nowcasting of gross regional product and analyzing regional business cycle nariyasu yamasawa
TRANSCRIPT
Nowcasting of Gross Regional Product and Analyzing Regional Business Cycle
Nariyasu Yamasawa
Introduction
• Which data and method is relevant to measure Regional business cycle?
• How similar are the prefectures business cycle? • To what extent have prefecture' recession and
expansion experiences been in sync each other ?
• what might explain the differences in business cycle ?
• 1.Data• 2.Methodology• 3.Emprical Result• 4.Conclusion
My presentation has 4 parts.
1.Data Problem in Japan
Annual Quarterly, MonthlyNational GDP Composite Index,
GDPRegional GRP
2years lagComposite Index, Industrial productionMonthly GRP
GDP and GRP(Gross Regional Product) is the best for analyzing business cycle.
For the analysis of the regional business cycle, the key is the choice of the data which represent the business cycle.
Nowcasting of GRP
Present
Official GRP
TIME
Real Monthly GRP
Past
2 years lag
90 days Lag
• The Japanese Cabinet Office has been releasing data on most of the GRP components in the form of a monthly index called the Regional Domestic Expenditure Index (RDEI) since May 2012,.
• We estimated the rest of components, that is Government Consumption, Net export.
• By summing up the expenditure components, we could estimate the monthly GRP.
How to estimate monthly GRP?
Item Methodology for estimation
Private consumption Divided by 44 types of consumption
Private residential investment
“Statistics of Construction Starts of Residential Properties”
Private fixed investment
Estimated by building, construction, machinery, aircraft, motor vehicles, and other transportation machinery
Public investment “Statistics of Construction Order by 47 Prefectures”
Government Consumption Estimated by Author.
Net Export Estimated by Author
RDEI
Real Monthly GRP for 47 prefectures
(Note) The data Start from April 2002
2.MethodologyHow do we measure business cycle?
• Band Pass filter (Baxter and King Filter)– Can remove noise and trend– Considered Business Cycle Frequency 18months – 96 months– Weak point : Baxter King filter cannot analyze present situation
• Regime Switching model(Hamilton(1989)) – Suppose mean growth rate switches between high- and low-
growth regimes.– Probability of recession – Apply spatial analysis with weights matrix W
We tried to extract business cycle by two types of methodology.
Band Pass Filter
ntntttntnt xBxBxBxBxBy 11011
18
2,
96
2,
1,)sin()sin(
0
baab
B
nn
nanbBn
Band Pass Filter
Level data After filtering
Regime Switching Model
We use regime switching model which enable us to identify recession period and expansion period. It suppose the series can divided by two regimes, that is, the high growth rate and low growth rate regime.
Regime Switching model
Growth Rate Recession Probability
Spatial Model
Spatial Contiguity Weights Matrix• Indicate whether prefectures share a
boundary or not. • Neighbors = 1
Then, calculate the share.
3. Estimation Result
• Analyze Mainly Great Recession 2008-2009
Result (Band Pass Filter)
Tokyo
Recession Period(Filter)123456789
101112131415161718192021222324252627282930313233343536373839404142434445464748
20142003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
PREFECTURES
Result(Band Pass filter)
• Almost all the data have the same behavior.• Tokyo is not the same. The peak is 10 months
earlier than the official peak(Feb. 2008).• Hokkaido, Aomori, Kanagawa went in
recession earlier.• Osaka, Hyogo, Aichi went in recession later.
Result of Regime Switching Model
GDPMGGDPATGDPYGGDPFSGDPIGGDPTGGDPGM
GDPSTGDPCBGDPTKGDPKGGDPNGGDPTYGDPIKGDPFIGDPYN
GDPNNGDPGFGDPSOGDPACGDPMEGDPSIGDPKTGDPOS
GDPHGGDPNRGDPWYGDPTTGDPSNGDPOYGDPHSGDPYI
GDPTSGDPKWGDPEMGDPKCGDPFOGDPSGGDPNSGDPKMGDPOTGDPMZGDPKSGDPON
0.00.10.20.30.40.50.60.70.80.91.0
2002
/04
2002
/12
2003
/08
2004
/04
2004
/12
2005
/08
2006
/04
2006
/12
2007
/08
2008
/04
2008
/12
2009
/08
2010
/04
2010
/12
2011
/08
2012
/04
2012
/12
2013
/08
2014
/04
GDPHK
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPAO
GDPAO
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPIW
GDPIW
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPMG
GDPMG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPAT
GDPAT
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPYG
GDPYG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPFS
GDPFS
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPIG
GDPIG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPTG
GDPTG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPGM
GDPGM
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPST
GDPST
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPCB
GDPCB
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPTK
GDPTK
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPKG
GDPKG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPNG
GDPNG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPTY
GDPTY
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPIK
GDPIK
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPFI
GDPFI
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPYN
GDPYN
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPNN
GDPNN
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPGF
GDPGF
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPSO
GDPSO
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPAC
GDPAC
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPME
GDPME
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPSI
GDPSI
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPKT
GDPKT
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPOS
GDPOS
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPHG
GDPHG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPNR
GDPNR
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPWY
GDPWY
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPTT
GDPTT
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPSN
GDPSN
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPOY
GDPOY
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPHS
GDPHS
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPYI
GDPYI
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPTS
GDPTS
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPKW
GDPKW
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPEM
GDPEM
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPKC
GDPKC
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPFO
GDPFO
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPSG
GDPSG
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPNS
GDPNS
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPKM
GDPKM
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPOT
GDPOT
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPMZ
GDPMZ
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPKS
GDPKS
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
2002
/04
2003
/04
2004
/04
2005
/04
2006
/04
2007
/04
2008
/04
2009
/04
2010
/04
2011
/04
2012
/04
2013
/04
2014
/04
GDPON
GDPON
Recession Period(Regime Switching)123456789
101112131415161718192021222324252627282930313233343536373839404142434445464748
2003 2004 2005 2006 2007 2013 20142008 2009 2010 2011 2012
PREFECTURES
Recession(Regime Switching)
0 400kmAug- 08
( )景気後退期
0. 8
0 400kmSep- 08
( )景気後退期
0. 8
0 400kmOct - 08
( )景気後退期
0. 8
• Prefectures in blue are in recession.• Hokkaido, Kagoshima, Yamaguchi, Hiroshima,Niigata, Shizuoka is earlier.• Prefectures which are far from Tokyo tend to go recession early.
Tokyo
It took 4 months for almost all prefectures to be in recession.
Spatial Model
Estimation of ρ
Ｐｒｅｆｅｃｔｕｒｅｓρ is positive and significant.
What might explain the differences in business cycle ?
• Dependent Variables = Beginning date of Recession– Date is number of days from 1900/1/1 – e.g.Feb.2008 is “39479”
• Explanation Variables various kind of data
Cross Section Regression ,Year of 2008
Explanation variablesPOP Population(person)
OLD Population of Old age(%of Total)
PERCAPITA Gross Regional Income Per capita(Yen)
HIGH High School Enrolment(%)
UNIV University Students(% of Total Population)
GDPAGRI Agriculture (% of GRP)
GDPMANU Manufacturing(% of GRP)
GDPCONST Construction(% of GRP)
GDPGOV Government Service(% of GRP)
RIPUB Public Construction(% of GRP)
LEND Lending(% of GRP)
TK Tokyo Dummy
KG Kanagawa Dummy
Regression Result
Peak Date(Fileter) Peak Date(Markov)Variable Coefficient S.E. Coefficient S.E.
Constant 39466 149.38 *** 40307 307.82 ***Population(person) 0.00 0.00 0.00 0.00Population of Old age(%of Total) 1.80 2.05 -9.44 3.75 **Gross Regional Income Per capita(Yen) -0.08 0.05 * -0.21 0.12 *High School Enrolment(%) 1.13 0.93 6.51 3.25 *University Students(% of Total Pop) -2.14 6.12 -28.73 20.02Agriculture (% of GRP) -2.47 4.53 -5.97 12.73Manufacturing(% of GRP) 2.30 1.02 ** 0.29 2.77Construction(% of GRP) 5.89 3.31 * -1.83 7.56Government Service(% of GRP) -1.13 3.11 1.56 10.12Public Construction(% of GRP) -0.60 4.91 -15.87 15.85Lending(% of GRP) 66.85 47.76 -14.34 83.38Tokyo Dummy 1061.08 102.46 *** 981.34 225.87 ***Kanagawa Dummy -43.27 33.82 -202.25 98.12 **
Adj R2 0.959 0.555
HAC standard errors & covarianceStatistically Signifcant at the 10% level(*),5%level(**),1%level(***).Included observations: 47
What affects the business cycle?Frequency Filter Markov Switching
Model1 Share of Manufacturing
Industry(%of GRP)Population Share of Old age (%)
2 GRP Per Capita(Yen) GRP per Capita(yen)
3 Share of Construction Industry(% of GRP)
High school enrollment (%)
Conclusion
• Which data is relevant to measure Regional business cycle. Monthly GRP
• How similar are the prefectures business cycle? Recession date is different, the range is about 4months
• To what extent have prefecture' recession and expansion experiences been in sync with each other's ? Neighborhood Effect exists
• what might explain the differences in business cycle ? GRP per capita etc.
Reference• Michael T. Owyang, Jeremy Piger and Howard J. Wall Source(2005)” Business Cycle
Phases in U.S. States” The Review of Economics and Statistics,Vol. 87, No. 4 (Nov., 2005), pp. 604-616
• Hamilton, J. D., (1989)"A New Approach to the Economic Analysis of Nonsta- tionary Time Series and the Business Cycle," Econometrica 57:2 (1989), 357-384.
0 400kml ength
( )累積表示
987654321
Earlier prefecture is darker
0 400km9- J ul
( )景気後退期
0. 8
Recovery (Regime Switching)
0 400km9- Mar
( )景気後退期
0. 8
0 400km9- May
( )景気後退期
0. 8
• Prefectures in Red are in recession.• Kagoshima, Yamaguchi, Osaka, Saitama, Chiba recovered earlier.• Prefectures which are near Tokyo and Osaka recovered earlier.
Spatial Weight Matrix• Based on Distance– Nearest Neighbor Weights– Radial Distance Weights– Power Distance Weights– Exponential Distance Weights
• Based on Boundaries– Spatial Contiguity Weights– Shared-Boundary Weights
Stakhovych and Bijmolt (2009)
Band Pass Filter
Regime Switching Model
Data Level Growth ratePeak Max End point of High
growth regime
Bottom Min End point of Low growth regime
Data Limitation
Need 18month lag and lead
Influenced outlier
Regime Switching Model
Markov Chain : Any persistence in the regime is completely summarized by the value of the state in the last period.