PRÉCIS® U.S. METRO • User’s Guide User’s Guide - Page 1 The distinction between mid-expansion and late expansion is based on the short-term trend observed in the economy. This is calculated using a K-means clustering approach, in which changes in job growth, the unemployment rate, and the housing market are normalized using standard deviations and benchmarked against national trends at various points in the business cycle. For those areas that have been classified as being in mid- or late-cycle expansion, this index is used to differentiate between the two. 2 Employment Growth Rank These numbers represent the ranking of all 410 metro areas and divisions of short-term employment growth (over the next two years, left) and long-term growth (over the next five years, right). The actual expected short-term and long-term employment growth rates can be found in the Metro Ranking Supplementary Files. Depending on the distribution of the forecast growth rates, large differences in metro area forecast rankings may or may not indicate large differences in metro area forecast growth rates. For the current distribution of metro area employment growth rates, see the Metro Ranking Supplementary Files. Cost of Living The cost of living index measures the relative cost to the average household in the nation to maintain its standard of living in each metropolitan area. The index is created by summing expenditures on various components of consumption in each metro area relative to average U.S. expenditures on the components. The components that vary across metro areas include housing, food and apparel, utilities, transportation, and auto insurance. Cost of Doing Business In order to better gauge regional economic prospects, Moody’s Analytics has developed a cost of doing business index for each metro area. The relative business cost index is composed of labor costs, energy costs, tax burdens, and office rent costs. Labor costs are measured by unit labor costs, or earnings per dollar of output. Unit labor costs are determined for each three-digit NAICS industry for each metro area and compared with unit labor costs for the same industries nationally. Energy costs are measured by average cents per kilowatt-hour (Kwh) charged to commercial and industrial users. Tax burdens are measured by city and county revenues within the metro area and expressing their sum as a percent of total personal income in each metro area. Business contributions to unemployment and workman’s compensation programs are also included in the tax measure because they represent costs for labor hired. Office costs are measured as the average price paid per square foot for class A office space. In the overall business cost index, a state-specific component weight system has been adopted to more accurately account for an area’s business cost structure. State-specific weights were generated by analyzing inter-industry capital flows via IMPLAN modeling software. Metro areas within a state use the state’s weight structure, which is modified to include metro area-specific office rent costs. On average across all metro areas, tax burdens have a 7% weight, energy a 15% weight, unit labor costs a 51% weight, and office rent costs a 28% weight. The index is configured so that the cost of doing business nationally equals 100. Thus, a metro area with a cost index of 110 has business costs 10% above the national average; an index of 90 means a metro area has business costs 10% below the national average. Indicator Units Source Gross Metro Product Chain-weighted dollars BEA, Moody’s Analytics Total Employment Ths BLS Current Employment Statistics Unemployment Rate % BLS Current Population Survey Personal Income Growth % change previous yr Bureau of Economic Analysis Median Household Income $ ths Census Bureau Population Ths Census Bureau Net Migration Ths Census Bureau Single-Family Permits Multifamily Permits Existing-Home Price Number of units Number of units 1980Q1=100 Census Bureau Census Bureau FHFA MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 Differences in the cost of doing business across regions are an important long-term determinant of regional economic performances. 4 COVID-19 Exposure COVID-19 exposure measures the degree to which structural factors make an economy more susceptible to the economic implications of the current pandemic. This is determined using a combination of variables measuring public health considerations, demographic factors, and industrial composition. For each variable, a z-score was calculated in order to standardize the measurement. A z-score is defined as the distance of an individual datapoint above or below the mean, such that a score of 1 signifies that a state or metro area sits a single standard deviation above the mean. More precisely, this is defined as: Z = (x-μ)/σ, where: x = state or metro area being examined μ = arithmetic mean across geographies σ = standard deviation A z-score is calculated for over a dozen series spanning six different categories, each capturing a specific type of economic exposure. The categories are (1) exposure to the virus, including per capita number of cases; (2) demographics, such as population density and share of seniors; (3) trade and travel, including export reliance; (4) dependence Page 1 Sample on tourism; (5) economic AKRON OH vulnerability, 345 365 capturing the 92% 94% 86% 341 5 6 3 2 importance of small 1 businesses and the poverty rate; and (6) share of output associated with natural resource-based 285 4 industries, including oil extraction. Each category is assigned a weight 7 Aa1 F that ranges from 10% to 20%, based on a subjective assessment of Data Buffet® MSA code: IUSA_MAKR ECONOMIC DRIVERS EMPLOYMENT GROWTH RANK MANUFAC ENERGY & TURING RESOURCES 2019-2021 2019-2024 5th quintile 5th quintile Late Expansion At Risk STRENGTHS & WEAKNESSES STRENGTHS » Below-average exposure to COVID-19. » Relatively low business and living costs. » Prime location for staffing business outsourcing and HR support roles. WEAKNESSES » Few jobs in high-value-added services. » Per capita income is below average. » Weak migration trends, slow population gains. » Manufacturing vulnerable to outsourcing. FORECAST RISKS SHORT TERM LONG TERM COVID-19 EXPOSURE JULY 2020 4th quintile BUSINESS VITALITY RELATIVE QUALITY OF LIFE Rank: 260 U.S.=100% Best=1, Worst=403 Best=1, Worst=378 ANALYSIS Mid Expansion Recovery In Recession RELATIVE COSTS LIVING Best=1, Worst=410 BUSINESS CYCLE STATUS X The business cycle status identifies the stage of the business cycle that characterizes an area’s recent performance. There are five categories: in recession, early expansion, mid-expansion, late expansion, and at risk. The evaluation of an area’s status is based on a six-month test of either contraction or expansion. The six-month test compares the six-month moving average of the business cycle index in the current period with the six-month moving average in the period six months earlier. An area is “in recession” if the six-month test shows contraction. If a trough has been reached, the economy shifts from recession to “early expansion.” Once the business cycle indicator reaches a peak, the area is in “mid-expansion” or “late expansion.” If it appears that a local peak may have been reached and the business cycle indicator is increasing but at a decreasing rate, then the economy is placed “at risk.” At risk indicates that the economy could slip from expansion or recovery to recession if the index has fallen but for less than six months. 3 Relative Costs W 1 Business Cycle Status Most=1 Least=403 UPSIDE » Demand for non-COVID-19-related health services fuels bigger gains in employment. » National vehicle sales surprise to the upside, leading to greater support to steel and auto production at local factories. DOWNSIDE » Out-migration picks up, hurting populationdependent services and housing. » A second wave of COVID-19 leads to more closures, bankruptcies and layoffs. MOODY’S RATING COUNTY AS OF SEP 27, 2017 Recent Performance. Akron, which was already underperforming its Buckeye State peers over the past several years, has succumbed to recession as the COVID-19 pandemic unfolds. Payroll employment has plunged to its lowest level since 1993 amid broad-based weakness. The harm has been most acute in retail, leisure/hospitality, and professional/business services, but no sector has been untouched by the virus. Moreover, the unemployment rate has spiked to near an all-time high of 12.9% and the labor force has plummeted to its lowest level since 1992 as the number of discouraged workers mounts. Businesses have furloughed and, in some cases, permanently laid off workers as their revenues have dwindled, especially in hard-hit leisure/hospitality as restaurants and hotels struggle to stay afloat. Homebuilding has stalled, but home values are climbing due to very few listings. COVID-19. Although the economic damage spurred by the virus has been unprecedented in modern history, local businesses have already started reopening in accordance with state guidelines and employment will rebound sharply in the third quarter. Payroll employment finally registered a slight rebound in May after clocking in sharp declines the prior few months. Timely data at the state level point to continued improvement in June; weekly initial claims for unemployment benefits in Ohio have dropped 88% since peaking in late March. Jobless claims will trend downward in coming quarters as revenues at businesses rebound and firms recall furloughed workers. Further, much like its other peer Ohio metro areas, AKR faces below-average exposure to the adverse economic impact of COVID-19. AKR ranks in the bottom 68th percentile of U.S. metro areas in terms of risk as measured by our COVID-19 z-score indicator. The hard-hit small business sector is a more modest share of the economy, the hit from weaker tourism has been smaller, and the infection rate is near the bottom one-third of areas. Factory restart. The key factory sector has switched back on and output will rebound in coming quarters as durable goods demand returns. Specifically, local steel manufacturers that supply the regional contingent of auto parts producers will bolster output as national vehicle demand rebounds. U.S. vehicle sales hit an all-time low of 8.7 million seasonally adjusted annualized units in April, but they have since rebounded to an annualized rate of 12.7 million units, reversing close to half of the drop that occurred between January and April. Auto demand will trend upwards over the next several quarters as households slowly regain confidence and are lured by rock-bottom auto financing costs as the national labor market continues to heal. Even still, it will not be until late 2022 that local manufacturing output returns to its prerecession level. Triage. Healthcare has also been hit due to a drop-off in non-COVID-19-related demand, but previously delayed procedures and examinations will occur in coming months as patients venture out, bolstering healthcare employment. Top hospitals, including Summa Health System and Akron’s Children’s Hospital, have resumed elective procedures and are boosting their telehealth options. Medical providers will slowly begin to hire back previously furloughed doctors, nurses and healthcare technicians to cope with greater patient demand, supporting incomes at a crucial time as federal fiscal policy turns less supportive. Akron will emerge from recession soon as businesses reopen and confidence gradually returns. The factory sector has already begun its rebound as auto demand improves. In addition, growing patient demand will support healthcare providers. Longer term, a subpar demographic profile will prevent AKR from keeping pace with the nation. 1-866-275-3266 Brent Campbell help@economy.com June 2020 2014 2015 2016 2017 2018 2019 INDICATORS 2020 2021 2022 33.2 3.8 332.7 1.9 5.9 4.8 50.7 704.9 0.2 0.5 684 79 132.6 34.6 4.2 337.7 1.5 4.9 2.8 51.2 704.4 -0.1 -0.6 792 175 137.9 35.7 3.2 340.2 0.7 5.1 1.0 53.1 703.5 -0.1 -1.0 905 4 142.1 36.3 1.6 340.9 0.2 5.1 4.1 55.9 704.0 0.1 0.6 901 19 148.6 36.6 0.6 339.9 -0.3 4.6 4.5 60.0 703.9 -0.0 -0.1 1,011 199 155.6 37.4 2.2 340.1 0.1 4.3 3.5 61.3 703.5 -0.1 -0.4 856 89 164.5 Gross metro product (C12$ bil) % change Total employment (ths) % change Unemployment rate (%) Personal income growth (%) Median household income ($ ths) Population (ths) % change Net migration (ths) Single-family permits (#) Multifamily permits (#) FHFA house price (1995Q1=100) 35.7 -4.5 315.1 -7.4 10.3 3.7 63.2 704.4 0.1 0.8 1,016 161 170.2 36.2 1.5 315.9 0.3 9.6 -3.2 62.2 705.6 0.2 1.1 1,707 385 167.3 38.2 5.6 325.1 2.9 7.0 4.2 64.2 707.0 0.2 1.4 2,259 488 173.6 2023 2024 2025 39.6 3.7 333.4 2.6 4.7 5.1 66.7 708.1 0.2 1.2 2,328 513 187.1 40.4 1.8 337.0 1.1 4.4 4.2 68.9 709.0 0.1 1.1 2,266 501 196.6 40.9 1.3 338.0 0.3 4.5 3.5 71.0 710.0 0.1 1.2 2,199 459 204.8 MOODY’S ANALYTICS / Précis® U.S. Metro / June 2020 Note GMP is the sum of all income produced in a metro area, including corporate profits. Thus, it does not necessarily track employment growth. Defined as sum of mining, construction, manufacturing, transportation/ utilities, trade, information, financial activities, professional and business, education and health, leisure and hospitality, and other services, and government. Measures income received by households from employment (including self), investments and transfer payments. Calculated as number of domestic and international people moving into a metro area minus those leaving. Index is not affected by mix of homes sold. 99 PRÉCIS® U.S. METRO • User’s Guide the importance of each factor. For example, tourism is weighted more heavily than natural resource dependence. The final weighted average z-scores are used as the basis for ranking each state and metro area. The higher the ranking, the more exposed an economy is to the economic effects of the pandemic. The index is updated monthly with new data on per capita COVID-19 cases. However, because about 90% of the index is determined based on other, more structural characteristics, the rankings tend to be stable over time. Other subjective factors such as the impact of a premature reopening are not explicitly factored into the index but provide important additional context. For more details, see “Assessing the Regional Economic Impact of COVID-19,” Regional Financial Review, March 2020. Note that some components of the index have changed slightly since this paper was published, but the broad methodology remains the same. 5 Vitality Index The Moody’s Analytics vitality index can be used to assess a metro area’s long-term economic potential. The index abstracts from business cycle fluctuations and near-term economic events. Only persistent forces of economic strength or weakness are considered. To maintain a long-term focus, the vitality index was created with the purpose of predicting the average annual growth rate in an area’s gross domestic product over the next 20 years. This index presents a quantitative alternative to the Moody’s Analytics regional forecasts, which are determined not only by econometric modeling but also by the qualitative judgment of regional analysts. The index is designed to capture sources of comparative advantage that drive stronger economic performance. These include industrial composition, workforce characteristics, and costs. More specifically, the following factors make up the vitality index: (1) industrial structure, based on implied GDP growth using the share of output associated with each industry and national growth rates; (2) growth in the prime working-age population (age 25-54) during the preceding 20 years; (3) educational attainment, based on the share of adults with a graduate or college degree; (4) immigration as a share of total population; (5) the Moody’s Analytics Rental Burden Index; (6) the Moody’s Analytics Cost of Doing Business Index; and (7) the Moody’s Analytics Broad-Based Startup Rate. The vitality index is based on each economy’s distance from the mean for each of the components above, with the average score equal to 0 and a value of 1 indicating that a state or metro area lies one standard deviation above the mean. Z-scores are calculated for each component and an average is then generated using weights that range from 5% to 25%. The weights are based on the combination of econometric analysis using factors that drove growth over a 20-year period and our discretion. A positive score indicates potential for faster growth, while a negative score indicates that an economy’s fundamentals suggest below-average growth. Because the index consists of a collection of z-scores, it is highly unlikely for the weighted average of standard deviations across metrics would exceed an absolute value of 2. Therefore, the index can be thought of as ranging from roughly -2 to 2. See Regional Financial Review, “An Update to the Moody’s Analytics Vitality Index,” October 2020 for more details. Finally, a measure of natural amenities was obtained from the U.S. Department of Agriculture. The USDA’s natural amenities scale quantifies the physical characteristics of a county area that enhance the location as a place to live. The scale was constructed by combining six measures of climate, topography and water area that reflect environmental qualities most people prefer. These measures include warm winter, winter sun, temperate summer, low summer humidity, topographic variation, and water area. Metro areas containing multiple counties were weighted using a household-weighted average of the amenity score. All variables in both models were then standardized. The U.S. average for each index component is zero. Thus, a metro area with an index score above zero has a quality of life above the national average; an index below zero means a metro area has a quality of life below the national average. Data limitations prohibited the use of Alaska and Hawaii. Incomplete data also necessitated assigning to metro divisions the scores and rankings of the metro areas in which they are located. Therefore, multiple metro areas and divisions have the same scores and rankings. 7 Moody’s Bond Rating 6 Quality of Life Index These numbers represent the ranking of metro areas and divisions in quality of life, with 1 being best. The quality of life for each metro area is an index of characteristics that individuals and households appear to prefer, weighted in proportion to how much they affect people’s demand to live in an area. The index is composed of metro area characteristics that predict the house price-to-income ratio and the net migration rate across metro areas. The most influential variables fall under four categories: child welfare, walkability/bikeability, recreation and natural amenities. Child poverty rates were obtained from the U.S. Census Bureau’s American Community Survey. Walkability/ bikeability represents the percentage of residents who report in the ACS that they walk or bike to work. Per capita access to recreational facilities was calculated using data on the number of workers in a subset of leisure and hospitality industries from the U.S. Bureau of Labor Statistics Current Employment Statistics. This category includes arts, entertainment, recreation and food services. This is the bond rating for general obligation bonds issued by a principal city or county government. Not all city and county governments issue GO bonds and thus some metro areas will have an “NA” here. The interpretation of the bond rating is as follows: Aaa Aa A Baa Ba B Best quality, smallest degree of investment risk High quality, margins of protection not as large as in Aaa Upper medium grade obligations, adequately secured Medium grade obligations, neither highly protected nor poorly secured Speculative, future cannot be considered as well assured Lacking characteristics of desired investment The modifier 1 indicates that the issue ranks in the higher end of its generic category; the modifier 2 indicates a midrange ranking; and the modifier 3 indicates that the issue ranks in the lower end of its generic category. User’s Guide - Page 2 Page 2 Sample PRÉCIS® U.S. METRO • Fargo ND-MN 9 Current Employment Trends Employment is organized into three sectors: government, goods producing industries, and private service producing MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 10 Business Cycle Index The Moody’s Analytics business cycle index is a measure meant to gauge the current trend of underlying economic activity. The indicator is designed to pick up distinct shifts in the economy through its four underlying components: employment, housing starts, industrial production, and ECONOMIC HEALTH CHECK 3-MO MA Dec 19 0.3 2.2 72.5 34.0 104.2 627 417 2014 3.9 Employment, change, ths Unemployment rate, % Labor force participation rate, % Average weekly hours, # Industrial production, 2012=100 Residential permits, single-family, # Residential permits, multifamily, # Dec/Dec Employment, change, ths Better than prior 3-mo MA Jan 20 0.3 2.2 72.4 34.0 104.3 303 410 2015 2.0 Feb 20 0.3 2.2 72.3 34.1 104.3 160 12 2016 0.5 BUSINESS CYCLE INDEX Mar 20 0.2 2.1 72.3 34.4 102.8 300 370 2017 0.8 Unchanged from prior 3-mo MA Apr 20 -1.5 4.1 72.5 34.2 97.3 594 533 2018 2.6 May 20 -2.9 ND ND 34.1 ND 866 728 2019 1.0 JAN 2010=100 135 130 125 120 115 110 105 100 95 10 11 12 13 14 15 16 17 18 19 20 FAR Worse than prior 3-mo MA CURRENT EMPLOYMENT TRENDS % CHANGE YR AGO 16 Government 17 18 19 Total Mining Construction Manufacturing Trade Trans/Utilities Information Financial Activities Prof & Business Svcs. Edu & Health Svcs. Leisure & Hospitality Other Services Government 20 Goods producing Private services Sources: BLS, Moody’s Analytics 1.4 1.1 4.1 0.6 -0.6 4.1 4.5 2.4 1.7 2.4 1.1 -0.0 0.7 1.1 -7.0 4.5 -1.9 -0.6 0.6 3.4 2.4 3.6 0.0 1.9 0.7 1.5 -5.0 -20.2 -0.7 -5.2 -3.9 -5.6 -1.0 0.4 4.4 -3.9 -29.6 -3.3 -2.4 Sources: BLS, Moody’s Analytics 3-DIGIT NAICS LEVEL, 6-MO MA 70 65 60 55 50 45 40 14 15 FAR JAN 2010=100 ▲ 5-Yr ▲ l ▼ 2-Yr 110 105 100 18 19 U.S. 20 1998Q1=100, NSA 260 240 220 200 180 160 140 120 100 80 95 98 10 11 12 13 14 15 16 17 18 19 20F 21F 22F 23F 24F ND 17 ND HOUSE PRICE FORECAST VS. 6 MO PRIOR 130 125 120 115 16 Sources: BLS, Moody’s Analytics RELATIVE EMPLOYMENT PERFORMANCE FAR U.S. DIFFUSION INDEX % CHANGE YR AGO, 3-MO MA May 19 Nov 19 May 20 8 6 4 2 0 -2 -4 -6 -8 -10 -12 15 ND Source: Moody’s Analytics Sources: BLS, Census Bureau, Moody’s Analytics ▲ l ▼ The year-over-year growth of payroll employment for the most recent month compared with six and 12 months prior enables the users to track how employment trends have changed over the preceding two years, and whether the pace of job creation has held steady, decelerated or accelerated. In addition to total payroll employment, data are available for all of the Bureau of Labor Statistics-defined “super sectors” listed above. In some smaller metro areas, some of the super sector data are estimated by Moody’s Analytics because they are not released by the BLS. house prices. These variables are chosen 10 8 for their timeliness, frequency and availability. Employment is 11 9 provided monthly by the Bureau of Labor Statistics and 13 house prices are provided quarterly 12 by the Federal Housing Finance 14 15 16 Agency. Housing starts are estimated by applying several adjustment factors to the Census Bureau’s monthly permits data and industrial production is created by combining detailed inhouse employment estimates with the Federal Reserve’s monthly U.S. industrial production data. l W W ▼ A heat map made up of high-frequency indicators provides insight into the factors that explain an area’s recent performance. The indicators considered are all produced in monthly frequency. In order to smooth out month-to-month fluctuations, the three-month moving average is calculated and compared with the three-month moving average in the prior month. If the change is positive, the cell is shaded green, if no change took place, the cell is shaded yellow, and if the change is negative, the cell is shaded orange. The high-frequency indicators include the change in payroll employment; change in the unemployment rate, where a lower rate connotes improvement; the labor force participation rate, defined as the share of the working-age noninstitutional population older than 16 either looking for work or employed; industrial production; single-family residential permits; and multifamily residential permits. The metro industrial production index is estimated using national-level industrial production and metro-level industry employment. industries. Goods producing industries include natural resources and mining, construction and manufacturing. Private service producing industries include trade, transportation and utilities, information, financial activities, professional and business services, education and health services, leisure and hospitality and other services. ▲ l ▼ 8 Economic Health Check 01 FAR 04 07 10 ND 13 16 19 U.S. U.S. Sources: FHFA, Moody’s Analytics Sources: BLS, Moody’s Analytics RENTAL AFFORDABILITY HOUSE PRICE TRENDS HOUSING AFFORDABILITY GREATER THAN 100=MORE AFFORDABLE % GREATER THAN 100=MORE AFFORDABLE 220 25 210 20 200 280 260 240 220 200 180 160 140 120 100 15 190 10 180 5 170 0 160 -5 150 -10 140 95 97 99 01 03 05 07 09 11 13 15 17 FAR ND U.S. Sources: Census Bureau, BLS, Moody’s Analytics 98 01 04 07 Overvalued Sources: FHFA, Moody’s Analytics 10 13 16 95 97 99 01 03 05 07 09 11 13 15 17 19 19 FAR Undervalued ND U.S. Sources: NAR, Moody’s Analytics MOODY’S ANALYTICS / Précis® U.S. Metro / June 2020 When constructing the index, employment, housing starts, and industrial production are smoothed using a three-month moving average in order to better grasp the underlying trends, while house prices are quarterly data that are converted into 100 PRÉCIS® U.S. METRO • User’s Guide a monthly frequency and led by six months. Economic data— particularly at the metro area level—can often be volatile even when smoothed, and to control for sporadic movements in the data, the weights assigned to each component in the final index are inversely proportional to their volatility. optimistic outlook and a downward arrow indicates a more pessimistic outlook. For the two-year forecast, a difference in average annual growth larger than 0.1 percentage point indicates a change. For the five-year forecast, a difference larger than 0.25 percentage point indicates a change. 11 Diffusion Index A diffusion index measures the breadth of private sector job creation in an area. A low diffusion index indicates that an area relies on just a few industries for growth. A high diffusion index indicates more balanced growth. The diffusion index is constructed by summing the share of three-digit NAICS industries that have added to payrolls in a given month and half of the share of those industries that have neither added to nor subtracted from payrolls, where 50% indicates an equal balance between industries with increasing and decreasing employment. Because of volatility in month-to-month movements, a six-month moving average is used. Detailed industry employment data, for 274 industries as specified by the BLS, are used to compile the industry diffusion indexes for states and metro areas. The BLS does not publish payroll numbers for all three-digit industries for metro areas every month. Moody’s Analytics estimates the data for any missing NAICS industries. The following calculation is then used to compute the diffusion index, where the denominator is the total number industries in which employment data are available at the three-digit NAICS level. ((positive/denominator)+(.5*(unchanged/denominator)))*100 12 Relative Employment Performance In order to compare the performance of a metro area’s labor market with that of the U.S. and state, an index is calculated in which the value of the Bureau of Labor Statistics payroll employment in the first quarter of 10 years prior to the current year is set at 100. Forecast data for the next five years are also provided. The shaded gray bar represents the period of the 2008-2009 national recession. In addition, we track how the two- and five-year employment forecasts for the metro area, state and U.S. have changed compared with six months prior. A dash indicates no change, an upward arrow indicates a more 13 House Prices FHFA Conventional and Conforming Home Price Index. The Federal Housing Finance Agency (FHFA) estimates and publishes quarterly house price indexes for singlefamily detached properties using data on conventional conforming mortgage transactions obtained from the Federal Home Loan Mortgage Corp. (Freddie Mac) and the Federal National Mortgage Association (Fannie Mae). These indexes use a repeat-purchase method, which is not affected by the mix of homes sold. For example, using traditional house price measures, a rise in the number of low-priced homes sold relative to higher-priced homes will bias house prices downward even though relative prices may not have changed. Because repeat-purchase house price indexes keep track of successive selling prices for the same property, they avoid this bias. Freddie Mac and Fannie Mae are private corporations with federal charters whose mandate is to provide liquidity to the nation’s residential mortgage market. The FHFA was created by the Housing and Economic Recovery Act of 2008. The FHFA is the regulator of Fannie Mae, Freddie Mac, and the Federal Home Loan Banks. This law combined the staffs of the Office of Federal Housing Enterprise Oversight (OFHEO), the Federal Housing Finance Board (FHFB), and the GSE mission office at the Department of Housing and Urban Development (HUD). such as California, Connecticut and New Jersey, where many homes are typically priced above the purchase limits. 14 Rental Affordability The recommended level of household median income spent on median annual gross rent should not exceed 30%. The Rental Affordability Index is 100 when a household spends exactly 30% of income on rent. If gross rent exceeds 30% of income, the index is below 100. If gross rent is lower than 30% of income, the index is higher than 100. The index is derived using data from the Current Population Survey, American Community Survey, decennial census, and the Bureau of Labor Statistics. 15 House Price Trends This chart compares the observed value of the FHFA purchase only index (for states) or FHFA all transactions index (for metro areas and divisions) with the value Moody’s Analytics projects if supply and demand in the housing market were in long-run equilibrium. When the observed value of house price index is greater than the equilibrium value, the average house price is overvalued; when the observed value is less than the equilibrium value, the average house price is undervalued. The primary factors that determine equilibrium include per capita disposable income, a measure of long-run demand, and construction costs, a gauge of long-run supply. These measures are updated monthly. 16 Housing Affordability The House Price Index is based on transactions involving conforming, conventional mortgages purchased or securitized by Fannie Mae or Freddie Mac. Only mortgage transactions on single-family properties are included. A conforming mortgage is one that both meets the underwriting guidelines of Fannie Mae or Freddie Mac and that does not exceed the conforming loan limit. The conforming limit for single-family homes is $484,350 as of January 2019, with higher limits for high-cost metro areas. Conventional means that the mortgages are neither insured nor guaranteed by the FHA, VA, or other federal government entity. Because of the conforming limit, the FHFA repeat-purchase index is less reliable in those states, The housing affordability index is designed to measure the degree to which a family that earns the median income can afford the mortgage payments on a median price existing single-family home. The index uses a conventional 30year mortgage with a 20% down payment and the FHFA composite mortgage rate. A value of 100 means that a family with the median income has exactly enough income to qualify for a typical mortgage. To qualify the mortgage debt service on the median price home can be no more than 25% of annual income. Higher index values indicate greater affordability. Any change in the index shows that homes are becoming more or less affordable based on changes in income, house prices and mortgage rates. structure as the U.S.; 0 means it has a totally different industrial structure than the U.S. where SYSVOL = systematic volatility; R2 = is the proportion of total variance in metro area i’s growth rate that is associated with contemporaneous fluctuations in national growth. User’s Guide - Page 3 Industrial Diversity Industrial diversity is defined as the extent to which a metro area’s industrial structure approximates the U.S. industrial structure. Employment Volatility Employment volatility is defined as the standard deviation in a metro area’s monthly year-over-year percentage nonagricultural employment growth relative to the standard deviation in U.S. year-over-year percentage nonagricultural employment growth over the past 10 years. Volatility of 100 means that employment volatility in a metro area is equal to employment volatility in the nation. Metro areas tend to be inherently more volatile than states. Diversity is derived using the following formula: Diversity=1/∑((EMPij/EMPUSj)*EMPij) Where EMP=share of employment in four-digit NAICS industry j during the past three years; i=metro area; US=U.S. The Diversity measure is bounded between 0 and 1. 1 means the metro area has the same industrial MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 Employment Volatility Due to U.S. Fluctuations Volatility due to U.S. fluctuations (also known as “systematic volatility”) is defined as: SYSVOL = (Ri2)1/2 Volatility not due to U.S. fluctuations (also known as “nonsystematic volatility”) is defined as: EMPLOYMENT AND INDUSTRY TOP EMPLOYERS Group Management Services Kent State University Summa Health System Akron General Health System Akron Children’s Hospital Goodyear Tire & Rubber Co. Signet Jewelers Inc. FirstEnergy Corp. University of Akron Babcock & Wilcox Power Co. Allstate Insurance Co. Diebold Inc. Giant Eagle Inc. FirstMerit Corp. Fred W. Albrecht Grocery Co. InfoCision Management Co. Jo-Ann Fabric & Craft Stores Robinson Memorial Hospital Newell Rubbermaid Hard Rock Rocksino ENTREPRENEURSHIP INDUSTRIAL DIVERSITY 17 EMPLOYMENT IN NEW COMPANIES, % OF TOTAL Most Diverse (U.S.) 8,499 4,907 4,571 4,180 3,751 3,000 2,854 2,478 2,207 1,900 1,625 1,569 1,391 1,385 1,338 1,200 1,159 946 926 800 1.00 18 0.80 0.69 0.0 0.60 Least Diverse EMPLOYMENT VOLATILITY Due to U.S. fluctuations Relative to U.S. 80% 60% 115 95 100 20% 2,011 16,023 28,055 0% Not due to U.S. 2016 AKR Due to U.S. U.S. COMPARATIVE EMPLOYMENT AND INCOME SECTOR % OF TOTAL EMPLOYMENT AKR 0.1 3.7 11.6 57.5 42.5 3.2 5.4 11.1 1.3 4.3 15.8 16.3 9.8 3.9 13.5 19 Mining Construction Manufacturing Durable Nondurable Transportation/Utilities Wholesale Trade Retail Trade Information Financial Activities Prof. and Bus. Services Educ. and Health Services Leisure and Hosp. Services Other Services Government OH 0.2 3.8 12.5 67.3 32.7 3.9 4.3 10.5 1.3 5.5 13.2 16.8 10.1 3.9 14.2 AVERAGE ANNUAL EARNINGS U.S. 0.4 4.7 8.6 62.5 37.5 3.8 4.1 11.0 1.9 5.7 14.0 15.7 10.8 3.9 15.4 AKR $85,964 $56,184 $72,272 nd nd nd $75,222 $37,356 $71,363 $36,059 $61,955 $51,955 $20,150 $34,612 $65,506 OH $59,929 $61,577 $76,372 $76,930 $75,184 $67,658 $77,559 $31,113 $74,226 $43,556 $63,249 $50,848 $22,786 $35,421 $70,691 U.S. $105,247 $64,491 $80,641 $82,129 $78,132 $63,272 $82,199 $34,349 $112,626 $53,176 $67,695 $53,615 $27,132 $36,277 $76,053 Sources: Percent of total employment — BLS, Moody’s Analytics, 2016, Average annual earnings — BEA, Moody’s Analytics,2015 BUSINESS COSTS Ths AKR Unit labor U.S. Energy 6,937.1 Ths Office rent 40 2010 60 Destination Africa Asia European Union Canada & Mexico South America Rest of world Total $ mil 31.0 541.0 389.0 1,814.8 135.1 108.5 3,019.3 % of GDP Rank among all metro areas 8.4 102 Sources: BEA, International Trade Administration, Moody’s Analytics, 2015 PRODUCTIVITY 22 REAL OUTPUT PER WORKER, $ 76,124 AKR 86,500 79,181 OH U.S. Sources: BEA, Moody’s Analytics, 2015 80 100 120 2015 Source: Moody’s Analytics 3.2 4.8 % of total AKR 25.2 7.4 U.S. 13,565.7 9.4 Source: Moody’s Analytics, 2016 Location Employees Quotient (ths) NAICS Industry % of total 23 10.7 HOUSING-RELATED EMPLOYMENT State and local taxes 20 $ mil ND 589.3 ND ND 338.5 164.0 225.8 ND 638.2 3,019.3 LEADING INDUSTRIES BY WAGE TIER HIGH-TECH EMPLOYMENT U.S.=100 Total 0 1.4 U.S. Product Food and kindred products Chemicals Primary metal manufacturing Fabricated metal products Machinery, except electrical Computer and electronic products Transportation equipment Miscellaneous manufacturing Other products Total 21 100% PUBLIC 1.0 OH EXPORTS 0.00 40% 20 Sources: Census Bureau, Moody’s Analytics, avg 2010-2014 0.20 Source: Crain’s Cleveland Business Book of Lists 2017 Federal State Local 0.5 AKR 0.40 HIGH 18 Diversity and Volatility Formula derived from Hachman index, Bureau of Business and Economic Research, Univ. of Utah, December 1994. MID Moody’s Analytics compiles top employers lists for every region for the most recent year available. Public sector employment, which is generally proportional to a metro area’s population, is provided separately. However, the lists do include public establishments that are not found in every metro area such as military bases or specific federal agencies. Page 3 Sample PRÉCIS® U.S. METRO • Akron OH LOW 17 Top Employers List 5511 6211 5415 4234 GVL 6221 3261 4841 7225 GVS 5613 4451 Management of companies & enterprises Offices of physicians Computer systems design & related srvcs. Prof. & comm. equip. & supp. merch. whlslrs. Local Government General medical and surgical hospitals Plastics product manufacturing General freight trucking Restaurants and other eating places State Government Employment services Grocery stores 24 3.3 1.1 0.6 1.6 0.8 1.6 3.9 1.9 1.0 1.4 0.9 1.1 17.1 6.1 2.8 2.2 27.2 16.4 5.1 4.4 24.0 16.3 7.8 6.7 Source: Moody’s Analytics, 2016 MOODY’S ANALYTICS / Précis® U.S. Metro / October 2017 2 1/2 NONSYS=1-(Ri ) where NONSYS = nonsystematic volatility in metro area i; R2 is the proportion of total variance in metro area i’s growth rate that is associated with contemporaneous fluctuations in national growth. 101 PRÉCIS® U.S. METRO • User’s Guide Formulas modified from “Assessing Regional Economic Stability: A Portfolio Approach,” Economic Review (Federal Reserve Bank of San Francisco), Winter 1990. 19 Comparative Income and Employment The comparative employment and income table shows how the distribution of employment and annual earnings by super sector in a metro area compares with the state and U.S. distributions. Average annual earnings in an industry can differ significantly across metro areas, states and the U.S. Low relative earnings, for example, indicate that the industry has a higher concentration of lowerpaying segments than the state or U.S. or that wages in the industry are lower than elsewhere. Low relative wages may give an area a competitive advantage. Combining employment and income provides a way of determining how much an industry contributes to overall income in a metro area. A relatively small number of jobs in highpaying industries may contribute more to income than a relatively large number of jobs in low-paying industries. 20 Entrepreneurship The Broad-Based Startup Rate (BBSR) is a measure of entrepreneurship in a metro area. It is constructed using county-level data from the Quarterly Workforce Indicators (QWI) produced by the Census Bureau. The QWI is a set of county-level data of quarterly frequency for all 50 states and the District of Columbia that includes the number of employees in firms of different ages in different industries. County-level data are mapped to metropolitan statistical areas. We calculate the ratio of workers in firms less than 2 years old in a particular industry to the total number of workers in the industry for each metro area in each quarter. For each metro area in each quarter, the median ratio of workers in new firms to total workers across 14 industries is calculated (agriculture and mining are excluded, as they tend to be driven more by geographical characteristics rather than startup amenability). By using a median value across industries, we get a truer sense of the amenability to firm entry and startups that is not skewed by large inflows of firms into one particular industry. For example, metro areas that have recently suffered a natural disaster may see a sharp uptick of workers in new construction firms in the quarters that follow, despite the fact that the natural disaster is the cause for the influx in new firms, and not a change in government policy or macroeconomic performance. Finally, in order to smooth out any seasonal effects, a four-quarter moving average is taken of the median ratio of new-firm workers to total workers across industries for each metro area. This number is then divided by the fourquarter moving average of the median for the entire U.S. and then multiplied by 100. This number is the BBSR. A number greater than 100 indicates that the metro area is more amenable to firm entry and entrepreneurship than the overall U.S. average, whereas a number less than 100 indicates the opposite. 5174 5179 5182 5191 5415 5417 5419 6215 23 Housing-Related Employment 21 Exports Metro-level export data are compiled from the U.S. Census Bureau’s Origin of Movement–ZIP code Based Series (OM-ZIP). Thus, the exported merchandise is not necessarily the production origin of the exported goods. Data are available only for merchandise. The degree of exposure that a metro has to international markets is determined by calculating the export share of nominal gross metro product and then by ranking this share across all metro areas. A higher share of exports to GMP is generally positive for a metro area since it indicates that the metro area draws on a larger market for its goods than do areas with smaller shares. However, a higher share increases an area to vulnerability in the event of global disruptions, such as recessions and natural disasters, and fluctuating exchange rates. 22 Productivity Productivity is measured as real output per worker in an area. High productivity incorporates the efficient use of labor, machines, and technological improvements. Generally, more productive areas will also have higher wages. However, higher wages do not necessarily reduce an area’s competitiveness because the higher productivity may more than offset the higher wages. High productivity may also reflect the industry composition in a metro area, as a concentration of more productive industries will boost overall productivity. 23 High-Tech Employment Moody’s Analytics defines high-tech employment as the sum of employment in the following industries: NAICS 3254 3341 3342 3344 3345 3391 5112 5171 5172 Industry Pharm. & Medicine Manuf. Computer and Peripheral Equip. Manuf. Communications Equipment Manuf. Semi. & Other Elec. Comp. Manuf. Nav., Meas., Elec. and Control Instr. Manuf. Medical Equip. and Supplies Manuf. Software Publishers Wired Telecommunications Carriers Wireless Telecom. Carriers (except Sat.) Satellite Telecommunications Other Telecommunications Data Proc., Hosting, & Related Services Other Information Services Computer Sys. Design & Related Services Scientific Research and Dev. Services Other Prof., Scientific and Tech. Services Medical & Diagnostic Laboratories Moody’s Analytics defines housing-related employment as the sum of employment in the following industries: NAICS 2361 238 444 5617 5413 522 5312 4233 5313 Industry Residential Building Construction Specialty Trade Contractors Building Material and Garden Equipment and Supplies Dealers Services to Buildings and Dwellings Architectural, Engineering and Related Services Credit Intermediation and Related Activities Offices of Real Estate Agents and Brokers Lumber and Other Construction Materials Merchant Wholesalers Activities Related to Real Estate 24 Leading Industries by Wage Tier To determine the high-, middle- and low-wage industries for a given geography, the average U.S. wage is calculated first by dividing total salary disbursements by total employment. Average wages by industry are calculated using U.S. level wage and employment data for all four-digit NAICS codes. Next, the standard deviation of the average wages across industries is calculated. One standard deviation centered at the mean defines the upper and lower bounds separating the high, middle and low tiers. The average wage in the given geography for each four-digit NAICS industry is calculated next. The industry is categorized as high, middle or low wage by comparing it with the national high and low cutoffs. The industries are then ranked by size. For each industry, the location quotient is calculated. Location quotients are used to indicate whether the industry serves a market larger than that of the metro area or is an “export” industry. A location quotient greater than 1 likely indicates an export industry. Location quotients are calculated according to the formula: LCim = (Eim/Etm)/(Eius/Etus) where LC = location quotient in metro area m for industry i; E = employment in industry i for metro area m or the U.S.; and t = total employment for metro area m or the U.S. User’s Guide - Page 4 Page 4 Sample PRÉCIS® U.S. METRO • Akron OH SKILLS MISMATCH 25 Skills Mismatch Skills mismatch is determined based on two components: the distribution of educational attainment of a population and the educational characteristics associated with jobs in an area. The two are compared along six dimensions, with each showing how closely aligned the educational attainment of the general population is with the requirements of an area’s jobs. Although educational attainment is not a perfect proxy for skills, it can be quantified in a way that specific skills, such as trade, cannot, making it a useful window into whether an economy faces struggles to find qualified workers or if skilled workers may struggle to find opportunities locally and be forced to migrate elsewhere. MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 Educational attainment for residents is obtained directly from the American Community Survey. The skill requirements side is based on local occupational employment data from the BLS. This was used to construct a matrix of occupations by educational attainment in each place being examined; this is calculated by applying the national educational share for each occupation to the total number employed in each occupation in a specific economy. The total for each educational level across all occupations was then summed to determine educational requirements for an area. The single bar above the chart indicates whether an economy is overeducated or undereducated. This is calculated by using the difference between the population’s educational attainment and requirements for the two highest education categories being examined. The differences are weighted so that mismatches for the highest level (graduate degree) are weighted most heavily. The final figure is 25 % OF TOTAL Less than HS High School MIGRATION FLOWS INTO AKRON OH U Number of Migrants O AKR U.S. Some College ECONOMIC DISENFRANCHISEMENT Associate’s Bachelor’s Graduate 0 5 10 15 20 25 30 35 40 Value 0.47 3.2 14.2% 26 Rank* 149 164 237 *Most unequal=1; Most equal=401 Population Occupations Sources: Census Bureau, ACS, Moody’s Analytics, 2015 HOUSEHOLDS BY INCOME, % PER CAPITA INCOME 20,000-39,999 40,000-59,999 28 60,000-74,999 75,000-99,999 100,000-124,999 125,000-149,999 40 150,000-199,999 200,000+ 35 0 07 08 09 10 11 12 13 14 15 16 5 10 15 AKR 2016 AKR $45,585 AKR $45,974OH $44,593 OH $44,876U.S. $49,246 U.S. $49,571 Sources: BEA, Moody’s Analytics 20 25 U.S. -500 -1,000 76.5% -1,500 -2,000 Top Five Outside Sources of Workers Akron OH Cleveland OH Canton OH Youngstown OH Columbus OH Pittsburgh PA Share 11.2 7.6 1.8 0.1 0.1 EDUCATIONAL ATTAINMENT POPULATION BY GENERATION, % % OF ADULTS 25 AND OLDER 100 80 30 Millennial Gen X 60 20 0 Silent & Greatest AKR 20 25 10 17 12 19 28 29 29 32 31 33 8 10 AKR OH < High school Some college Graduate school 30 U.S. Sources: Census Bureau, Moody’s Analytics, 2016 11 20 40 Baby Boom 15 13 Domestic Foreign Total 14 15 16 2013 2014 2015 2016 -931 1,233 302 -812 1,358 546 -2,767 1,399 -1,368 -2,470 1,364 -1,106 Sources: IRS (top), 2014, Census Bureau, Moody’s Analytics Gen Z 10 -1,897 NETNet MIGRATION, # Migration, AKR 0 29 Share 18.0 3.3 0.9 0.1 0.1 GENERATIONAL BREAKDOWN 5 Net migration 500 Sources: Census Bureau, Moody’s Analytics, avg 2009-2013 0 5,951 3,003 814 750 207 185 165 164 129 123 22,044 1,000 WORKERS WHO LIVE IN AKR 76.0% Top Five Outside Sources of Jobs Akron OH Cleveland OH Canton OH Youngstown OH Columbus OH Pittsburgh PA 27 Cleveland OH Canton OH Youngstown OH Columbus OH Phoenix AZ Chicago IL Pittsburgh PA Austin TX Charlotte NC Tampa FL Total out-migration Sources: Census Bureau, ACS, Moody’s Analytics, 2015 COMMUTER FLOWS RESIDENTS WHO WORK IN AKR 6,223 2,550 904 474 215 125 102 96 87 85 20,147 FROM AKRON OH 0-19,999 $ THS 50 45 Index Gini coefficient Palma ratio Poverty rate Cleveland OH Canton OH Youngstown OH Columbus OH Pittsburgh PA Chicago IL Los Angeles CA Washington DC Cincinnati OH Toledo OH Total in-migration 27 13 U.S. High school College POPULATION BY AGE, % ≥75 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 32 0 1 2 AKR Sources: Census Bureau, ACS, Moody’s Analytics, 2016 MOODY’S ANALYTICS / Précis® U.S. Metro / October 2017 102 3 4 5 6 U.S. Sources: Census Bureau, Moody’s Analytics, 2015 7 8 PRÉCIS® U.S. METRO • User’s Guide indexed to 100 (the black line), such that anywhere over 100 features excess supply of skilled workers, while an economy below 100 does not have enough worker skills to fill all jobs. 26 Economic Disenfranchisement Economic disenfranchisement indicators measure the degree to which income inequality plagues certain economies. To capture this, three measures are used. The Gini coefficient and poverty rates are published by the American Community Survey (ACS), produced by the Census Bureau. The Gini coefficient measures income concentration, with 0 representing perfect equality and 1 representing an economy in which all the wealth is held by one individual. The Palma ratio is a newer measure of income inequality that examines the total income held by earners in the top 10% of households and divides that by aggregate income held by the bottom 40%. This typically requires household-level financial information, but Moody’s Analytics uses a broader distribution of income by household from ACS data to approximate both the numerator and denominator. A higher Palma ratio indicates that a larger share of wealth is concentrated in the wealthiest households in an economy. An advantage of this measure is that it is more sensitive to movements at the tails of the distribution, which typically better represent income inequality given that the middle 50% is typically more stable across history and geographies (for more information, refer to Jose Gabriel Palma’s paper, “Why is inequality so unequal across the world?”). 27 Migration Flows IRS data. When a taxpayer notifies the IRS of a change in address, the IRS records the household’s current county of residence, the county to which the household is moving, and the number of household members. Moody’s Analytics aggregates these data by metro area into gross migration. The data are then sorted to show the 10 metro areas providing the largest number of new residents and the 10 metro areas to where the largest number of current residents moves. Subtracting the gross outmigration flows from the gross in-migration flows gives net out-migration. The IRS migration data cover only households that file returns and thus do not provide a complete tally of domestic migration flows. Census data. The Census measure of net migration attempts to capture all migration to and from counties. Unlike the IRS data, Census data cover all migrants, including international migrants. Moody’s Analytics aggregates county net migration data to metro areas and to states. Domestic and international net migration were reestimated for years 2001-2010, because the Census has no plans to do this. Pre-existing net migration estimates (derived from new census population estimates combined with constant birth and death rates) were used. The “weights” for domestic and international migration are the same as those that existed before. 28 Per Capita Income Per capita income is defined as personal income divided by population. It is not adjusted for inflation. 29 Commuter Flows Metro area commuter flows are derived from countylevel figures reported in the 2009-2013 American Community Survey (ACS) Journey to Work data. The ACS creates estimates based on where surveyed individuals worked in a given week and matched that against their place of residence. Moody’s Analytics aggregated these counties to metro areas and examined flows at this higher-level geography. The data are split into two sections. The first represents the commuting patterns of residents of an area; the second shows the commuting patterns of workers in an area. While these are correlated, there can be noticeable differences; for example, a large urban metro area likely attracts a material share of workers from elsewhere, with a smaller share of its residents commuting outside of the area. provides a glimpse of which places are most closely linked economically to the area. 30 Generational Breakdown The distribution of an area’s population into generations employs definitions from the Pew Research Center. Generations are defined by the following birth years: The Greatest Generation – 1901 to 1927 The Silent Generation – 1928 to 1945 The Baby Boom Generation – 1946 to 1964 Generation X – 1965 to 1980 The Millennial Generation – 1981 to 1998 Generation Z – 1999 to present 31 Educational Attainment The Census Bureau provides data on the educational attainment of residents older than 25 years of age of metro areas and their component counties, states, and the U.S. Educational attainment reflects the industrial composition of an area as well as the prospects that an area has in expanding its industries. 32 Population by Age The Census Bureau provides data on population by age for metro areas and their component countries, states, and the U.S. A distribution that differs significantly from the national distribution has implications for the labor, housing and consumer markets in an area. For example, a distribution skewed toward older cohorts implies higher than average demand for healthcare services and lower than average demand for single-family housing. Region Definition The pie charts reflect the share of residents or workers whose commute does not extend beyond a metro area’s borders. Not surprisingly, each figure averages higher than 80%, as metro areas are defined in large part by commuting patterns to begin with. The rank indicates how self-sufficient an area is. The tables below each chart show where residents work and where workers reside. This The Moody’s Analytics definition of the Northeast differs from the Census Bureau’s definition of the Northeast Census Region in that it includes Maryland, Delaware, and the District of Columbia in addition to Middle Atlantic and New England states. The Moody’s Analytics definition of the South excludes Maryland, Delaware, and the District of Columbia. The Moody’s Analytics definitions of the Midwest and West match the Census Bureau’s definitions of the Midwest and West Census Regions, respectively. Income distribution. Travel time to work. This map illustrates the median household income within each block group of a state or metro area. Median Household Income estimates by block group come from the U.S. Census Bureau’s American Community Survey and are updated annually. This map illustrates the average commute time to work for those employed outside of their place of residence within each block group of a state or metro area. The map indicates the areas within the MSA where employment and output are concentrated—areas with the shortest average commute times generate the most output. The aggregate commute time to work in minutes by block group and the number of employees who work outside of their place of residence by block group come from the U.S. Census Bureau’s American Community Survey and are updated annually. Moody’s Analytics calculates the average commute time to work for each block group. User’s Guide - Page 5 Maps Population density. This map illustrates the number of residents per square mile within each census block group of a state or metro area. A block group is a collection of adjacent census blocks and is the smallest geographic unit for which the Census Bureau publishes sample data. Population estimates by block group come from the U.S. Census Bureau’s American Community Survey and are updated annually. The U.S. Census Bureau’s Geography Division reports the area of each block in square meters every 10 years. Moody’s Analytics converts the area in square meters to square miles and calculates the population per square mile for each block group. MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 103 PRÉCIS® U.S. METRO • User’s Guide Metro Classifications Agriculture FED. GOV. Federal Government–Nondefense $ AGRICULTURE FR 311 312 4238 4245 4249 4442 4931 Farms Food Manufacturing Beverage and Tobacco Product Manufacturing Machinery, Equipment and Supplies Merchant Wholesalers Farm Product Raw Material Merchant Wholesalers Miscellaneous Nondurable Goods Merchant Wholesalers Lawn and Garden Equipment and Supplies stores Warehousing and Storage COLLEGE College Towns TOWN Metro areas in this category are heavily reliant on a large university or universities for employment growth. They do not generally fluctuate in tandem with national business cycles and are usually more stable than other metro areas. DEFENSE Defense Metro areas in this category are heavily dependent on military bases and/or spending on defense-related manufacturing and services. The share of military employment in these areas is well above the national average, and consequently they generally have low industrial diversity levels. The most prominent upside risk these metro areas are faced with is the prospect of attracting defense-related firms in the private sector. However, any significant reduction in the number of military personnel will hurt the economies of these metro areas. Generally, these areas do not follow the national business cycle because of the limited importance of the private sector to the local economy. Defenserelated manufacturing is also sensitive to changes in government spending priorities. As defined under the North American Industrial Classification System: Defense-related employment includes the following industries in addition to direct government employment, although some of these industries also include nondefense activities: GVFD 3329 3341 3342 3345 3364 3366 3369 4831 5413 5415 5416 5417 Department of Defense Ammunition, Small Arms, Other Ordnance and Accessories Manufacturing Computer and Peripheral Equipment Manufacturing Communications Equipment Manufacturing Navigational, Measuring, Electromedical and Control Instruments Manufacturing Aerospace Product and Parts Manufacturing Ship and Boat Building Armored Military Trucks Deep Sea, Coastal and Great Lakes Water Transportation Architectural, Engineering, Mapping Services Computer Systems Design Management, Scientific and Technical Consulting Scientific Research and Development ENERGY & Energy Production/Distribution Hubs This category has a heavy concentration of firms involved in natural resource production and distribution. Commodity prices play a large RESOURCES role in employment trends in these metro areas. With developing countries’ energy needs growing rapidly, demand for the products produced and distributed should remain high over the next few years. However, stricter carbon emission legislation does pose a downside risk to employment growth. Energy production/distribution hubs were identified by the energy/mining/utilities employment location quotient. Energy/mining/utilities employment is defined as the aggregate of employment in the following industries, as defined under the North American Industrial Classification System: 2111 2121 2122 2123 2211 2212 2131 2213 3241 486 Oil and Gas Extraction Coal Mining Metal Ore Mining Nonmetallic Mineral Mining and Quarrying Electric Power Generation, Transmission and Distribution Natural Gas Distribution Support Activities for Mining Water, Sewage and Other Systems Petroleum and Coal Products Manufacturing Pipeline Transportation MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 $ Areas with a dependence on the federal government include a high share of federal government employment as well as high exposure to nondefense-related federal government contracts. Such areas have generally been stable, but more recently they have been vulnerable to changing federal government spending priorities, particularly cuts in the growth of government spending. It is difficult to isolate private industries since many industries can receive government contracts. $ Metro areas with a high concentration of agriculture are those with a higher than average share of farm employment and farm income. In addition, such areas include a high share of food processing that is directly related to the agricultural produce in the area. Activities related to agriculture are either totally or partly included in the following industries as defined under the North American Industrial Classification System: NONDEFENSE FINANCIAL $ € Financial Centers Metro areas in this category have a relatively large concentration £ of non-real estate related employment in financial services and CENTER are heavily dependent upon the health of global equity and credit markets. Rapid economic growth in developing countries has given a larger percentage of the world’s population greater access to financial markets, particularly equity markets. Jobs in these industries generally pay high salaries. Financial centers are identified by the financial employment location quotient. Financial employment is defined as the aggregate of employment in the following industries, as defined under the North American Industrial Classification System: 5211 5221 5222 5223 5239 5511 5231 5232 5241 5242 5251 5259 5331 8132 Monetary Authorities–Central Bank Depository Credit Intermediation Nondepository Credit Intermediation Activities Related to Credit Intermediation Other Financial Investment Activities Management of Companies and Enterprises Securities and Commodity Contracts Intermediation and Brokerage Securities and Commodity Exchanges Insurance Carriers Agencies, Brokerages, and Other Insurance-Related Activities Insurance and Employee Benefit Funds Other Investment Pools and Funds Lessors of Nonfinancial Intangible Assets (except Copyrighted Works) Grantmaking and Giving Services LOGISTICS Logistics Metro areas in this category are heavily influenced by domestic and global business cycles. Slowdowns in overall economic activity generally influence these areas to a greater degree than most other metro areas. Areas with more extensive exposure to developing economies, either through the presence of deep sea ports or air transportation hubs, will outperform those that are more dependent on the U.S. economy. Transportation hubs were identified by the transportation and distribution employment location quotient. Transportation and distribution employment is defined as the aggregate of employment in the following industries, as defined under the North American Industrial Classification System: 4831 4832 4883 4885 4882 4889 4821 4841 4931 4884 4231 4232 4233 4234 4235 4236 4237 4238 4239 4251 4241 4242 4243 4244 4246 4247 Deep Sea, Coastal and Great Lakes Water Transportation Inland Water Transportation Support Activities for Water Transportation Freight Transportation Arrangement Support Activities for Rail Transportation Other Support Activities for Transportation Rail Transportation General Freight Trucking Warehousing and Storage Support Activities for Road Transportation Motor Vehicle and Motor Vehicle Parts and Supplies Merchant Wholesalers Furniture and Home Furnishing Merchant Wholesalers Lumber and Other Construction Materials Merchant Wholesalers Professional and Commercial Equipment and Supplies Merchant Wholesalers Metal and Mineral (except Petroleum) Merchant Wholesalers Electrical and Electronic Goods Merchant Wholesalers Hardware, Plumbing and Heating Equipment and Supplies Merchant Wholesalers Machinery, Equipment and Supplies Merchant Wholesalers Miscellaneous Durable Goods Merchant Wholesalers Wholesale Electronic Markets and Agents and Brokers Paper and Paper Product Merchant Wholesalers Drugs and Druggists’ Sundries Merchant Wholesalers Apparel, Piece Goods and Notions Merchant Wholesalers Grocery and Related Product Wholesalers Chemical and Allied Products Merchant Wholesalers Petroleum and Petroleum Products Merchant Wholesalers 104 PRÉCIS® U.S. METRO • User’s Guide Metro Classifications 4248 4249 4812 4842 4921 4922 Beer, Wine, and Distilled Alcoholic Beverage Merchant Wholesalers Miscellaneous Nondurable Goods Merchant Wholesalers Nonscheduled Air Transportation Specialized Freight Trucking Couriers Local Messengers and Local Delivery MANUFAC Manufacturing These areas maintain a high dependence on manufacturing and manufacturing-related employment. They typically have a large TURING concentration of industries such as domestic auto, industrial machinery and textile manufacturing. Per capita income growth is generally well below the national average because many of the lost manufacturing jobs paid high wages and some manufacturers, particularly auto-related manufacturing, have implemented two-tier wage systems. Additionally, while manufacturing employment has declined in most of these areas, many have not been able to develop alternative growth drivers. As a result, demographic trends are typically weak. MEDICAL Medical Centers Metro areas in this category have a relatively high share of employment at general and specialty hospitals, as well as medical laboratories. Their long-term growth prospects are excellent, CENTER largely because of the aging of the U.S. population. As an increasing percentage of the baby boomers become senior citizens, their demand for healthcare will steadily increase, with these metro areas being the primary beneficiaries. Medical centers are identified by the hospital and medical labs employment location quotient. Hospital and medical labs employment is defined as the aggregate of employment in the following industries, as defined under the North American Industrial Classification System: 6221 6222 6223 6215 General Medical and Surgical Hospitals Psychiatric and Substance Abuse Hospitals Specialty (except Psychiatric and Substance Abuse) Hospitals Medical and Diagnostic Laboratories RETIREE Retiree Haven Metro areas in this category have exhibited robust in-migration, above-average growth in the 65 and older age cohort, and have a relatively large proportion of their population aged 65 and older. HAVEN These areas will see steady demand for multifamily housing over the long term, as well as healthy growth in leisure/hospitality services. Moreover, rapid population growth will limit the cyclical volatility in these metro areas. STATE CAPITAL State Capital The metro areas in this category are home to their respective state capitals. They depend heavily on tax revenue growth to sustain their economies. MOODY’S ANALYTICS / Précis® U.S. Metro / April 2021 HIGH TECH Tech Centers Metro areas in this category have an extensive presence of firms involved in electronic and biomedical manufacturing, telecommunications carriers, and scientific research facilities. These areas attract a large number of highly skilled workers, which is reflected in the high share of residents who hold a bachelor’s degree. Not only will these areas record above-average employment growth, but they will also experience a rapid expansion in per capita income levels. Tech centers were identified by the high technology using employment location quotient. High tech using employment is defined as the aggregate of employment in the following industries as defined under the North American Industrial Classification System: 3254 3341 3342 3344 3345 3391 5112 5171 5172 5173 5174 5179 5181 5182 5415 5417 5419 6215 Pharmaceutical and Medicine Manufacturing Computer and Peripheral Equipment Manufacturing Communications Equipment Manufacturing Semiconductor and Other Electronic Component Manufacturing Navigational, Measuring, Electromedical, and Control Instruments Manufacturing Medical Equipment and Supplies Manufacturing Software Publishers Wired Telecommunications Carriers Wireless Telecommunications Carriers (except Satellite) Telecommunications Resellers Satellite Telecommunications Other Telecommunications Internet Service Providers and Web Search Portals Data Processing, Hosting and Related Services Computer Systems Design and Related Services Scientific Research and Development Services Other Professional, Scientific and Technical Services Medical and Diagnostic Laboratories TOURIST Tourism Destinations Metro areas in this category have a large concentration of firms involved in entertainment, sightseeing and vacation activities. These areas are dependent upon both consumer spending and exchange DESTINATION rates. If consumers are cutting back on their discretionary spending, these areas will be hit particularly hard because of their reliance on industries that are closely tied with discretionary consumer spending patterns. Exchange rates also play a large role in the health of these metro areas. A depreciating U.S. dollar makes vacationing domestically relatively cheap and greatly benefits areas in this category, while the opposite is true when the dollar is appreciating. Tourism destinations were identified by the tourism and entertainment employment location quotient. Tourism and entertainment employment is defined as the aggregate of employment in the following industries, as defined under the North American Industrial Classification System: 487 4811 4881 5615 5121 7211 7212 7139 7111 7112 7131 7132 7115 7121 5122 Scenic and Sightseeing Transportation Scheduled Air Transportation Support Activities for Air Transportation Travel Arrangement and Reservation Services Motion Picture and Video Industries Traveler Accommodation RV (Recreational Vehicle) Parks and Recreational Camps Other Amusement and Recreation Industries Performing Arts Companies Spectator Sports Amusement Parks and Arcades Gambling Industries Independent Artists, Writers and Performers Museums, Historical Sites and Similar Institutions Sound Recording Industries 105 BOSTON MA Data Buffet® MSA code: IUSA_DMBOS ECONOMIC DRIVERS MEDICAL HIGH TECH FINANCIAL 2020-2022 2020-2025 1st quintile 1st quintile 47 $£€ CENTER RELATIVE COSTS EMPLOYMENT GROWTH RANK CENTER 42 Recovery Best=1, Worst=410 At Risk STRENGTHS & WEAKNESSES STRENGTHS » Business capital of New England. » Access to skilled labor force and venture capital for emerging companies. » Dynamic high-tech and biomedical research industries. » Labor market stability due to education/ healthcare. WEAKNESSES » High business and living costs. » High exposure to cyclical finance and tech. COVID-19 EXPOSURE May 2021 LONG TERM 22 1st quintile W W FORECAST RISKS SHORT TERM Most=1 Least=403 UPSIDE » Continued rise in equity prices provides a larger than expected boost to finance hiring. » Healthcare employment bounces back sooner than anticipated. DOWNSIDE » Population growth sputters as remote working enables more out-migration. » It takes longer than expected to replace local services firms that failed. MOODY’S RATING Aaa 2015 2016 175.7 5.1 1,209.2 2.4 4.5 7.2 74.3 1,986.3 0.7 7.4 1,626 6,311 255.1 179.7 2.3 1,240.7 2.6 3.8 5.5 78.0 2,001.9 0.8 8.8 1,882 4,519 269.5 CITY AS OF MAR 01, 2016 2017 QUALITY RELATIVE OF LIFE U.S.=100% Best=1, Worst=403 Best=1, Worst=378 53 ANALYSIS Late Expansion In Recession BUSINESS 123% 131% 0.61 Rank: 39 BUSINESS CYCLE STATUS Mid Expansion LIVING VITALITY Recent Performance. Boston’s economy is heading in the right direction, although it is still digging out of a very large hole. As of April, employment was 9.5% below its pre-pandemic peak, a much weaker showing than regionally or nationally. Fortunately, BOS has added jobs faster than the Northeast and the U.S. since the start of this year thanks to strengthening in finance, professional/business services, healthcare, leisure/hospitality, and retail. On the other hand, local service industries that were hit hardest by the pandemic still have more losses to recoup than their U.S. peers. The weak labor market means that the unemployment rate is higher than nationally. Meanwhile, the housing market is faring well as house price appreciation exceeds the nation’s and residential building is picking up. Healthcare. BOS’s economy will take longer than the U.S. to recover from the pandemic partially because of sore spots in the large healthcare industry. BOS’s reliance on healthcare jobs is nearly 1½ times that of the U.S. due to the older-than-average population and the large cluster of destination hospitals. The good news is that employment at BOS’s hospitals is nearing its pre-pandemic peak and will rise in coming months due to solid demand from both local and regional patients. On the downside, healthcare jobs are down far more than nationally due to struggles at doctors’ offices and nursing care facilities. Doctors’ offices have paid the price for a reduction in elective procedures, and nursing homes took it on the chin as occupancy plunged. The winding down of the pandemic will spark a recovery, but it will take time for providers to recoup lost revenue and add to payrolls. Finance. The large finance industry has fared well during the pandemic, but near-term gains will be muted. BOS’s reliance on finance employment is among the nation’s highest thanks 2018 2019 2020 INDICATORS 184.4 191.3 2.6 3.8 1,259.3 1,269.6 1.5 0.8 3.6 3.2 5.7 5.6 82.0 86.7 2,016.9 2,024.8 0.7 0.4 8.9 1.9 1,875 1,920 6,551 5,392 285.5 300.9 195.6 2.2 1,291.8 1.7 2.8 3.4 92.0 2,031.9 0.3 1.5 1,684 4,677 314.0 187.8 -4.0 1,159.8 -10.2 9.3 4.4 91.3 2,033.8 0.1 -1.7 1,840 4,964 328.1 Gross metro product (C12$ bil) % change Total employment (ths) % change Unemployment rate (%) Personal income growth (%) Median household income ($ ths) Population (ths) % change Net migration (ths) Single-family permits (#) Multifamily permits (#) FHFA house price (1995Q1=100) MOODY’S ANALYTICS / Précis® U.S. Metro / May 2021 to the large contingent of banks and investment managers. Such institutions did not reduce headcounts much in the past year as they benefited from soaring stock and bond prices and the absence of widespread defaults and bankruptcies in the broader economy. However, asset prices are unlikely to rise much further and actively managed investment funds face stiff competition from passively managed funds that charge lower fees and employ fewer people. Thus, near-term hiring will be subdued, which will slow gains in industries reliant on local spending. Demographics. Weak demographics will also weigh on BOS’s recovery. Although its population fell in 2020, conditions are ripe for population additions to resume. The subsiding pandemic and immigration-friendly policies from the Biden administration will allow more foreign workers to move to BOS. Unfortunately, the permanent increase in remote work will curtail population gains, which were trailing the nation’s even before the pandemic. Some well-paid finance and IT staff who can work remotely full time will move to less expensive locales, and some workers who only need to come into the office occasionally will purchase single-family homes farther away from BOS in Cambridge, New Hampshire and Rhode Island. Boston’s economy will continue to recover in coming months, but a full recovery will take longer than nationally. Consumer-reliant industries have a deep hole to dig out of and increased remote working will slow population gains. Fortunately, BOS will best the Northeast in the long run due to dynamic industries and proximity to world-class universities. 1-866-275-3266 Marc Korobkin help@economy.com May 2021 2021 2022 2023 204.5 215.9 8.9 5.6 1,196.2 1,265.5 3.1 5.8 6.6 4.6 3.6 0.5 95.2 94.7 2,039.2 2,043.6 0.3 0.2 2.3 0.3 3,025 3,480 2,777 1,770 342.6 351.9 222.2 2.9 1,298.0 2.6 3.1 6.1 99.1 2,053.0 0.5 5.6 3,991 2,501 356.4 2024 2025 2026 229.9 236.9 243.1 3.4 3.1 2.6 1,314.7 1,327.9 1,338.3 1.3 1.0 0.8 2.7 3.0 3.2 6.4 6.1 5.8 104.1 109.3 114.5 2,063.0 2,072.3 2,081.2 0.5 0.5 0.4 6.4 6.0 5.9 4,494 4,494 4,219 3,241 3,063 2,667 358.5 360.7 363.8 PRÉCIS® U.S. METRO • Boston MA ECONOMIC HEALTH CHECK 3-MO MA Nov 20 16.3 9.0 66.5 34.7 102.0 1,737 5,286 Dec 15 28.0 Employment, change, ths Unemployment rate, % Labor force participation rate, % Average weekly hours, # Industrial production, 2012=100 Residential permits, single-family, # Residential permits, multifamily, # Dec/Dec Employment, change, ths Better than prior 3-mo MA Dec 20 8.4 8.6 66.9 34.6 103.1 2,007 6,135 Dec 16 27.2 Jan 21 4.1 8.3 67.3 34.7 103.7 2,283 6,418 Dec 17 17.4 BUSINESS CYCLE INDEX Feb 21 3.4 7.8 67.4 34.5 103.9 2,533 4,840 Dec 18 9.4 Unchanged from prior 3-mo MA Mar 21 5.7 7.2 67.4 34.7 103.7 2,521 4,029 Dec 19 22.0 Apr 21 6.7 6.7 67.3 34.6 103.8 2,445 8,315 Dec 20 -146.6 JAN 2011=100 130 125 120 115 110 105 100 95 10 11 12 13 14 15 16 17 18 19 20 21 BOS Worse than prior 3-mo MA Source: Moody’s Analytics Sources: BLS, Census Bureau, Moody’s Analytics CURRENT EMPLOYMENT TRENDS Total Mining Construction Manufacturing Trade Trans/Utilities Information Financial Activities Prof & Business Svcs. Edu & Health Svcs. Leisure & Hospitality Other Services Government 10 0 -10 -20 -30 16 17 Government 18 19 DIFFUSION INDEX % CHANGE YR AGO, 3-MO MA Apr 20 Oct 20 Apr 21 % CHANGE YR AGO 20 20 21 Goods producing Private services Sources: BLS, Moody’s Analytics -5.7 -4.1 -7.9 -5.1 -9.6 -8.4 -0.8 -1.9 0.2 -3.3 -21.7 -15.6 0.3 -11.7 -3.9 -5.2 -7.5 -11.1 -24.9 -7.4 -4.5 -4.0 -8.9 -40.1 -26.0 -4.0 -2.9 8.4 9.2 -1.5 3.4 -7.6 -4.8 -0.3 0.2 -3.6 -19.9 -8.5 -2.3 Sources: BLS, Moody’s Analytics 3-DIGIT NAICS LEVEL, 6-MO MA 70 65 60 55 50 14 15 16 BOS 19 20 U.S. 21 13 19 HOUSE PRICE JAN 2011=100 100 95 90 2-Yr 5-Yr X X X 120 115 110 105 X X X FORECAST VS. 6 MO PRIOR 125 1998Q1=100, NSA 280 260 240 220 200 180 160 140 120 100 80 98 11 12 13 14 15 16 17 18 19 20 21F 22F 23F 24F 25F MA 17 18 MA Sources: BLS, Moody’s Analytics RELATIVE EMPLOYMENT PERFORMANCE BOS U.S. MA 01 BOS U.S. 04 07 10 MA 16 U.S. Sources: FHFA, Moody’s Analytics Sources: BLS, Moody’s Analytics RENTAL AFFORDABILITY HOUSE PRICE TRENDS HOUSING AFFORDABILITY GREATER THAN 100=MORE AFFORDABLE % GREATER THAN 100=MORE AFFORDABLE 190 50 180 40 220 200 180 160 140 120 100 80 60 30 170 20 160 10 150 0 140 -10 -20 130 95 97 99 01 03 05 07 09 11 13 15 17 19 BOS MA U.S. Sources: Census Bureau, BLS, Moody’s Analytics MOODY’S ANALYTICS / Précis® U.S. Metro / May 2021 98 01 04 07 Overvalued Sources: FHFA, Moody’s Analytics 10 13 16 Undervalued 19 95 97 99 01 03 05 07 09 11 13 15 17 19 BOS MA Sources: NAR, Moody’s Analytics U.S. PRÉCIS® U.S. METRO • Boston MA EMPLOYMENT AND INDUSTRY TOP EMPLOYERS ENTREPRENEURSHIP INDUSTRIAL DIVERSITY Mass General Brigham University of Massachusetts Stop & Shop Supermarket Co. Steward Health Care System Boston University State Street Corp. Boston Medical Center Health System Wayfair LLC Northeastern University Fidelity Investments Verizon Communications Liberty Mutual Insurance Dana-Farber Cancer Institute Inc. Bank of America Boston College Santander Bank Blue Cross Blue Shield Medical Insurance John Hancock Financial Eversource Energy Cushman & Wakefield BROAD-BASED START-UP RATE U.S.=100, 4-QTR MA Most Diverse (U.S.) 74,013 23,614 20,153 16,977 10,514 9,997 7,612 6,100 5,740 5,700 5,640 5,559 5,453 5,000 4,216 3,961 3,788 3,752 3,472 3,424 2019 1.00 0.80 0.65 0 0.60 Least Diverse EMPLOYMENT VOLATILITY Due to U.S. fluctuations Relative to U.S. 100 80 60 145 95% 100 20 20,408 47,748 76,881 0 2020 Not due to U.S. BOS Due to U.S. U.S. COMPARATIVE EMPLOYMENT AND INCOME % OF TOTAL EMPLOYMENT BOS 0.0 4.2 3.2 55.5 44.5 2.9 3.0 7.9 2.6 10.4 18.5 23.5 7.8 3.4 12.5 MA 0.0 4.5 6.8 65.5 34.5 2.8 3.4 9.4 2.6 6.4 17.2 22.5 7.8 3.4 13.0 U.S. 0.4 5.1 8.6 62.2 37.8 4.3 4.0 10.4 1.9 6.1 14.2 16.3 9.4 3.8 15.4 AVERAGE ANNUAL EARNINGS BOS nd $102,897 $103,985 nd nd $62,031 $112,879 $47,856 $119,162 $126,695 $126,324 $74,642 $44,883 $51,346 $107,100 MA U.S. $61,392 $152,860 $88,273 $71,226 $110,311 $87,452 $120,296 $90,347 $92,356 $82,632 $57,986 $65,743 $110,569 $92,590 $41,142 $38,405 $132,671 $136,729 $85,318 $59,335 $109,939 $76,266 $65,380 $59,504 $37,490 $31,046 $46,223 $39,932 $95,132 $83,178 Sources: Percent of total employment — BLS, Moody’s Analytics, 2020, Average annual earnings — BEA, Moody’s Analytics, 2019 BUSINESS COSTS HIGH-TECH EMPLOYMENT Energy BOS 79.3 6.8 U.S. 7,540.4 5.3 HOUSING-RELATED EMPLOYMENT State and local taxes Ths Office rent 2013 150 200 2018 Source: Moody’s Analytics MOODY’S ANALYTICS / Précis® U.S. Metro / May 2021 250 HIGH Unit labor % of total MID Ths 100 Product Food and kindred products Chemicals Primary metal manufacturing Fabricated metal products Machinery, except electrical Computer and electronic products Transportation equipment Miscellaneous manufacturing Other products Total $ mil ND 3,250.4 ND ND 2,969.6 7,172.2 1,968.4 2,754.1 5,391.0 23,505.9 Destination Africa Asia European Union Canada & Mexico South America Rest of world Total $ mil 247.7 8,731.0 7,747.4 4,464.3 642.3 1,673.2 23,505.9 % of GDP Rank among all metro areas 5.0 169 Sources: BEA, International Trade Administration, Moody’s Analytics, 2019 PRODUCTIVITY REAL OUTPUT PER WORKER, $ 116,356 BOS 105,325 MA 93,674 U.S. Sources: BEA, Moody’s Analytics, 2019 NAICS Industry % of total BOS 117.8 10.2 U.S. 14,373.7 10.1 Source: Moody’s Analytics, 2020 LOW Total 50 100 LEADING INDUSTRIES BY WAGE TIER U.S.=100 0 80 MA EXPORTS 0.00 PUBLIC 60 Sources: Census Bureau, Moody’s Analytics 0.20 40 Sector Mining Construction Manufacturing Durable Nondurable Transportation/Utilities Wholesale Trade Retail Trade Information Financial Activities Prof. and Bus. Services Educ. and Health Services Leisure and Hosp. Services Other Services Government 40 BOS 0.40 Source: Boston Business Journal Book of Lists, 2020 Federal State Local 20 6221 6113 5239 5221 GVL GVS 5613 7211 7225 6241 4451 5617 General medical and surgical hospitals Colleges, universities and prof. schools Other financial investment activities Depository credit intermediation Local Government State Government Employment services Traveler accommodation Restaurants and other eating places Individual and family services Grocery stores Services to buildings and dwellings Source: Moody’s Analytics, 2020 Location Employees Quotient (ths) 2.3 2.5 7.3 1.7 0.7 1.2 0.8 1.0 0.9 1.4 1.1 1.0 86.9 37.1 27.7 24.8 77.6 51.9 22.5 14.9 80.6 25.0 24.8 16.3 PRÉCIS® U.S. METRO • Boston MA SKILLS MISMATCH MIGRATION FLOWS % OF TOTAL INTO BOSTON MA Less than HS Undereducated High School Balanced Overeducated BOS Some College U.S. ECONOMIC DISENFRANCHISEMENT Associate’s Bachelor’s Graduate 0 5 10 15 20 25 30 Index Gini coefficient Palma ratio Poverty rate Rank* 32 17 321 *Most unequal=1; Most equal=403 Population Occupations Sources: Census Bureau, ACS, Moody’s Analytics, 2018 HOUSEHOLDS BY INCOME, % PER CAPITA INCOME 40,000-59,999 60,000-74,999 70 75,000-99,999 60 100,000-124,999 50 125,000-149,999 40 150,000-199,999 200,000+ 30 10 11 12 13 14 15 16 17 18 19 20 2020 BOS MBO $87,642 MAMA $79,721 0 2 4 U.S. U.S. $59,729 Sources: BEA, Moody’s Analytics 6 8 10 12 14 16 18 BOS U.S. 26,384 11,313 3,489 3,208 2,413 1,126 885 789 764 749 80,323 Net migration Sources: Census Bureau, ACS, Moody’s Analytics, 2019 -12,856 NET MIGRATION, Net Migration, BOS # COMMUTER FLOWS RESIDENTS WHO WORK IN BOS 22,492 8,016 3,569 2,678 2,049 879 735 733 706 679 67,467 Cambridge MA Providence RI New York NY Worcester MA Barnstable Town MA Los Angeles CA Washington DC Portland ME Rockingham County NH Chicago IL Total out-migration 20,000-39,999 80 Cambridge MA Providence RI New York NY Worcester MA Barnstable Town MA Washington DC Chicago IL Hartford CT Los Angeles CA Springfield MA Total in-migration FROM BOSTON MA 0-19,999 $ THS 90 2018 0.50 3.9 10.6% Number of Migrants 10,000 WORKERS WHO LIVE IN BOS 8,000 6,000 4,000 2,000 78.9% 0 67.2% -2,000 Top Outside Sources of Jobs Boston MA Cambridge MA Providence RI Worcester MA Barnstable Town MA New York NY Share 14.8 3.4 1.1 0.7 0.1 Top Outside Sources of Workers Boston MA Cambridge MA Providence RI Worcester MA Barnstable Town MA Rockingham County NH -4,000 Share 20.4 7.4 2.1 0.7 0.5 GENERATIONAL BREAKDOWN EDUCATIONAL ATTAINMENT POPULATION BY GENERATION, % % OF ADULTS 25 AND OLDER 100 Gen Z 22 20 60 26 25 Gen X 40 21 22 Baby Boom 20 22 9 24 9 BOS MA 80 Millennial 0 Silent & Greatest 5 10 15 BOS 20 25 Domestic Foreign Total 18 19 20 2017 2018 2019 2020 -8,746 17,965 9,219 -10,785 12,983 2,198 -8,833 12,286 3,453 -13,388 9,717 -3,671 Sources: IRS (top), 2018, Census Bureau, Moody’s Analytics Sources: Census Bureau, Moody’s Analytics, avg 2011-2015 0 17 30 U.S. Sources: Census Bureau, Moody’s Analytics, 2019 MOODY’S ANALYTICS / Précis® U.S. Metro / May 2021 < High school Some college Graduate school 13 20 29 27 11 U.S. High school College Sources: Census Bureau, ACS, Moody’s Analytics, 2019 POPULATION BY AGE, % ≥75 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 0 2 BOS 4 6 U.S. 8 Sources: Census Bureau, Moody’s Analytics, 2019 10 PRÉCIS® U.S. METRO • Boston MA GEOGRAPHIC PROFILE POPULATION DENSITY MEDIAN HOUSEHOLD INCOME POPULATION & HOUSING CHARACTERISTICS Units Total area Total water area Total land area Land area - developable Land area - undevelopable sq mi sq mi sq mi sq mi sq mi 1,657.8 544.3 1,113.3 1,109.4 4.1 219 38 275 130 340 pop. to developable land ths % of population % of population % of population 1,813.9 2,034.7 77.1 11.3 9.2 17 39 368 28 50 37.3 266 Population density Total population U.S. citizen at birth Naturalized U.S. citizen Not a U.S. citizen MEDIAN COMMUTE TIME Value Rank* Median age Total housing units Owner occupied Renter occupied Vacant ths % of total % of total % of total 836.8 53.2 38.9 7.9 39 318 31 300 1-unit; detached 1-unit; attached % of total % of total 41.9 5.5 397 124 Multifamily % of total Median year built 51.8 1960 3 * Areas & pop. density, out of 410 metro areas/divisions, including metros in Puerto Rico; all others, out of 403 metros. Sources: Census Bureau, Moody’s Analytics, 2019 except land area 2010 Sources: ACS, Moody’s Analytics MOODY’S ANALYTICS / Précis® U.S. Metro / May 2021 About Moody’s Analytics Moody’s Analytics provides financial intelligence and analytical tools supporting our clients’ growth, efficiency and risk management objectives. The combination of our unparalleled expertise in risk, expansive information resources, and innovative application of technology helps today’s business leaders confidently navigate an evolving marketplace. We are recognized for our industry-leading solutions, comprising research, data, software and professional services, assembled to deliver a seamless customer experience. Thousands of organizations worldwide have made us their trusted partner because of our uncompromising commitment to quality, client service, and integrity. 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