutz (2007): used CVAR and VeqEM
modeling approach to study the long run and short run relationship between
oil price and Venezuela's GDP and government revenue.
10% rise in oil price => 2.5% and 2.3% rise in the level of GDP and Rev,
and adds 1.7% and 2.8% directly to the short run growth rate
General Macro Model
• Basic Oil Exporting Country Macroeconomic
Model:
Y = Kα*Lβ*(Poil)γ
• Linkage Economic Growth, Fiscal Revenues,
Capital Stock, Labor and Oil Sector
Data (sample: 1996q1-2010q3)
• All in a log form
Data Analysis
• Sample period is 1996Q1 through 2010Q3
• Capital stock represents the capital acquired after
1995q1 and used as a proxy for the entire capital
stock in the economy
• Augmented Dickey Fuller Test
 The levels are nonstationary
 The first differences are stationary
all of the five series are I(1) series
 We can apply CVAR and VEC modelling approach
VAR in Levels and Cointegration Analysis
• Lag Structure Analysis
 VAR(5) -> VAR(4)
 VAR (4) is the most appropriate
• Model Stability
 1-step Chow test
 Break point Chow test
=> model is stable
• Johansen Test
=> two cointegrating vector
Long Run Equilibrium Relations
GDP and Government Revenue
• GDP relations
gdp = 0.35*capital stock + 0.46*oil price
• Government revenue relations
revenue = 0.56*gdp + 0.44*oil price
• Capital stock is weakly exogenous
=> capital stock does not enter VEC model as
endogenous variable
Table 3: Final Vector Error Correction Model
Sample Period 1996q1 – 2010q3
DLrgdp: Change in real quarterly GDP
DLrgrev: change in real quarterly Government Revenue
Equation
Equation
for DLrgdp
Coefficient
t-value for DLrgrev Coefficient
Constant
1.4676
6.71
Constant
0.3337
DLrgrev_1
-0.3655
-8.49
DLroilprice
0.5321
DLrgrev_2
-0.2032
-5.78
ECMg_1
-0.7552
DLrgrev_3
-0.2078
-7.69
I:1998(4)
0.3758
DLroilprice
0.3486
6.99
I:1999(2)
-0.3160
DLroilprice_1
0.1162
2.69
I:2005(4)
0.4023
ECMy_1
-0.4407
-6.70
I:2008(4)
0.6828
ECMg_1
0.3272
6.84
I:1998(4)
-0.0810
-2.10
I:2009(2)
-0.1570
-2.31
sigma =
0.0341
sigma =
0.1169
RSS =
0.0383
RSS =
0.4513
R^2 =
0.9739
F(30, 70) =
9.7785
Vector AR 1-4 test:
F(16,48)
=
1.0870
Vector Normality test:
Chi^2(4)
=
3.6889
Vector Hetero test:
F(51, 72)
=
0.8709
Vector RESET2 test:
F(8, 56)
=
1.5634
t-value
0.444
3.11
-4.60
2.84
-2.14
3.05
3.93
[0.0000]
[0.3927]
[0.4497]
[0.6967]
[0.1569]
Interpreting the Final Error Correction Model
Feedback from Long-Run Relations
• Inclusion and estimation of the CVAR provide important insights to longrun economic performance
• And provides information in the specification and understanding of the
short-run dynamics.
• Fiscal ECM enters the change equations for
– GDP (0.32) higher revenue encourages higher spending
– Government Revenue (-0.75) sluggish adjustment to deviation from
“steady-state”
• Economic Growth ECM enters the change equations for
– GDP (-0.44) slow adjustment to deviations from “steady state”
Interpreting the Final Error Correction Model
Short-Run Dynamics (Growth or Changes)
• Contemporaneous and lagged oil price changes have a
direct positive effect on GDP growth rate
• Changes in contemporaneous and lagged values of
government revenue have a negative effect on GDP.
• Oil prices have a positive direct dynamic effect on
government revenues.
Conclusions
• Comments and suggestions welcome
• Thank you!
Autometrics –
General to specific modeling algorithm
1.
2.
3.
4.
5.
Hendry and Krollzig (2001) There are five basic steps:
Specification of the GUM (General Unrestricted Model) by the
empirical modeler.
Tests for mis-specification usually through residual
diagnostics.
Begin Model Reduction Process. Investigation of possible
paths for variable selection. Elimination of “irrelevant”
variables.
Test terminal models or paths for congruency.
Evaluate terminal models for final model(s) through
encompassing tests.
End Result: Retain only Variables in GUM that Matter!!
23
Reduction from the General Cointegrated VAR
• Process of Reducing the Statistical Model
• Retain Characteristics of the Original Relationships in Data or
DGP
• The pattern of short run dynamics is identified by sequentially
eliminating insignificant regressors and then estimating the
resulting model with FIML.
• Hypothesis Tests used for Model Evaluation and Model Design
• Parsimony
• Maintain White Noise Property of Residuals
• Stability
• Interpretability
• Final Model is Congruent