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Local Area Economic Growth Patterns: A Comparison of the 1980s ant! Previous Decades DANIEL H. GARNICK Looking back from the vantage point of the 1980s, it is clear that the much publicized reversal of growth that occurred in the 1970s from metropolitan to nonmetropolitan areas was tempo- rary. In three earlier articles documenting the resumption of higher growth in metropolitan areas in the 1980s, the author showed that (1) the perceived growth reversal was not uniform among all regions, (2) there are underlying industrial and regional continuities, appar- ently of a structural nature, as well as cyclical or shorter term ele- ments, that may from time to time result in or exaggerate perceived shifts ant] reversals, (3) tests of hypotheses associated with polar- ization/polar reversal (counterurbanization) theory failed to support the theories of polar growth and reversal, and (4) the wage rate as the equilibrating mechanism in area growth only weakly supported neoclassical theory (Garnick, 1983, 1984, 1985~. The import of these results is that, although there appear to be many long-term indus- trial and regional structural elements at work underlying the shifting balances in metropolitan and nonmetropolitan area growth, no single or overarching theory appears to be able to describe adequately the The views expressed in this paper are not necessarily those of the U.S. Department of Commerce or of the Bureau of Economic Analysis where the author is associate director for regional economics. 199

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200 Daniel H. Garruck dynamics of area growth and decline. Thus, no overarching policy or single instrument is likely to resolve the problems associated with the uneven development and differential growth patterns of regions and areas. This paper is developed in four sections. The first section briefly updates the review of metropolitan-nonmetropolitan area patterns in the 1980s thus far, contrasting them with the patterns in the 1960s and 1970s; the section focuses on the same metropolitan and nonmetropolitan designations and the same economic and popula- tion aggregates dealt with in the earlier articles. The second section follows the fortunes of the 50 largest metropolitan statistical areas (MSAs) over the same time spans, adding employment to the list of economic aggregates reviewed and placing particular emphasis on the relationship between employment change and population change. The third section disaggregates the geography further into four cat- egories of county groups within each of the MSA and non-MSA designations. Additional economic aggregates are introduced into the analysis of the patterns in these geographic configurations. The final section interweaves the findings from the first three sections with a longer term review of national production and employment patterns and with an outlook for policy. MSA/NON-MSA GROWTH PATTERNS Tables 1, 2, and 3 show the average annual rates of growth in total personal income, population, total earnings, and in earnings excluding farm and manufacturing. (Earnings are the sum of wages and salaries, other labor income, and proprietors' income.) Growth rates are shown for the United States and its regions by non-MSA and MSA areas, and by size class of the latter, for three time spans: 1959-1969, 196~1979, and 1979-1984. The choice of years for the first two tables is based on national business cycle peaks, with the aim of separating trend from cyclical changes. The last year is the most recent for which data are available. Thus far in the 1980s, MSA growth has continued to exceed non-MSA growth in total personal income, population, and earnings in the nation as a whole and in all but three highly urbanized re- gions: the New England, Mideast, and Great Lakes regions, in which population growth in non-MSAs continued to exceed that in MSAs.i iThe Bureau of Economic Analysis' regional classification differs somewhat from that of the Bureau of the Census (see Appendix A, p. 59~.

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205 C~ C9 ~ ~ ~ o o C9 C~ CO C;) ~ oo ~ oo ~ ~ oo ~ ~ CO . . . . . . . . . · . oo ~ oo ~ oo oo oo ~ ~ ~ o 0 e4 co ~ 0 ~ 0 ~ C~ 00 ~ 00 tD ~ . . . . . . . oo =co moo oooo CO oo ~ ~ o oo ~ ~ ~ ~ C~ o . . . · . . . oo Ch oo ~ oo oo oo e~ ~ ~ oo C5) oo U: ~ ~ ~ ~ C~ o . . . . . . . oo ~oo == oooo e~ cs ~ cs ~ ~ c~ ~ ~ C~ ~ ~ o o . · . . . . . o o o o o o o 1 CD co ~ ~ CO CD O ~ CS) ~ ~ ~ 00 C5) CD ~ ~ ~ . . . . . . . . . ~ o oo Ch oo oo oo ~ o oo ~ e~ o . . . . C5) U: ~ ~ CC oo ~ oo oo . . . . . . . o ~ ~ ~ c9 ~ CD o co u~ oo oo C~ CO U U~ CO o ~ oo . . . · . . · · . o ~ ~ C~ o o _1 ~ ~CD ct)e~ eo~ U) ~U: "CO COO · . . · . . . o <9 ~ CO ~ CS ~ ~ U. CO . · . . . . . ooooooo 0 e~ ~ ~ <9 oo c9 ~ c~ O C~ CO ~ C4 ~ C~ o · . . . . . . . . . — O ~ 0 ~ e~ ~ c~ ~ ~ e~ u: ~ ~ _1 ~ ~ _. u~ ~ co u~ co C5) ~ °O C5) u CO CD ~ CD ~ CD · . . . . . . . . . O O O O ~ O ~ c~ ~ c~ O co O . . . ~ C4 ~ co ~ oo 0 ~ 0 ~ ~ c~ =` u: ~ ~ CD C~ ~ CS) 00 . . . . . . . . . . . O O O ~ c~ ~ e~ ~ u: o~ ~ ~ ~ u, C9 u~ (D ~ C9 ~ ~ . . . . . . . O O O O 0 0 ~ e~ ~ ~ ~ o: e~ °O ~ O C~ O ~ c~ · . . · . · . ~ ~ e~ ~ e~ c. ~ O CO ~ (D oo ~ {D ~ oo a~ cs e~ oo ~ ~ ~ co ~ ~ a: co u: . . . . . · · · · · · — ~ O ~ ~ C53 ~ _ ~ ~ _. ~ ~ co a~ e~ ~ 0 a~ co O ~ c~ co~ 00 . . · . . . . c~ ~ e~ _1 u, 0 e~ oo CS) oo u . . . . . . . e4 ~ e~ co ~ ~ <9 ~ oo e~ 0 u~ co u~ ~ c~ ~ u: . . . . . . . ~ ~ c~ ~n oo ~ ~n ~ o ~ ~ o ~ ~ o ~ ~ o o c - o - - :- ~ o o 3 o N ~ O o — ~ N ~ O ~ — ~ N ~ O ~ _ ~ N G, o U, ~ _. => ~ O ~ ~ => ~ O ~ ~ ~ => ~ O ~ ~ ~ => ~ O `0 _ _ ~ ~ L4 _ _ 0O ~ o L. °O _ _ tn ~ O $, ~ ~0 ~0 ~ O - > ~ ~0 ~0 ~ O - > ~ O O ~ O - O ~ ~ O U] U)

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207 00 ^ (:, O c~ ~ 00 ~ aS O — ~,, v ~ N o ~ O |_, ._ _ ~ ~ _ O ~n O ~o 2 E~ ~ _% __ _ b4 ~ C: [Q ~, C} ~ L. o _ s" ~n o ’ V) - 3 ~ o s" _ ~ o V _ ~ ._ s" bO ’ :>, co oo to .- m £ co ~0 ._ ~0 ._ b.0 ~ ~ — crS ~ _ ~ c: ~ EO 2 ~ ~4 ._ s" ~o ~ ·— (d _ X ~ _. ~ 2 ~o ._ _ X ~ o o ._ - C. ~ o o - ~ ~, o ~ L. o ’ ~ Y O ~ oq V oo ~ ~ ° a., V bO ~ a, ~ >, b4 ~ ~ U' U~ ~ <9 U: o oo o ~ ~ Ut . . . . · · — oo ~ Ch oo 00 CS) ~ CD O ~ e~ U~ ~ O C5) ~ CO C~ . . . . . . . 00 CD ~ ~ ~ ~ CS) e~ e~ ~ co e~ o ~ o: oO 'o o co . . . . . . — oocsoo~oomoo CO O C9 00 : ~ ~ c~ oo . . . . . . . omoo = - o ~ ~ _1 ~ ~ cO ~ ~ ~ t9 o ~ cO c~ ~ u: co oo u: . . . . . . . ~ ~ ~ oo c~ ~ ~ <9 ~ c~ co ~ cO ~ co co o~ ~ u: CS) ~ e~ ~ ~ ~ c . . . . . . . . . . . . . . o ~ o o ~ ~ o ~ co ~ oo c~ ~ ~ 0 ~ ~ a) ut u: ~ ~ ~ ~ u: ~ e~ 0 oo ~ ~ ~ ~ ~ oo ~ o, ~ ~ ~ ~ co . . . . . . . . . . . . . . ~ 00 C~ O 00 ~ O 00 CD 00 CD 00 ~ ~ ~ oo co 0 ~ e~ 0 ~ 0 0 u: u~ co ~ co ~ c9 00 0 C~ C~ U~ O CO ~ 00 ~ ~ ~ ~ 00 ~ ~ C~ (D O ~ U . . . . . . . . . . . . . . . · . . . . . C9 00 ~ 00 ~ 00 ~ 00 ~ O 00 ~ O 00 CO 00 CD ~ 00 ~ ~ ~ e~ ~ 0 ~ e~ ~ 0 ~ e~ ~ ~ ~ oo ~ ~ oO ~ 0 oo 0 oo O e~ ~ ~ ~ co oo e~~ ~ co ~ ~ c~ . . . . . . . . . . . . . . . . . . . . . - - - - o oo oo oo o oo oo oo o l 0 cs ~ co e~ e~ co c~ ~ co ~ oo ~ o . . . . . . . ~ oo ~ oo ~ ~ ~ e~ ~ co 0 u, 0 co CD O CO ~ CO CO '~ ~ oo oo co ~ ~ ~ c~ ~ u) c~ '~ . . . . . . . . . . . . . o o o ~ o o ~ oo ~ oo ~ ~ ~ . oo os oo a, ~ o ~ ~ o ~ ~ o ~ u ~ ~ ~ - ~ ~ ~ ~ ~ .s ’ ~ ~ ~ ~ ~ ~ ’ ~ ~ - ~ ~ ~ ’ 2 ~ o ~ ~ _ ~ ~ ~ o ~ ~ ~ 2 ~ o ~ _- _ ~ ,`, ~ o ~ _- _- 9 ~ o o ~ _- _ ~ ~ o o .~= ~ ~ 3 ~ :Z 2

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208 ~q b4 .5 ._ o v _, CO m ._ ~ C ~ _ ~ X ~ ~ S" bO ·— C _ ~ _ C: 03 2 bO ._ ~ L. X C. o o ._ C~ - C: ~ o o C 4U o ~ ~ o O ~ a~ r~ a, _ ~ ~n ~n ~ ~ O ~ V bO ~ a' >, e; oo CO 0 0 C~ C9 ~ ~ ~ ~ ~ ~ CD · . . . · · . (D u: ~ CD ut ~ co CO ~ ~ CO ~ ~ ~ co o. co e~ oo co c9 CO Ut ~ ~ Ut ~ C9 U. ~ U. C' ~ C~ ~ ~ O . . . . . . . U~ U~ U~ U~ ~ CD ~ C5) ~ oo ~ CC U. _ ~ ~ ~ ~ O · . . . . · — CO oo ~ oO co ~ e~ co ~ ~ ~ ° O O O ~ ~ C~ Co . · . . · · · · — CO U~ oo ~ oo ~ oo CD ~ ~ 00 ~ co ~ ~ e~ CD · . · . . . . ~ U: ~ CO ~ ~ oo o ~ o o ~ ~ ~C9 . . . . . . . C53 ~ O oo 0 oe~ oo e~ ~ co . · . . co o o ~ o oO O 03 C9 ~ CS 00 U, . . . · . · . e~ r4 oo ~F oo t~ ~ co ~ o~ u~ _~ e~ oo 0 0 c~ u~ co c~ ~ ~ ~ ~ C~ O ~ O ~ ~ O u: CO ~ O (D oo 00 U) 0: ~ oO U) . . . . · . . . · . . . . · . . . . · · — U, u: ~ CD U, CD =^ O~ ~ 00 00 CD ~ 00 ~ ~ C~ ~ co u, oo oo ~ ~ oo e~ ~ oo co oo U3 0 ~ 0 CD 00 o ~ o o o o ~ ~ c~ ~ cs) cs) co ~ ~ oo ~ u: . · . . · . . . · . . . . · . . · · · · — o o o o o! 0 ~ co co ~ ~ ~ 0 e~ co ~ ~ ~ ~ O C~ ~ o ~ u: ~ ~ ~ ~ O CD co a, · . . . . ~ . . . . . . · . ~ e~ {D ~ tD ~ CD 00 ~ 00 ~ 00 ~ ~ ~ oo ~ ~ o ~ : · · . . . . oo o ~ o o c~ ~ - ~ ~ ~ oo a~ al ~ ~ E ~ E ~ ~ E C E ~ C E C ~ E ~ o=~ - E~ o~ - s~ o=~ - s =: ~ 2 ~ o ~ ~ ~ 2 ~ o ~ ~ ~ ~ 2 ~ o ~ ~ 0 ~ ~° ° ~e a5 0 U ~ 0 (D ~3 ~~5 0 U~ ·~D 0 o o~O - 2 =~o~o~°~ ~ ~o o~°~> o~ V]

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247 CO ~ ~ ~ CO C~ ~ ~ ~ CC C~ C9 0 00 U. 00 C9 ~ CD O CD oo ~ ~ co 0 oo oo oo ~ oo ~ ~ e~ ~ co oo oo ~ (D CS) . . . · · · · . · . . . . . . · . . . . . . . CD ~ U. ~ O CO ~ ~ e~ ~ e~ ~ e~ ~ ~ e~ o~ ~ ~ ~ c~ ~ ~ oo co e~ u: C~ ~ 00 ~ ~ (D O C~ ~ 00 CO u~ <9 ~ e~ u: co 00 ~ 03 03 CC ~ ~ ~ CD ~ O ~ a: ~ ut ~ ~ O co oO oO . . . . . . . . . . . · . . . · . . . . . . — o ~ ~ ~ ~ o o o o o ~ o ~ o ~ ~ ~ C' ~ ~ ~ o co oo ~ a~ {D ~ u~ CD C~ e~ CD ~ ~ ~ ~ 00 e~ co oo ~ o ~ oo ~ CO CO CO oo ~ oo ~ o: ~ ~ U~ oo ~ o. CO oo o o. O CO O CD ~ 00 ~ ~ ~ 00 0 ~ u: e~ ~ ~ ~ 0 e~ ~ ~ co O4 c~ ~ ~ ~ ~ ~ c~ ~ c~ e~ ~ ~ c~ oo u: ~ ~ ~ ~ ~ oo e~ 0 u, ~ 0 ~ a, u: ~ ~ ~ ~ ~ c~ U, ~ 00 ~ ~ ~3 0 ~ ~ 00 u, 00 ~ ~ oo O ~ U, CD ~ ~ O . . . . . . . . . . . . . . . . . . . . . . . u~ ~ u~ ~ 0 ut ~ CD a~ ~ CD ~ ~ 00 0O 0O u: ~ ~ ~ CO cs ~ ~ 0 oo ~ e~ ~ e~ 0 c~ CD ~ C~ CC ~ o oo c~ ~ ~ u: ~ ~ ~ ~ u: o oo ~ u: u: ut . . . . · . . . . . . . . . . . . . . . . . . u~ u: ut ~ ~ u~ cD u~ ~ u~ ~ u: ~ ut u~ 49 u~ u: e~ u~ co ~ c~ oo ~ ut CD a~ e~ a~ oo e~ oo ~ ~ ~ ~ ~ ~ a~ e~ u3 CO CD O ~ U: O ~ ~ C9 ~ ~ ~ C9 e~ ~ 0 co C~ ~ ~ oo u, . · · · · . . . . . . . . . . . · . · . · . . u, ~ e~ e~ ~ oo ~ oo co ~ 0 ~ ~ ~ oo ~ ~ ~ c~ oo u~ ~ U~ ~P ~ U: CD U: CD U~ U: U~ ~ ~ U) C9 U~ U: U: ~ ~ U: CC ~ U, C9 ~ ~ O ~ ~ ~ ~ ~ ~ ~ O — ~ ~ ~ ~ ~ ~ ~ ao =~= ~ =~= ~=P~ :^ >, >, >, >, >, 0 ~, >, #, ~, >, ^, >, >, ~ ~ ~ ~ ~ ~ ~ :^ ~ ~ ~ ~ ~ S ~ ~ ~ ~ ~ ~ ~ ~ OO ~ ~ ~ ~ ~ ~ ~ ~ .~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ 3 ~ ~ ~ ~ ~ o o o o o ~ o o o o o o o o o o o o o o o o V V V V V o V V V V V V V V C: V V V V V V V V _` oo ° C, ~ ~ ’, ° = ’ ’ ~ O ·= d ~ ~ I I O O C .~ § ~ Oo || || $ J ~ ~ O ~·S ~ o O ~ ~ S, - ’ ~ o ~ oS ~ ~ 0,= a, 0 0 ~ _ ~ ~ m ~ °, · c e ° ° IA ~ ~ m ° .° .C ~ ~ ~ ~ ~ S O ~ ~ [t ~; ° °._ O ° a,< O ~ ~ ~ ,0 .0 ~ ~ ~ o 11 ~ 50 ~ O ~ ~ E ' E - o ~l s o 03 ~ ~ o o~l ~ ~

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248 Daniel H. Garruck cation is a continuation of Tong-term trends. Regions and areas have, in the past, experienced the loss of one industrial source of employ- ment and income and gained another source. With the increasing internationalization of the U.S. economy, however, the requirements for adjustment seem to be becoming more difficult, more diverse, and more wiclespread. Should policy be directed toward areas, industries, trade, or persons? The shifting patterns and longer term trends shown in the 25- year time span included in this study are part and parcel of an even longer history of labor reallocation. Ehrenhalt (1986) calls attention to the milestone reached in the first decade of this century when the number of blue-collar workers first exceeded the number of farmers; now, in the ninth decade of the century, the number of professional, technical, and managerial workers is fast approaching the point at which it will exceed the number of blue-collar workers. In 1929, the first year for which BEA prepared estimates, the number of persons engaged (full time-equivalent employment and self-employment) in goods-producing industries and the number en- gaged in service-producing industries were approximately equal. By 1985, the most recent year for which estimates have been prepared, goods-producing industries accounted for only 28 percent of persons engaged in production; service-producing industries accounted for the other 72 percent. Over this more than Midyear time span, the number of persons engaged in production more than doubled, from 45.66 million to 102.96 million, and both population settlement and industrial location patterns across America underwent vast changes. From 1929 through 1936 the number of persons (excluding un- paid family members) engaged in farming held steady at about 8.3 million. By 1947 the number had fallen to 6.4 million, and it fell fur- ther during the next two decades to 2.8 million by 1969. Throughout the 1970s the number of persons engaged in farming declined at a much reduced rate, falling to 2.5 million by 1979; the rate of decline reaccelerated in the 1980s, however, and by 1985 there were only 2.1 million persons engaged in farming. Further decreases appear to be in the offing owing to rising world production. The agricultural revolution has spread to densely populated countries that formerly were net importers of farm products. Continued subsidies to farm- ers in industrially advanced countries are increasingly less effective in maintaining farm population and increasingly more burdensome on national government budgets. Areas experiencing falling employ-

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LOCAL AREA ECONOMIC GRO WTH PATTERNS . 249 ment in agriculture would like to see policies that would protect farmers against competing imports and that would promote exports. Yet the net effect of such policies is that they raise prices and in- voke trade wars that disadvantage trade in the products of other industries. Mining, another major goods-producing industry located mainly in rural areas, has had a somewhat more checkered pattern in terms of persons engaged in production. In 1929 more than 1 million persons were engaged in mining production. The number fluctuated somewhat during the Depression and post-WorId War IT years but then began a steep decline in the 1950s, falling to 625,000 by 1972. With the fossil fuel price explosion, mining employment began to rise, and with the second oil price "shock," it reached 1.6 million in 1981. But it then fell slowly to 926,000 in 1985 and since then has fallen much further, with the steep slide in world oil prices and the sympathetic movement of competing fuel prices. Mining employment exhibits a somewhat different pattern than farm employment, which has continued to fall over the last 50 years, albeit at a different rate. The different pattern of employment can be explained in part by the different patterns of productivity change in the two industries, which are so important to the fortunes of non- MSAs. Table 15 shows real gross national product (GNP) by industry for selected years from 1947-1985, the first and most recent years for which BEA has prepared these estimates; Table 16 shows persons engaged in production by industry. In these tables, the industry detail is given at the major division level. Farming is included in agriculture, and in 1985 farm employment accounted for 71 percent of agricultural employment, which also includes agricultural services, forestry, and fisheries all industries that tend to concentrate in non-MSAs. In 1947 farm employment accounted for 96 percent of agricultural employment. Table 17 shows the ratio of real GNP by industry to the num- ber of persons engaged in production in each industry—a measure of labor productivity. As can be seen in the table, productivity in agriculture rose over the entire period, but mining productivity fell sharply in the 1970s. Mining output growth was not commensu- rate with employment growth, but internationally determined rising product prices were more than enough to offset the rising wage bill. Falling prices will have the opposite effect. Areas experiencing falling employment in mining would like to see mining product prices kept

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250 Daniel H. Garruck TABLE 15 Gross National Product (GNP) (in millions of 1982 dollars) by Industry, for Selected Years Industry 1947 1959 1969 1979 1985 Total GNP 1,066.8 1,629.1 2,423.3 3,192.3 3,585.3 Goods-producing sector 426.0 658.3 914.5 1,076.7 1162.8 Agriculture 55.6 65.8 65.3 76.1 92.2 Mining 67.6 94.1 128.9 130.0 130.6 Construction 76.7 160.4 183.6 173.5 163.1 Manufacturing 226.1 338.0 536.7 697.1 776.9 Service-producing sector 641.7 976.4 1,504.0 2,070.3 2,389.4 Transportation 100.0 123.5 200.3 293.4 323.3 Wholesale trade 54.6 89.2 149.0 217.3 264.5 Retail trade 103.2 151.5 212.7 294.4 339.8 Finance, insurance, and real estate 103.0 195.9 314.0 459.2 523.9 Services 124.7 183.5 287.8 429.8 538.5 Government 156.2 232.8 340.2 376.2 399.4 1947 1959 1969 1979 1985 Total GNP 100.0 100.0 100.0 100.0 100.0 Goods-producing sector 39.9 40.4 37.7 33.7 32.4 Agriculture 5.2 4.0 2.7 2.4 2.6 Mining 6.3 5.8 5.3 4.1 3.6 Construction 7.2 9.8 7.6 5.4 4.5 Manufacturing 21.2 20.7 22.1 21.8 21.7 Service-producing sector 60.1 59.6 62.3 66.3 65.6 Transportation 9.4 7.6 8.S 9.2 9.0 Wholesale trade 5.1 5.5 6.1 6.8 7.4 Retail trade 9.7 9.3 8.8 9.2 9.5 Finance, insurance, and real estate 9.7 12.0 13.0 14.4 14.6 Services 11.7 11.3 11.9 13.5 15.0 Government 14.6 14.3 14.0 11.8 11.1 high through the use of tariffs imposed on competing imports, a policy that could invoke countermoves from countries that export mining products. Manufacturing employment rose relatively continuously over the period, although at clecTining rates of increase in the late 1960s and 1970s. The same is true of manufacturing productivity. In the 1980s,

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LOCAL AREA ECONOMIC GRO WTH PATTERNS 251 employment has fallen but productivity growth has begun to rise from $33,000 in real GNP per worker to $40,000 per worker. The in- crease in productivity growth, all other things being equal, would be expected to enhance U.S. competitiveness in world markets. Areas experiencing falling employment in manufacturing industries, how- TABLE 16 Persons Engaged in Production (in thousands) by Industrya and as a Percentage of the Total Number of Persons Engaged in Production, for Selected Years Industry 1947 1959 1969 1979 1985 Total persons engaged in production 57,320 63,965 78,853 95,502 102,957 Goods-producing sector 26,028 25,350 28,132 30,674 28,922 Agriculture 6,657 4,704 3,193 3,161 2,960 Mining 968 742 626 957 926 Construction 3,007 3,533 4,256 5,607 5,823 Manufacturing 15,396 16,371 20,057 20,949 19,213 Service-producing sector 31,292 38,615 50,721 64,828 74,035 Transportation 4,231 4,083 4,488 5,166 5,301 Wholesale trade 2,620 3,351 4,041 5,339 5,814 Retail trade 8,376 8,911 10,596 14,086 15,930 Finance, insurance, and real estate 1,864 2,668 3,653 5,305 6,370 Services 7,444 9,430 13,313 18,849 23,879 Government 6,762 10,306 14,652 16,106 16,765 Rest of world -5 -134 -22 -23 -24 1947 1959 1969 1979 1985 Persons engaged in production (id) 100.0 100.0 100.0 100.0 100.0 Goods-producing sector 45.4 39.6 35.7 32.1 28.1 Agriculture 11.6 7.4 4.0 3.3 2.9 Mining 1.7 1.2 0.8 1.0 0.9 Construction 5.2 5.5 5.4 5.9 5.7 Manufacturing 26.9 25.6 25.4 21.9 18.7 Service-producing sector 54.6 60.4 64.3 67.9 71.9 Transportation 7.4 6.4 5.7 5.4 5.1 Wholesale trade 4.6 5.2 5.1 5.6 5.6 Retail trade 14.6 13.9 13.4 14.7 15.5 Finance, insurance, and real estate 3.3 4.2 4.6 5.6 6.2 Services 13.0 14.7 16.9 19.7 23.2 Government 11.8 16.1 18.6 16.9 16.5 Rest of world -0.0 -0.2 -0.0 -0.0 -0.0 aPersons engaged in production equals the number of full time-equi~ralent employees plus the number of self-employed persons. Unpaid family workers are not included.

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252 TABLE 17 Ratio of Gross National Product (GNP) to Persons Engaged in Productiona (in thousands of 1982 dollars), by Industry, for Selected Years Daniel H. Garruck Industry 1947 1959 1969 1979 1985 Total GNP Goods-producing sector Agriculture Mining Construction Manufacturing Ser~rice-producing sector Transportation Wholesale trade Retail trade Finance, insurance, and real estate Services G overnment 18,610 25,469 16,367 25,968 8,352 13,968 69,835 126,819 25,507 45,401 14,686 20,646 20,478 25,140 23,635 30,247 20,840 26,619 12,321 17,001 55,258 16,752 23,100 30,732 33,428 34,822 32,508 35,101 40,205 20,451 24,075 31,149 205,911 135,841 141,037 43,139 30,943 28,010 26,759 33,276 40,436 29,747 32,634 32,720 44,630 56,794 60,988 36,872 40,701 45,494 20,074 20,900 21,331 73,426 85,957 19,459 21,618 22,589 23,219 86,560 22,802 23,358 82,245 22,551 23,823 aPersons engaged in production equals the number of full time equivalent employees plus the number of self-employed persons. Unpaid family workers are not included. ever, would like to see these industries protected. Removing compe- tition could result in higher product prices and in countermoves by other countries that are adversely affected. The fortunes of these goods-producing industries in world mar- kets directly affect the fortunes of the areas in which the industries are located. Therefore, the question has been raised: Should there be an overall U.S. regional or urban policy, or a national industrial policy? Because regional and area growth patterns are influenced by a wide variety of economic policies, as suggested in the preced- ing paragraphs, it does not make sense to establish regional policies in isolation from other major areas of policy concern. Moreover, the complexity of the public and private forces affecting regional growth patterns is sufficiently great to cast doubt on the efficacy of fine-tuning regional policy. If policy is to be made, its objectives must be distinguished more clearly. In particular, is the objective in most cases to slow down the pace of change because of the high externality costs of rapid regional transformation? Or is the objective in most cases to facilitate change because of the high social costs associated with the failure to adjust rapidly to forces for change?

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LOCAL AREA ECONOMIC GROWTH PATTERNS 253 There is also a need to match policy tools to policy objectives more effectively. For example, if the objective is primarily to facilitate change, general investments in human capital that increase individual mobility would seem appropriate. If the objective is primarily to mitigate the costs of "excessively rapid" change, direct payments to the persons affected may be more effective than policies directed specifically at particular government or industrial entities. The growth in services industries, particularly those producer services that tend to locate in major metropolitan areas, has increas- ingly taken up the stack in falling employment in the goods-producing industries in MSAs and non-MSAs alike. Advances in telecommu- nications technology permit "backroom" operations in producer ser- vices to locate at distances remote from face-t~face operations; thus local jurisdictions will be subject to competitive pressures, but this is not a question of national urban policy. Ehrenhalt (1986) notes that half of all professional, technical, and managerial jobs are currently held in the service-producing industries. These jobs require high levels of human capital investment. Policies geared to improved and enhanced training of people may well prove to be the most effective approach to improving the national urban situation. ACKNOWLEDGMENTS ~ have relied on and benefited from the comments and statistical work of Daniel Zabronsky, who organized the data base for this study and constructed the detailed analytical tables, and Gary Kennedy's statistical work. As always, ~ have benefited from Vernon Renshaw's insightful comments in general and with particular respect to the c .lscusslon on policy issues. REFERENCES Ehrenhalt, S. M. 1986 Work-force shifts in the 80's. New York Times, August 15, 1986 p. D2. Garnick, D. H. 1978 Reappraising the Outlook for Northern States and Cities in the Con- text of U.S. Economic History. Working Paper No. 51. Joint Center for Urban Studies of the Massachusetts Institute of Technology and Harvard University. 1983 Shifting patterns in the growth of metropolitan and nonmetropolitan areas. Survey of Current Business 63 (May) :39-44.

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254 Daniel H. Garruck 1984 Shifting balances in U.S. metropolitan and nonmetropolitan area growth. International Regional Scienec Review 9~3) :2 57-2 73. 1985 Patterns of growth in metropolitan and nonmetropolitan areas: An update. Suruey of Current Bun 65(May):33-38. Regional Economic Measurement Division 1986 State personal income, 1969-1985: Revised estimates. Survey of Current Business 66(August):21-35.