Economic ripple effects of biomass electricity power plants for earthquake
disaster reconstruction in the coastal area of Iwate prefecture
National Agriculture and Food research Organization KUNIMITSU, Yoji
Tohoku University NAKATA, Toshihiko
Rinergen Co. ltd. YOSHIMI, Masaharu
Abstract
East coast region in Iwate prefecture was seriously damaged by East Japan big earthquake in 2011, andrevitalization of this region is important issue in Japan. This study aims to estimate the input-output tablesof this region before and after the earthquake and to show impacts of earthquake and a revitalization
measure, i.e. construction of biogas electricity power plant, by using these tables. The results showed thefollowing features. First, value added production in 2011 became higher than previous year due torecovery construction investment, but both intermediate inputs and total production decreased. This
happens because ratio of value added production in construction sector was higher than other industries
that were seriously damaged by the earthquake. Second, investment demand increased in 2011 and 2012,
but intermediate inputs and private and public consumption decreased by earthquake. Order of influence
coefficients and sensitivity coefficients were not so changed by the earthquake, but increasing rate ofinduced production became low after the earthquake. Third, induced production of construction of thebiogas plant would be 0.73, if it was constructed before the earthquake. However, that value after theearthquake was 0.21, because industrial linkage was damaged. As compared to the conventional
electricity sector, biogas sector induced more production because import rate of this sector was 0 and mostinduced demand occurred within the region. Therefore, biogas electricity power plant can contribute torevitalization of regional economy, although electricity generation capacity was small.
Keywords: Input-output (I/O) analysis, induced production, induced labor, biogas electricity power plant
Economic ripple effects of biomass electricity power plants for earthquake disaster reconstruction in the
coastal area of Iwate prefecture

Economic ripple effects of biomass electricity power plants for earthquake
disaster reconstruction in the coastal area of Iwate prefecture
National Agriculture and Food research Organization KUNIMITSU, Yoji
Tohoku University NAKATA, Toshihiko
Rinergen Co. ltd. YOSHIMI, Masaharu
1. Introduction
Coastal area of Iwate Prefecture suffered fatal damage due to the tidal wave caused by East Japan big
earthquake in March, 2011. After that, reconstruction has been conducted with the support of government
and the cooperation of civic association. However, there are many people who still have to live in thetemporary house in this time which passed 4 years after the earthquake disaster. Some industries, such as
fishery, cannot reach the same level of production as before the earthquake disaster. After getting suchserious disaster, the policy makers try to build resilient country and community.
In addition to needs for recovery, the government tries to revitalize local economy, which faces aging
and decrease in population, by using local resources. The construction of biogas electricity power plant isplanned for such purpose. This plant is supposed to produce methane gas from food residues and generate
electricity with it in Ohfunato city located in the coastal area. This plant has also carbon neutral feature
which does not increase or decrease CO2 even after burning materials. However, this technology isexpensive and low efficiency as compared to usual power plants. In order to operate biogas power plant,
support from government is generally needed. For getting consensus of people on such support, economic
evaluation is important.
Urbanchuk (2009) analyzed the macro economic effects of bio-ethanol production by using the inputoutput (I/O) model; and showed that bio-ethanol production induced $32.5 billion of added value andcreated 110 thousands of employees in the USA in 2006. Polagye et al. (2009) showed profit from a bioethanol production factory in the USA. Hayashi (2009) analyzed Japanese E10 policy by using I/Oanalysis and pointed out that the economic benefit of bio-ethanol production can be positive in the near
future if the fossil oil price increases along with the recent trend. Kunimitsu and Ueda (2009) measured
the economic effects of bioenergy production in Thailand by using an I/O analysis. However, there were
few studies to evaluate macro-economic impacts and ripple effects of biogas production in local economy
as compared to environmental evaluations.
The present study aims to estimate the input-output tables of this region before and after theearthquake and to show impacts of earthquake and a revitalization measure, i.e. construction of biogas
electricity power plant, by using these tables. The features of this study are that recent I/O tables after theearthquake are estimated by the RAS method by using statistics on net town-person-income published by
prefectural government, (ii) impacts of the earthquake on industrial linkage are shown by analyzing
inverse matrixes of I/O tables, and (iii) ripple effects of construction and operation of biogas electricity
power plant are estimated by these I/O tables.

２．Methodology
2.1 Changes in industrial linkage by earthquake and introduction of biogas sector
Latest published regional I/O table in coastal region, Iwate prefecture was 2005, and it consists of 9
towns that are Miyako, Ohfunato, Rikuzentakada, Kmaishi, Ohzuchi, Yamada, Iwaizumi and Tanohata.
Industrial linkage was obviously changed by 2011 earthquake, so we estimated 2010, 2011 and 2012 I/O
tables by assuming as follows.
(i) Total regional demand (= intermediate production + final demand within region + export to otherregions and abroad) changed in accordance with net residents production of town in 2010, 2011 and2012 that is published by prefectural government.
(ii) Industrial linkage changed subject to the total regional demand, as the control total, with the leastchange from whole input coefficients. Under such assumption, new I/O data are estimated by the RAS
method which solves matrix balance problem.
(iii) The contents of value added production, i.e. "consumption expenditures outside households," "labor
income," "depreciation of capital stocks," and "tax - subsidies", are assumed to keep their share even after
total value added production is changed. So we calculate these values according to the initial share rate ofthem in 2005 I/O table.
(iv) The contents of final demand, i.e. "consumption expenditures outside households," "household
consumption," "public consumption," "public investment," "private investment," and "inventory
investment", are also assumed to keep their share rate within total final demand even after total regional
demand is changed. So we calculate these values as the same way as (iii).
(v) For initial settings, column-wise input coefficients and total regional production of biogas sector are
based on the plant design of the operation costs. Row-wise input coefficients of biogas sector are the sameas electricity generation sector and total regional demand of this sector corresponds to the total regional
production. Total regional demand and total regional production of biogas sector are subtracted from thetotal of electricity generation sector. After these settings, the RAS method is applied to balance columnwise and row-wise totals.
2.2 Estimation method for induced production
Induced production by an increase in construction investment and final demand for biogas
products are calculated as follows.
X  I  ( I  M ) A  1 F(1),where X is total production vector (size is 35x1), I is the unit matrix, M is import coefficientmatrix from both other regions and abroad that is defined as ( M / (AX  F  E) ) (35x1), A is input
coefficient matrix (35x35), F is final demand vector (35x1), and E is export matrix (1x35).
Eq. (1) calculates only backward linkage effects via derived demand diffusion, so called
Leontief multiplier. Forward linkage effects caused by an increase in wage income andconsumption of household can be calculated as follows (Miyazawa, 2002).

X '  B C K V B F X  B C K FY

Thiseffects

are

so

(2)

called Keynesian

multiplier.

Here,

B  (I  A  m ) 1

andK  I  V B C  1 . C is average propensity to consume vector (35x1), V is a matrix (35x1) consists of

the rates to the total production of the wage income in each industry, FX is final demand vector (35x1)
regarding to material demand, and FY is final demand regarding to final demand change (1x1).
３．Results
3.1 Estimation results on I/O table
Fig.1 shows net residents production of town published by Iwate prefectural government.
As shown in this table, net income increased even incident year, 2011, when earthquake
happened. It is because of an increase in construction for recovery. However, other industries,
such as fishery, manufacturing and service sector, decreased income due to a demolition ofcapital stocks.

Fig. 2 shows estimation results of intermediate inputs and value added production in eachyear. These values were estimated by applying the RAS method.
Even though value added production in 2011 became higher than previous year due to theearthquake, intermediate inputs and total production were both lower than former year. This
happened because ratio of value added production in construction sector was higher than otherindustries that were seriously damaged by the earthquake.
Fig.3 shows chronological changes in final demand by contents. Final demand in 2011 thatconsists of consumption and investment was larger than previous year because of an increasein value added production. Private and public consumption were both decreased but public andprivate investments were increased due to recovery investment for damaged capital stocks
under earthquake. Investment in 2012 was also much higher than before earthquake. Imports
and exports decreased in 2011, and these components recovered afterward. This is owing torecovery construction work continuing even after 2011.
Fig. 2 Chronological change in cost components

Fig. 3 Chronological change in final demand

900

600
500

billion yen

10 billion yen

800
700
600

400
300
200

500

100

400

0

300
Intermediate inputs
2005

Gross value added production

2010

2011

2012

2005

2010

2011

2012

3.2 Changes in industrial linkage structure
Fig. 6 shows summation of elements in the inverse matrix, which shows total effects of
induced production caused by an increase in final demand. Those numbers are decreased in2011 when earthquake happened, but after that year, total effects of induced production
increased and reached to the higher level than before the earthquake. Especially, when biogas
power plant was installed in 2012, that coefficient became the highest. In this sense, newinvestment relating to electricity sector can stimulate domestic economy by switching demandof imports to domestic production.
Fig. 6 Sum of invers matrix
48
47
46
45
44
43
42
41
40
39
38
2005

2009

2010

2011

2012

2012BG

3.3 Induced production of biogas power plant
Table 3 shows contents of input cost for construction of the plant. Table 4 is about running costs during
operation of this plant. These values were used for simulation shown in the latter part.
Table 5 is the induced production and labor which were increased by construction of the biogas
electricity power plant. For estimation of induced production, investment for the plant was assumed to be
conducted in two ways, i.e. construction in 2010 before earthquake and construction in 2011 afterearthquake. Each induced production was calculated by using each I/O table and inverse matrix. Since
import rate to other regions and abroad was high and hence leakage of effects was large in this region,
induced multiplier (=induced production / investment) was 0,73 and lower than 1. If induced multipliersin 2010 and 2011 were compared, latter one (0.21) was much lower than former (0.73). This happened
because of the damage in industrial linkage in this economy by earthquake. In this sense, effects ofrecovery investment become lower than investment in the normal time, even if investment amount was
the same.
Table 3. Cost components for construction
Table 4. Operational cost for biogas electricity(thousands yen)generation of biogas electricity power plant

Input sectors
Ceramic
Metal
General machineElectronic machine
Construction
Transportation
Business srvice
Subtotal
Value added
Total production(thousands yen)
Inputs amount for
construction of thebiogas plant
20,00011,000225,000
70,000230,000
10,00040,000606,000
0
606,000

Input sectors
Gneral machineElectronic machine
Construction
Electricity, Gas, Heat s
Water, Recicle
Finance
Transportation
Communication
Business service
Office supplies
SubtoalWage
Capital depreciation
Value added
Total production

Operation stage
13,500
7,000
500
2,500
16,000
360
5,100
120
120
120
45,32016,96035,65052,61097,930

Table 5 Induced production and labors by construction of biogas electricity plant
Constraction Investment Induced production
year
a
b
b/a
2010
606
444
0.73
2011
606
126
0.21

(million yen, person)
Induced labors
c
c/a
37
0.061
14
0.024

Table 6 Induced production and labors by annual operation of biogas electricity plant
Sectors
Electricity, Gas, Heat supply
Biogas Electricity
OthersTotal(million yen, person)
Operation Induced Net increase
cost
production
in labors
-98
-20
-0.53
98
98
2.59
0
19
0.75
0
97
2.81

Table 6 shows the induced production and labor at the stage of operation after constructionof the plant. In this estimation, we set 98 million yen as an increase in final demand of biogas
sector but at the same time -98 million yen for conventional electricity generation sector. Total

increase in final demand in whole economy was 0, but induced process was different for both
sectors. As compared to the conventional electricity sector, biogas sector induced moreproduction because import rate of this sector was 0 and most induced demand occurred within
the region. Induced labors were 2.8 person per year, and this is pure increase in this reason.
Hence, biogas electricity power plant is effective for revitalization of regional economy.
４．Summary and conclusion
This study aims to estimate the input-output tables of this region before and after the earthquake andto show impacts of earthquake and a revitalization measure, i.e. construction of biogas electricity power
plant, by using these tables. The results showed the following features.
First, value added production in 2011 became higher than previous year due to recovery construction
investment, but both intermediate inputs and total production decreased. This happens because ratio ofvalue added production in construction sector was higher than other industries that were seriously
damaged by the earthquake. Second, investment demand increased in 2011 and 2012, but intermediate
inputs and private and public consumption decreased by earthquake. Order of influence coefficients andsensitivity coefficients were not so changed by the earthquake, but increasing rate of induced production
became low after the earthquake. Third, induced production of construction of the biogas plant would be
0.73, if it was constructed before the earthquake. However, that value after the earthquake was 0.21,
because industrial linkage was damaged. As compared to the conventional electricity sector, biogas sector
induced more production because import rate of this sector was 0 and most induced demand occurred
within the region. Therefore, biogas electricity power plant can contribute to revitalization of regional
economy, although electricity generation capacity was small.
There are many remained issues in this study. Estimated I/O table should be secured by comparing
actual data survey or official published table that will be published in the future. We need to consider otherinvestment rather than biogas electricity power plant in order to revitalize regional economy.