U N I V E R S I T Y O F T H E P H I L I P P I N E S

SCHOOL OF STATISTICSw w w . s t a t . u p d . e d u . p h

The Effect of Diesel Excise Tax on Inflation and Poverty: Evidence from Econometric Analysis

Dr. Dennis S. Mapa BSP Sterling Professor of Government and Official Statistics

Dean and ProfessorSchool of Statistics

University of the Philippines Diliman

Outline of the Presentation

Motivation and Objectives of the Study

Overview of the Tax Reform for Acceleration and Inclusion (TRAIN)

Proposed Diesel Excise Tax

Data Description and Variables (Headline Inflation and Inflation of the

Poorest 30% of Households)

Econometric Models (ARDL and VAR)

Discussion of Results

Conclusion and Policy Recommendation

Motivation of the Study

To achieve a simpler, fairer and efficient tax system, the government is

pushing for the Tax Reform for Acceleration and Inclusion (TRAIN) as a

critical component of the Philippine Development Plan 2017-2022;

One of the contentious issues is the proposed Excise Tax on diesel fuel;

4 laws enacted relative to excise taxation of petroleum products since

1987 to 2017, the most recent 2005 (RA 9337), removed the excise tax on

diesel fuel.

Figure 1. First Half of 2016 Production / Demand Mix

Source: Department of Energy

Motivation of the Study

Being a widely-used and important commodity, significant increases in

diesel prices (due to the excise tax) would affect people (income groups:

POOR and NON-POOR) in the country.

Increase in fuel prices have negative effect in the welfare of people, hence

it is vital to identify which income group would actually carry the tax

burden before implementing any tax [Son (2008), Reyes et al (2009),

Mapa, Han and Estrada (2011), Nicolson et al (2003) and Coady, Flamini

& Sears (2015)].

Objectives of the Study

Using econometric models (ARDL and VAR), this study will estimate the

effect of the diesel fuel excise tax on inflation rate;

Measure the effect of the proposed diesel excise tax on the poor and non-

poor households and identify which among the two carries the burden of the

excise tax;

Estimate of the effect of the diesel excise tax on poverty;

Highlight the use of the inflation rate of the poorest 30 percent of

households in research and policy discussion.

• The House Bill (HB) No. 4774,

also known as the Tax Reform

for Acceleration and Inclusion,

amends certain sections of the

National Internal Revenue Code

of 1997

• Introduced by Rep. Dakila Carlo

E. Cua of the Lone District of

Quirino at the 17th Congress -

First Regular Session

Overview of the Tax Reform for Acceleration and Inclusion (TRAIN)

Under the new tax reform proposal, all petroleum products will have (additional)

excise taxes.

Comparison between the Existing vs. the Proposed Excise Tax on Diesel Fuel

(House and Senate Versions)

Proposed Tax Rate

Product Type Existing Tax Rate

1st Year

(2018)

2nd Year

(2019)

3rd Year

(2020)

Diesel Fuel Oil and other similar fuel oil

products 0.00 3.00 5.00 6.00

(House Version)

Diesel Fuel Oil and other similar fuel oil

products 0.00 1.75 3.75 6.00

(Senate Version)

The net gain from the proposed tax reform would be allocated

for the social protection programs of the government (e.g.

cash transfers);

The comprehensive tax reform package shall also augment

the needed infrastructure investments to transform the

country into a high-income economy by 2040 (Ambisyon Natin

2040);

Overview of the Tax Reform for Acceleration and Inclusion (TRAIN)

Weight in the Consumption Basket (in Percent)

Particular Items

All households

(Base: 2006)

All households

(Base: 2000)

Poorest 30 Percent

(Base: 2000)

FOOD 36.00 46.60 70.00

a. Rice 9.00 9.36 23.00

FUEL 2.55 2.35 5.10

Transportation and

Communications 7.81 7.52 3.22

Headline (all households) and Poorest 30% HHs Consumer Price Index

-4

0

4

8

12

16

20

24

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Poorest 30%

All Households (Headline)

Headline Inflation Rate (all Households) and Inflation Rate of the Poorest 30%

(January 2007 to March 2017)

Headline Inflation

Inflation of the Poorest 30%

Mean 3.72 4.67

Max 10.50 20.31

SD 2.01 4.02

N 123 123

2.8

3.2

3.6

4.0

4.4

3.0

3.2

3.4

3.6

3.8

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

LOG(DIESEL) LOG(RICE)

Prices of Rice (Regular Milled; Php/kg) and Diesel (Php/liter)

(January 2007 to March 2017; in Natural Logarithm)

Variable Name DF-GLS Test Statistic

(Elliott, Rothenberg, Stock)

p-value Remarks

Headline Inflation -4.00 < 0.01 Stationary; I(0)

Inflation of the Poorest 30% -3.74 <0.01 Stationary; I(0)

Price of Rice (in Natural Log) 0.30 >0.10 Non-Stationary; I(1)

Price of Diesel (in Natural Log) -2.22 >0.01 Non-Stationary; I(1)

Results: Tests for Presence of Unit Roots (DF-GLS; ERS)

The econometric models used in analyzing the incidence of a diesel excise tax are the

Auto-Regressive Distributed Lag (ARDL) Models. Consider the ARDL(p,q) models:

Econometric Model (ARDL)

• Next, the study compares the total marginal effect of diesel fuel obtained

from estimating Models (1) and (2). The marginal effects are multiplied to

the ratio of the excise tax to a base price of diesel. Hence, the marginal

effect of diesel tax, is simply:

1. Total Marginal Effect of Diesel Fuel Price to Inflation Rate

2. Marginal Effect of Diesel Fuel Excise Tax

Steps in Determining Tax Burden:

We select Php 30.00 as base price for convenience of interpretation since the

proposed excise tax for diesel are Php 3.00 and Php 6.00 in the first and third

years upon implementation.

For the analysis on household characteristics, this study uses the Family Income &

Expenditure Survey (FIES) 2015 from the PSA.

For the econometric models, the study used the following data:

• log(diesel price) - Department of Energy (DOE)

• log(rice price) - Philippine Statistics Authority (PSA)

• headline inflation rate - Philippine Statistics Authority (PSA)

Model 1

Explanatory Variables

Dependent Variable

• log(diesel price) - Department of Energy (DOE)

• log(rice price) - Philippine Statistics Authority (PSA)

• poorest 30 % inflation rate - Philippine Statistics Authority (PSA)

Model 2

Explanatory Variables

Dependent Variable

Figure 2. Monthly Headline Inflation Rate, Rice

Price and Diesel Price in the Philippines from

Jan 2006 to March 2017

Figure 3. Quarterly Poorest 30% Inflation Rate,

Rice Price and Diesel Price in the Philippines

from Jan 2006 to March 2017

2.8

3.2

3.6

4.0

4.4

0

2

4

6

8

10

12

06 07 08 09 10 11 12 13 14 15 16 17

LOG(DIESEL)

LOG(RICE)

Headline Inflation

Headline Inflation, Rice Price (in Natural Logarithm) and

Diesel Price (in Natural Logarithm) January 2006 to March 2017

3.0

3.2

3.4

3.6

3.8

4.0

0

5

10

15

20

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

LOG(RICE) LOG(DIESEL) PINF

Inflation of the Poorest 30%, Price of Rice (in Natural Logarithm)

and Price of Diesel (in Natural Logarithm) from 1st Quarter 2006 to 1st Quarter 2017

1. Effect of Diesel Price on the Inflation Rates of the Poor & Non-Poor

Table 3. Regression Estimation Results on Monthly Headline Inflation Rate

Table 4. Regression Estimation Results on Quarterly Poorest 30 Percent Inflation Rate

Non-Poor

Poor

Total Marginal Effect of

Diesel Price

= 0.09 ppt.

Total Marginal Effect of

Diesel Price

= 0.009 ppt.

Variable Coefficient Std. Error t-Statistic Prob.

Constant 0.555 0.446 1.245 0.223

Rice (in DLOG) 0.270 0.102 2.648 0.013

Diesel (in DLOG; lag 1) 0.040 0.016 2.476 0.019

Inflation (lag 1) 0.776 0.068 11.369 0.000

Diesel (in DLOG; lag 2) 0.051 0.015 3.446 0.002

Rice (in DLOG; lag 1) 0.143 0.050 2.859 0.008

Variable Coefficient Std. Error t-Statistic Prob.

Constant 0.096 0.063 1.524 0.130

Inflation (lag 1) 0.970 0.078 12.370 0.000

Inflation (lag 2) -0.465 0.074 -6.268 0.000

Rice (in DLOG) 0.055 0.012 4.703 0.000

Diesel (in DLOG) 0.009 0.005 1.931 0.056

Rice (in DLOG; lag 12) -0.040 0.746 -5.409 0.000

2. Simulation of the Proposed Excise Tax on Diesel Fuel:

The study simulates the effect of diesel tax on the non-poor and poor’s

inflation rates across different specific value using a diesel base price of

Php 30.00 per liter

Effect of the Tax Rates on the Inflation Rates of the Non-poor and Poor

Welfare Effect of the Proposed Excise Tax on Diesel Fuel

Using the Family Income and Expenditure Survey (FIES) 2015, this study

estimated the effect of the tax rates on the households as measured by

the new number of households pushed into poverty by the increase in

diesel price (in Php). We use the following formulas for the estimation:

As of 2015, a family of five needed at least Php 9,064, on average, every

month to meet both basic food and non-food needs. This amount represents

the poverty threshold (PSA).

where

= Poverty threshold for 2015

= Marginal effect of diesel fuel excise tax on the

inflation rate of the poor

1. Adjusted Poverty Threshold

2. Percentage Increase in No. of Poor HH

where

= total no. of households below the adjusted poverty threshold

= total no. of households below the 2015 poverty

threshold from PSA

= total number of households

Note: the study used the FIES 2015

Estimated Additional Number of Poor HHs

where

= total number of households in the Philippines

PSA reported that the total no. of HH in the Philippines as of 2015

is 22.98 Million

= percentage increase in the no. of poor HH

Estimated Increase in the No. of Poor Households from

the Proposed Diesel Fuel Excise Tax

Welfare Effect of the Proposed Excise Tax on Diesel Fuel

Vector AutoRegressive (VAR) Model

We can generalized the mathematical representation of a VAR model as:

where yt is a (k x 1) vector of endogenous variables, A1, A2,…, Ap are

matrices of coefficients to be estimated, and et is a (k x 1) vector of

innovations that may be contemporaneously correlated but are uncorrelated

with their own lagged values and uncorrelated with all of the right-hand side

variables. et is assumed to be normally distributed with mean 0 and

covariance matrix Σ.

tptpttteyAyAyAy

...

2211

Econometric Model (VAR Estimates)PINF DLOG(RICE) DLOG(DIESEL)

PINF(-1) 1.10 0.01 -0.02

(0.20) (0.01) (0.02)

[ 5.61373] [ 1.14934] [-0.92652]

PINF(-2) -0.38 -0.01 0.00

(0.18) (0.01) (0.02)

[-2.11177] [-0.96806] [ 0.18254]

DLOG(RICE(-1)) 9.38 -0.06 1.28

(7.26) (0.22) (0.63)

[ 1.29225] [-0.26189] [ 2.02694]

DLOG(RICE(-2)) -1.86 -0.48 -0.31

(7.07) (0.21) (0.62)

[-0.26286] [-2.28196] [-0.49626]

DLOG(DIESEL(-1)) 1.95 0.00 -0.24

-2.1434 (0.06) (0.19)

[ 0.91201] [-0.07556] [-1.28755]

DLOG(DIESEL(-2)) 3.52 0.02 0.00

(2.12) (0.06) (0.18)

[ 1.66352] [ 0.32909] [-0.02403]

C 1.30 0.01 0.04

(0.53) (0.02) (0.05)

[ 2.44066] [ 0.88874] [ 0.86837]

R-squared 0.813282 0.183236 0.237893

Adj. R-squared 0.775939 0.019884 0.085472

Quarter S.E. Poorest Inf DLOG(RICE) DLOG(DIESEL)

1 1.96 45.96 53.94 0.09

2 3.32 35.45 63.12 1.43

3 4.15 30.06 64.24 5.71

4 4.44 28.18 63.87 7.95

5 4.49 27.72 63.22 9.06

6 4.50 27.70 63.07 9.23

7 4.52 27.76 63.09 9.15

8 4.54 27.73 63.12 9.15

9 4.55 27.67 63.13 9.20

10 4.55 27.65 63.11 9.24

11 4.55 27.65 63.10 9.25

12 4.55 27.65 63.10 9.25

Variance Decomposition

Cholesky Ordering: DLOG(RICE) DLOG(DIESEL) PINF

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

1 2 3 4 5 6 7 8 9 10 11 12

POINT LOWER UPPER

Impulses Response Function (IRF): Response of Poorest Inflation to Shock in DLOG(DIESEL)

Period DLOG(DIESEL) t-stat (diesel)

1 0.06 0.27

2 0.39 0.90

3 0.91 1.45

4 0.77 1.26

5 0.51 1.08

6 0.20 0.65

7 -0.02 -0.09

8 -0.13 -0.53

9 -0.14 -0.67

10 -0.10 -0.67

11 -0.05 -0.51

12 -0.01 -0.10

Impulse Response Function (IRF): Response of

Poorest Inflation to a Shock on DLOG(DIESEL)

Cholesky Ordering: DLOG(RICE) DLOG(DIESEL) PINF

A Php 3.00 excise tax on diesel (in Php) per liter would cause inflation rates for the

poor and non-poor to increase by about 0.897 and 0.090 percentage points,

respectively; a Php 6.00 per liter tax on diesel, the effect on the inflation rate of the

poor becomes (approximately) ten times more than the effect on the inflation rate of the

non-poor (1.794 ppt and 0.180 ppt, respectively);

When the tax is implemented, the estimated additional number of poor households due

to Php 6.00 tax rate is 0.205 million households (0.89 percent), This translate to more

than a million individuals.

Conclusions

The government could undertake mitigation measures as a signal that

they will protect poor and non-poor (but near poor) households from

the negative effect of the price shocks. Currently, the proposal is a cash-

transfer of Php 200.00 per month (or Php 2,400.00 per year) for one

year. Is this enough?

The Philippine Statistics Authority (PSA) must update and regularly

report the inflation rate of the poorest 30 percent of households to

provide the appropriate information to the policymakers.

Policy Recommendations

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