Download Reduced Form Equation for Real GDP Growth in OPT

 PMA WORKING PAPER
WP/12/05 A SHORT RUN REDUCED FORM
EQUATION FOR REAL GDP GROWTH
IN OPT
Mohammed Aref and Michel Dombrecht
PMA Working Paper
Research and Monetary Policy Department
A SHORT RUN REDUCED FORM EQUATION FOR REAL GDP GROWTH IN OPT
Prepared by Mohammed Aref1 and Michel Dombrecht2
April 2012
Abstract
The paper aims at designing (semi) reduced form equations for quarterly Real Gross Domestic product (RGDP)
growth in the Occupied Palestinian Territory (OPT). This need was based on the observation that not sufficiently
long time series exist to build a structural quarterly model.
Main result of this paper show that the quarterly RGDP is very much driven by some of the exogenous variables
identified in the PMA’s annual structural models. Among these, the external environment was found to play a
dominating role. Besides external influences, quarterly RGDP growth is also driven by construction of new
buildings activity for which the issued new building licenses are a reliable quarterly indicator.
These models have been used to produce out of sample quarterly RGDP forecasts over the period 2012 – 2013.
These point forecasts were accompanied by alternative optimistic and pessimistic scenario’s.
© April, 2012
All Rights Reserved.
Suggested Citation:
Palestine Monetary Authority (PMA), 2012. A SHORT RUN REDUCED FORM EQUATION FOR REAL GDP
GROWTH IN OPT
Ramallah – Palestine
All Correspondence should be directed to:
Palestine Monetary Authority (PMA)
P. O. Box 452, Ramallah, Palestine.
Tel.: 02-2409920
Fax: 02-2409922
E-mail: [email protected]
www.pma.ps
JEL Classification Numbers: C22; E20; E27
Keywords: Reduced form equation; ARDL; Economic growth
Authors’ E-mail addresses: [email protected]; [email protected]
1
2
Palestine Monetary Authority. University of Antwerp, Belgium and Hogeschool Universiteit Brussels, Belgium.
Thanks to our colleague Mahmoud Bsharat for his assistance
1 CONTENTS
1. Introduction
5
2. The Model
5
2.1
A truly exogenous mode
9
2.2
A semi-reduced form equation
14
3. GDP Forecast and Scenario Analysis
15
4. Conclusion
17
2 List Of Tables:
Tables 1: Frequency and Start Data of Main Exogenous Variables for Real OPT
VARIABLES FOR REAL OPT GDP
7
Tables 2: Unit Root Test of Variables in Levels and First Difference
8
Tables3: OLS Simple Regression for Real GDP in OPT for the Period 2001Q1 2011Q4
12
Tables 4: CHOW’ Frequency Breakpoint Test
12
Tables 5: The Equilibrium Correction of ARDL (1,1,1) RGDP Equation
13
List Of Figures:
Figure 1: Index of Real GDP in OPT and The Exogenous Variable
9
Figure 2: The Estimated Trend of The GDP Ratio
11
Figure 3: Actual and Fitted Real GDP in OPT
11
Figure 4: The Baseline Forecast of Quarterly Real GDP in OPT
14
Figure 5: Baseline Forecast For Building Licenses
15
Figure 6: Forecast in Different Scenarios for Quarterly Real GDP in OPT
16
3 Abbreviations:
CIM$
The weighted average prices set by foreign suppliers on the
domestic market (cost of imports)
PWFPI
World food price index
FTAID
Grants and donations
RGI
Real Government Investment
NCDT
Number of clousre days for trade
BL
Building licenses (new builiding)
EIS
Employment in Israel and settlement
DDAWIS
Daily average wage in Israel and Settlements
MFFRUS
US Federal Funds rate
NGS
Nominal Government Spending
MEXGRISINDEX Exchange rate index (USD/NIS)
CPI
Consumer price idex in Palestine
PCPIP$
Consumer price index adjusted to USD
REER
Real effective exchange rate
OPT
Occupied Palestinian Territory
PMA
Palestine Monetary Authority
RGDP
Real Gross Domestic Product in Palestine
RGDPI
Real Gross Domestic Product in Israel
LRWGDPAIMEX The weighted average real GDP in Palestinian Territory main
export and import markets
4 1. Introduction
The PMA’s structural and financial programming models are on an annual frequency. The main
reason for this is that most of the data used in those models are not available on quarterly
frequency. Such annual models are extremely useful for the analysis of the effects of all kind of
shocks on the economy and for policy analysis. They also provide forecasts for many other
macroeconomic variables in a way that is coherent and consistent with the real GDP forecast.
Such models also allow to build up the narrative of the forecast and provide for a coherent
framework to explain recent developments, the medium term economic outlook and the main
transmission mechanisms of external and internal shocks.
On the other hand, for the purpose of short term real GDP growth forecasting the annual
models may miss at least part of the influence of the short term economic dynamics and their
short term forecasts may therefore be sub-optimal. In most central banks (as well as outside
central banks) forecasts are the result of a mixture of information, among which the above
mentioned models. Apart from the structural models, forecasts also tend to rely on other
available information such as those present in single and composite business cycle indicators,
either of quantitative or qualitative nature.
An alternative is to use the information present in the annual structural model and to explore
the main driving forces in that model and to verify which of the data among them are available
on a higher frequency. This is the approach we follow in this paper.
Yet another alternative would be to estimate real GDP equations using available high
frequency indicators which are not necessarily present in the structural models. Such
estimations may then be used to construct a business cycle indicator, but this a-theoretical
approach will be explored in a separate paper.
2. The Model
The supply side of an economy basically reflects the forces behind firms' production of goods
and services, their demand for factors of production, their price setting behaviour and the
structural characteristics of wage negotiations between employers and employees. Firms
produce goods and services on the basis of a well defined production technology, Michel, Aref
5 and Khalil (2011). This technology is assumed to be Cobb-Douglas. This implies that in the
long run the shares of both factors of production, capital and labour, in total income (value
added at factor cost) remain constant. This is a fairly reasonable assumption since it is not
realistic to assume that one of those shares would continuously increase or decline. Forces
would come into play to restore the normal shares of labour and capital incomes in the
economy's total value added.
On other hand, demand is driven by real income growth, which is itself sourced in the labour
productivity growth which originates in the supply environment of the economy. In a world of
perfect competition, prices would be solely determined by intersections of demand and supply
and the mark up would be zero. In most countries markets are basically characterised by
imperfect competition, more in particular by so called 'monopolistic competition'. Therefore
the demand for goods and services is mainly driven by the real income growth of all sectors in
the economy and by the price setting behaviour of profit maximizing firms. The main demand
components are consumption by households, private investment expenditures, government
expenditure, exports and imports.
These elements of the structural model can be integrated so as to obtain a reduced form model
in which real GDP is only a function of the main exogenous variables. A similar approach has
been applied by, among others, Kandil, Mirzaie (2003) and Bahmani-Oskooee, Kandil (2007).
Both papers used this kind of approach to analyze the effects of exchange rate fluctuation on
output and prices in developing countries. Zeng (2011) evaluates different approaches to
growth forecasts for Korea where the initial selection of the indicators is driven by economic
theory.
In the structural models developed for OPT the following main exogenous variables can be
found, which together with their available highest frequency and earliest start dates are
presented in table 1.
As to the external demand and supply shocks, special attention can be drawn to the links
between the economies of OPT and Israel:

Israel’s weight in OPT’s foreign demand variable (real GDP in OPT’s main export
markets, weighted by each country’s weight in OPT’s international trade) is very high;

A substantial proportion of the OPT labour force is employed in Israel,
6 
The daily average wage rate of employees employed in Israel is larger than wages in
local employment,

Israel has a very high weight in the calculation of OPT’s NEER, REER and CIM;
Table 1: Frequency and start data of main exogenous variables for real GDP in the OPT
Item
Model variable
name
Highest
frequency
Start
date
Source
Monthly
Monthly
1997M1
PMA
IMF
Annual
Annual
1996
1994
External price
Cost of imports
World food price index
CIM$
PWFPI
Fiscal
Grants and donations
Real Government investment
FTAID
RGI
External demand and supply
Number of closure days for trade
Real world GDP
Received private sector transfers from
abroad
NCDT
RWGDPAIMEX
GREMIT
Quarterly
Quarterly
Annual
2000Q4
2000Q1
1998
UNSCO
PMA
BOP
Employment in Israel and settlements
EIS
Quarterly
1996
PCBS
DDAWIS$
Quarterly
Daily average wage of Palestinian
workers in Israel and Settlements
PCBS
Financial market
Exchange rate index (USD/NIS)
US Federal Funds rate
MEXGRISINDEX
MFFRUS
Monthly
Monthly
1997M1
PMA
PMA
Quarterly
Monthly
Monthly
-
2000 Q1
PCBS
PCBS
PMA
PMA
Other needed
Real GDP
Consumer Price Index
Real Effective Exchange Rate
Deterministic trend and seasonal
dummy’s
RGDP
PCPIP$
REER
T, SD1, SD2, SD3
1997M1
-
Other potentially interesting indicators relating to domestic demand and supply shocks but
which are not included among the exogenous variables mentioned in table 1 are:

For fiscal shocks: Quarterly public employment, quarterly daily average wage in the
public sector;

Other: building licenses, especially the number of licenses of new buildings.
In what follows we will build a quarterly real GDP models for OPT based on the above
mentioned indicators that are found to have a significant impact on economic growth in OPT.
These models will then be used for generating a baseline forecast as well as a pessimistic and
7 optimistic scenarios. All candidate Relevant variables to be used in the analysis were found to
be integrated of order 1 (see table 2). Hence Augmented Dickey Fuller (ADF), and Phillips
Perron (PP) were used to test for the stationary of those variables.
Table 2: Unit root test *
Variables
Level
LCIM
1st difference
Level
LCIM$
1st difference
Level
LCPI
1st difference
Level
LDAWIS
1st difference
Level
LEIS
1st difference
Level
LNCDT
1st difference
Level
LNGS
1st difference
Level
LRDAWIS
1st difference
Level
LREER
1st difference
Level
LRGDP
1st difference
Level
LRGDPI
1st difference
Level
LWFP
1st difference
Level
LBL
1st difference
* Presented values represent the P-value.
ADF
0.1385
0.0010
0.0044
0.0008
0.8711
0.0002
0.7955
0.0000
0.7723
0.0000
0.1501
0.0000
0.7142
0.0000
0.6426
0.0001
0.9436
0.0002
0.9289
0.0000
0.9703
0.0000
0.8603
0.0000
0.0560
0.0000
PP
0.1929
0.0007
0.0245
0.0013
0.8591
0.0037
0.8190
0.0000
0.7059
0.0000
0.1670
0.0000
0.6397
0.0000
0.6522
0.0002
0.9436
0.0002
0.9724
0.0000
0.9980
0.0000
0.9528
0.0000
0.0500
0.0000
2.1
A truly exogenous model
In this kind of approaches, real quarterly GDP is modeled by using exogenous variables only.
As for quarterly GDP in the OPT, being a small open economy, the external environment is the
natural supplier of such exogenous variables on which the local policy makers or economic
agents have no control. As mentioned above, the external environment in OPT is very much
conditioned by political, as well as, economic developments and conditions in Israel. Our basic
reduced form model is therefore based on the variables shown in Figure 1 which shows a
likelihood of finding a co-integrating vector between these variables.
8 Figure 1: Index of Real GDP in OPT and the exogenous variable
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
RGDP Israel 2005=1
RGDP PT 2005=1
EYMPLOYMENT IN ISRAEL 2005=1
As can be seen from the above Figure, real GDP in OPT is much more volatile as compared to
Israel. This illustrates the numerous and severe shocks to which the OPT economy has been
exposed in the past. It is also clear that the period 2004 – 2005 was relatively prosperous
period in OPT, whereas part of 2006 up till early 2009 the ratio3 was under the period average.
Since then the growth rate of real GDP in OPT has outpaced that of Israel.
The annual real GDP growth rate showed obvious fluctuations during the period (2001 –
2011), the study period due to the political conditions that OPT lived under . This period, has
witnessed deep political, economic, social, and security developments, which still have direct
implications on the economic performance in general, and on living standards and welfare of
the Palestinian people.
After the relative stability and the start of recovery of the Palestinian economy in 2004,
following the negative economic implications in the previous period of re-occupation of West
Bank (WB) in 2002, the Palestinian economy deteriorated further in the wake of the legislative
and presidential elections in 2006. As a result of the elections outcome in favor of Hamas,
international aid stopped and Israel refused to transfer tax revenues to the Palestinian
Authority (PA), which led to a financial distress and the inability of the Palestinian
3
the ratio = RGDP index in OPT divided by RGDP index in Israel
9 government to pay salaries for more than 15 months. This political and financial siege
continued until the mid of 2007. Then came the Palestinian division after Hamas takeover of
Gaza in June 2007.
An emergency government was formed in Gaza Strip (GS), while a caretaker government was
instituted in the WB. This led to the lifting of the political and financial siege from WB and a
tightening of the siege in GS. Consequently the economic and social conditions deteriorated in
GS but improved in WB. In 2008, Israel waged a war on GS and inflicted substantial casualties
and material damage, thus worsening the economic and social conditions. With the
comprehensive and tightened siege on GS for years, the financial requirements on the
Palestinian economy to rebuild what was destroyed in the war and to address the serious
structural effects in the Gaza economy soared.
Then a period of relative stability in all political, economic, and security aspects, especially in
the WB, followed and a reform plan for the period (2008 – 2010) was developed. The plan led
to an improvement in the economic performance, particularly in the public finance and
spending rationalization, and the reduction of the budget deficit. In the WB, this was
accompanied by development of the infrastructure and an improved investment environment.
However, the plan did not achieve the desired objectives in GS because of the division and the
tightened Israeli siege and the almost complete prevention of the entrance of construction
material for reconstruction.
As result of all above circumstances the annual real GDP growth rate showed obvious
fluctuations during 2001 – 2011, but In general, the average annual real GDP growth rate
reached 4.3 percent during this period.
Following the theoretical ‘convergence hypothesis’, one would expect growth per capita to be
higher in OPT as compared to Israel which is already in a more advanced stage of economic
10 welfare as measured by the level of real income per capita. In other words, over the long run
we would expect a positive trend in the RGDP-ratio.
Figure 2: The estimated trend of the GDP ratio
1.15
1.1
1.05
1
0.95
0.9
0.85
0.8
0.75
RGDP ratio
Average
There is indeed a positive trend, which is not necessarily the result of a higher growth rate of
GDP per capita, but could also be the result of higher employment (population) growth. But
again, during end-2003 up till end of 2005, the ratio was significantly above trend and
conversely from mid-2006 till start of 2009. The estimation of the quarterly real GDP model
for OPT will have to take these structural breaks into account.
Figure 3: Actual and Fitted Real GDP index in OPT
1.2
1.1
1
0.9
0.8
0.7
0.6
Actual
Fitted
As a starting point, we estimated a long run equation for real GDP in OPT as a function of real
GDP in Israel and the number of OPT residents working in Israel (and settlements). The loglinear equation was estimated as:
11 Table 3 : OLS simple regression for real GDP in OPT (RGDP)
For the period 2001Q3 2011Q4
Variable
C
LRGDPI
LEIS
F-statistic
Durbin-Watson
Coefficent
-7.6753
1.0186
0.2287
0.867
135.6
0.634
Standard Error
1.4166
0.1921
0.0972
Prob.
0.0000
0.0000
0.0238
We tested this equation for the presence of structural breaks using Chow’s Breakpoint test.
As can be seen from table 4 the null hypothesis of no structural breaks during the periods
mentioned is rejected by all test statistics mentioned in the table.
Table 4: Chow’ Breakpoint test
Chow Breakpoint Test
2003Q4 2005Q4 2006Q3 2009Q1
Null Hypothesis
No breaks at specified breakpoints
Varying regressors
All equation variables
Equation Sample
F-statistic
Log likelihood ratio
Wald Statistic
2001Q3 2011Q4
10.804
73.843
129.64
Prob. F(12,27)
Prob. Chi-Square (12)
Prob. Chi-Square (12)
0.0000
0.0000
0.0000
Given these findings we estimated a dynamic equation which was derived from the ARDL
technique (see Khalil and Michel, 2011).
To determine the appropriate lag length (P), we estimated this conditional equilibrium
correction model (ECM ) by OLS for P = 1, 2, 3, 4, 5,6 over the period 2001Q3 to 2011Q4. Then
we tested the Akaike (AIC) and Schwarz Bayesian Information Criteria (SBC) for all lags.
These are statistics calculated in E-views which deviate from the formulas in PSS, although
both are essentially based on the log likelihood parameter.
12 Results show a small differences between these criteria underlying the choice of the lag order
of the dynamic equation, we have adopted a parsimonious approach and we will therefore
concentrate on the most simple (P = 1) model.
∆
7.749
∆
0.741
0.189 ∆
2006 3 2009 1
The error correction term
0.916
0.181
0.316 ∆
0.056 ∆
0.076
2003 4 2005 4
0.873
0.067
1 can be written as follows:
2 Where,
0.741,
0.916,
0.181
The long-run relationship between LRGDP and LRGDPI and LEIS can be written as follows:
1.29
0.244
3 Table 5: The equilibrium correction of ARDL (1,1,1) RGDP equation
Regressor
Coefficient
Standard Error
‐0.7408 0.1208 0.9164 0.1829 0.1813 0.0696 ∆
0.8727 0.3182 ∆
0.1894 0.0611 Intercept
‐7.7493 1.4174 Dum2006q32009q1
‐0.0674 0.0171 Dum2003q42005q4
0.0762 0.0182 0.5510
3.5214
3.1901 P-Value
0.0000 0.0000 0.0136 0.0097 0.0039 0.0000 0.0004 0.0002 2.2
A semi - reduced form equation
As an alternative to the approach discussed above, we will extend the analysis by including a
domestic indicator of economic activity. The variable that was found to be of particular
significance in explaining economic activity in OPT was the number of issued licenses for new
buildings. In many countries this is, found to be a reliable indicator to measure recent
13 developments in the building sector, which is known to generate multiplier effects on the rest
of the economy. Again we used the ARDL technique to test for a significant levels relationship
and to estimate the dynamics of the relationships between quarterly RGDP in OPT, RGDP in
Israel, number of Palestinian employees in IS and the number of licenses for new buildings in
OPT.
∆
7.958 0.826
0.962
0.639 ∆
0.127 ∆
2006 3 2009 1 0.0538
0.143
0.103
0.111 ∆
0.0406
2003 4 2005 4
4 3. GDP Forecasts and Scenario Analysis
We used the models explored above to generate a real GDP forecast for OPT for the period
2012 – 2013. The baseline forecast is based on the simple reduced form equation, taking into
account the most recent real GDP forecast for Israel produced by the BOI. BOI forecasts
RGDP in Israel to grow by 3.1% in 2012 and 3.5% in 2013. The result of the baseline forecast for
real quarterly GDP in OPT is shown in Figure 4. This forecasts implies an annual RGDP grow
by 6.1% in 2012 and 6.2% in 2013.
Figure 4: the Baseline forecast of quarterly real GDP in OPT
2000
Million US$
1800
1600
1400
1200
1000
800
600
RGDP
RGDPF
14 This baseline forecast does not include an explicit scenario for the activity in the building
sector (number of licenses for new buildings). We inverted the second equation reported
above to calculate the implied forecast for building licenses implied by the baseline forecast.
7.958
0.8258
0.0075
0.639 ∆
2006 3 2009 1 0.0538
01 / 0.1105
0.9617
0.1432
0.1275 ∆
0.111 ∆
2003 4 2005 4
5 0.0406
Figure 5 Shows that the baseline RGDP forecast implies slowing growth of construction
activity (BL_0). On the other hand building activity shows a strong upward trend since 2009.
Figure 5: Baseline forecast for building licenses
2000
1600
1200
800
400
0
Building licenses new builidings (estimate for 2008Q1)
BL_0
As an alternative (optimistic) scenario we have extrapolated this recent trend in building activity into
the future as shown in Figure 6. In this optimistic scenario real GDP in OPT would grow by 8.8% in
2012 and by 8.3% in 2013.
15 Figure 6: Forecast in different scenarios for quarterly real GDP in OPT
2500
2000
1500
1000
500
0
RGDP
Baseline
Optimistics
Pessimistics
As the OPT economy has been subjected to severe shocks due to the particular political
environment, a pessimistic scenario was designed that takes into account the kind of situation
prevailing in part of 2006 up till early 2009. We reactivated that dummy variable from the
second half of 2012 onwards. Under this pessimistic scenario, the OPT economy would grow
by 2.2% in 2012 and by 0.8% only in 2013. The latter figures indicate drastic drop in the
growth rate under the pessimist scenario versus the baseline scenario.
16 4. Conclusion
The objective of this paper was to design (semi) reduced form equations for quarterly RGDP
growth In OPT. This need was based on the observation that not sufficiently long time series
exist to build a structural quarterly model.
It was found that quarterly RGDP is very much driven by some of the exogenous variables
identified in the PMA’s annual structural models. Among these, the external environment was
found to play a dominating role. Besides external influences, quarterly RGDP growth is also
driven by construction of new buildings activity for which the issued new building licenses are
a reliable quarterly indicator.
These models have been used to produce out of sample quarterly RGDP forecasts over the
period 2012 – 2013. These point forecasts were accompanied by alternative optimistic and
pessimistic scenario’s.
17 References
Bahmani-Oskooee, M and Kandil, M, “Exchange Rate Fluctuations and Output in OilProducing Countries: The Case of Iran”, IMF, WP/07/113.
Kandil, M. and Mirzaie, I., “The Effects of Exchange Rate Fluctuations on Output and Prices:
Evidence from Developing Countries”, IMF, WP/03/2000.
Michel, D. Aref, M., and Khali, S., 2011, “Analysis of the Supply Side of the Palestinian Territory
Economy”, PMA.
Pesaran, H., Y. Shin, and R. Smith, 2001, “Bounds Testing Approaches to the Analysis of Level
Relationships”, Journal of Applied Econometrics, special issue in honour of J.Sargan on the
theme “studies in Empirical Macroeconometrics”, (eds.) D. Hendry and M. Pesaran, Vol.16.
Khalil, S., and Michel, D., 2011, “The Autoregressive Distributed lag Approach to Cointegration Testing: Application to OPT Inflation”, PMA.
Zeng, L., “Evaluating GDP Forecasting Models for Korea”, IMF, WP/11/53.
18