Patterns of economic change by state and area : income, employment, & gross domestic product

著者

    • Ryan, Mary Meghan
    • Anderson, Hannah M.
    • Krog, Hannah Anderson

書誌事項

Patterns of economic change by state and area : income, employment, & gross domestic product

edited by Mary Meghan Ryan

Bernan Press, 2013-

  • 1st ed. : 2013
  • 2nd ed. : 2014
  • 3rd ed. : 2015
  • 4th ed. : 2016
  • 5th ed. : 2017
  • 6th ed. : 2018
  • 7th ed. : 2019

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注記

Edited by Hannah M. Anderson (4th ed., 2016), Hannah Anderson Krog (5th ed., 2017-)

"Special edition of Business statistics of the United States"--Cover of 2013, 2015, 2017-

内容説明・目次

巻冊次

1st ed. : 2013 ISBN 9781598886962

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States: Patterns of Economic Change. This book presents data on personal income, employment, and gross domestic product for the United States as a whole, the seven regions, each state, and 366 metropolitan statistical areas (MSAs). Data on personal income and employment extends back to 1958 for the states and regions and to 1969 for the MSAs.
巻冊次

2nd ed. : 2014 ISBN 9781598887341

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States and a new addition to the Bernan Press library of reference titles. This title presents data on personal income, employment, and gross domestic product for the United States as a whole, and by region, state, and metropolitan statistical area (MSA). Data on personal income and employment extends back to 1958 for the states and regions and to 1969 for the MSAs. Patterns of Economic Change complements other Bernan Press titles such as the State and Metropolitan Area Data Book and County and City Extra. In contrast to their predominantly current and detailed cross-section data on states and metropolitan areas, this book contributes historical time-series measurements of key aggregates that show how the economies of regions, states, and metropolitan areas have responded over time to cyclical currents and long-term trends. Statistics at the state level provide a framework for analyzing current economic conditions in each state and can serve as a basis for decision making. For example: *Federal government agencies use the statistics as a basis for allocating funds and determining matching grants to states. The statistics are also used in forecasting models to project energy and water use. *State governments use the statistics to project tax revenues and the need for public services. *Academic regional economists use the statistics for applied research. *Businesses, trade associations, and labor organizations use the statistics for market research. The second edition includes information on 381 MSAs-more than in the previous edition and new figures on income and poverty.
巻冊次

3rd ed. : 2015 ISBN 9781598887969

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States.This title presents data on personal income, employment, and gross domestic product for the United States as a whole, and by region, state, and metropolitan statistical area (MSA). Data on personal income and employment extends back to 1958 for the states and regions and to 1969 for the MSAs. Patterns of Economic Change complements other Bernan Press titles such as the State and Metropolitan Area Data Book and County and City Extra. In contrast to their predominantly current and detailed cross-section data on states and metropolitan areas, this book contributes historical time-series measurements of key aggregates that show how the economies of regions, states, and metropolitan areas have responded over time to cyclical currents and long-term trends. Statistics at the state level provide a framework for analyzing current economic conditions in each state and can serve as a basis for decision making. For example: *Federal government agencies use the statistics as a basis for allocating funds and determining matching grants to states. The statistics are also used in forecasting models to project energy and water use. *State governments use the statistics to project tax revenues and the need for public services. *Academic regional economists use the statistics for applied research. *Businesses, trade associations, and labor organizations use the statistics for market research.

目次

Preface PART A: PERSONAL INCOME AND EMPLOYMENT BY REGION, STATE,AREA United States Region Far West Great Lakes Mideast New England Plains Rocky Mountain Southeast Southwest State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Metropolitan Statistical Area Abilene, TX Akron, OH Albany, GA Albany, OR Albany-Schenectady-Troy, NY Albuquerque, NM Alexandria, LA Allentown-Bethlehem-Easton, PA-NJ Altoona, PA Amarillo, TX Ames, IA Anchorage, AK Ann Arbor, MI Anniston-Oxford-Jacksonville, AL Appleton, WI Asheville, NC Athens-Clarke County, GA Atlanta-Sandy Springs-Roswell, GA Atlantic City-Hammonton, NJ Auburn-Opelika, AL Augusta-Richmond County, GA-SC Austin-Round Rock, TX Bakersfield, CA Baltimore-Columbia-Towson, MD Bangor, ME Barnstable Town, MA Baton Rouge, LA Battle Creek, MI Bay City, MI Beaumont-Port Arthur, TX Beckley, WV Bellingham, WA Bend-Redmond, OR Billings, MT Binghamton, NY Birmingham-Hoover, AL Bismarck, ND Blacksburg-Christiansburg-Radford, VA Bloomington, IL Bloomington, IN Bloomsburg-Berwick, PA Boise City, ID Boston-Cambridge-Newton, MA-NH Boulder, CO Bowling Green, KY Bremerton-Silverdale, WA Bridgeport-Stamford-Norwalk, CT Brownsville-Harlingen, TX Brunswick, GA Buffalo-Cheektowaga-Niagara Falls, NY Burlington, NC Burlington-South Burlington, VT California-Lexington Park, MD Canton-Massillon, OH Cape Coral-Fort Myers, FL Cape Girardeau, MO-IL Carbondale-Marion, IL Carson City, NV Casper, WY Cedar Rapids, IA Chambersburg-Waynesboro, PA Champaign-Urbana, IL Charleston, WV Charleston-North Charleston, SC Charlotte-Concord-Gastonia, NC-SC Charlottesville, VA Chattanooga, TN-GA Cheyenne, WY Chicago-Naperville-Elgin, IL-IN-WI Chico, CA Cincinnati, OH-KY-IN Clarksville, TN-KY Cleveland, TN Cleveland-Elyria, OH Coeur d'Alene, ID College Station-Bryan, TX Colorado Springs, CO Columbia, MO Columbia, SC Columbus, GA-AL Columbus, IN Columbus, OH Corpus Christi, TX Corvallis, OR Crestview-Fort Walton Beach-Destin, FL Cumberland, MD-WV Dallas-Fort Worth-Arlington, TX Dalton, GA Danville, IL Daphne-Fairhope-Foley, AL Davenport-Moline-Rock Island, IA-IL Dayton, OH Decatur, AL Decatur, IL Deltona-Daytona Beach-Ormond Beach, FL Denver-Aurora-Lakewood, CO Des Moines-West Des Moines, IA Detroit-Warren-Dearborn, MI Dothan, AL Dover, DE Dubuque, IA Duluth, MN-WI Durham-Chapel Hill, NC East Stroudsburg, PA Eau Claire, WI El Centro, CA Elizabethtown-Fort Knox, KY Elkhart-Goshen, IN Elmira, NY El Paso, TX Erie, PA Eugene, OR Evansville, IN-KY Fairbanks, AK Fargo, ND-MN Farmington, NM Fayetteville, NC Fayetteville-Springdale-Rogers, AR-MO Flagstaff, AZ Flint, MI Florence, SC Florence-Muscle Shoals, AL Fond du Lac, WI Fort Collins, CO Fort Smith, AR-OK Fort Wayne, IN Fresno, CA Gadsden, AL Gainesville, FL Gainesville, GA Gettysburg, PA Glens Falls, NY Goldsboro, NC Grand Forks, ND-MN Grand Island, NE Grand Junction, CO Grand Rapids-Wyoming, MI Grants Pass, OR Great Falls, MT Greeley, CO Green Bay, WI Greensboro-High Point, NC Greenville, NC Greenville-Anderson-Mauldin, SC Gulfport-Biloxi-Pascagoula, MS Hagerstown-Martinsburg, MD-WV Hammond, LA Hanford-Corcoran, CA Harrisburg-Carlisle, PA Harrisonburg, VA Hartford-West Hartford-East Hartford, CT Hattiesburg, MS Hickory-Lenoir-Morganton, NC Hilton Head Island-Bluffton-Beaufort, SC Hinesville, GA Homosassa Springs, FL Hot Springs, AR Houma-Thibodaux, LA Houston-The Woodlands-Sugar Land, TX Huntington-Ashland, WV-KY-OH Huntsville, AL Idaho Falls, ID Indianapolis-Carmel-Anderson, IN Iowa City, IA Ithaca, NY Jackson, MI Jackson, MS Jackson, TN Jacksonville, FL Jacksonville, NC Janesville-Beloit, WI Jefferson City, MO Johnson City, TN Johnstown, PA Jonesboro, AR Joplin, MO Kahului-Wailuku-Lahaina, HI Kalamazoo-Portage, MI Kankakee, IL Kansas City, MO-KS Kennewick-Richland, WA Killeen-Temple, TX Kingsport-Bristol-Bristol, TN-VA Kingston, NY Knoxville, TN Kokomo, IN La Crosse-Onalaska, WI-MN Lafayette, LA Lafayette-West Lafayette, IN Lake Charles, LA Lake Havasu City-Kingman, AZ Lakeland-Winter Haven, FL Lancaster, PA Lansing-East Lansing, MI Laredo, TX Las Cruces, NM Las Vegas-Henderson-Paradise, NV Lawrence, KS Lawton, OK Lebanon, PA Lewiston, ID-WA Lewiston-Auburn, ME Lexington-Fayette, KY Lima, OH Lincoln, NE Little Rock-North Little Rock-Conway, AR Logan, UT-ID Longview, TX Longview, WA Los Angeles-Long Beach-Anaheim, CA Louisville/Jefferson County, KY-IN Lubbock, TX Lynchburg, VA Macon, GA Madera, CA Madison, WI Manchester-Nashua, NH Manhattan, KS Mankato-North Mankato, MN Mansfield, OH McAllen-Edinburg-Mission, TX Medford, OR Memphis, TN-MS-AR Merced, CA Miami-Fort Lauderdale-West Palm Beach, FL Michigan City-La Porte, IN Midland, MI Midland, TX Milwaukee-Waukesha-West Allis, WI Minneapolis-St. Paul-Bloomington, MN-WI Missoula, MT Mobile, AL Modesto, CA Monroe, LA Monroe, MI Montgomery, AL Morgantown, WV Morristown, TN Mount Vernon-Anacortes, WA Muncie, IN Muskegon, MI Myrtle Beach-Conway-North Myrtle Beach, SC-NC Napa, CA Naples-Immokalee-Marco Island, FL Nashville-Davidson--Murfreesboro--Franklin, TN New Bern, NC New Haven-Milford, CT New Orleans-Metairie, LA New York-Newark-Jersey City, NY-NJ-PA Niles-Benton Harbor, MI North Port-Sarasota-Bradenton, FL Norwich-New London, CT Ocala, FL Ocean City, NJ Odessa, TX Ogden-Clearfield, UT Oklahoma City, OK Olympia-Tumwater, WA Omaha-Council Bluffs, NE-IA Orlando-Kissimmee-Sanford, FL Oshkosh-Neenah, WI Owensboro, KY Oxnard-Thousand Oaks-Ventura, CA Palm Bay-Melbourne-Titusville, FL Panama City, FL Parkersburg-Vienna, WV Pensacola-Ferry Pass-Brent, FL Peoria, IL Philadelphia-Camden-Wilmington, PA-NJ-DE-MD Phoenix-Mesa-Scottsdale, AZ Pine Bluff, AR Pittsburgh, PA Pittsfield, MA Pocatello, ID Portland-South Portland, ME Portland-Vancouver-Hillsboro, OR-WA Port St. Lucie, FL Prescott, AZ Providence-Warwick, RI-MA Provo-Orem, UT Pueblo, CO Punta Gorda, FL Racine, WI Raleigh, NC Rapid City, SD Reading, PA Redding, CA Reno, NV Richmond, VA Riverside-San Bernardino-Ontario, CA Roanoke, VA Rochester, MN Rochester, NY Rockford, IL Rocky Mount, NC Rome, GA Sacramento--Roseville--Arden-Arcade, CA Saginaw, MI St. Cloud, MN St. George, UT St. Joseph, MO-KS St. Louis, MO-IL Salem, OR Salinas, CA Salisbury, MD-DE Salt Lake City, UT San Angelo, TX San Antonio-New Braunfels, TX San Diego-Carlsbad, CA San Francisco-Oakland-Hayward, CA San Jose-Sunnyvale-Santa Clara, CA San Luis Obispo-Paso Robles-Arroyo Grande, CA Santa Cruz-Watsonville, CA Santa Fe, NM Santa Maria-Santa Barbara, CA Santa Rosa, CA Savannah, GA Scranton--Wilkes-Barre--Hazleton, PA Seattle-Tacoma-Bellevue, WA Sebastian-Vero Beach, FL Sebring, FL Sheboygan, WI Sherman-Denison, TX Shreveport-Bossier City, LA Sierra Vista-Douglas, AZ Sioux City, IA-NE-SD Sioux Falls, SD South Bend-Mishawaka, IN-MI Spartanburg, SC Spokane-Spokane Valley, WA Springfield, IL Springfield, MA Springfield, MO Springfield, OH State College, PA Staunton-Waynesboro, VA Stockton-Lodi, CA Sumter, SC Syracuse, NY Tallahassee, FL Tampa-St. Petersburg-Clearwater, FL Terre Haute, IN Texarkana, TX-AR The Villages, FL Toledo, OH Topeka, KS Trenton, NJ Tucson, AZ Tulsa, OK Tuscaloosa, AL Tyler, TX Urban Honolulu, HI Utica-Rome, NY Valdosta, GA Vallejo-Fairfield, CA Victoria, TX Vineland-Bridgeton, NJ Virginia Beach-Norfolk-Newport News, VA-NC Visalia-Porterville, CA Waco, TX Walla Walla, WA Warner Robins, GA Washington-Arlington-Alexandria, DC-VA-MD-WV Waterloo-Cedar Falls, IA Watertown-Fort Drum, NY Wausau, WI Weirton-Steubenville, WV-OH Wenatchee, WA Wheeling, WV-OH Wichita, KS Wichita Falls, TX Williamsport, PA Wilmington, NC Winchester, VA-WV Winston-Salem, NC Worcester, MA-CT Yakima, WA York-Hanover, PA Youngstown-Warren-Boardman, OH-PA Yuba City, CA Yuma, AZ PART B: GROSS DOMESTIC PRODUCT BY REGION, STATE, AND AREA Gross Domestic Product by Region and State Gross Domestic Product by Metropolitan Statistical Area Quantity Indexes for Real GDP by Metropolitan Area PART C: INCOME AND POVERTY BY STATE Median Household Income by State Poverty Status by State Number and Percent of People in Poverty by Region APPENDIX
巻冊次

4th ed. : 2016 ISBN 9781598888768

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States.This title presents data on personal income, employment, and gross domestic product for the United States as a whole, and by region, state, and metropolitan statistical area (MSA). Data on personal income and employment extends back to 1960 for the states and regions and to 1970 for the MSAs. Patterns of Economic Change complements other Bernan Press titles such as the State and Metropolitan Area Data Book and County and City Extra. In contrast to their predominantly current and detailed cross-section data on states and metropolitan areas, this book contributes historical time-series measurements of key aggregates that show how the economies of regions, states, and metropolitan areas have responded over time to cyclical currents and long-term trends. Statistics at the state level provide a framework for analyzing current economic conditions in each state and can serve as a basis for decision making. For example: *Federal government agencies use the statistics as a basis for allocating funds and determining matching grants to states. The statistics are also used in forecasting models to project energy and water use. *State governments use the statistics to project tax revenues and the need for public services. *Academic regional economists use the statistics for applied research. *Businesses, trade associations, and labor organizations use the statistics for market research.
巻冊次

5th ed. : 2017 ISBN 9781598889468

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States. It presents data on personal income, employment, and gross domestic product for the United States as a whole, and by region, state, and metropolitan statistical area (MSA). Data on personal income and employment extends back to 1960 for the states and regions and to 1970 for the MSAs. Patterns of Economic Change complements other Bernan Press titles such as the State and Metropolitan Area Data Book and County and City Extra. In contrast to their predominantly current and detailed cross-section data on states and metropolitan areas, this book contributes historical time-series measurements of key aggregates that show how the economies of regions, states, and metropolitan areas have responded over time to cyclical currents and long-term trends. Statistics at the state level provide a framework for analyzing current economic conditions in each state and can serve as a basis for decision making. For example: *Federal government agencies use the statistics as a basis for allocating funds and determining matching grants to states. The statistics are also used in forecasting models to project energy and water use. *State governments use the statistics to project tax revenues and the need for public services. *Academic regional economists use the statistics for applied research. *Businesses, trade associations, and labor organizations use the statistics for market research.
巻冊次

6th ed. : 2018 ISBN 9781641432771

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States. It presents data on personal income, employment, and gross domestic product for the United States as a whole, and by region, state, and metropolitan statistical area (MSA). Data on personal income and employment extends back to 1960 for the states and regions and to 1970 for the MSAs. Patterns of Economic Change complements other Bernan Press titles such as the State and Metropolitan Area Data Book and County and City Extra. In contrast to their predominantly current and detailed cross-section data on states and metropolitan areas, this book contributes historical time-series measurements of key aggregates that show how the economies of regions, states, and metropolitan areas have responded over time to cyclical currents and long-term trends. Statistics at the state level provide a framework for analyzing current economic conditions in each state and can serve as a basis for decision making. For example: *Federal government agencies use the statistics as a basis for allocating funds and determining matching grants to states. The statistics are also used in forecasting models to project energy and water use. *State governments use the statistics to project tax revenues and the need for public services. *Academic regional economists use the statistics for applied research. *Businesses, trade associations, and labor organizations use the statistics for market research.
巻冊次

7th ed. : 2019 ISBN 9781641433839

内容説明

Patterns of Economic Change by State and Area: Income, Employment, and Gross Domestic Product is a special edition of Business Statistics of the United States. It presents data on personal income, employment, and gross domestic product for the United States as a whole, and by region, state, and metropolitan statistical area (MSA). Data on personal income and employment extends back to 1960 for the states and regions and to 1970 for the MSAs. Patterns of Economic Change complements other Bernan Press titles such as the State and Metropolitan Area Data Book and County and City Extra. In contrast to their predominantly current and detailed cross-section data on states and metropolitan areas, this book contributes historical time-series measurements of key aggregates that show how the economies of regions, states, and metropolitan areas have responded over time to cyclical currents and long-term trends. Statistics at the state level provide a framework for analyzing current economic conditions in each state and can serve as a basis for decision making. For example: ·Federal government agencies use the statistics as a basis for allocating funds and determining matching grants to states. The statistics are also used in forecasting models to project energy and water use. ·State governments use the statistics to project tax revenues and the need for public services. ·Academic regional economists use the statistics for applied research. ·Businesses, trade associations, and labor organizations use the statistics for market research.

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