31:T435,table( d3 .groups(table_sectors, d => d.subsector.slice(0,50)) .filter(([, table_sectors]) => table_sectors.some(d => d.gdp_dollars)) .map(([key, table_sectors]) => ({ Sector: key, Trend: line(table_sectors.map(d => Math.max(0, d.gdp_dollars)).reverse(), { width: 125, height: 18, color: {gradient: ["blue", "lightblue", "grey", "red"]}, highlights: { max: "blue" }, margin: { vertical: 0.1, horizontal: 0.01 } }), "3 yr CAGR": table_sectors[0].gdp_cagr, "GDP": table_sectors[0].gdp_dollars, "% of GDP": table_sectors[0].state_gdp_perc, "Rank /50": table_sectors[0].prior_rank, "\u0394 in Rank": table_sectors[0].current_rank - table_sectors[0].prior_rank })), { width: "700px", layout: "fixed", widths: ["300px", "150px", "50px", "50px", "50px", "50px", "50px"], formats: [null, null, ".0%", ".2s", ".1%", ",", "+,"], align: ["left", "right", "right", "right", "right", "right", "right"], color: [null, null, null, null, null, null, null] } )32:[] 2f:{"title":"Sector Intelligence Tool","cells":[{"id":0,"value":"# Sector Intelligence Tool\n\n#### Source: [Bureau of Economic Analysis](https://www.bea.gov/)\n\n

","pinned":false,"hidden":false,"mode":"md"},{"id":34,"value":"Last updated: December 18, 2021","pinned":false,"hidden":false,"mode":"md"},{"id":680,"value":"**To-do**: Diagnose data gaps for Maryland and DC, South Carolina","pinned":false,"hidden":false,"mode":"md"},{"id":1391,"value":"This report was generated to provide economic developers insight into a state's portfolio of sectors. The information available in this report may be used as a \"first-stop\" for accessing and interpreting economic data, not as a final decision-making tool.","pinned":false,"hidden":false,"mode":"md"},{"id":1177,"value":"Full transparency into data collection, manipulation, and calculation methods are available on [Github](https://github.com/jcferrara).","pinned":false,"hidden":false,"mode":"md"},{"id":674,"value":"## **Sector specialization and growth by year**","pinned":false,"hidden":false,"mode":"md"},{"id":59,"value":"viewof state_filter = Inputs.select([\n\"Alabama\",\n\"Alaska\",\n\"Arizona\",\n\"Arkansas\", \n\"California\",\n\"Colorado\",\n\"Connecticut\",\n\"Delaware\",\n\"Florida\",\n\"Georgia\",\n\"Hawaii\",\n\"Idaho\",\n\"Illinois\",\n\"Indiana\",\n\"Iowa\",\n\"Kansas\",\n\"Kentucky\",\n\"Louisiana\",\n\"Maine\",\n\"Maryland\",\n\"Massachusetts\",\n\"Michigan\",\n\"Minnesota\",\n\"Mississippi\",\n\"Missouri\",\n\"Montana\",\n\"Nebraska\",\n\"Nevada\",\n\"New Hampshire\",\n\"New Jersey\",\n\"New Mexico\",\n\"New York\",\n\"North Carolina\",\n\"North Dakota\",\n\"Ohio\",\n\"Oklahoma\",\n\"Oregon\",\n\"Pennsylvania\",\n\"Rhode Island\",\n\"South Carolina\",\n\"South Dakota\",\n\"Tennessee\",\n\"Texas\",\n\"Utah\",\n\"Vermont\",\n\"Virginia\",\n\"Washington\",\n\"Washington DC\",\n\"West Virginia\",\n\"Wisconsin\",\n\"Wyoming\"], {label: \"Select state: \"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":105,"value":"viewof year_filter = slider({\n min: 2011, \n max: 2020, \n step: 1,\n value: 2020,\n format: v => `Year: ${v}`\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":172,"value":"chart = Plot.plot({\n grid: true,\n //color: {\n // type: \"categorical\",\n // scheme: \"Tableau10\",\n // columns: 5,\n // width: 600,\n // tickFormat: d => d.slice(0,12),\n // swatchSize: 11,\n // legend: false\n //},\n x: {\n label: \"GDP 3-year CAGR (%) →\",\n tickFormat: \"+%\",\n domain: [-0.1, 0.1]\n },\n y: {\n label: \"↑ Specialization (LQ)\",\n tickFormat: \"~s\",\n domain: [0, 2.5]\n },\n marks: [\n Plot.ruleY([1]),\n Plot.ruleX([0.02]),\n Plot.dot(sector_data_state, {x: \"gdp_cagr\", y: \"lq\", r: \"gdp_dollars\", fill: d => d.naics_level_1, stroke: \"white\"})\n ]\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":641,"value":"chart.legend(\"color\", {type: \"categorical\",\n scheme: \"Tableau10\",\n columns: 5,\n width: 600,\n tickFormat: d => d.slice(0,15),\n swatchSize: 11,\n marginLeft: 40})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1121,"value":"The health of a state's portfolio of sectors can signal to economic developers which sectors face headwinds or tailwinds for further development. Generally, a state should amplify high-growth sectors, especially if the sector accounts for a large share of GDP and/or is an existing strength for the economy. Lower-growth sectors where a state lacks specialization may not signal a need for additional attention.","pinned":false,"hidden":false,"mode":"md"},{"id":1104,"value":"#### **Quadrant 1: Scale (High growth, high specialization)**\nTo be completed\n#### **Quadrant 2: Scale (Low growth, high specialization)**\nTo be completed\n#### **Quadrant 3: Scale (Low growth, low specialization)**\nTo be completed\n#### **Quadrant 4: Scale (High growth, low specialization)**\nTo be completed\n","pinned":false,"hidden":false,"mode":"md"},{"id":1441,"value":"Consider how business attraction efforts, in tandem with workforce development and placemaking, may best align with the positioning of each sector.","pinned":false,"hidden":false,"mode":"md"},{"id":1412,"value":"## Historical sector health in ${state_filter}","pinned":false,"hidden":false,"mode":"md"},{"id":309,"value":"viewof sector_filter = Inputs.select([...new Set(sector_data.map(x => x.subsector))], {label: \"Select sector: \"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1058,"value":"The ${sector_filter} sector in ${state_filter} is experiencing changing **concentration** and **growth** levels as illustrated by the trendline below.","pinned":false,"hidden":false,"mode":"md"},{"id":1082,"value":"Frequent movement between and across quadrants in the industry specialization matrix indicate sector volatility, and thus should foster uncertainty, so decision-makers should conduct deeper analysis before setting a strategy.","pinned":false,"hidden":false,"mode":"md"},{"id":297,"value":"Plot.plot({\n grid: true,\n x: {\n label: \"GDP 3-year CAGR (%) →\",\n tickFormat: \"+%\",\n domain: [-0.1, 0.1]\n },\n y: {\n label: \"↑ Location quotient (LQ)\",\n tickFormat: \"~s\",\n domain: [0, 2.5]\n },\n marks: [\n Plot.ruleY([1]),\n Plot.ruleX([0.02]),\n Plot.line(track_subsector, {x: \"gdp_cagr\", y: \"lq\", curve: \"catmull-rom\", stroke: \"black\"}),\n Plot.dot(track_subsector, {x: \"gdp_cagr\", y: \"lq\", fill: \"black\"}),\n Plot.text(track_subsector, {filter: d => d.year % 1 === 0, x: \"gdp_cagr\", y: \"lq\", text: \"year\", dy: -8})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1098,"value":"Sector concentration and growth rates in ${state_filter} should be considered alongside the state's broader portfolio of sectors. Factors such as the sector's share of a state economy and relative sector GDP compared to the other states can provide additional context.","pinned":false,"hidden":false,"mode":"md"},{"id":720,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1183,"value":"md`\n

\n#### Notes\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1189,"value":"Sectors used in this report follow the NAICS classifications adopted by the Bureau of Economic Analysis.","pinned":false,"hidden":false,"mode":"md"},{"id":1204,"value":"md`\nSector specialization in a state is measured by its location quotient, which is calculated using the local concentration of a sector in a geography divided by the national concentration of a sector:\n\n ${tex.block`\nLQ = \\frac{\\frac{GDP_{state,sector}}{GDP_{state}}}{\\frac{GDP_{natl,sector}}{GDP_{natl}}}\n`}\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1308,"value":"md`\nGrowth of sector GDP is measured using the compound annual growth rate (CAGR), not its year-over-year growth rate. CAGR is calculated as:\n\n ${tex.block`\nCAGR = (\\frac{GDP_{year}}{GDP_{year-3}})^{(1/3)}-1\n`}\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1008,"value":"md`\n

\n#### Data Prep\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":726,"value":"table_sectors = sector_data.filter(sector_data => sector_data.state == state_filter)","pinned":false,"hidden":false,"mode":"ojs"},{"id":320,"value":"track_subsector = track_subsector_allstates.filter(track_subsector_allstates => track_subsector_allstates.state == state_filter)","pinned":false,"hidden":false,"mode":"ojs"},{"id":301,"value":"track_subsector_allstates = sector_data.filter(sector_data => sector_data.subsector == sector_filter)","pinned":false,"hidden":false,"mode":"ojs"},{"id":220,"value":"sector_data_state = sector_data_yr.filter(sector_data_yr => sector_data_yr.state == state_filter)","pinned":false,"hidden":false,"mode":"ojs"},{"id":209,"value":"sector_data_yr = sector_data.filter(sector_data => sector_data.year == year_filter)","pinned":false,"hidden":false,"mode":"ojs"},{"id":163,"value":"sector_data = d3.json(\"https://raw.githubusercontent.com/jcferrara/sector-intel-tool/main/state_sector_gdp.json\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1011,"value":"md`\n

\n#### Imported Packages\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":144,"value":"import {table, line} from \"@hamzaamjad/tiny-charts\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":449,"value":"import {addTooltips} from \"@mkfreeman/plot-tooltip\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":97,"value":"import {slider} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1014,"value":"md`

`","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}