Vital Statistics: Up, Up, Down, Down

Last week, the National Statistical Coordination Board came out with the analysis report, "GDP, GDP, GDP: Who’s the FAREst ofthem all?" The article compares the economic performance of the five presidents of the country's Fifth Republic.

NSCB, my current employer, said that among the post-martial law presidents, President Benigno Aquino III (N. Aquino) got the highest GDP growth rate in his first year in office with 5.4% while former President Estrada got the lowest with 0.1%. Aquino also got the highest GDP growth rate in his second year of service with 4.9%, while Ramos got the lowest with 3.4%.

The article used the average annualized growth rate, a measure of central tendency, to compare the economic performance of each administration. While it is enlightening to parallel the average growth rates of each regime, I believe that it is equally important to consider another barometer of performance, which is stability.

How can we measure stability and why is this important? Businesses, and ordinary people for that matter, would want to be situated in a stable environment. Having a turbulent economy makes it impossible to look forward and forecast. How could a retailer project revenues if the economy keeps on swinging from a 10% surge one quarter to a 2% slowdown the next, to a 4% rebound the quarter after that. It would make forecasting a pain. If a company cannot forecast its sales, it cannot forecast its profits, and if it cannot project its profits, it would have a difficulty time deciding how much capital to invest.

The lack of stability creates a risky environment for businesses and investors, and we were taught in Economics 101 that we need investments to create jobs and raise the income of the average citizen.

Economists often use the measures of dispersion, the standard deviation and the variance are two of the most popular ones, to estimate risk and ultimately evaluate stability.

If you have a strong foundation in mathematics, statistics or economics, you may skip this part and move on to the next paragraph, but for those of you who don't, carry on. The measures of dispersion would give us a summary on spread of the data in a given set. It gives us a sense on how distant the observations are from one other. When the value of the measures of dispersion is high, then it is likely that observations in your data set are really distant from each other. For example, data set A (8, 56, 16, 6, 105, 2) would have a standard deviation* of 43, compare it to the data set B (1, 2, 2, 1, 5), which would have a standard deviation of 2. Notice how far way the values of each observations in set A are and how that resulted into set A having a significantly higher standard deviation compared to set B.

I've taken the liberty of computing for the standard deviation of annual GDP growth rates of the Corry Aquino (C. Aquino), Ramos, Estrada, and Arryo administrations. I felt that it was unfair to include the performance of the N. Aquino administration in the analysis since his term is still on-going. One may argue that the same consideration must be given with Estrada's, since his time in office was cut short by the revolt which launched Arroyo into power,. However, I believe that there is credit in including Estrada's administration in the analysis since his term has ended and the data needed to evaluate the overall stability of his entire regime is already complete.

Cory
INDUSTRY	Agri., Hunting, Forestry & Fishing	Industry Sector	Service Sector		GDP		GNI
85-86	3.7	2.3	4.2		3.4		4.1
86-87	3.1	3.9	5.1		4.3		6.7
87-88	3	8.4	6.9		6.8		8
88-89	2.7	7.1	6.7		6.2		6.2
89-90	0.20	2.30	4.60		3.00		7.90
90-91	1.5	-2.6	0.2		-0.6		2.2
91-92	0.4	-0.6	1		0.3		3.6
standard dev	1.39	3.92	2.60		2.77		2.25
Ramos
INDUSTRY	Agri., Hunting, Forestry & Fishing	Industry Sector	Service Sector		GDP		GNI
91-92	0.4	-0.6	1		0.3		3.6
92-93	2.1	1.6	2.5		2.1		3.8
93-94	2.5	5.6	4.1		4.4		5
94-95	0.6	6.4	4.7		4.7		5.2
95-96	3.70	6.30	6.20		5.80		9.40
96-97	2.9	6	5.3		5.2		5.4
97-98	-7	-2.7	2.8		-0.6		1.9
standard dev	3.62	3.77	1.80		2.53		2.33
Erap
INDUSTRY	Agri., Hunting, Forestry & Fishing	Industry Sector	Service Sector		GDP		GNI
97-98	-7	-2.7	2.8		-0.6		1.9
98-99	9.6	-1.5	4.5		3.1		2.7
99-00	3.4	6.5	3.3		4.4		7.7
00-01	3.4	1	4		2.9		3.6
standard dev	6.88	4.09	0.75		2.14		2.58
GMA
INDUSTRY	Agri., Hunting, Forestry & Fishing	Industry Sector	Service Sector		GDP		GNI
00-01	3.4	1	4		2.9		3.6
01-02	3.3	2.9	4.2		3.6		4.1
02-03	4.7	4.3	5.5		5		8.5
03-04	4.3	5.2	8.3		6.7		7.1
04-05	2.20	4.20	5.80		4.80		7.00
05-06	3.6	4.6	6		5.2		5
06-07	4.7	5.8	7.6		6.6		6.2
07-08	3.20	4.80	4.00		4.20		5.00
08-09	-0.7	-1.9	3.4		1.1		6.1
09-10	-0.2	11.6	7.2		7.6		8.2
standard dev	1.90	3.46	1.70		1.94		1.66

Based on the estimates, it is during the regime of former President Arroyo when the country experienced the least variability in terms of GDP fluctuation. The standard deviation of the GDP growth rates of the president, who is now facing criminal charges for corruption, was at 1.9, substantially lower compared to the standard deviation of the growth rates during the time of Estrada (2.13), Ramos (2.5), and C. Aquino (2.77). This means that despite the roller coaster boom and bust the country experienced during Arroyo's regime (GDP growth peaked growing at 6.6% in 2004, then it suddenly dropped to 1.1% two years later due to the Wallstreet Meltdown), the economy was still at its most stable.

I also thought that it would be interesting to find out which administration was most stable in the first 10 quarters of their terms. This is the most objective way, I believe, we can compare the stability of the N. Aquino administration with the administration of his predecessors. I computed for the standard deviation the growth rates of all five presidents in the first 10 quarter of their terms.

According to the estimates, the Arroyo regime still has the smallest standard deviation, at 0.99, suggesting that the economy during her first two years in office was still the most stable. The standard deviation for N. Aquino's regime only came in second, at 1.5. The standard deviation for C. Aquino, Ramos, and Estrada were estimated at 2.28, 1.9, and 2.6, respectively.

After giving it a lot of thought, I'm inclined to believe that the level of standard deviation in the first 10 quarters of the Arroyo rule may not necessarily be the result of her administration's policies. Normally, the first few quarters of a government regime would start from a high base because the previous year would be an election year. Election spending often fuels the economy. A slowdown usually follows an election year since the political spending would come to a stop by then. This is called the high-base effect. The sharp slowdown would reasonably result to a high discrepancy between the GDP growth of the first and second year in office, ultimately causing the standard deviation to be higher.

In Arroyo's case, there was no election prior to the start of her term. She was put to office by a popular revolt. There would be no base-effect to cause a discrepancy in the growth rates in the first two years of her term. Standard deviation would be moderate.

Cory
INDUSTRY		Agri., Hunting, Forestry and Fishing	Industry Sector	Service Sector		GDP		GNI
1985-1986	Q1	1.7	-1.7	0.5		-0.1		3.4
	Q2	3.2	2.3	2.9		2.8		-0.3
	Q3	7.8	7.1	8.1		7.7		12.4
	Q4	3.2	1.5	5.2		3.6		2.2
1986-1987	Q1	2.4	-0.6	6.3		3.1		3.4
	Q2	4.4	1.2	5.2		3.6		3.9
	Q3	3.7	11.8	3.7		6.7		13.5
	Q4	2	3.1	5.2		3.9		6.3
1987-1988	Q1	0.2	9.8	5.3		6		10.5
	Q2	-5.5	1.4	6.1		2.4		5.2
Standard Dev		3.40	4.48	2.08		2.28		4.60
Ramos
INDUSTRY		Agri., Hunting, Forestry & Fishing	Industry Sector	Service Sector		GDP		GNI
1991-1992	Q3	-1.7	1	0.5		0.4		7.4
	Q4	3.4	-5.8	1.4		-0.8		0.1
1992-1993	Q1	5	-3.2	2		0.7		2
	Q2	2.8	2.7	2.4		2.5		7.5
	Q3	-1.8	4	2.9		2.7		2
	Q4	1.7	3	2.6		2.5		3.6
1993-1994	Q1	-1.1	6.1	3.7		3.6		3.9
	Q2	5.9	4.5	4.4		4.6		4.3
	Q3	10.2	4.1	4.5		5.1		6.7
	Q4	-1.6	7.7	3.9		4.2		5
Standard Dev		4.00	4.12	1.31		1.94		2.47
Erap
NDUSTRY		Agri., Hunting, Forestry and Fishing	Industry Sector	Service Sector		GDP		GNI
1997-1998	Q3	-1.3	-3	3		0.2		2.3
	Q4	-8	-6.4	0.8		-3.1		0.1
1998-1999	Q1	6.3	-6	3.5		0.5		0.8
	Q2	12.8	-2.2	4.4		3.1		3.1
	Q3	8.9	0.3	4.7		3.6		2.3
	Q4	10.8	1.7	5.3		4.9		4.4
1999-2000	Q1	-0.4	7.7	3.2		4.1		6.8
	Q2	3.3	5.7	3.9		4.4		7
	Q3	6.7	7.5	3.9		5.5		8.5
	Q4	4.3	5.5	2.4		3.7		8.3
Standard Dev		6.25	5.38	1.28		2.67		3.10
GMA
INDUSTRY		Agri., Hunting, Forestry and Fishing	Industry Sector	Service Sector		GDP		GNI
2000-2001	Q3	2.9	0.8	4		2.7		4.2
	Q4	4.2	0.9	4.7		3.3		1.8
2001-2002	Q1	6	1.2	3.7		3.2		4.9
	Q2	0.5	5	4.2		4		2.8
	Q3	0.4	1.8	3.8		2.7		2.1
	Q4	5.5	3.5	5.1		4.6		6.6
2002-2003	Q1	4.1	4.5	5.1		4.8		7.9
	Q2	1.6	4.5	5.8		4.8		9.1
	Q3	6.4	4.7	5.4		5.3		9.7
	Q4	6.1	3.4	5.7		5		7.3
Standard Dev		2.31	1.69	0.78		0.99		2.89
PNoy
Industry		Agri., Hunting, Forestry & Fishing	Industry Sector	Service Sector		GDP		GNI
2009-2010	Q3	-2	9.8	7.8		7.3		6.9
	Q4	4.1	6.5	6.4		6.1		5.6
2010-2011	Q1	4.4	7.3	3.6		4.9		3.5
	Q2	8.3	-1.4	5.6		3.6		2.4
	Q3	2.2	0.1	5.2		3.2		2.2
	Q4	-2.5	3.4	5.9		4		4.5
2011-2012	Q1	1	5.3	8.1		6.3		5.1
	Q2	0.6	5.5	7.4		6		5.7
	Q3	4.1	8.1	7		7.1		6.6
	Q4	4.7	7.5	6.9		6.8		5.4
Standard Dev		3.3	3.6	1.4		1.5		1.6

My goal in writing this blog entry is to provide addition insight and supplement the information provided by NSCB. I admit that there are weaknesses the methodology used.  As the NSCB article said, "some analysts suggest that the changes in GDP mirror how Philippine presidents and their economic managers manage our economy. Of course, other analysts would think that this may be far too simplistic given that the starting conditions and other factors, including the external environment, were not the same across the periods of these Presidents." However, I believe that my analysis would somehow contribute to the on-going discourse on public policy and macroeconomic trends.

*the formula for the standard deviation is as follows:

Data Source: National Statistical Coordination Board