COVER STORY • 9Current Status & Future of
Statistical Reform – Utilization of
Real-Time Data & Alternative Data
AuthorNariyasu Yamasawa

By Nariyasu Yamasawa

Foreword
Enhanced statistics are important in the promotion of EvidenceBased Policy Making (EBPM). Fiscal 2022 is the fifth year of theperiod covered in the “Master Plan Concerning the Development of
Official Statistics”. In the meantime, an inadequate statistical process
was discovered in the Monthly Labour Survey and the Construction
Orders Survey, and mistrust of statistics has yet to be resolved.
However, statistical reform is making steady but sure progress, andthe “Economic Conditions Survey” was conceived as one outcome.
On the other hand, the spread of the Covid-19 pandemic has had ahuge impact on society, and has completely changed the scenery ofdata analysis. This article describes the progress of the two efforts
on real-time database and alternative data.

Creation of “Economic Conditions Survey”
In 2017, the “Statistical Reform Promotion Council” wasestablished and fundamental statistical reform began. Statistical
reform became concrete in the form of newly creating the Master
Plan Concerning the Development of Official Statistics which is afive-year working plan. The period covered is between fiscal 2018
and fiscal 2022. Fiscal 2022 is the last year of the Basic Plan andalso the year to formulate the plan for the next period (fiscal 2023 to
fiscal 2027).
One of the achievements of this period was the creation of the
Economic Conditions Survey. The highlight of the statistical reform isimproving the accuracy of GDP statistics and the newly createdstatistics aim to realize this goal.
The three features of the statistics are: (1) speed of the cycle, (2)compatibility with GDP, and (3) survey of all industries. The first is
the speed of the cycle at one year, which is fast for structure
statistics. The most detailed statistics that comprehensively capture
corporate activities are the “Economic Census for Business Activity”.
Census refers to a “complete survey” and it surveys all businesses.
The statistics are accurate but the survey is only conducted once
every five years. The gap between the years that are not surveyed(called the interim years) has been an issue. The Economic
Conditions Survey will function as the statistics to fill these interim
years.
The second is that the statistics are adequate in creating GDP.
There is the “Financial Statements Statistics of Corporations byIndustry” from the Ministry of Finance for corporate statistics, andhttps://www.jef.or.jp/journal/

figures such as sales, capital investment, and current profits can be
grasped from these statistics. But in order to calculate GDP, moredetailed information is required: information such as which industry
used what products and how these products were supplied. The
Economic Conditions Survey also surveys the input-output structure
which indicates the inter-industry relationship.
The third is that the statistics cover all industries. Reflecting thevertically segmented bureaucracy, statistics have thus far beencreated separately for each industry. The service industry had the“Report on the Annual Survey on Service Industries” and the“Survey of Selected Service Industries”, while the wholesale andretail industry had the “Census of Commerce”. These three statistics
were first consolidated, and then a survey for the manufacturingindustry was also conducted to begin the Economic Conditions
Survey (Chart 1).
In 2022, the “Census of Manufacturers” will also be consolidated,surveys for the construction industry and agriculture will begin, anda survey of almost all industries is set to begin. With the introductionof the Economic Conditions Survey, data necessary for GDP for allindustries will be available to be surveyed. Improvement in theaccuracy of GDP statistics can be expected.

CHART 1

Transition of Economic Conditions
SurveyReport on theannual survey onservice industries– Extended Survey

Census of Commerce

Survey of Selected
Service Industries

Economic Conditions
Survey(until 2020 survey)

Census of Manufactures
Manufacturing Industry
Ministry of Agriculture,
Forestry and Fisheries

Economic Conditions
Survey(after 2020 survey)

Construction Industry
Note: For 2021, “Economic Census for Business Activity” was carried out.

Source: Compiled by the author

Japan SPOTLIGHT • May / June 202237

Capturing Cost Structure & Non-Main Business
Projects Now Possible
Let us look at what the Economic Conditions Survey can actually
capture. Two surveys have been conducted so far: the 2019 survey(2018 was the scope of the survey) and the 2020 survey (2019 was
the scope of the survey). Since there have only been two surveys,
analysis by time-series is limited but detailed analysis of theeconomic structure is possible. Total value-added for all industries
was 255.7 trillion yen. The highest percentage by major industry
classifications was the manufacturing industry. This was followed by
the wholesale industry and the retail industry. Next come industries
that are around the same size. These are “health care and welfare
services”, “transportation industry and postal services”,“telecommunications industry”, “financial services and insurance
business”, and “academic research, and professional and technicalservices”.
Cost structures are also surveyed and therefore features byindustry can also be revealed. “Employment placement and worker
dispatch business” and “medical services” are both thought to belabor-intensive industries, but there are differences in the
breakdown. With “Employment placement and worker dispatch
business”, “total wages” were very high at 69.7% and “welfare
benefits” for the employees take up 8.7%. It shows that personnel
expenses alone account for close to 80%.
In looking at “medical services”, on the other hand, “total wages”
were relatively high at 45.6%, but the percentage is also high forpharmaceuticals and equipment with “medicine costs” at 12.3% and“costs of materials” at 10.2%.
In addition, the survey also looks at non-main business activities.
Sales of Uniqlo as a retailer are large, but in terms of making
garments in-house, it is also a manufacturer. In the Economic
Conditions Survey, in addition to sales from its main business inretail, sales for each of the non-main businesses such as
manufacturing are surveyed, and a snapshot which is closer toreality can be captured.

Real-Time Data & Alternative Data

38 Japan SPOTLIGHT • May / June 2022

Major Revision to GDP During the Lehman ShockThe revision status of GDP has been tracked by using the real-time
database of the Tokyo Foundation for Policy Research. Preliminary
data is used when making policy decisions. Later, when the extent of
the revisions becomes large, the initial policy decision becomessomething that was made based on inaccurate information.
Let us first look at the GDP statistics during the Lehman Shock.
Table 1 follows the trend in how the real GDP growth rate changed ateach of the release dates. The more to the right of the chart, themore up-to-date the data is. The real GDP growth rate for the period
July-September 2008 was initially an annual rate of negative 0.4%
year-on-year for its First preliminary release, but a year later it wasrevised downwards to a negative 6.5%. When future analysts analyze
the policy responses to the Lehman Shock, they may wonder “whypolicy responses were delayed when they knew of the sharp drop forthe period July-September 2008”. However, what was first revealed
was the slight drop in GDP. Conducting policy assessment using
revised data can lead to errors in judgement.
The First preliminary value for the period July-September 2009
was a very high growth of 4.8%, but a year later it was a negative
1.5%. This implies that the growth rate which was thought to bepositive was actually negative, and preliminary figures can no longer
be trusted. The size of the revision is one reason behind the mistrust

TABLE 1

GDP statistics during the Lehman Shock
as ofReal GDP growth rate(seasonally adjusted year-on-year growth rate)

Next, new developments brought onby the spread of novel coronavirus
infections will be explained. These are thereal-time data and alternative data.
First, let us look at real-time data.
Real-time may be thought to be definedas “currently ongoing”, but that is notwhat it means. Real-time data refers todata that is available at the time ofmaking policy decisions. Statistics arerevised whenever new information is
obtained. When assessing past policies,
analysis is oftentimes conducted using
data that is available at the time of theanalysis, but most times the data has
been revised since the time the policy

decision was made. When the spread of novel coronavirus infections
was expanding, the number of newly infected patients, ways ofregulation, and economic activities all changed every passing
moment. What is important when assessing policies later on is not
to bring out the “posteriori argument”. Making decisions based on all
available past incidents and making decisions relying only on
available data under future uncertainties are different. In order to
conduct an accurate assessment, it is important to prepare andutilize real-time data.
While real-time data is being prepared primarily by central banksin Europe and the United States, such movements cannot be
observed in Japan. A research team with the Tokyo Foundation for
Policy Research to which I belong has been constructing andoffering real-time data.

2008/7-9.
10-12.
2009/1-3.
4-6.

2008:3-0.4

2008:4

2009:1

2009:2

2009:3

2009:4

2010:1

2010:2(%)
2010:3

2010:4

-2.3

-2.5

-3.9

-6.5

-4.3

-4.2

-5.4

-5.4

-5.0

-12.7

-14.4

-13.1

-11.5

-11.4

-9.6

-10.0

-10.4

-10.9

-15.2

-11.7

-12.2

-12.3

-15.9

-16.6

-15.8

-20.1

3.7

2.7

5.2

7.4

10.4

9.9

10.8

4.8

0.0

0.5

-1.0

-1.5

-1.9

4.6

4.2

4.1

4.2

7.3

4.9

4.4

6.6

6.0

0.4

1.8

2.1

7-9.
10-12.
2010/1-3.
4-6.
7-9.

3.9

10-12.

Note: The period as of was upon the release of the First preliminary results. For example, 2008:3 denotes figure as of therelease of the First preliminary results for the period July to September 2008.

Source: The Tokyo Foundation for Policy Research real-time database

3.3
-1.1

of GDP statistics.

Size of Revision Shrinks During Coronavirus
Infections

negative sign has changed to be positive, and there is a need tofurther verify how much it will be revised.

Utilization of Alternative Data

Real GDP growth rate(seasonally adjusted year-on-year growth rate)

During the period when the spread of novel coronavirus infections
What is anticipated for utilization is alternative data. Alternative
was expanding, major revisions were not conducted for a year after
data is substitute data which is not official statistics. It is like utilizing
the First preliminary results were released. The deviation between theinformation generated from businesses as byproducts, so to speak,First preliminary results and the Second preliminary results
as they conduct economic activities.
especially have been kept small compared to the period of theWhat first came to be utilized with the spread of novel coronavirus
Lehman Shock. With the spread of novel coronavirus infections
infections was data on the workforce. When infections expand, there
expanding, the April-June 2020 data, when a State of Emergency
is a need to restrict economic activities depending on the status of
was declared for the first time, was initially released to be a decline
the infections, and there is also a need to find out how much of theby an annual rate of 27.8% year-on-year, but the rate of decline
economy was suppressed by that restriction. Statistics such as GDP
remained approximately the same after 18 months (Table 2).
which is released at a delayed timing and can only be grasped on a
There are two reasons for this. The first is the ingenuity of thequarterly basis are not enough to respond to that.
seasonal adjustment method. GDP statistics include increases andIn relation to government statistics, the Ministry of Economy,
decreases by season, and therefore there is a need to create
Trade and Industry has constructed a system which allows results ofseasonally adjusted values which exclude this element. The reason
the Census of Commerce, official statistics, to be known early byfor seasonally adjusted values greatly swinging during the Lehman
using the POS (Point of Sale information management system) data,
Shock was because the large drop due to the turmoil of the financial
and it is called the “METI POS – Indices for retail sales amountmarket was processed as seasonal fluctuation. Past values are(micro indices)”.
revised to cancel out seasonal fluctuations. This time, the big shock
Weekly sales statistical data can be gained and since data can also
was processed as a temporary decline not through seasonal
be obtained by region and business categories (convenience stores,
fluctuations, and therefore there were no major revisions tomass home electronics retailers, supermarkets, and others), it isseasonally adjusted values. This is an example where improvement
important data to find the most up-to-date trends in consumption.
proved successful.
Looking at sales by business categories, supermarket sales grew
The other is that the First preliminary results utilized various data.
with the stay-at-home demand immediately after the novel
Upon the release of the First preliminary results, some data did notcoronavirus infections expanded, but by 2021 the growth has been
have enough information for the entire quarter (three months). This
stable also as a reaction. Sales for convenience stores were sluggish
is when there is two months’ worth of data but data for the third
with people not going in to offices when working from home, but asmonth is not yet public. Originally, the growth rate for the two
workforces recovered, growth gradually turned positive. Sales formonths has been applied to estimate the three months of data. Thenmass home electronics retailers and home-centers have recently
there came cases such as the period January-March 2020, when
been mostly declining year-on-year, but in contrast sales for drug
January and February were not affected by the spread of novel
stores have been increasing.
coronavirus infections but March was greatly affected. If a similar
numerical value as January and February were to be used for March,
V-RESAS also Revolutionary
it would deviate greatly from reality.
Thus, estimations were devised by using industry data and data
V-RESAS, which was constructed after the spread of coronavirusthat was available only from large
TABLE 2
corporations. For example, the air
Minor revisions during the spread of Covid-19
(%)
transport industry has official statistics
called the “Annual Report on Air
as of
2019:3 2019:4 2020:1 2020:2 2020:3 2020:4 2021:1 2021:2 2021:3 2021:4
Transport Statistics”, but data collected
2019:7-9
0.2
0.5
0.0
0.2
0.2
0.7
0.5
0.5
0.5
0.1
by interviewing the major airline
2019:10-12
-6.3
-7.3
-7.0
-7.1
-7.1
-7.4
-7.5
-7.6
-10.6
companies was used. For the food2020:1-3
-3.4
-2.5
-2.3
-2.2
-1.9
-2.3
-2.3
1.8
2020:4-6
-27.8
-28.8
-29.3
-28.6
-28.2
-28.2
-28.2
service industry, data collected by the
2020:7-9
21.4
22.7
22.9
22.8
23.5
23.0
industry organization was utilized. By
2020:10-12
12.7
11.6
11.9
11.8
7.5
doing so, the size of the revision between
2021:1-3
-5.1
-3.7
-4.1
-2.1
the First preliminary and the Second
2021:4-6
1.3
1.5
2.4
preliminary results remained small.
2021:7-9-3.0-2.7January-March 2020 data was initially a2021:10-12
5.4
negative growth of 3.4%, but mostNote: The period as of was upon the release of the First preliminary results. For example, 2019:3 denotes figure as of therecently it has been revised to 1.8%
release of the First preliminary results for the period July to September 2019.
Source: The Tokyo Foundation for Policy Research real-time databasegrowth, and while small, the positive/
Japan SPOTLIGHT • May / June 2022

39

CHART 2

Recovery trend in ticket sales for various events
(%)
100

50

0

-50

-100

Period of State of Emergency Declared

Theater (plays, traditional performing arts, comedy, etc.)

2022/1/4w

2022/1/1w

2021/12/3w

2021/11/4w

2021/11/1w

2021/9/4w

2021/10/2w

2021/9/1w

2021/8/2w

2021/7/4w

2021/7/1w

2021/6/2w

2021/5/3w

2021/4/5w

2021/4/2w

2021/3/3w

2021/2/4w

2021/2/1w

2021/1/2w

2020/12/4w

2020/12/1w

2020/11/2w

2020/10/4w

2020/9/2w

2020/10/1w

2020/8/3w

2020/7/5w

2020/7/2w

2020/6/3w

2020/5/4w

2020/5/1w

2020/4/3w

2020/3/4w

2020/3/1w

2020/2/2w

2020/1/4w

2020/1/1w-150

Music (pop, classic, etc.)

Note: Weekly, Growth from the 2019 same week in ticket sales. Created by using V-RESAS.

Source: PIA Corporation

infections, is also a revolutionary data analysis system. It is offeredby the Cabinet Secretariat Council for the Realization of the Vision for
a Digital Garden City Nation Secretariat and the Cabinet Office
Promotion Office for Vitalizing Local Economy. It is a website createdby collecting various alternative data.
RESAS is a system which analyzes regional economies such asprefectures and municipalities, and V-RESAS was created as a
version to respond to the novel coronavirus. “V” in V-RESAS stands
for vital signs – a generic term used for pulse and body temperature.
It signifies frequently used data which reflects economic activities.
Fast data can be obtained in addition to allowing data view byregions.
For the turnout of people which impacts the pace of the spread of
infections, GPS information from smartphones was used to capture
populations that stayed at various locations. For consumption
trends, there is the credit card payment information used as data forthose on the pay-side, and there is the POS (Point of Sale) data at
supermarkets as data for the sell-side.
Declarations of a State of Emergency and Quasi-State ofEmergency have had a grave impact on the activities of restaurants.
The situation of their activities can be estimated by using the viewcount of restaurant information websites. In addition to the entire
sector, individual activities can be viewed by different genres such as“Western cuisine”, “Cafés and sweets”, “Family restaurants and fast
food”, and “Izakaya and bars”. The impact on the tourism industry is
also large, and trends in the number of lodgers can also be viewed.
In relation to the employment environment, the number of job
offers that were published can be tracked by industry classifications
such as construction, manufacturing, and distribution, andmoreover, information can also be grasped by job types such as
specialist jobs and sales and services.
Chart 2 is the status of ticket sales which shows trends in events.
April-May 2020 when the State of Emergency was declared
40 Japan SPOTLIGHT • May / June 2022

throughout Japan saw almost all activities coming to a halt, andshows a negative 100%. Later, activities slowly began to expand withminimal regard to the State of Emergency declaration. There weresome weeks that temporarily exceeded the level of 2019 which was
before the spread of coronavirus infections.
These data do not cover all activities, and therefore their reliability
falls short of that of official statistics. But they allow us to catchsigns of economic activities before accurate data is released, and in
this sense can be said to be useful data.

Conclusion
This article has described how GDP statistics were improved topromote EBPM. The big achievement was the establishment of the
Economic Conditions Survey. It will become the statistics at the coreof GDP estimations in the future.
Since the spread of coronavirus infections, enhancement of realtime data and alternative data became a challenge. With the use ofreal-time data, data that was available at the time when policy
decisions were made can be identified and should be useful in
conducting policy assessments. Especially during the period when
the spread of coronavirus infections was fast expanding, thesituation was changing rapidly and thus it is important to record datathat was used at the time. Similarly, during the period when the
spread of coronavirus infections was fast expanding, the importanceof alternative data heightened. Going forward, using alternative datato complement official statistics will be useful in analyzing thecurrent situation.
Nariyasu Yamasawa is a professor of the Faculty of Management at Atomi
University. He has worked for the Nihon Keizai Shimbun (Nikkei) and the Japan
Center for Economic Research, and is a former director of the Statistics
Commission Office at the Ministry of Internal Affairs and Communications.