ࡱ> ik`abcdejA( / 0DArialngs b b ;bb 0b 0bDTimes New Romanbb 0b 0b DWingdingsRomanbb 0b 0b@ .  @n?" dd@  @@`` XP`Y- **//HGHH.."#)+,-./12345 789$:;<= >?@ABCDE.F%GJHIIAJKLMNbOQQRTUVW 0AA ff3___@8Wʚ;ʚ;g4EdEdb 0&bppp@ <4ddddbqt 0 b;b \___PPT10DTimes New Roman>$}Identified industries that are most similar in the various economic measures. For example Insurance Carriers and Aircraft and Missile Engines industries were grouped together in Connecticut because of high industry export shares and declining employment shares Most of the variables are not based on industry linkages. The variables that do use I-O data only measure local linkagesLNPZ#PZ#yPZ#Ny)Identifying Clusters: Feser and Bergman **$  2Overview of Feser and Bergman Data and Methodology33$Only data used is derived from an I-O transactions matrix. The methodology identifies industries with similar I-O requirements. Regional results compared to the nation to identify gaps and emerging clusters.@#!4Data Preparation and Methodology - Feser and Bergman55$Create two coefficient matrices based on the transactions matrix  Buy matrix: shares of the purchases of each industry by all other industries  Sell matrix: the transpose of shares of the sales of each industry to all other industries*A@#@#A"4Data Preparation and Methodology - Feser and Bergman55$LCreate a double Industry-x-Industry matrix of both buy (production functions) and sell (distribution functions) by placing the  sell matrix next to the  buy matrix PZ##4Data Preparation and Methodology - Feser and Bergman55$kResulting correlation matrix has four industry-x-industry sub-matrices Buy-buy Buy-sell Sell-buy Sell-sell.G@#%@#G%$ 4Data Preparation and Methodology - Feser and Bergman55$From each of these four matrices the largest Industry-by-Industry correlation is identified and used to create a matrix that has a measure of the maximum of any industry-by-industry linkage (the diagonal of 1.00s is excluded)@#%!4Data Preparation and Methodology - Feser and Bergman55$# RApply factor analysis using principal components to maximum correlations matrix. S@#S0,tIdentifying Industries in each Cluster  Feser and Bergman;;() Each industry s factor loading value reveals how strongly that industry is associated with that factor (cluster). Industries clustered based on factor loads for each factor. Factor analysis identifies the groups of industries with the similar input-output linkages @# &">Results and Observations of the Feser and Bergman Methodology??$Industry clusters identified are clearly based on similar industry linkages Regional and national comparisons for gaps and emerging clusters. Industries with similar input or output functions do not necessarily have strong direct links.@#.*IMPLAN I-O Data and Clusters '#Exploring industry clusters:(What share of a cluster s total input requirements are supplied from other identified clusters? What are important non-cluster industries supplying all the clusters? What industries supply goods to the secondary industries? What industries produce similar commodities?)%<Gathering the data One example( Export the IMPLAN transactions or coefficient matrices and import the tables into Access. Regional Industry-x-Industry Direct Coefficients Regional Industry-x-Industry Transactions Create a set of queries that run through the data tables to gather the necessary data.:Z[WZ[W*&One series of examples(-Data Structure for exploring cluster linkages..+'Table of Major Driver-clusters,(;Table of Inputs for Transportation and Distribution Cluster<<$-).Table of Non-Driver Inputs for Driver Clusters//  Conclusions  Multiple definitions of industry cluster concept Complex regional industry structures Regional geography problems Value of industry linkage data from I/O models Value of robust hooks into I/O database($Clusters and IMPLAN(TIMPLAN s data available through MS Access database links gives ability to Easily aggregate industry data to match SIC or other data classifications Examine different industry cluster groups Create standardized tables Export, import or change data quickly Get your IMPLAN model really messed up&KK1- Thank You `f + b` z` ff[[ffRR|` py``Ӣ` ΂´vy` hk][^ROQGTП` N]1FS+BO)33` vs3db3` f` r3>?" dd@,?ldd@ n23 d3@` n?" dd@   @@``PR    @ ` `6p>>  (   ڈ 6Ȋ #" `] `}  \*  ۈ 6 #" `] `}  Z*  ܈ 6 #" `]}   \* $ ݈ 0䖑 " `  RClick to edit Master text styles Second level Third level Fourth level Fifth level!     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33___PPT10i.Q.+D=' b= @B + b (    02% pg  Clusters in Connecticut Defining the industry cluster concept Methods to identify industry clusters Examine industry clusters Conclusionsr  S 5%ވfZH  % H  0޽h ? ff[[ffRR|___PPT10i.Q@+D=' b= @B +S b jb(  x  c $X%݈  %   0P# P` Economic development strategy leveraging industry cluster theory developed during the recession in early 1990s. Goal of this strategy was to create industry organizations to represent the needs of companies within those industries and encourage communications among the companies. Aerospace component manufacturer s cluster BioScience cluster (Connecticut United for Research Excellence) eBizCT  Software/information technology cluster Metal Manufacturing cluster.@ @ ,E 6G  0$]%  Z IMPLAN and Clusters: Background!( 2!333H  0޽h ? ff[[ffRR|___PPT10i.Q@+D=' b= @B +4 b R(  x  c $0#݈R #   0 # .0zw,$@0 D Presentation reviews three methodologies used in a larger project to objectively analyze Connecticut s industry structure. This larger project assessed Connecticut s existing industry clusters and identified potential industry clusters. All three methodologies used input-output data. IMPLAN I-O model used based on Connecticut political boundaries economic marketsH@ I@ '@ I'  0#  Z IMPLAN and Clusters: Background!( 2!333H  0޽h ? ff[[ffRR|___PPT10.Q@+ED' b= @B D' = @BA?%,( < +O%,( < +D@' b=%(D' =%(D' =4@BBBB%())))?D' b=1:Bvisible*o3>+B#style.visibility<*|%(D' =4@BBBB%())))?D' b=1:Bvisible*o3>+B#style.visibility<*|%(Dn' b=%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*D' =+4 8?dCB1+#ppt_h/2BCB#ppt_yB*Y3>B ppt_y<*D ' b=%(D ' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*J%(D' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*JD' =+4 8?dCB1+#ppt_h/2BCB#ppt_yB*Y3>B ppt_y<*JD' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*J`%(D' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*J`D' =+4 8?dCB1+#ppt_h/2BCB#ppt_yB*Y3>B ppt_y<*J`D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*`q%(D' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*`qD' =+4 8?dCB1+#ppt_h/2BCB#ppt_yB*Y3>B ppt_y<*`q+ b ( (  x  c $#݈` # >  0<# P`P  *Kolie Chang of the Connecticut Department of Economic and Community Development Daniel Kennedy and Roger Therrien of the Connecticut Department of Labor William Lott and Stan McMillan of the UCONN Connecticut Center for Economic Analysis Jeff Blodgett, Alissa DeJonge and Dale Shannon of CERC, Incd+@ =) '/2 ,i  0x)#  Z IMPLAN and Clusters: Background!( 2!333H  0޽h ? ff[[ffRR|___PPT10i.Q@+D=' b= @B +: b QI(  x  c $1#ވ`P0  # )  0L2# @  Clusters in Connecticut Defining the Industry Cluster Concept Identifying Industry Clusters Exploring Industry Clusters Conclusions*&FH  0޽h ? ff[[ffRR|___PPT10i.Q@+D=' b= @B + b  J(  r  S 9#ވP  # 8 k  ` @    k hR  s *3"`   0<# T IDriver Industries( 23  0@#p0 q  QPrimary Supply Industries( 23  0p#` `  e-Tertiary Industries and Foundational Elements.( 2.3TB  c $D,p pTB   c $D-   0s# ,$0 >Direct( 23  0F# ,$0 @Indirect ( 2 3  0J# J@ ,$0 ?Induced( 23H  0޽h ? ff[[ffRR|  ___PPT10b .R6+TD' b= @B DI' = @BA?%,( < +O%,( < +D' b=%(D(' =%(D@' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<* %(D' =-o6Bdissolve*<3<* D@' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<* %(D' =-o6Bdissolve*<3<* D@' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<* %(D' =-o6Bdissolve*<3<* ++0+ # ++0+ # ++0+ # + b #b(  x  c $X#ވP  #   0Z# 0 C Non-local ( 2 3  s *^#"`  D Final Demand ( 2 3  0b#g ;  JNon-local inputs( 23XB  0DoP pRB  s *Do  0f#`  OLocal (Within region)( 23  6j#1"` P  a'Non-driver industries demand for inputs(( 2(3  6n#1"`0 `  `&Non-driver industries supply of inputs'( 2'3RB  s *DfP RB  s *DfPP @RB  s *Df  `  s *1"`p0 p RB  s *Df`@XB  0Df @ f2  0"`R   0t#  LIndustry cluster 1 2 3r8 8  p  !- n2  0ff"`P p   08#8 >  $  LIndustry cluster 3 2 3r8 E  4t  "o ^- n2  0"`E  %t   0Ī#T 4  LIndustry cluster 2 2 3  0w#A  IDriver/Clusters 23XB  0Dfm } XB  0Df" a t q XB  0Df   r XB #@ 0Df w  H  0޽h ? ff[[ffRR|___PPT10i.R6+D=' b= @B + b  (  x  c $#݈ 0U # [  0# 1P,$D0 Industries affected by the same changes in the structure of the regional or national economy Industries with the similar labor requirements Industries needing similar capital/technology investments Industries that produce the same commodities Industries with similar production or distribution functions Industries with similar resource requirements Industries linked through input or output requirements@   0#@  i/IMPLAN and Clusters: Defining Industry Cluster0( 20333R  6>"`6 ,$D 0H  0޽h ? ff[[ffRR|:2___PPT10.Q@+ڄD' b= @B D' = @BA?%,( < +O%,( < +D4' b=%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*]%(D4' b=%(D' =%(D' =4@BB